Issuu

Vol. 01 No. 02 | Aug-Sep, 2026

PRGI No. HRENG/26/A4764

CONTROLLING PROCESS VARIABILITY

COVER

Systems for Consistent Papermaking

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CONTENTS Aug-Sep, 2026

14 CONTROLLING PROCESS VARIABILITY Systems for Consistent Papermaking

24.

28.

38.

54.

60.

64.

24. Pudumjee Paper Products Beyond Automation: Pudumjee Paper Products Achieving Process Stability...

28. Seshasayee Paper and Boards From Single-Loop PID Control to Integrated Autonomous Control

38. TNPL From Single-Loop Control to Mill-Wide Process Intelligence

54. Sripathi Paper and Boards Stabilises Process Variability Through Intelligent Automation

60. Trident Group Reducing Variability Through Smarter Process Control

64. Emami Paper Mills From Back-End Stability to Reel Consistency

70. Kuantum Papers Connecting Control, Data and Intelligence for Consistent...

76. Ruchira Papers Process Stability and Intelligent Control in Modern Paper... 70.

76.

80. Pakka

80.

Shift From ‘Individual Loop Control To Process-Wide Optimization’

83. Jani Sales Optimises Chemical Consumption and Stabilises Paper Quality... 83.

86.

86. JMC Paper Tech The Road Ahead from Automation to Optimisation

94. Oryx Kraft Mill

to Push UAE’s Circular Economy and Downstream Manufacturing Ecosystem

91. Rinheat, OrbiGreen Techsource

94.

Unite for Advancing EnergySmart Paper Mills...

98. Where Is Global Pulp & Paper Capacity Headed?

102. Parason

Commissions 400–450 TPD Recycled OCC Stock Preparation Line...

NEWS | 105

91.

JK Paper’s BCTMP Plant Surpasses Design Capacity...

102.

Kuantum Papers Plans 50% Capacity Increase Through...

TNPL Commissions 100 TPD Tissue Paper Facility with INR 350...

Rajasekar Veerichetty Elevated to Deputy Managing Director...

PROCESS VARIABILITY MINIMISATION

CONTROLLING PROCESS VARIABILITY Systems for Consistent Papermaking

14 | Aug-Sep 2026

www.papermart.in

PROCESS VARIABILITY MINIMISATION

Paper quality and machine performance depend on how tightly a mill can control process variability. Across critical stages of papermaking, mills are using advanced control, real-time measurement and automation to detect deviations earlier and maintain more consistent operating conditions.

apermaking is often described as a highly automated process. Yet automation by itself does not guarantee stability. The more fundamental challenge is variability. Changes in furnish, fibre characteristics, stock consistency and chemistry can affect conditions further along the process. Refining, steam, moisture, machine speed and mechanical conditions can add to this variability, resulting in quality variation, sheet breaks, higher consumption or lost production. For an integrated mill, the consequences can extend well beyond the point at which the variation originates. Ganesh Balakrishna Bhadti, Executive Director (Operations & Projects), Seshasayee Paper and Boards describes the effect particularly starkly. According to Ganesh Balakrishna, “variability compounds nonlinearly across the value chain.” He cites an uncorrected 1.5 Kappa-unit variation at the digester as an example. It can translate into a 10–15% shift in bleaching chemical demand, wet-end charge instability and a reported 3–5% increase in web breaks on the paper machine hours later. The same interconnectedness is evident closer to the paper machine. Suresh Babu Thallapaneni, Vice-President, Kuantum Papers identifies stock preparation, basis-weight control, moisture profiling, refining, headbox consistency, drying and reel operations as persistent sources of variation. “Even a small fluctuation can eventually show as a quality issue or an efficiency loss,” he says. Ashok Kumar, Executive Director, Pudumjee Paper Products, emphasizes that a small variation in one part of an integrated process can affect subsequent sections, leading to quality problems, runnability issues, sheet breaks, higher energy consumption and reduced production efficiency. For TNPL, the challenge is particularly pronounced in the wet-end approach-flow system and CD profiles. “Because TNPL utilizes a unique, delicate agriculturalresidue, bagasse-heavy furnish mix, the wet-web strength of the paper sheet is inherently lower than pure softwood kraft pulp. Consequently, small hydraulic, chemical or thermal variations propagate downstream rapidly, triggering quality defects or costly machine downtime,” notes Kumar Jayant, Additional Chief Secretary/Chairman & Managing Director.

SVR Krishnan, CEO, Sripathi Paper and Boards approaches the problem in terms of common-cause and special-cause variation. He identifies ambient conditions,

15 | Aug-Sep 2026

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PROCESS VARIABILITY MINIMISATION

Variability Across the Paper Mill

Changes at any stage can propagate downstream and affect quality, runnability and efficiency. Indicative sources of process variability.

Furnish & Raw Materials

Stock Preparation

Wet End (Approach Flow)

Fibre

Consistency & Refining

Chemistry & Flow

Paper Machine (Forming, Pressing & Drying) Basis weight & Formation

Moisture & Drying

Reel

Speed & Tension

Reel Quality

VA R I AT I O N C A N P R O PA G AT E D O W N S T R E A M

Quality variation

Web breaks

Higher resource consumption

Lost production / lower efficiency

Source: Paper Mart

equipment wear and raw-material fluctuations as potential sources of common-cause variation, while incorrect furnish mix, operator error, machine setup, sensor failure, chemical application and unplanned operating changes can create assignable causes. The consequence is not simply an unstable parameter, but reduced process capability, making it difficult to keep the process consistently within the required specification limits. The practical question for paper mills, therefore, is not simply how much automation they have, but how effectively measurement, control and data systems work together to contain variability across the process. The focus, therefore, is on maintaining stable process conditions across interconnected stages of production. This makes the sources of variability across the mill important to understand: how early they arise, how they propagate and where they can be controlled.

The Problem Is Variability, Not Automation

Variability can originate at many points across the mill. SVR Krishnan traces the chain from furnish and raw-material control through wet-end controls, short circulation, steam and condensate systems and tension

16 | Aug-Sep 2026

and draw control up to the pope reel. Jagjeet Singh Khanna, Paper Machine Head, Pakka Ltd. identifies stock-preparation variables such as freeness, consistency and furnish mix, wet-end chemistry and ash, headbox consistency, and CD/MD basis-weight and moisture profiles as particularly important. The important point is that these parameters cannot be treated independently. Ashish Gupta, Unit Head and Senior President, Emami Paper Mills, makes this explicit. “…the greatest gains come not from controlling one isolated parameter, but from stabilising the complete process chain from stock preparation to the finished sheet.” TNPL’s experience illustrates why upstream stability matters. Kumar Jayant reports that maintaining approachflow consistency within ±0.02%, for example, stabilises headbox delivery and reduce machine-direction basisweight swings, allowing production targets to move closer to the lower allowable limit and thereby reducing raw-fibre usage by a reported 1–2%. At the other end of the process, CD moisture and calliper, drying behaviour, machine speed and reel tension can determine whether the paper machine remains stable.

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PROCESS VARIABILITY MINIMISATION

HOW ADVANCED CONTROL USES PROCESS INFORMATION

MEASURE Online sensors | QCS

PROCESS DATA & CONTROL SYSTEMS DCS | QCS | PLC | Historian

CONTROL PID | Feedforward | APC | MPC

ANALYSE / PREDICT Analytics | AI / ML

CORRECTIVE ACTION

FEEDBACK TO MEASUREMENT

OUTCOMES

Consistent paper quality

Better runnability

Lower resource use

Higher production efficiency

Source: Paper Mart

Suresh Babu Thallapaneni, Vice-President, Kuantum Papers notes that an uneven cross-direction (CD) moisture profile can result in curl, cockle and dimensional instability, while reel operations require precise tension and winding control to minimise breaks, wrinkles and defects. The implication is significant: the variability visible at the paper machine may not be caused there. SVR Krishnan notes that longitudinal weight and moisture variation is controlled by machine loops, but its root causes can originate in stock preparation. This makes the limitations of individual-loop control more apparent.

Coordinated and Predictive Control

For decades, the basic operating model was straightforward: measure a variable, compare it with its target, and correct the deviation. Operators played a central role in interpreting the process and adjusting individual loops. That approach remains fundamental, while current control practices increasingly combine multiple variables and anticipate process disturbances. Advanced Process Control (APC) and Model Predictive Control (MPC) are central to this approach.

18 | Aug-Sep 2026

Jagjeet Singh Khanna describes the distinction succinctly. According to him, mills traditionally depended on operator intervention and PID-based feedback control; today, they are increasingly using APC, MPC, feedforward strategies and real-time process data. Instead of waiting for variability to affect quality, the aim is to predict and correct disturbances beforehand. Ashish Gupta sees greater integration of DCS, QCS, advanced process control, process historians and analytics as the next stage of automation. Such integration can help identify process deviations earlier and enable corrective action before they develop into quality or production problems. “For example, instead of waiting for GSM or moisture to move outside the target and then correcting it, an integrated control system can identify changes in consistency, stock flow, steam conditions or machine speed that are likely to cause the deviation and initiate corrective action,” says Ashish Gupta. The reason advanced control is particularly relevant to papermaking is that many variables interact and some processes have substantial delays. Ganesh Balakrishna points to processes with 15–45-minute or longer lag

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PROCESS VARIABILITY MINIMISATION

times, such as continuous digesters and bleaching towers, as well as the cross-coupling between CD moisture, basis weight and steam pressure. MPC can therefore consider several variables simultaneously and calculate corrective action while respecting process constraints, rather than allowing individual loops to respond independently. “In paper machine applications, MPC has demonstrated measurable benefits by reducing machine-direction (MD) moisture variability. Also, across operating paper machine Quality Control Systems (QCS), coordinated multivariable control has reduced MD moisture variation by 40%, enabling a target shift of +0.6% moisture in finished paper while maintaining product specifications,” says Ganesh Balakrishna. “This is resulting in reduced drying energy consumption and improved profitability.” The next layer is AI and machine learning. But the industry’s views suggest that AI should not be portrayed as replacing APC, MPC or DCS. Rather, it is increasingly being positioned above the control layer, identifying patterns and relationships that conventional control may not capture. Ganesh Balakrishna describes AI as “the real-time predictive layer above MPC,” identifying non-linear patterns across multi-departmental datasets. Ashish Gupta sees AI and ML as a predictive intelligence layer above DCS, QCS and APC, capable of providing early warnings of instability, predicting quality characteristics and identifying patterns associated with web breaks or quality drift. Ruchika Garg, Director, Ruchira Papers, identifies practical applications including predictive quality control for basis weight, moisture and calliper, predictive maintenance and anomaly detection. Ashok Kumar points to another potential application of AI/ML: historical production data can be used to identify settings associated with good results and recommend or automatically apply them when the same grade is produced again. These settings can range from headbox dilution and vacuum to steam pressure and sectionaldrive draw. But prediction depends on something more basic: the mill must first be able to see what is happening.

Seeing the Variation: Measurement, Data and the Digital Control Loop

Effective control architecture requires reliable information. Better algorithms cannot compensate for poor

20 | Aug-Sep 2026

measurements. Modern QCS systems can continuously measure basis weight, moisture, calliper, ash and colour, while smart instrumentation and machine vision extend visibility into process conditions and surface defects. Ashish Gupta notes, “At Emami Paper Mills, we consider reliable measurement to be the foundation of automation. Once a parameter can be measured accurately and consistently, it becomes possible to move from manual correction towards closed-loop control.” Sneh Patel, Chief Operating Officer, JMC Paper Tech puts the principle more bluntly: “You cannot effectively control what you cannot reliably measure.” This perspective is important because it identifies measurement quality, not simply automation, as a continuing constraint. An incorrectly calibrated consistency transmitter, unreliable flowmeter or poor laboratory data can undermine an otherwise sophisticated control algorithm. SVR Krishnan describes a transition from process experts manually adjusting the machine after analysing laboratory reports towards online QCS measurements, virtual measurements and real-time process monitoring and quality-management systems. Feedforward control can use measurements at an earlier process stage to provide predictive information to a later stage before the variation reaches the product. Yet the measurement gap has not disappeared. Abiali Jani, Director, Jani Sales, identifies fibre quality, refining efficiency, wet-end chemistry and sheet formation as areas where online measurement remains less developed and where mills continue to depend on laboratory testing or operator experience. Ruchika Garg similarly points to limited online measurement of fibre characteristics, wet-end chemistry and retention efficiency, while pitch, stickies and deposits remain difficult to detect before they affect the process. She also identifies a second problem: many mills still have isolated DCS, QCS, PLC and condition-monitoring systems, limiting plant-wide analytics. Kumar Jayant describes the use of real-time virtual sensors at TNPL. Process data such as pressure, temperature and flow are used to estimate properties that are otherwise difficult to measure continuously. An AI-driven soft sensor, for example, can estimate drainage capability from refiner power, stock flow and consistency rather than waiting for periodic laboratory testing. The effectiveness of that architecture ultimately has to appear in the product and the mill’s operating results.

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PROCESS VARIABILITY MINIMISATION

Assessing Outcomes: Quality, Runnability and Efficiency

The ultimate test of improved control is not the sophistication of the control system. It is whether the mill produces more consistent paper while running more reliably and consuming fewer resources. The most visible quality parameters are basis weight, moisture and calliper, but the interviews also point to formation, ash, strength, colour, stiffness, ply bond and reel quality. SVR Krishnan identifies basis weight, moisture, calliper, ply bond, bulk and stiffness as key indicators of paper/paperboard variability, with weight and moisture among the most critical. Abiali Jani also points to weight, moisture, calliper, ash, formation, thickness profile and reel quality as parameters benefiting most from automation, advanced process control and integrated process data. The relationship between tighter control and product quality is evident in Ashok Kumar’s account. The control systems he describes continuously monitor process variables and can adjust thick- and thin-stock flows or steam pressure when deviations occur. Ruchika Garg reports that APC/MPC applications can produce tighter CD/MD profiles, improved grade-change performance and lower break frequency, alongside reported reductions in fibre, steam and refining energy consumption. The efficiency effect is particularly important because a narrower variation band can allow a mill to operate closer to its specification or process limits without increasing the risk of off-specification production. JMC explains that reducing standard deviation around the target can enable higher production, lower fibre and steam consumption and fewer breaks. Drives and motion control are another part of process stability. They are not a separate automation story but an important means of controlling physical variability in speed, tension and synchronisation. SVR Krishnan reports that advanced frequency drives, sensor less vector drives and direct-drive motors can eliminate backlash and slippage, while high-speed communication helps synchronise multiple machine sections. The reported result is more precise speed and tension control and fewer web breaks and instances of product variability. Ashish Gupta similarly regards sectional AC drives, electronic line-shafting, torque control and improved tension control as integral to overall process automation, helping maintain accurate draws, speed relationships and

22 | Aug-Sep 2026

web tension. At TNPL, these controls also link paper-machine performance with upstream furnish and approach-flow conditions. TNPL links furnish stabilisation, approachflow consistency, CD profile control and moisture management to fibre and steam utilisation. It reports that improved structural uniformity allows a higher average reel moisture target, with a 0.5% increase in moisture potentially generating fibre and drying-energy savings. That is why the focus is increasingly shifting from improving averages to reducing variation around those averages.

Implementation Challenges: Systems, Skills and Integration

Implementing advanced control requires more than installing APC or AI-based systems. In many cases, the first requirement is considerably less glamorous: reliable instrumentation, clean data and sound basic control. Emami’s approach is explicit. It advocates strengthening instrumentation, basic control loops and data quality before progressively building advanced-control capabilities, noting that APC/MPC can perform only as well as the measurements and basic control infrastructure supporting them. Abiali Jani identifies the principal practical obstacles as legacy control systems, poor or missing process data, outdated instrumentation and insufficient integration between DCS, QCS and other plant systems. Workforce readiness is another factor: operators and maintenance personnel need training to work effectively with advanced automation and AI. Ruchika Garg makes a similar observation about isolated automation systems, while Sneh Patel of JMC Tech broadens the issue to data architecture and organisational integration. Legacy PLC/DCS systems, disconnected databases, inconsistent tag naming, unreliable sensors, insufficient historical data and manual laboratory records can all restrict the value that advanced analytics can extract. Advanced automation also changes the operator’s role. Rather than disappearing from the process, the operator increasingly becomes a supervisor of a more automated process, dealing with abnormal conditions, troubleshooting, grade changes and decisions that require contextual knowledge. Jagjeet Singh Khanna describes the transition as a move towards “process supervision and exception

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PROCESS VARIABILITY MINIMISATION

management.” Ashish Gupta similarly stresses that the objective is not to replace the operator, but to provide better information, faster response and more consistent control. Sneh Patel adds an important qualification: automation should not become a black box. Operators need to understand why a system is recommending or making a particular change, and the strongest operating environment combines AI’s analytical capability with the practical knowledge of experienced papermakers. Effective implementation therefore depends on system maturity as well as technology.

sensors, AI overlays on MPC, anomaly detection and high-frequency analytics. Other mills place greater emphasis on selective and pragmatic AI adoption. Ashish Gupta argues that AI should be introduced selectively and pragmatically, with reliable instrumentation, clean data, process knowledge and operator validation preceding sophisticated applications. The objective is to keep the process closer to its optimum despite disturbances.

The preceding examples point to the importance of integrating control systems, data and process knowledge rather than treating them as separate functions.

Sneh Patel, JMC Paper Tech captures the distinction well: “The greatest benefit is often not simply a higher average production rate. It is the reduction in standard deviation around the target.” The statement captures the relationship between process variability, production and resource efficiency.

TNPL’s description of this progression is particularly ambitious: from single-loop control to multivariable control, from reactive feedback to proactive feedforward, and from isolated automation islands to mill-wide orchestration. Its proposed architecture includes virtual

The extent of the benefit depends on reliable instrumentation, quality data, integrated systems and process knowledge. For mills, the objective remains straightforward: consistent paper quality, stable machine operation and efficient use of fibre, chemicals and energy.

Integrating Control, Data and Process Knowledge

23 | Aug-Sep 2026

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PROCESS VARIABILITY MINIMISATION

Pudumjee Paper Products Beyond Automation: Pudumjee Paper Products Achieving Process Stability Through Intelligent Control Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains.

Dr. Ashok Kumar, Executive Director, Pudumjee Paper Products Limited

In an exclusive interview with Paper Mart, Dr. Ashok Kumar, Executive Director, Pudumjee Paper Products Limited, highlights the shift from conventional automation to intelligent process control systems to attain greater process stability and product consistency. He emphasises the role of Advanced Process Control (APC), Model Predictive Control (MPC), Artificial Intelligence (AI), and Machine Learning (ML) and other emerging technologies in predicting and controlling process variability, improving operational efficiency and enhancing paper quality. He also shares insights from a recent project involving replacing a conventional hydraulic headbox with a modern dilution control headbox integrated with the approach flow system, which substantially reduced variability and improved quality consistency.

24 | Aug-Sep 2026

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Ashok Kumar: In all sections of the paper manufacturing process, process variations happen continuously because several process parameters and operating conditions keep changing. These variations depend on the specific section of the manufacturing operation. At times, even small variations in one section can significantly affect the subsequent sections of the paper machine, as all the processes are integrated. On a paper machine, such variations can lead to quality problems, runnability issues resulting in sheet breaks, higher energy consumption, reduced production efficiency and increased overall losses.

PM: How has the approach to controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples. AK: Earlier, control systems were primarily used to control one process variable at a time. Today, modern control systems can monitor a large number of process variables simultaneously and understand how they influence one another. Suppliers are integrating Advanced Process Control (APC), Model Predictive Control (MPC), Artificial Intelligence (AI), and Machine Learning

PROCESS VARIABILITY MINIMISATION

Integrated automation and process data have transformed paper production from a process that primarily reacts to problems into one that can predict and prevent them. (ML), along with other emerging technologies, to predict and control process variations before they become major problems affecting overall operational efficiency and product quality.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains? AK: Advanced control systems can distinguish whether a problem originates from the process or the control system and respond accordingly. This helps maintain process stability while reducing product variation and process disturbances. By utilising the experience from many installations, suppliers of these systems have developed control models that can recognise unusual process behaviour and help correct the problem before it affects production.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?

AK: Advanced technologies, such as AI and Machine Learning (ML), can detect unusual process behaviour before it affects paper quality or equipment problems. They can also estimate important process values that cannot be measured continuously. By analysing data from previous production runs, the system learns which settings give the best results and recommends or automatically applies those settings when the same grade is produced again. These settings, for example, may include parameters such as headbox dilution valve positions,

25 | Aug-Sep 2026

vacuum controls, steam pressure settings, sectional drive draw and many other important process parameters.

AK: Modern paper machines use various online measuring systems. These include Quality Control Systems (QCS), sheet formation index measurement, fibre orientation measurement, vibration monitoring, control valve diagnostics, flow measurement devices, machine vision cameras, infrared sensors, felt and wire tensions, colour and gloss sensors that continuously monitor both the process and paper quality. These systems detect process variations in real time, enabling immediate corrective actions. Advanced control systems automatically tune control loops, optimise performance, and detect operational limitations. Today’s paper machines are highly automated, as it is not possible to manufacture such a thin sheet of paper consistently without having advanced process measurement and control.

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over the years. Modern digital AC and DC drives provide better speed regulation, torque control, and web tension control, thereby improving machine stability. The use of regenerative drives also improves energy efficiency. Improved drive performance helps reduce sheet breaks and ensures the production of more consistent paper quality. However, digital drives pose a threat of power quality problems, which makes it essential to take necessary measures to mitigate power quality disturbances and maintain optimal drive performance.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most? AK: Integrated automation enables different sections of the paper machine to communicate with each other. Process data is shared across the machine, allowing corrective actions to be taken before defects develop. If systems are not integrated, many opportunities for optimisation are lost. Integrated automation and process data have transformed paper production from a process that primarily reacts to problems into one that can predict and prevent them. Among the various quality parameters, basis weight, moisture profile, ash and calliper have improved the most because they can be measured continuously and controlled automatically through closed-loop systems. This helps maintain consistent paper quality and makes the production process more stable and efficient.

PROCESS VARIABILITY MINIMISATION

Further improvements will come from better integration of automation systems, wider use of advanced process control systems, intelligent sensors, data analysis, and upgradation of older control systems with modern technology. PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?

AK: As automation becomes more advanced, the operator’s role is also changing. Instead of making frequent manual adjustments, operators now supervise automatic control systems, monitor process performance and system alarms & instructions, handle abnormal situations, and make decisions based on real-time process information and system recommendations. To realise the full benefits of advanced automation, mills also need trained personnel who understand process analysis, advanced process control, data interpretation, AI-based tools, and digital troubleshooting. In many cases, operator training is as important as investing in new technology.

PM: What typically prevents a mill from achieving the full benefits of advanced automation and intelligent control? Please tell us more about issues such as legacy systems, data quality, system integration, instrumentation, workforce capabilities, etc. AK: Many mills still face challenges when implementing advanced automation. Older control systems, disconnected equipment, incompatible communication protocols, limited instrumentation, poor-quality process data, cybersecurity requirements, and a shortage of skilled personnel all reduce the effectiveness of implementing advanced control

26 | Aug-Sep 2026

systems. Reliable measurements and comprehensive process data are essential for successful implementation of advanced automation applications. A clear understanding and transparency between the system supplier and the mill personnel involved in the implementation is crucial for the successful and timely project execution.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next? AK: One of our recent projects involved replacing a conventional hydraulic headbox with a modern dilution control headbox integrated with the approach flow system. The primary objective was to improve cross-direction (CD) basis weight control by reducing profile variations across the machine width. The dilution control headbox adjusts stock consistency across the machine width more accurately than the conventional system. This produces a more uniform basis weight profile, improves paper formation and fibre orientation, and thus improves overall process stability. After commissioning the new system, we achieved better sheet formation, a significant reduction in CD basis weight variation, and a clear improvement in the 2-sigma profile. The machine now operates under more stable and repeatable conditions, resulting in more consistent product quality, reduced process fluctuations, and improved machine performance. This project

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clearly demonstrated the advantages of dilution control headbox technology in improving paper machine efficiency and product consistency. Overall, modern automation has helped paper mills to reduce their process variability, resulting in improvement of paper quality and consistent production of highquality products. This has led to cost savings by reducing fibre consumption, chemical and energy usage, improving machine uptime, and reducing waste. In future, further improvements will come from better integration of automation systems, wider use of advanced process control systems, intelligent sensors, data analysis, and upgradation of older control systems with modern technology. The Indian paper industry has made significant progress in improving the level of automation across its operations. Today, most paper mills are implementing this strategy in their own way to achieve consistency of automation in operational processes to deliver quality products with the desired quality attributes.

PROCESS VARIABILITY MINIMISATION

Seshasayee Paper and Boards: From Single-Loop PID Control to Integrated Autonomous Control In an exclusive interview with Paper Mart, Mr. Ganesh Balakrishna Bhadti, Executive Director (Operations & Projects), Seshasayee Paper and Boards Limited, shares that the transition from traditional PID-based control to integrated and autonomous control is reshaping process stability across paper mills. Today, the integration of DCS, APC, QCS, online analysers and AI-based predictive analytics is enabling mills to respond more proactively to process variations. At Seshasayee Paper and Boards, APC implementation in the pulp mill has helped minimise bleaching cost, brightness variation and optimise bleach chemical demand, while AI is being implemented for online monitoring of steam trap controls.

Paper Mart: Process variability remains a central challenge in integrated paper manufacturing. Where does variability remain most persistent today, how does it impact quality and performance, and which specific process stages or parameters offer the greatest measurable gains when stabilised? Ganesh Bhadti: In an integrated mill, variability compounds non-linearly across the value chain, significantly impacting quality, quantity, and bottomline costs, depending on input availability and price. For example, an uncorrected 1.5 Kappa unit variation from the digester translates into a 10–15% shift in bleaching chemical demand, wet-end charge instability, and a 3–5% increase in web breaks on the paper machine hours later.

Mr. Ganesh Balakrishna Bhadti, Executive Director (Operations & Projects), Seshasayee Paper and Boards Limited

28 | Aug-Sep 2026

Variability can originate from raw materials, equipment, operations, operating crews and operating systems. However, the criticality and impact of these variables are evident in the pulp mill and stock preparation areas, which eventually influence machine runnability, cost and quality. Based on operational metrics across integrated facilities, variability remains most persistent across eight primary zones:

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Where Values Lead to Success PAPER BAG PAPER BAG

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PROCESS VARIABILITY MINIMISATION Rank

Source of Variability

Impact on Mill Performance

Digester Kappa Variation

Bleaching cost, quality stability

Wet-End Retention Variation

Chemical cost, cleanliness, runnability

Basis Weight & Moisture Control

Product quality, customer complaints

Refining/Freeness Variation

Strength and formation

Steam & Dryer Variability

Moisture quality, energy cost

Drive/Draw Variability

Web breaks and OEE

Chip Moisture Variation

Yield, pulping consistency

Black Liquor Solids Variation

Energy efficiency and recovery

Table: Key High-Impact Variability Sources (Priority Order) The largest contributors to mill-wide variability are raw material variation, particularly chip moisture, digester Kappa variability, refining consistency, wet-end chemistry stability, basis weight and moisture control, and dryer/ drive stability. Among these, Kappa number control, wet-end retention, basis weight/moisture control, and chip moisture stabilisation typically provide the highest measurable economic gains because their effects cascade through the entire integrated mill process.

process targets. For example, instead of waiting hours for manual freeness lab tests to adjust refiner disc gaps, online freeness sensors integrated with AI continuously optimise specific energy against fibre quality in real time. In our pulp mill, the implementation of APC has helped minimise brightness variation and optimise bleach chemical demand. On the energy front, we are currently implementing AI-based online monitoring of steam trap controls to identify and address heat losses.

Stabilising these parameters delivers immediate gains, including better machine runnability, fewer web breaks, and optimised chemical consumption.

Overall, variability originating from raw materials and equipment can be minimised through reduced manual intervention and the adoption of predictive control. The key to further improvement is accurately predicting future process conditions and taking corrective action in advance rather than reacting to deviations after they occur. Advanced technologies such as AI, APC, and DCS are helping mills achieve this objective and improve process stability.

PM: How has the approach to controlling process variability changed in recent years? How are mills moving beyond conventional automation and feedback control to achieve greater stability?

GB: The transition from traditional single-loop PID control to integrated autonomous control has fundamentally changed the way we approach process stability and key performance benchmarks. Historically, mills relied on reactive Single-Input, Single-Output (SISO) feedback loops and operator intervention, often after laboratory results became available. Today, mills combine island-level Distributed Control Systems (DCS) with Advanced Process Control (APC), online analysers, Quality Control Systems (QCS), and cloud-based AI predictive analytics to dynamically adjust

PM: How are Advanced Process Control (APC) and Model Predictive Control (MPC) being applied to reduce process variability, and where have they delivered measurable gains?

GB: The true strength of Model Predictive Control (MPC) lies in its ability to handle processes with long lag times of 15–45 minutes or more, such as continuous digesters and bleaching towers, as well as processes with significant cross-coupling, such as interactions between crossdirection (CD) moisture, basis weight and steam pressure.

By minimising process oscillations and keeping operations closer to optimal targets, APC and MPC improve runnability, increase production rates, reduce operating costs, and deliver more consistent product quality across the entire integrated mill. 30 | Aug-Sep 2026

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PROCESS VARIABILITY MINIMISATION

APC and MPC are increasingly being deployed to address some of the most persistent sources of process variability in integrated pulp and paper mills, particularly in processes characterised by long dead times, strong process interactions, and frequent disturbances. Their greatest value lies in managing complex operations such as continuous digesters, bleaching operations, stock preparation systems and paper machine quality control, where traditional PID-based control often struggles to maintain stability. Variability typically originates from fluctuations in raw material properties such as chip moisture and fibre quality, digester Kappa number variation, refining consistency, wet-end chemistry instability, steam pressure fluctuations, and interactions between basis weight, moisture and machine speed. These disturbances propagate throughout the production chain, resulting in increased chemical consumption, reduced quality consistency, higher web break frequency, and lower machine efficiency. MPC reduces this variability by simultaneously controlling multiple interrelated process variables, predicting future process behaviour, and proactively compensating for disturbances before they impact product quality. In paper machine applications, MPC has demonstrated

32 | Aug-Sep 2026

measurable benefits by reducing machine-direction (MD) moisture variability. Also, across operating paper machine Quality Control Systems (QCS), coordinated multivariable control has reduced MD moisture variation by 40%, enabling a target shift of +0.6% moisture in finished paper while maintaining product specifications. This is resulting in reduced drying energy consumption and improved profitability. Similar gains have been achieved through tighter Kappa control, improved bleaching chemical efficiency, stabilised refining performance, enhanced wet-end retention, and improved basis weight and moisture profiles. By minimising process oscillations and keeping operations closer to optimal targets, APC and MPC improve runnability, increase production rates, reduce operating costs, and deliver more consistent product quality across the entire integrated mill.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality? GB: AI operates as the real-time predictive layer above MPC, identifying non-linear patterns across multidepartmental datasets that may not be detected by human operators or standard algorithms.

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Today, mills combine island-level Distributed Control Systems (DCS) with Advanced Process Control (APC), online analysers, Quality Control Systems (QCS), and cloud-based AI predictive analytics to dynamically adjust process targets. Practical applications and quantified impact of AI and Machine Learning (ML): •

•

Predictive Web Break Prevention: By analysing over 200 high-frequency signal streams, including vibration, draw tension, headbox pressure variations, vacuum levels, and QCS profiles, neural network models predict sheet break risks 3–7 minutes before occurrence with an 84–89% accuracy rate. Automated target adjustments can reduce actual web breaks by 25–35%. Soft Sensors for Unmeasured Variables: Machine learning algorithms estimate real-time continuous Kappa numbers, achieving a correlation (R^2) of 0.93 against lab tests, as well as wet-end charge demand. This can reduce the latency associated with laboratory testing from 120 minutes to virtually zero. Equipment Health Monitoring & Predictive Maintenance: Vibration analytics combined with thermal profiling detect bearing wear and valve hysteresis 30–45 days prior to functional failure, helping reduce total unplanned mill downtime from an industry average of 4.5% down to <1.8%.

Looking ahead, AI in manufacturing will focus heavily on implementing deep learning, computer vision, digital twins, and LLM-assisted decision tools to convert these predictions into actionable shop-floor routines. The objective is to move beyond simply predicting deviations towards enabling faster and more informed corrective action before they affect production or product quality.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of variation? Where do significant measurement or data gaps still remain?

GB: Modern online measurement, smart instrumentation and Quality Control Systems (QCS) are enabling mills to detect and respond to process variation in real time, supporting tighter and more responsive process control. Modern QCS frame scanners measure at scan speeds up to 500 mm/sec with spatial resolution below 1 mm, enabling tight process control loops and more precise

34 | Aug-Sep 2026

monitoring of paper quality parameters. However, significant measurement and data gaps still remain in several areas: •

Freeness (SR/CSF): Online freeness analysers have improved, but sensor fouling remains an issue and requires recalibration every fortnight.

•

Wet-End Chemistry/Micro-Stickies: Charge analysers provide good trend monitoring, but absolute sticky quantification of stickies still relies on laboratory extraction methods, with a 3–4 hour lead time.

•

Finished Paper Physicals: Structural metrics like Shortspan Compressive Test (SCT), Ring Crush Test (RCT), and internal bond strength (Scott Bond) still depend on physical testing in climate-controlled laboratories maintained at 23°C, 50% RH.

•

Fibre morphology: Further advancements are required in fibre morphology, which remains a largely untapped area. Fibre morphology could provide valuable information on final paper properties and enable furnish optimisation while maintaining targeted strength level.

PM: Drives and motion control directly influence speed, tension, synchronisation, and machine stability. How are newer drive technologies helping mills reduce variability across the machine? GB: Modern paper machines operating at 1,000–1,500 m/min move the paper web at speeds exceeding 80 km/h. At these velocities, dynamic speed matching across machine sections must be instantaneous. •

Speed Synchronisation: Modern Direct Drive Systems (DDS) using AC Variable Frequency Drives (VFDs) over high-speed optical fieldbuses, such as PROFINET IRT and EtherCAT, maintain section-to-section speed accuracy within ±0.001%.

•

Draw Tension Control: Real-time load-sharing algorithms control web draws to precision tolerances of ±0.05 N/m, reducing strain-induced micro-fractures in the sheet.

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PROCESS VARIABILITY MINIMISATION

The proposed futuristic steps include a Cloud-Edge Integrated Predictive Asset and Process Analytics Platform across our pulp and paper operations, optimisation of soot blowing in the recovery boiler, optimisation of the steam and power distribution system, and AI-based safety systems. •

Reel Hardness Optimisation: Coordinated torque control of the primary and secondary reel arms helps eliminate nip-pressure variations, reducing rollstructure defects, such as starring and crepe wrinkles, at the winder by 80–90%.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality, and which quality parameters have benefited most?

GB: Integrating DCS, QCS, drives, pulp mill analytics, and ERP systems removes operational buffers between departments, directly contributing to improved bottom-line profitability and quality consistency. Making integrated information readily available in the format required by users improves transparency and troubleshooting efficiency. It also reduces dependency on specific individuals by capturing and sharing operational knowledge. By transferring the experience of operators into digital systems, every operator can benefit from process-engineering expertise and make more informed decisions. All these operational improvements are contributing to improvements in mill efficiency, reductions in specific energy consumption, yield improvements, and reductions in specific water consumption.

wherein the time allocation is largely being directed towards validation of AI results, process optimisation, root cause analysis and good maintenance practices. In the system improvements part, we are witnessing a reduction in the number of alarms to operators on operational deviations that remain within safe cognitive limits. Real-time decision-support dashboards reduce the mean time to detect and correct process drifts (MTTD/ MTTR) within a few minutes.

PM: What typically prevents a mill from achieving the full benefits of advanced automation and intelligent control?

GB: There are several technical and organisational friction points that can prevent mills from realising the projected benefits of automation and intelligent control. On the technical front, instrumentation and calibration drift is the first challenge. The second is legacy systems and fragmentation, where over 60% of operating paper mills run a mixture of legacy platforms. The third is the data quality and silos, and the final is the workforce capability and trust. When operators lack training or trust in “black-box” models, override rates can exceed 35%, potentially returning the process to suboptimal manual control limits.

The quality parameters that have benefited most include GSM and moisture profiles, where CD/MD profile variance has been reduced by more than 60%. Caliper and smoothness have also improved contributing to more uniform reel hardness and surface printability. In addition, improved control of ash distribution and formation enables optimisation of strength-to-filler ratios with minimal chemical consumption.

From an organisational perspective, advanced automation needs a mindset change at the leadership level, which must then be transferred to the different hierarchy of the mill.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?

GB: As mentioned earlier, the implementation of APC in our bleach plant operations has provided significant leverage in reducing bleaching chemical cost while maintaining consistent quality through real-time closedloop brightness control. The proposed futuristic steps include a Cloud-Edge Integrated Predictive Asset and Process Analytics Platform across our pulp and paper operations, optimisation of soot blowing in the recovery boiler, optimisation of the steam and power distribution system, and AI-based safety systems.

GB: Automation is shifting the operator’s role from manual execution towards high-level process management, decision-making and exception handling. We are witnessing a significant change in how operators allocate their time. Traditionally, a substantial portion of an operator’s time was spent on manual adjustments, which is now shifted towards an autonomous mill,

36 | Aug-Sep 2026

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next?

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PROCESS VARIABILITY MINIMISATION

TNPL:

From Single-Loop Control to Mill-Wide Process Intelligence Process variability remains most persistent in the wet-end approach flow, press section and cross-machine direction profiles. In an exclusive interaction with Paper Mart, Mr. Kumar Jayant, Additional Chief Secretary/Chairman & Managing Director, Tamil Nadu Newsprint & Papers Ltd (TNPL), discusses TNPL’s shift from reactive, single-loop control to integrated, predictive automation through APC, MPC, AI/ML and advanced measurement systems. He highlights the transition towards a highly integrated “Smart Mill” infrastructure through the integration of the Valmet Auto Paper Lab with ERP and AI, advanced fibre line upgrades and millwide APC. He further elaborates on the evolving role of operators as proactive system supervisors and process strategists, while identifying wet-end stabilisation, AI/APC integration and digital reliability as key investment priorities for the next phase of mill automation. Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains.

Kumar Jayant: In modern paper manufacturing, process variability remains most persistent in the wet-end approach flow system and the press section. Because papermaking is a high-speed, continuous fluid-to-solid transformation, small upstream fluctuations multiply downstream. This forces mills to run defensively, away from optimal limits, driving up costs and degrading product consistency. Key areas of process variability and their impact: • Wet End Approach Flow & Stock Preparation: Fluctuations in stock consistency, raw material composition and chemical additive feeds remain the key issues in the wet-end approach flow and stock preparation. The variability persists because multi-variable interactions between retention aids, fillers and starches make realtime chemistry control highly stochastic.

Mr. Kumar Jayant, Additional Chief Secretary/ Chairman & Managing Director, Tamil Nadu Newsprint & Papers Ltd (TNPL)

• Cross-Machine Direction (CD) Profiles: Uneven basis weight, moisture, and caliper (thickness) across the wide width of the machine are the key issues in CD profiles. This variability persists due to online Quality Control System (QCS) scanners measuring the moving web in a diagonal “Z”-shaped path, blending machine-direction (MD) and CD data together, and making exact separation difficult. Slice-lip warping or thermal expansion across the headbox also causes localised profile imbalances. • The Press Section (Nip Profile Dynamics): Ageing of the press felts, mechanical roll wear, improper crown settings and felt

38 | Aug-Sep 2026

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YOUR CONCERN, OUR EXPERTISE Engineering | Surveying | Solutions We are a company that started almost two decades ago with a vision to provide practical and long lasting solutions to the burgeoning paper industry in India by creating a fusion of chemistry applications and local industry environment and requirements.

INDUSTRIES WE SERVE Developing Green & Cost Effective Solutions For Water Intensive Industries Packaging & Board

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Surface Additives

Dispersants

Felt Cleaning and Conditioning Program

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PROCESS VARIABILITY MINIMISATION

choking are the key issues causing variability in the press section. The variability persists because the type of furnish (more recycled fibre) and high ash content lead to uneven moisture, resulting in a non-uniform CD moisture profile. This may lead to sheet breaks in the dryer section, causing immediate downtime. • The Drying Section: Uneven thermal profiles, edge shrinkage and variable condensate removal in drying cylinders are key issues in the drying section causing variability. The reasons include web edges drying faster and shrinking more than the centre, creating persistent cross-directional tension gradients.

KJ: Key transitions in process control from the past to the present include • From Single-Loop to Multi-Variable Control: Traditional PID loops handle one variable (e.g., valve position) at a time. Modern Model Predictive Control (MPC) manages dozens of interacting variables simultaneously, accounting for long process time delays.

In the high-speed, continuous operations of Tamil Nadu Newsprint and Papers Limited (TNPL), process variability remains most persistent within the wet-end approach flow system and across the Cross-Machine Direction (CD) profiles of the paper and packaging board machines. Because TNPL utilises a unique, delicate agriculturalresidue, bagasse-heavy furnish mix, the wet-web strength of the paper sheet is inherently lower than pure softwood kraft pulp. Consequently, small hydraulic, chemical or thermal variations propagate downstream rapidly, triggering quality defects or costly machine downtime.

• From Reactive Feedback to Proactive Feedforward: Instead of waiting for a defect to reach the QCS scanner at the end of the machine, mills now measure upstream disturbances and adjust parameters before the error ever forms in the sheet.

Key parameters where greater stability can deliver the most value: • Pulp Washing and Chemical Cooking Uniformity: By targeting specific parameters, TNPL stabilises its production lines and utilising Valmet Continuous Cooking G3 and TwinRoll Press technology stabilises pulp cleanliness and Kappa number variations. Tighter control here optimises bleach plant chemical dosing, directly reducing chemical consumption and specific steam demands in the pulping line.

Modern frameworks that are replacing conventional automation are: • Real-Time Virtual Sensors (Soft Sensors): Traditional physical sensors only provide measurements after a process is complete or at specific physical locations, whereas soft sensors use real-time process data (such as pressure, temperature and flow) fed into mathematical models to estimate product qualities instantly. For example, instead of waiting for a destructive lab test every two hours to check freeness (fibre drainage), a mill uses an AI-driven soft sensor. This model calculates drainage capability continuously based on refiner power, stock flow, and consistency, allowing operators to adjust refining energy on the fly.

• Approach Flow Stock Consistency: Maintaining consistency variations below ±0.02% stabilises headbox delivery. This minimises machine-direction basis weight swings, enabling the mill to safely shift production targets closer to the lower allowable limit, reducing raw fibre usage by 1% to 2%. • Headbox Jet-to-Wire Speed Ratio: Locking down this hydraulic parameter improves fibre orientation, resulting in uniform cross-directional tensile ratios (MD:CD strength). • CD Moisture and Caliper Profiles: The structural uniformity allows TNPL to safely increase the average moisture target at the reel. Because water replaces fibre in the sellable tonnage, a 0.5% moisture target increase drives major fibre savings while lowering specific steam consumption in the drying cylinders.

40 | Aug-Sep 2026

• From Localised Islands to Mill-Wide Orchestration: Automation no longer stops at individual machine sections. Mills now link the pulping, chemical additive, and paper machine stages into a singular, interconnected control strategy.

• Model Predictive Control (MPC) with AI Overlays: Classic MPC manages highly coupled variables, but it can struggle when grade changes or raw material properties shift drastically. Modern systems overlay Machine Learning (ML) on top of MPC to adapt the underlying models dynamically without human intervention. During a grade change, such as switching from 60 gsm to 80 gsm paper, an adaptive MPC calculates the ideal trajectories for stock flow, steam pressure, and machine speed simultaneously. This reduces grade change transition times and the associated off-spec waste by up to 50%. • Proactive Machine Learning for Anomaly Detection:

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PROCESS VARIABILITY MINIMISATION

Instead of triggering an alarm when a variable passes a dangerous threshold, AI models analyse subtle correlations across hundreds of historical data tags to predict failures before they happen. To prevent sheet breaks, an ML model continuously monitors wire tension, wet-end chemical retention and dryer section drive currents. If it recognises a data pattern that historically preceded a break, it alerts operators 15 to 30 minutes in advance, allowing them to adjust chemical dosage or machine speed to stabilise the web. • Edge Computing and High-Frequency Analytics: Traditional Distributed Control Systems (DCS) process data in 1-second intervals, potentially missing highfrequency hydraulic or mechanical vibrations, whereas edge computing devices process data at millisecond speeds directly at the source. High-speed pressure transducers in the headbox approach-flow piping capture micro-pulsations from screens or pumps. Fast Fourier Transform (FFT) analytics isolate the root cause of these pulsations, adjusting wet-end dilution valves at a sub-second level to neutralise basis weight barring before it affects the sheet. Concrete examples of advanced control in action at TNPL include: • Integrated Valmet Auto Paper Lab Framework: TNPL integrated its Valmet Auto Paper Lab directly into its DCS and SAP ERP networks. The automated laboratory tests structural parameters such as tensile strength, smoothness, and porosity, enabling automated quality monitoring and feedback control. • Advanced Fibre Line Upgrades (Valmet Continuous

41 | Aug-Sep 2026

Cooking G3): TNPL’s primary furnish consists of sugarcane bagasse and agricultural residues. These materials suffer from natural, seasonal variations in fibre morphology. To address this variability, TNPL modernised its hardwood kraft pulp production using Valmet Continuous Cooking G3 and TwinRoll Press technology. Advanced process control (APC) software models the chemical cooking and bleaching timeline. It continuously adjusts chemical charging, temperatures, and wash-zone fluid dynamics based on the incoming raw material mix. This ensures highly uniform pulp quality and washing cleanliness at the source, preventing fibre variation from disrupting downstream processes.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?

KJ: In paper mills, Advanced Process Control (APC) and Model Predictive Control (MPC) are applied by wrapping an intelligent automation layer over traditional Distributed Control Systems (DCS) and PID loops. Because papermaking involves extreme time delays (dead times), complex multi-variable interactions, and non-linear dynamics, standard PID controllers often fail, forcing operators to revert to manual control. MPC solves this by using real-time dynamic mathematical models to anticipate process trajectory and proactively adjust multiple variables simultaneously. Core applications of APC and MPC at TNPL: • Optimisation of the Fibre Line and Bleaching Sequences: TNPL applies APC overlays across its pulp production

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PROCESS VARIABILITY MINIMISATION

line, specifically targeting the Valmet Continuous Cooking G3 and Elemental Chlorine Free (ECF) bleaching stages. Bleaching and cooking involve long process time delays; chemical changes made at the input stage can take over an hour to register downstream. The MPC uses predictive models to calculate the future impact of changes in raw bagasse and wood mixtures. It coordinates chemical charges, temperature profiles and extraction-stage pH levels simultaneously. This prevents the excessive chemical over-dosing that occurs under manual control when trying to compensate for unexpected raw material swings. • Wet-End Chemistry Stability and Retention Control: FirstPass Retention (FPR) of fibres and ash fillers is highly variable in multi-furnishings due to fluctuating drainage speeds and system charge dynamics. An MPC algorithm can balance the inputs of multiple variables, such as coagulant flow, retention polymer dosing and thick-stock dilution.

• Faster Grade Transitions: Grade change recovery times are reduced by adjusting the stock flow, machine speed, jet-to-wire ratios and steam pressures simultaneously, reducing off-specification transition wastes by 40% to 60%.

• Cross-Machine Direction (CD) and Machine Direction (MD) Quality Profiles: Handled through the Quality Control System (QCS), large-scale multivariable MPC manages the cross-directional profiles of basis weight, moisture and thickness (caliper). Rather than adjusting a single localised headbox dilution valve, the MPC relies on a detailed spatial interaction matrix. It isolates true MD variations from position-based CD defects, adjusting hundreds of profile actuators in real time to flatten the sheet uniformity curve.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?

Key areas where APC and MPC have delivered measurable gains: Implementing these advanced supervisory controls has yielded clear operational returns for TNPL, directly supporting market competitiveness and resource conservation. • Reduction in Profile Variability: Mills typically achieve a 30% to 50% reduction in CD moisture and basis weight 2σ (two-sigma) variability. This extreme flattening of the profile ensures uniform roll build and eliminates converting defects. • Fibre and Furnish Savings: By narrowing basis weight variability, the “target-shifting” typically reduces fibre usage by 0.5% to 1.5% while maintaining minimum strength requirements. • Increased Moisture Efficiency: Flattening the moisture profile allows operators to increase the average moisture target at the reel by 0.5% to 1.0%. Because water replaces expensive fibre in the final sellable product weight, which enables greater fibre efficiency.

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• Energy and Steam Reduction: Preventing over-drying and stabilising the dryer section steam demand reduces overall specific steam consumption by 3% to 7%.

KJ: Rather than relying on reactive automation, AI acts as a proactive overlay that forecasts and corrects process deviations before they degrade paper quality or cause machine downtime.

Real-time roles of AI/ML in modern mills involve: • Predictive Anomaly Detection (Early Warning Systems): Deep learning models ingest thousands of highfrequency data tags, including temperatures, vibrations and motor currents, simultaneously. The AI establishes a baseline for “normal” operation across all variables and flags micro-deviations that human operators cannot detect. For example, in sheet break prediction, an ML model analyses the combined interaction of wetend retention, wire tension, vacuum levels and dryer section loads. It identifies a known signature pattern of instability and alerts operators 15 to 20 minutes before a break occurs, giving them a window to adjust speed or chemical dosage. • Virtual Sensors (Continuous Quality Estimation): Vital paper qualities like tensile strength, tear and freeness can traditionally only be measured through destructive physical testing in a laboratory every few hours. ML algorithms use real-time process data to calculate these qualities continuously and make real-time strength predictions. For example, an AI model uses continuous

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PROCESS VARIABILITY MINIMISATION

inputs from the refiners, including power, flow and consistency, along with press section nip pressures and fibre characteristics, to calculate the paper’s current tensile strength index. If the predicted strength drops below the target, the AI automatically prompts the refiner control loop to add energy before offspecification paper reaches the reel. • Root Cause Analysis (RCA) and Diagnostic AI: When a quality deviation occurs, finding the root cause in a large mill is difficult. Diagnostic AI uses causal inference algorithms to scan historical data, trace the timeline of the deviation and isolate the exact source of the trouble. For instance, if a mill experiences a sudden spike in paper porosity, the AI reviews the process backwards, isolates the exact time the variance started and traces it to a specific raw material batch change in the pulp mill or a chemical pump malfunction three hours earlier. • Autonomous Optimization Overlays: AI acts as an “autopilot” layered on top of existing Distributed Control Systems (DCS) and MPC. It continuously searches for the most cost-effective operating window by balancing chemical costs, energy prices and production speed. For example, in chemical dosage optimisation, wet-end chemistry is highly variable due to changes in recycled fibre quality. A Reinforcement Learning (RL) agent adjusts retention aids and biocides in real time, maintaining perfect sheet retention while preventing chemical over-dosing, resulting in cost savings. Concrete industry examples are: • ABB Ability™ Performance Optimisation for Paper Mills: Uses predictive ML models to track sheet break risks and pinpoint exactly which section of the machine (forming, pressing, or drying) is driving the instability. • Voith OnCumulus & Papermaking 4.0: Deploys virtual sensors for parameters such as strength and ash content. Mills using this technology can run closer to lower raw material thresholds without risking quality rejection. • Solenis OPTIX™ Applied Intelligence: A machine learning platform that predicts functional product quality, such as dry strength or sizing. In wet-end applications, it has allowed mills to reduce chemical additive costs by up to 25% while stabilising quality parameters.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant

44 | Aug-Sep 2026

measurement or data gaps still remain?

KJ: Technologies enabling real-time detection and process control: • Next-Generation Quality Control Systems (QCS): Traditional scanners move slowly across the paper web, potentially missing fast-occurring variations. Modern platforms, such as the Valmet IQ Scanner, use variablespeed scanning and edge-dwell acceleration. This decouples MD and CD data much faster, allowing the system to correct profile defects before they propagate into major issues. Real-time dashboards provide instant visibility into moisture and basis weight fluctuations, enabling rapid, closed-loop corrections. • Advanced Machine Vision & Web Inspection Systems (WIS): Moving beyond legacy single-camera configurations, modern mills utilise multi-camera edgevision setups. These tools combine high-speed capture technology with specific light angles to scan 100% of the moving web continuously. The system catches micro-defects such as pinholes, slime spots, edge cuts, and colour variations at machine speeds exceeding 2,000 meters per minute. Integrating WIS with web monitoring tools allows operators to backtrack defects instantly and isolate what caused a sheet break. • Smart Instrumentation & Inline Wet-End Analysers: Rather than relying entirely on manual grab samples, modern mills place smart instruments directly into the process piping. Automated wet-end analysers continuously track total and ash retention, charge demand and drainage properties. This inline data feeds directly into the DCS, stabilising chemical dosing on a minute-by-minute basis. Current measurement and data gaps: • The Press Section Blind Spot: The press section lacks scanning equipment because the web is too wet and fragile to handle a traversing frame. Operators there cannot directly measure the moisture profile exiting the press section in real time. Mills must estimate how effectively water is being mechanically removed. If a press felt degrades unevenly, the drying section receives a non-uniform thermal load, forcing the mill to over-evaporate water at the reel. • Internal Sheet Structure and Z-Direction Strength: QCS scanners and machine vision systems look primarily at the surface of the paper. They cannot measure internal structural parameters such as Z-directional tensile strength, internal bond strength (Scott Bond) or fibre orientation throughout the sheet layer. Mills therefore still rely heavily on periodic laboratory testing or uncalibrated virtual soft sensors to guess

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PROCESS VARIABILITY MINIMISATION

internal strength. True physical failures within the sheet structure are often discovered only after the paper has reached the reel or the customer. • Real-Time Fibre Morphology Instability: While inline freeness sensors exist, they do not track rapid variations in fibre morphology such as micro-fibrillation, individual fibre length distribution, and cell wall thickness. This is especially problematic in mills utilizing high percentages of recycled waste paper. Shifting fibre quality can therefore enter the forming section unnoticed, causing unpredictable variations in drainage and sheet formation that existing feedback loops can only react to after the fact. • The Time-Delay Blur of Scanners: Because a single scanner head must weave back and forth across a massive web, it takes anywhere from 30 to 60 seconds to complete a single profile scan. Any process disturbance that occurs at a frequency faster than the scan time, such as short-term hydraulic pulsations from a headbox screen, is therefore blurred or missed entirely, causing hidden MD variations.

• Sectional Direct-Drive Systems (Eliminating Mechanical Slack): Older machines used a single large motor connected to a complex network of line-shafts, belts, clutches and open gears to power different sections, like wire, press, dryers and calender. Modern machines utilise sectional direct-drive systems, where Permanent Magnet Synchronous Motors (PMSMs) are coupled directly to the roll shafts without gearboxes. Removing mechanical transmission components eliminates backlash, torsional vibration and gear play. This ensures that the velocity command sent by the automation system matches the physical rotation of the roll instantly, eliminating micro-jerks that stretch or tear the paper web. • Ultra-Fast High-Bandwidth Inverters & Direct Torque Control (DTC): Modern Variable Speed Drives (VSDs) leverage advanced motor control algorithms like Direct Torque Control (DTC). Rather than relying on traditional pulse-width modulation (PWM) that passes through a separate speed controller loop, DTC calculates the motor’s torque and magnetic flux up to 40,000 times per second. The drive therefore reacts to load changes

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in milliseconds. For example, when a wet lump of paper enters a press nip, it causes a sudden torque spike. A DTC drive senses this load instantly and adjusts current to maintain exact speed, preventing localised web slack or tension spikes. • Common DC Bus Architectures: Multi-drive systems are engineered with a shared, common DC bus infrastructure, allowing energy to be shared globally across the entire paper machine drive network. The dryer section typically requires heavy motoring power, while the reel or unwind section might be braking and generating electricity. The common DC bus funnels the braked, regenerative energy directly back to the motoring sections. This stabilises line voltage across the mill, preventing electrical grid sags from destabilising adjacent drives or causing micro-speed fluctuations. • Advanced Motion Control Algorithms in Action Electronic Line Shaft (ELS) and Virtual Master Sync: Traditional master-slave drive configurations suffer from a cascade delay: if the first section changes speed, the second section takes a few milliseconds to react, creating a transient tension wave. Electronic Line Shafting (ELS) creates a mathematically perfect “virtual master” clock in the controller, with every drive section referencing this virtual clock simultaneously. If a speed change or grade ramp is initiated, all sections move in absolute synchronisation with zero phase lag, maintaining a consistent sheet draw. • Dynamic Tension and Draw Control (Predictive Slack Management): Paper stretches and shrinks as it transitions from 99% water at the wet end to 5% water at the reel. Motion controllers now utilise dynamic draw control. Instead of keeping speed ratios static, the controller uses load cells or optical sensors to measure web tension continuously. It dynamically alters the speed percentage (draw) between sections to keep web tension perfectly uniform, absorbing raw material variations, such as sudden shifts in fibre length or refining levels, without fracturing the sheet. Measurable operating gains: • 90%+ Reduction in Speed Variation: Modern sectional drives can maintain a steady-state speed accuracy of ±0.001%, virtually eliminating MD basis weight barring caused by speed cycles. • Drastic Decline in Tension-Induced Sheet Breaks: Stabilised web tension and instant load recovery reduce tension-related sheet breaks by 30% to 50%, boosting Overall Equipment Effectiveness (OEE).

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• Extended Mechanical Asset Life: Eliminating highfrequency torque oscillations protects expensive rolls, bearings and felts from premature wear, smoothing out the overall vibration profile of the machine

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most?

KJ: By combining high-frequency process measurements, Quality Control Systems (QCS), and advanced control loops into a single data infrastructure, mills have moved past simple manual sampling. Today, integrated data platforms allow systems to track mill-wide process adjustments and automatically execute corrections before physical variations harden into the paper web. How integrated data and automation drive quality consistency: • Closed-Loop Multi-Variable Correction: Modern mills link real-time QCS scanner data directly to wet-end chemistry and headbox actuators. Because the system understands how a change in stock preparation affects the final sheet minutes later, it continuously adjusts fibre refining, dilution valves and chemical pumps. This replaces the conventional method of operators manually making large, reactive adjustments based on lab tests. • True Machine-Direction (MD) and Cross-Machine Direction (CD) Decoupling: Integrated automation platforms use high-speed processing to separate time-based variations (MD) from position-based variations (CD) across the wide paper web. By accurately identifying the root cause of a deviation, the Distributed Control System (DCS) can execute precise corrections, such as altering total stock pump speed for MD errors or adjusting localised slice lip actuators for CD errors, without accidentally worsening adjacent areas. • Upstream Feedforward Adjustments: Integrated data structures allow the paper machine to “see” variations coming from the pulp mill or recycling plant. If a batch of recycled fibre shows a sudden drop in drainage capability, the automation system automatically slows down the machine or adjusts the wet-end retention polymer dosage before that specific batch of stock enters the headbox. Quality parameters benefiting most: The integration of advanced control systems has flattened the variation curves of several critical structural and functional paper properties, improving quality across the following parameters:

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• Moisture Content: Moisture has historically been the most volatile parameter due to uneven drying, edge shrinkage and variable press nip pressures. Modern multi-variable MPC coordinates steam pressure, machine speed and CD moisture spray booms simultaneously. Mills can reduce moisture variability by 40% to 60%. This flat profile eliminates roll-build defects like corrugations and wrinkles, while preventing downstream customer issues like paper curl, cockling and tight edges during printing. • Basis Weight (Grammage): Basis weight uniformity relies entirely on a steady water-to-fibre ratio leaving the headbox. Automated thick-stock valves, paired with high-frequency dilution control loops, neutralise short-term hydraulic and consistency variations. Total basis weight variation is minimised to negligible levels. This extreme stability allows the mill to execute “target shifting”—intentionally running production closer to the lower allowable weight limit without risking a subspecification product, directly saving raw fibre. • Caliper (Thickness) and Smoothness: Controlled at the calender stack, caliper profile consistency requires immediate thermal management. Automated QCS systems control induction heating coils or variablecrown rolls across the calender width based on realtime thickness measurements. This eliminates localized thick or thin spots, resulting in uniform roll density, excellent reel winding and superior runnability on high-speed commercial printing presses and converting lines. • Tensile and Internal Bond Strength (MD:CD Ratios): Mechanical paper strength depends on the angle and orientation of the fibres as they land on the forming wire. Automated motion control systems keep the headbox jet-to-wire speed ratio locked within micro-tolerances, regardless of overall machine speed changes. This guarantees predictable, uniform directional strength, and drastically minimises web snap risks during high-speed printing, corrugated box forming or packaging conversion.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?

KJ: As control systems become more intelligent, the papermaking operator’s role is shifting fundamentally. Operators are transitioning from reactive loop-tenders to proactive system supervisors and process strategists. Instead of manually chasing individual set points, modern operators manage the higher-level boundaries of an autonomous system. Today, the operator’s role is shifting:

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PROCESS VARIABILITY MINIMISATION

• From Reactive Tuning to Exception Management: Previously, operators constantly monitored individual PID loops. They spent their shifts manually adjusting thick stock valves, tweaking dilution slice positions, or changing steam pressures to counter process drift. Now, intelligent control systems handle these coupled variables autonomously. The operator now acts as an “exception manager”, stepping in only when the system flags an anomalous pattern it cannot resolve internally, or when a physical asset requires immediate mechanical inspection.

• Mill-Wide Systems Thinking: Because intelligent systems link fibre preparation, wet-end chemistry and the dry-end into one interconnected loop, operators must understand how a decision in one section propagates through the entire process sequence.

• From Executing Changes to Evaluating Scenarios: Earlier, during a grade change, operators manually adjusted speed, basis weight and dryer profiles in stages based on personal experience. This created wide performance variances between different shifts. Today, the automation system calculates and executes the optimal multi-variable transition trajectory. The operator’s role is to verify the boundary constraints of the new grade, such as checking raw material availability or downstream converting readiness, and authorising the system to run the transition autopilot.

KJ: Despite massive investments in Advanced Process Control (APC) and AI, many mills fail to capture the full economic benefits of these technologies. The roadblocks are rarely caused by the algorithms themselves; instead, they stem from foundational gaps in hardware, fragmented data, and human resistance. The primary barriers preventing mills from achieving full automation maturity include the following:

• From Hunting Data to Validating AI Insights: When paper strength or moisture drifted out of specification, operators had to wait for laboratory results, examine historical trends and determine the root cause. But today, AI-driven diagnostic platforms analyse thousands of data tags instantly. Instead of hunting for the problem, the operator reviews a prioritised list of recommendations generated by the system, such as a “92% probability that a wet-end retention drop is caused by low polymer flow on pump B, with a recommendation to increase stroke by 4%. The operator then evaluates and approves these high-level actions. New skills required for modern papermakers: To successfully manage intelligent control systems, the modern operator’s skillset must shift from purely mechanical intuition towards systems and data literacy: • Model Performance Monitoring: Operators must recognise when an MPC or AI model is operating outside its calibrated boundary limits, for example, due to an unusual recycled fibre blend, and know when to safely adjust constraints or override the automation. • Data-Driven Problem Solving: Instead of adjusting a valve based on physical sound or sight, operators use digital twins and soft-sensor dashboards to visualise chemical, hydraulic and thermal dynamics that are invisible to the naked eye.

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Legacy systems and infrastructure bottlenecks: • DCS Processing Limits: Legacy Distributed Control Systems (DCS) often lack the memory and processing power to handle the high-frequency data calculation required by modern AI overlays or large-scale Model Predictive Control (MPC). • Proprietary Data Silos: Older automation platforms frequently rely on closed, proprietary communication protocols, making it expensive to extract data into a modern cloud platform or data lake without custombuilt APIs or middleware. • High Latency: Legacy networks often update data at 1-second to 5-second intervals. This slow refresh rate is insufficient to capture high-frequency wet-end hydraulic variations, rendering real-time edge analytics ineffective. The “garbage in, garbage out” data dilemma: • Uncalibrated Physical Sensors: Advanced software depends entirely on the accuracy of physical instruments. If a basic consistency transmitter or flow meter drifts out of calibration, the MPC or AI model processes inaccurate data and issues incorrect control commands. • Fragmented Data Environments: Lab testing data from Quality Management Systems (QMS), process data from historians, and business tracking data from ERP often run on completely separate servers. Without automated time synchronisation, AI models cannot accurately link upstream fibre properties to the final paper quality at the reel.

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• Missing High-Frequency Tags: Standard data historians often compress data to save storage space, removing the micro-vibrations and sub-second pressure spikes needed to train predictive anomaly detection models. Smart instrumentation & maintenance deficits: • The Cost of “Blind Spots”: Critical zones like the press section lack continuous online scanning. Trying to run an advanced drying optimiser without real-time moisture data exiting the press section forces the model to rely on estimates. • Neglected Valve Mechanics: An intelligent controller can calculate the perfect control move down to the millimetre, but if the physical control valve suffers from mechanical backlash, stiction or poor tuning, it cannot execute the command accurately. • Insufficient Instrumentation Maintenance: Mills regularly invest millions in advanced software while underfunding the instrument technician teams required to clean, calibrate, and service the specialised sensors that feed the system. Workforce capabilities and change management: • The “Black Box” Scepticism: If operators do not understand how an AI model or MPC arrives at a recommendation, they will not trust it. When the system makes an unexpected move, sceptical operators often switch the loop back to manual control, reducing the benefits of automation. • The Erosion of Basic Process Skills: Relying heavily on automation can cause younger operators to lose touch with physical papermaking intuition. If the advanced control system fails or encounters an edge-case scenario, the workforce may struggle to stabilise the machine manually. • Skill Gaps in System Maintenance: Traditional mill engineers are experts in mechanical and chemical processes, but they often lack training in data science, Python, or advanced control theory. When the vendor leaves, the mill lacks the internal expertise to retune models as the machine ages or grade mixes change.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next? KJ: TNPL has achieved a major milestone in process stabilisation by shifting from isolated, selective automation loops to a highly integrated “Smart Mill” infrastructure. Some of the key implementations and results

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achieved by the mill are as follows: • Integration of the Valmet Auto Paper Lab with ERP and AI: Rather than relying exclusively on manual, retrofitted grab samples from the machine reel, TNPL integrated its automated testing laboratory (Valmet Auto Paper Lab) directly with its Enterprise Resource Planning (ERP) architecture and machine-learning models. This framework slashed quality testing time and minimised cross-shift variability. Real-time quality tracking allows the Distributed Control System (DCS) to make localised, rapid corrections to production parameters, drastically stabilising structural properties, reducing off-specification paper waste, and ensuring uniform reel building. • Advanced Fibre Line Upgrades (Valmet Continuous Cooking G3 & TwinRoll Press): To eliminate variations stemming from changing raw material batches, especially seasonal fluctuations in bagasse and agricultural residues, TNPL modernised its hardwood kraft pulp production line using Valmet’s Continuous Cooking G3 and TwinRoll Press technology. This minimised fibre morphology fluctuations at the source. The combination ensures highly uniform pulp quality and superior washing cleanliness, while significantly lowering chemical consumption and specific steam demands in the bleaching and cooking cycles. • Mill-Wide Advanced Process Control (APC): TNPL deployed broad APC overlays designed to network smart sensors and process data from the pulp mill through to the wet end. This integration has directly optimised chemical additive functionality, lowering overall chemical expenditures while preventing the severe retention swings that typically trigger web weakness and sheet breaks. Where mills should prioritise investment next: • Wet-End Stabilisation & Retention Control: Invest in accurate, continuous consistency sensors and automated retention measurement loops to control ash and fines, preventing sheet breaks and basis weight drift. • AI and Advanced Process Control (APC) Integration: Move beyond basic automation by layering machine learning predictive models over legacy Quality Control Systems (QCS) to manage multi-variable constraints in real time. • Digital Reliability & Lubrication Routes: Digitally map equipment health, focusing first on vibration monitoring of critical bearings and automated lubrication routes to convert emergency breakdowns into planned downtime.

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Sripathi Paper and Boards Stabilises Process Variability Through Intelligent Automation In an exclusive interview with Paper Mart, Mr. SVR Krishnan, CEO, Sripathi Paper and Boards Private Limited, shares that the next phase of operational excellence in the pulp and paper industry will be driven by intelligent automation rather than conventional process control. He explains how intelligent automation, Artificial Intelligence (AI), Machine Learning (ML), predictive analytics, and Advanced Process Control (APC) are helping mills to reduce process variability, enhance product quality, and optimise the use of water, energy, and chemicals. He stresses that investing in robust digital infrastructure and intelligent control technologies will enable mills to build more efficient, resilient, and sustainable manufacturing operations, as mentioned while discussing the challenges of legacy systems, data silos, and the skills gap.

SVR Krishnan: Most of the variability for any paper mill starts with furnish/ raw material control, followed by wet-end controls, short circulation, the steam and condensate system, and tension & draw control up to the pope reel of the paper machine.

Mr. SVR Krishnan, CEO, Sripathi Paper and Boards Private Limited

In the current era of cost savings, addressing the issue of process variability has become most important. There are two types of process variations. Common-Cause Variation/Chance Variation: This involves reasons such as ambient temperature, equipment wear and tear, and fluctuations in the quality of raw material. A process with only common cause variation is

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acknowledged as statistically stable. Special-Cause/ Assignable Cause Variation: This occurs due to identifiable causes such as a wrong mix of raw material, operator error, incorrect machine setup, sensor failure, wrong application of chemicals, or an unplanned change in operating conditions. All these causes make the process unstable and unpredictable. Variability in the process significantly affects quality and operating performance as it will drift the output specifications out of limits, and create inconsistency from batch to batch or unit to unit, causing non-conforming production. Also, variability reduces process capability, meaning the process may not be able to consistently meet specification windows for the final product. Further, the key quality parameters used for tracking variability of paper/ paperboard quality include basis weight, moisture, caliper, ply bond, bulk, and stiffness. Among them,

PROCESS VARIABILITY MINIMISATION

In recent years, mills are moving to auto sampling and measurement systems, and Real-time process monitoring & Quality Management (RTQM) systems, from the conventional laboratory sampling and periodic measurements. weight and moisture control are critical stages where tighter stability can deliver the greatest measurable gains. Transversal variability amounts to a significant portion of overall process variability. Quality Control System (QCS) scanners provide 2-sigma values for dry weight and moisture; however, effective control involves more than simply adjusting cross-sectional spindles. It also requires interactions between the type of fibre being used, jet/ wire ratios, and various head box adjustments. Longitudinal variability in weight and moisture is always present during production and varies longitudinally. This is mostly controlled by the paper machine’s control loops. However, the root causes of the problems come from stock preparation. By ensuring effective wet-end controls, including chest levels, flow rates, consistency at every stage, and the automatic dosing of specialty chemicals, we can significantly improve process stability and deliver measurable gains in product quality and operating performance.

PM: How has the approach to controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples. SK: A big shift has taken place from process experts manually adjusting the machine by analyzing laboratory

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reports to online Quality Control System (QCS) measurements, which automatically control process parameters. Such control uses feedback-driven predictive analytics to generate virtual measurements of key process parameters and quality properties that are impossible to measure manually in real time. Based on these measurements, the platform executes timely adjustments to key control elements, thereby optimising production and improving efficiency. Proactive and accurate process control is critical for optimising plant performance and reducing quality variation. AI-driven technology provides real-time process improvement recommendations and optimal control parameters, thereby enhancing production line efficiency, revenue, and throughput. Also, in recent years, mills are moving to auto sampling and measurement systems, and Realtime process monitoring & Quality Management (RTQM) systems, from the conventional laboratory sampling and periodic measurements. For example, mills are moving from traditional feedback systems to feedforward systems & controls, where earlier-stage measurement systems and the values give predictive controls to the successive stage for correcting the process. This predictive approach helps to reduce off-quality production during the manufacturing process.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have

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they delivered measurable gains? SK: AI-driven technology leverages real-time and historical data to accurately control chemical dosages, minimizing overfeeding while maintaining quality standards that ultimately reduce energy and raw material usage. Predictive analytics with feedback systems help to anticipate quality issues before they occur to ensure consistent and reliable output that meets production standards.

Advanced AI and machine learning models learn from the mill’s historical data, prescribing real-time adjustments and executing corrective action to meet unique production specification needs. The measurable gains include improved machine runnability; lower steam, water, and energy consumption; savings in process/specialty chemicals; and a reduction in off-quality generation/ the Cost of Poor Quality (COPQ).

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?

SK: AI and Machine Learning (ML) act as real-time predictive controllers in the paper industry, identifying anomalies and adjusting process variables minutes before physical defects appear. By processing high-frequency sensor data, these technologies transition mills from reactive troubleshooting to autonomous, proactive optimisation. ML models analyze vibration, temperature, and acoustic data from jumbo rollers and bearings. The

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Mills should prioritize investment in basic end devices and sensors for measuring, monitoring, and controlling key resources like water, steam, and power on a section-wise basis, which will certainly make them much more efficient and sustainable in the business systems detect micro-deviations weeks before a catastrophic mechanical failure occurs, enabling preventive maintenance during planned shutdowns rather than unplanned emergency stops.

Process Optimisation and Control

Advanced Process Control (APC): Reinforcement learning models continuously adjust chemical dosages, steam pressure, and valve positions based on historical data from the best-performing production runs (golden batches). Web break prediction: Deep learning models analyze historical data to predict process deviations such as vacuum fluctuations, consistency variations, flow changes, and chemical dosage variations to warn operators of web breaks on the paper machine 15 to 30 minutes in advance. Speed and tension balancing: AI dynamically adjusts the web tension, torque, machine draws between the sections, and machine speed to stabilize the wet-end and drying sections, up to the pope reel.

Real-Time Quality and Strength Prediction

Virtual sensors (soft sensors): AI calculates critical product metrics like tensile strength, tear strength, and basis weight in real time. Eliminating lab delays: Algorithms replace traditional destructive laboratory testing, which normally takes hours. AI also analyses fibre length, kinking index, curl index, and predicts fibre behavior with respect

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to twist angle and Tensile Stiffness Orientation (TSO) profile. Instant recipe adjustment: The system instantly detects fibre attributes deviating from target specifications and adjusts the process accordingly.

Resource and Energy Efficiency

Chemical dose optimisation: AI calculates the precise amount of bleaching agents and retention aids needed based on incoming wood or secondary fibre pulp quality. Steam and energy reduction: Neural networks, with monitoring at various sections from the press to the pope reel, optimise the thermal energy profile in drying cylinders to optimise fuel consumption. Water recycling loops: Predictive models manage wastewater treatment chemistry through the automatic dosing of the required chemicals to maximize process water reuse.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant measurement or data gaps still remain? SK: As explained earlier, these control systems bring stability to the wet end of the paper/board machine and enable precise control of the steam and condensate system, resulting in smooth machine runnability with optimum quality at pope reel. However, gaps still exist between

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AI-generated data and the departmental data stored in various silos, resulting in a lack of seamless process control. This practical gap between AI and human intelligence (HI) is due to the poor understanding of AI systems among the operators, as well as inadequate validation of AI models through human expertise.

PM: Drives and motion control directly influence speed, tension, synchronization, and machine stability. How are newer drive and control technologies helping mills reduce variability across the paper machine and associated processes? SK: New drive systems and control technologies, including advanced frequency drives, sensorless vector drives, and direct-drive motors, eliminate mechanical backlash and slippage. By using high-speed, real-time communication networks to synchronize dozens of machine sections, these systems achieve precise speed matching and tension control, significantly reducing web breaks and product variability across the paper machine.

Direct-Drive Technology:

Mechanical drive components such as gearboxes, belts, and couplings are prone to backlash and wear. Many modern rebuilds and new paper machines use Permanent Magnet Synchronous Motors (PMSMs) directly coupled to the rolls. Direct-drive motors completely eliminate motor slip, providing precise rotational accuracy and higher low-speed torque.

Digital Twins & Simulation: Mills can digitally map out

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mechanical dynamics and test drive tuning in virtual environments to prevent instability before physical implementation. This will reduce the real-time commissioning time and accelerate the stabilization of new projects.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most? SK: Real-Time Feedback Loops: Advanced sensors and scanners, such as QCS, continuously monitor sheet properties. If a deviation is detected, automated systems instantly adjust factors such as thick stock and thin stock flows or steam pressure to correct the issue before off-spec paper is produced.

Soft Sensors and Virtual Measurements: As some critical parameters, such as Kappa number in pulp digestors, are notoriously difficult to measure physically, Advanced Process Control (APC) modules use soft sensors to estimate these values and make immediate and even-cooking corrections. Integrated Process Data: By connecting process control with Manufacturing Execution Systems (MES), mills centralize end-to-end data. This enables operators to implement data-driven, closedloop strategies that maintain ideal operating conditions with limited fluctuations in raw material quality.

Benefits to Quality

Real-time control systems have

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significantly reduced the standard deviation of key sheet properties, allowing mills to operate closer to their optimal process limits. Caliper: Automated controls reduce variations in paper thickness, resulting in a more uniform surface finish, improved runnability on the carton converting lines, and higher productivity. Basis Weight & Moisture: Controlling the flow of fibre stock and managing steam pressure ensures consistent paper weight and moisture content. Once grammage and moisture are well controlled, most of the customer-related quality problems are addressed. Colour & Shade: Colour accuracy benefits directly from APC Sheet Ash & Opacity: The standard deviation for sheet ash is routinely reduced by over 50%, allowing mills to maintain higher average ash levels while minimizing raw material costs.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing? SK: With the help of AI and ML, the operator’s role is evolving from reactive to predictive decisionmaking. Operators are consistently guided by the intelligent control systems for their decision-making to allow deviations within acceptable limits or to indicate when action needs to be taken. Without automation, the same decision will take more time or

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could even be missed. Operators are no longer just fixing paper breaks or off-spec issues as they happen. Instead, advanced control systems and AI algorithms predict web defects or equipment failures hours before they occur, allowing operators to take proactive steps to avoid the breaks, avoid equipment damage, and reduce the Cost of Poor Quality / COPQ.

PM: What typically prevents a mill from achieving the full benefits of advanced automation and intelligent control? Please tell us more about issues such as legacy systems, data quality, system integration, instrumentation, workforce capabilities, etc. SK: Legacy infrastructure, poor data quality, and fragmented system integration are the primary barriers that prevent paper mills from achieving the full benefits of advanced automation.

Legacy Infrastructure: Many mills operate with very old assets. These machines rely on proprietary Distributed Control Systems (DCS). Older controllers lack the computational bandwidth required to process the advanced algorithms needed for predictive AI model control. Replacing a functional DCS costs heavily, and requires extended machine stoppage, along with substantial investment, in the current business scenario. Data Quality and Silos: Mills generate massive volumes of data. However, much of it is trapped in isolated historians without proper

PROCESS VARIABILITY MINIMISATION

context or time-synchronization. Data points often lack metadata. Without tags explaining the paper grade or wood species being processed, the data is meaningless for machine learning. Mills often mix technologies from different eras and vendors, making system integration challenging. Bridging proprietary communication protocols creates significant integration issues. Operational Technology (OT) on the mill floor is traditionally isolated from Information Technology (IT) networks. Workforce and Cultural Barriers: Existing mill operators excel at manual, reactive tuning. However, they often lack the data literacy required to manage automated control systems. Operators frequently override automated suggestions. They lack knowledge and required skills to validate

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AI Models. Process engineers understand the chemistry, while automation engineers understand the code. A lack of cross-disciplinary collaboration stalls deployment.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritize investment next? SK: Furnish recipe control systems, stock and chemical flow control systems, and stage-wise consistency controls have resulted in better stability of the whole process. AI tools with various end devices connected to the process chemical system have improved the performance of the process chemicals with respect to consistent wet-end process parameters and reduced chemical consumption.

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Significant improvements have been made in the effluent treatment plant through AI-based models, which monitor the vital parameters of liquid effluent and control the mill influent for various production grades. AI-based models are being developed for the order management systems to provide better visibility beyond the pope reel up to despatch, and efforts are now being made to extend this visibility up to the customer’s premises. Mills should prioritize investment in basic end devices and sensors for measuring, monitoring, and controlling key resources like water, steam, and power on a section-wise basis, which will certainly make them much more efficient and sustainable in the business.

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Trident Group:

Reducing Variability Through Smarter Process Control As paper mills focus on greater process stability and consistent quality, advanced control technologies are enabling a shift from reactive automation to proactive process management. In an exclusive interview with Paper Mart, Mr. Rajnish Gera, CEO, Trident Group, discusses how Advanced Process Control (APC), real-

time process data, predictive models, AI and Machine Learning are helping mills manage variability before it affects quality. He highlights the integration of online sensors, QCS, DCS and laboratory systems to enhance visibility of critical parameters such as basis weight, moisture and ash content. Mr. Gera also explains how optimised chemical dosing and tighter process control can reduce chemical consumption and waste, improve machine efficiency, strengthen operational stability and support consistent paper quality and overall manufacturing performance.

Mr. Rajnish Gera, CEO, Trident Group

Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains. Rajnish Gera: Paper manufacturing operations often face challenges in furnishing consistent raw materials and ensuring adequate water quality and availability. These variations can significantly impact chemical dosing efficiency and wet-end chemistry

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performance, leading to fluctuations in critical quality parameters. Inaccurate or unstable chemical dosing can result in quality defects, yield losses, increased rejections, and higher production costs. By optimising chemical dosing and maintaining tighter control over key process parameters, mills can improve product consistency, reduce chemical consumption and waste, enhance machine efficiency, increase operational stability, and achieve superior manufacturing performance while ensuring customer satisfaction.

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By optimising chemical dosing and maintaining tighter control over key process parameters, mills can improve product consistency, reduce chemical consumption and waste, enhance machine efficiency, increase operational stability, and achieve superior manufacturing performance while ensuring customer satisfaction. PM: How has the approach to controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples.

RG: Paper mills are increasingly adopting Advanced Process Control (APC) to move beyond traditional reactive automation and achieve greater process stability. By leveraging real-time process data, predictive models, and multi-variable control strategies, APC proactively manages process variability before it can impact product quality. Integrated with online sensors, quality measurement systems, and DCS platforms, APC optimises chemical dosing and critical quality parameters such as basis weight, moisture, and ash content. This results in improved paper quality consistency, enhanced machine runnability, reduced raw material and chemical consumption, lower operating costs, and higher production efficiency.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?

RG: The paper industry is facing increasing challenges due to an ageing workforce, dependence on operator expertise, and legacy automation systems that primarily rely on reactive control strategies. These constraints often result in process variability, inefficient resource utilisation, and inconsistent product quality. Advanced Process Control (APC) addresses these challenges by leveraging real-time process data, predictive analytics, and multivariable control techniques to optimise chemical dosing and critical quality parameters. By proactively managing process variations and reducing reliance on manual intervention, APC enhances paper quality consistency, machine runnability, operational stability, and resource efficiency while minimising costs, waste generation, and process variability.

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(ML) are revolutionising paper manufacturing processes by transforming process data into actionable insights through real-time dashboards, predictive analytics, and intelligent monitoring systems. By integrating data from DCS, QCS, laboratory systems, and online sensors, mills gain enhanced visibility of critical quality and process parameters. Advanced solutions provided by technology suppliers enable early detection of process deviations, help optimise chemical consumption, improve product quality consistency, reduce variability, minimise production losses, enhance machine performance, and support proactive, data-driven decision-making across operations.

RG: Online measurement systems, smart instrumentation, machine vision, and Quality Control Systems (QCS) are enabling paper mills to monitor and control critical quality parameters in real time. Continuous tracking of basis weight, moisture, caliper, ash content, brightness, and formation helps reduce process variability and improve product consistency. Machine vision systems enhance defect detection, while advanced dashboards provide greater operational visibility and faster decisionmaking. Although challenges remain in measuring certain raw material and wet-end chemistry variations, these technologies significantly improve process stability, machine runnability, quality control, and overall manufacturing performance.

PM: Drives and motion control directly influence speed, tension, synchronization, and machine stability. How are newer drive and control technologies helping mills reduce variability across the paper machine and associated processes? RG: Drives and motion control systems are essential for ensuring paper machine stability through precise control of speed, tension, synchronisation, and load distribution. Modern digital drives and intelligent controllers continuously optimise machine performance, minimising process disturbances and quality variations. Effective synchronisation across machine sections reduces sheet

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PROCESS VARIABILITY MINIMISATION

Advanced Process Control (APC) addresses these challenges by leveraging real-time process data, predictive analytics, and multivariable control techniques to optimise chemical dosing and critical quality parameters. breaks and production losses, while real-time diagnostics, predictive maintenance, and integrated dashboards enhance operational visibility and decision-making. As a result, mills achieve improved product quality, higher machine efficiency, reduced downtime, and more reliable and consistent manufacturing performance.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most?

RG: Automation, Advanced Process Control (APC), and integrated process data enable paper mills to achieve superior quality consistency through real-time monitoring, predictive control, and data-driven decisionmaking. By integrating information from online analysers, QCS, laboratory systems, and process controls, mills can optimise chemical dosing and maintain tighter control over critical quality parameters. Automated adjustments reduce process variability, improve machine runnability, and minimise chemical overconsumption. As a result, mills achieve improved brightness, ash content, moisture, basis weight, and strength properties while reducing waste, lowering costs, and enhancing customer satisfaction.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?

RG: As automation, Advanced Process Control (APC), and AI-powered systems become more intelligent, the operator’s role is evolving from manual process control to proactive monitoring and data-driven decision-making. Operators now focus on tracking trends in critical quality parameters such as basis weight, moisture, caliper, ash

content, brightness, pH, retention, and formation through real-time dashboards. Proactive monitoring of chemical consumption, stock consistency, machine efficiency, and process stability enables early detection of deviations and preventive action before quality or production is affected. This approach improves product consistency, reduces variability, enhances machine runnability, and drives continuous operational excellence.

RG: While advanced automation, AI, and intelligent control systems offer significant benefits, several challenges can limit their effectiveness in paper mills. Legacy automation systems often lack connectivity with modern digital platforms, restricting real-time data utilisation and advanced analytics. In addition, unreliable instrumentation, sensor calibration issues, and data quality gaps can affect control accuracy and process optimisation. Many mills also struggle with integrating DCS, QCS, maintenance, laboratory, and production systems into a single operational view. Furthermore, operators must develop competencies in analysing trends related to basis weight, moisture, brightness, ash content, pH, retention, and chemical consumption. Addressing these challenges through reliable instrumentation, integrated data platforms, and workforce upskilling enables mills to achieve the full benefits of advanced automation, improve process stability, and enhance overall operational performance.

Proactive monitoring of chemical consumption, stock consistency, machine efficiency, and process stability enables early detection of deviations and preventive action before quality or production is affected. This approach improves product consistency, reduces variability, enhances machine runnability, and drives continuous operational excellence.

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PROCESS VARIABILITY MINIMISATION

Emami Paper Mills:

From Back-End Stability to Reel Consistency

Mr. Ashish Gupta, Unit Head and Senior President, Emami Paper Mills Limited

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As paper mills increasingly focus on process stability, consistent quality and operational excellence, automation is evolving beyond conventional control systems towards integrated, data-driven process management. In an exclusive interaction with Paper Mart, Mr. Ashish Gupta, Unit Head and Senior President, Emami Paper Mills Limited, discusses the mill’s approach to reducing process variability, strengthening control and progressively building a more stable and intelligent manufacturing environment. At Emami Paper Mills, this approach combines reliable instrumentation, DCS, QCS, APC, process data and predictive technologies, supported by operator expertise. The recent PM2 rebuild, including a new QCS-enabled headbox with profile control and a heated calendar with caliper-control capability, reflects this direction.

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PROCESS VARIABILITY MINIMISATION

Ashish Gupta: Process variability in a paper mill is primarily seen in rawmaterial furnish, stock preparation and refining, wet-end chemistry, headbox operation, and MD/CD basis-weight and moisture profiles. Variations in fibre characteristics, consistency, charge demand, retention, refining and chemical dosage ultimately translate into changes in formation, strength, calliper, moisture, and printability.

changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples. AG: The philosophy of process control is evolving from conventional loop-by-loop PID control and operator intervention towards integrated, predictive and datadriven control. At EPM, we see the next stage of automation as the integration of DCS, QCS, advanced process control, process historians and analytics, so that process deviations can be identified earlier and corrective action can be taken before they become quality or production problems.

At Emami Paper Mills, we recognise that stability at the back end is fundamental to consistency at the reel. Better control of furnish quality, refining and stock consistency, followed by tighter control of wetend chemistry, provides significant benefits in fibre utilisation and chemical consumption.

For example, instead of waiting for GSM or moisture to move outside the target and then correcting it, an integrated control system can identify changes in consistency, stock flow, steam conditions or machine speed that are likely to cause the deviation and initiate corrective action.

At the machine end, tighter control of headbox flow, slice opening, basis-weight profile, moisture profile, steam pressure and calliper can deliver measurable improvements in machine speed, energy efficiency and finishing yield. In our view, the greatest gains come not from controlling one isolated parameter, but from stabilising the complete process chain from stock preparation to the finished sheet.

We are progressively moving in this direction. The objective is not to replace the operator, but to provide the operator with better information, faster response and more consistent control of the process.

PM: How has the approach to controlling process variability

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains? AG: APC and MPC are particularly useful where several process variables are interdependent

and where there are significant process delays. In a paper machine, parameters such as stock flow, consistency, headbox pressure, basis weight, moisture, steam, hood conditions and machine speed are closely interconnected. An MPC-based approach can optimise several variables simultaneously while respecting operating and quality constraints. It can, for example, coordinate stock flow, dilution, steam and machine speed, rather than allowing individual loops to respond independently. At Emami Paper Mills, our approach is to first strengthen the instrumentation, basic control loops and data quality, and then progressively build advanced control capabilities on this foundation. This is important because APC or MPC can only perform as well as the measurements and basic control infrastructure supporting it. Our experience with automationenabled machine upgrades has demonstrated that tighter profile control can improve GSM and calliper uniformity, productivity and finishing yield. We see significant opportunity as advanced control is progressively implemented across the mill.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?

AG: We see AI and machine learning primarily as a predictive intelligence layer above the existing DCS, QCS and APC systems, rather than as a

Variations in fibre characteristics, consistency, charge demand, retention, refining and chemical dosage ultimately translate into changes in formation, strength, calliper, moisture, and printability. 65 | Aug-Sep 2026

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PROCESS VARIABILITY MINIMISATION

The future lies in combining online measurements, laboratory data and process knowledge into a single decision-making framework. replacement for them. Historical process data can be used to identify relationships that may not be immediately visible to an operator. AI models can provide early warnings of developing process instability, predict quality characteristics from online process parameters, and identify patterns associated with web breaks, quality drift or equipment problems. For Emami Paper Mills, the immediate value proposition is in moving from reactive decisionmaking to predictive decisionmaking. The system should tell the operator not only what has happened, but also what is likely to happen next and which process variables are contributing to it. However, we believe AI should be introduced selectively and pragmatically. Reliable instrumentation, clean data, sound process knowledge and operator validation must come before sophisticated AI applications.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant measurement or data gaps still remain? AG: Modern QCS has transformed paper-machine control by providing continuous measurement of parameters such as basis weight, moisture, caliper, ash and colour, along with MD/CD profile information. At Emami Paper Mills, we consider

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reliable measurement to be the foundation of automation. Once a parameter can be measured accurately and consistently, it becomes possible to move from manual correction towards closedloop control.

Modern sectional AC drives, electronic line-shafting, highperformance torque control and improved tension control allow the machine to maintain accurate draws, speed relationships and web tension across different sections.

Machine vision is also becoming increasingly valuable for detecting surface defects at full machine speed. When defect detection is integrated with process data, it becomes possible to link a defect to its probable process origin and address the cause rather than simply removing the defective material downstream.

This reduces speed fluctuations, draw disturbances and synchronisation errors, which can otherwise result in wrinkles, edge cracks, breaks and unstable running.

There are nevertheless measurement gaps. Parameters such as formation at the fibre level, z-direction bonding, complex wet-end chemistry and microbiological activity are not always directly measurable online. Strength and some other final properties also continue to depend significantly on laboratory measurements. Therefore, the future lies in combining online measurements, laboratory data and process knowledge into a single decisionmaking framework.

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At Emami Paper Mills, we consider drive and motion control as an integral part of overall process automation. The objective is to ensure that the machine responds smoothly to changes in operating conditions and maintains stable operation across the entire machine.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most? AG: The strongest benefits are generally seen in basis weight, moisture and calliper, followed by colour, ash and derived strength properties.

A paper machine is a highly interconnected system. A change in furnish, consistency or refining can ultimately affect strength and formation; changes in dryer conditions can affect moisture and dimensional stability; and changes in calendering can affect caliper and bulk. Therefore, automation must also become integrated. At Emami Paper Mills, our focus is on progressively bringing DCS, QCS,

PROCESS VARIABILITY MINIMISATION

The next generation of paper mills will combine reliable field instrumentation, DCS and QCS, advanced process control, integrated data platforms, analytics and AI, supported by experienced and capable operating teams. machine controls, process data and advanced control into a common operating framework. Our recent machine automation upgrades, including improved headbox profile control and calliper control, have already contributed to tighter GSM and calliper profiles and better product consistency. The ultimate objective is to run closer to the customer’s specified target rather than maintaining unnecessarily large operating margins. This improves quality consistency, fiber utilisation, energy efficiency and finishing yield.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing? AG: The operator’s role is not becoming less important; it is becoming more skilled and more analytical.

Earlier, operators spent considerable time monitoring individual parameters, adjusting setpoints and responding to alarms. With advanced automation, these routine activities can increasingly be handled by control systems. The operator can then focus on process optimisation, managing constraints, interpreting trends, handling exceptions and making decisions involving quality, cost, production and safety. At Emami Paper Mills, we believe that the best automation combines technology with operator experience. The system may identify a developing deviation, but an

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experienced operator understands the process context and can validate whether the recommended action is appropriate.

and optimisation Fifth: Predictive analytics and AI Sixth: Equally important is people’s capability

The objective is therefore not “man versus machine”. It is man plus machine, with automation providing consistency and speed and the operator providing judgement, experience and process understanding.

Operators, engineers and maintenance teams must understand the technology and trust the system. Without appropriate training and ownership, even a technically excellent automation project can gradually revert to manual intervention.

For this reason, we consider technology, people and process discipline to be equally important pillars of successful automation.

AG: The biggest challenge is often not the advanced technology itself, but the foundation on which it has to operate. Many mills have legacy DCS and QCS systems, ageing instrumentation, inconsistent measurement practices, fragmented databases and equipment from multiple automation vendors. Inadequate instrumentation and poor-quality data can severely limit the effectiveness of advanced control. At Emami Paper Mills, we believe the implementation should therefore follow a structured hierarchy: First: Reliable instrumentation and measurement

Second: Strong basic process control Third: Data connectivity and governance Fourth: Advanced process control

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PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next? AG: One of the important examples at Emami Paper Mills is the recent rebuild of PM2, where a new headbox with profile-control capability through QCS and a heated calendar with calliper-control capability were introduced. These automation-enabled improvements have contributed to significantly better GSM and calliper profiles, improved product quality consistency and better machine performance. The tighter control has also helped reduce finishing losses and supported higher productivity. This experience reinforces our belief that automation should be closely integrated with machine and process improvements, rather than treated as a standalone IT or instrumentation project.

PROCESS VARIABILITY MINIMISATION

Emami Paper Mills is progressively strengthening its automation roadmap. One important area is the proposed Power Management System (PMS) for the power plant, which will help optimise generation capacity and power utilisation while operating in synchronisation with the grid. Looking ahead, Emami Paper Mills is progressively strengthening its automation roadmap. One important area is the proposed Power Management System (PMS) for the power plant, which will help optimise generation capacity and power utilisation while operating in synchronisation with the grid. This has the potential to improve energy utilisation, operational visibility and decision-making. Plans are also underway for mill-wide DCS upgrades to enhance control capability and integration of process data.

More broadly, our priorities are to strengthen the automation foundation, improve instrumentation and data quality, and then progressively introduce APC, predictive analytics and AI where they can deliver measurable business value. Overall, the long-term objective is to build a more stable, datadriven and intelligent paper mill capable of producing consistently high-quality paper with lower variability, lower energy and chemical consumption, reduced losses and higher sustainable productivity. The next generation

of paper mills will combine reliable field instrumentation, DCS and QCS, advanced process control, integrated data platforms, analytics and AI, supported by experienced and capable operating teams. The real measure of success will not be the sophistication of the automation system itself, but the extent to which it delivers lower process variability, consistent product quality, higher machine availability, improved energy and fibre efficiency, reduced waste and ultimately better value for the customer and the business.

NEWS

Sidhu Engineering Works Secures Order for 7 Robo Cleaners from Sidharth Papers Sidhu Engineering Works receives an order for seven advanced Robo Cleaners for wire, felt, and dryer screens from Sidharth Papers’ Unit 1 in Kashipur, aimed at extending fabric life and enhancing paper machine performance. Aug 27, 2026 idhu Engineering Works has received a valued order for seven Robo Cleaners for the wire, felt, and dryer screens from Sidharth Papers Unit 1, Kashipur. The order has been placed by Sushil Bansal and Vineet Sangal, owners of Sidharth Papers.

The Robo Cleaner systems are designed to provide effective and consistent cleaning of paper machine fabrics, helping to enhance fabric life and improve overall machine performance. The technology is expected to support smoother operations and contribute to improved efficiency at the plant.

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Sidhu Engineering Works is scheduled to deliver the project by the end of November 2026.

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Connecting Industries Creating Opportunities

PROCESS VARIABILITY MINIMISATION

Kuantum Papers:

Connecting Control, Data and Intelligence for Consistent Papermaking Papermaking remains a complex process, with persistent variability across stock preparation, basis weight control, moisture profiling, refining, headbox consistency, drying and reel operations. In an exclusive interaction with Paper Mart, Mr. Suresh Babu Thallapaneni, Vice-President - Process Excellence, Kuantum Papers Limited, discusses the shift from traditional PID loops towards integrated and intelligent automation through APC, MPC, digital twins, AI/ML, machine vision, online measurement, smart instrumentation and real-time analytics. He highlights their role in strengthening process stability, quality consistency and runnability, while improving energy and raw material utilisation. Drawing on a recent mill automation modernisation project, he outlines the benefits of APC across pulp and paper operations, including improved basis weight consistency, reduced quality variability, lower waste generation and increased OEE.

Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains. Suresh Babu Thallapaneni: Papermaking is a complex process, and in our experience, the most persistent variability is usually seen in stock preparation, basis weight control, moisture profile, refining, headbox consistency, drying and reel operations. Each of these stages has a direct influence on sheet formation, strength, grammage, and runnability. Even a small fluctuation can eventually show as a quality issue or an efficiency loss.

Mr. Suresh Babu Thallapaneni, Vice-President Process Excellence, Kuantum Papers Limited

In stock preparation, variability in fibre quality and furnish composition leads to inconsistent bonding and drainage behaviour. Refining adds another layer of complexity, as uneven energy input alters fibre fibrillation, affecting tensile strength and surface properties. At the headbox, fluctuations in consistency can cause streaks and poor formation, undermining uniform fibre distribution across the sheet. Basis weight control is equally important, because deviations in grammage not only affect product quality but also increase raw material costs. Moisture management is another persistent challenge. An uneven Cross-Direction (CD) moisture profile results in curl, cockle and dimensional instability, while variability in drying affects sheet strength and energy consumption. Reel operations, meanwhile, require precise tension and winding control to minimise breaks, wrinkles and defects that can compromise downstream processing. Machine speed stability ties all these factors together as fluctuations in speed alter fibre orientation, drying balance, and reel quality, making stability a cornerstone of smooth operations. In practical terms, the greatest gains come from improving overall stability rather than optimising individual parameters in isolation.

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PROCESS VARIABILITY MINIMISATION

Consistency, refining, basis weight, moisture and CD profile control need to work together, supported by stable machine speed and reel operation. When these variables are tightly controlled, mills can achieve better sheet uniformity, fewer breaks, improved raw material and energy utilisation and more predictable production.

PM: How has the approach to controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples. SBT: Over the last few years, papermaking mills have increasingly moved beyond traditional PID loops toward a more integrated approach built around advanced process control (APC), model predictive control (MPC), digital twins and realtime analytics. The real advantage is that these platforms analyse multiple

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process variables simultaneously, which helps mills identify disturbances before they begin to affect production. In practical terms, APC and MPC systems can adjust refining energy, chemical dosing and stock consistency based on realtime feedback from sensors and predictive models. Instead of waiting for deviations in sheet properties to appear, the system anticipates changes in fibre quality, furnish composition or machine speed and can make the required correction instantly. Digital twins also allow operators to simulate scenarios, test control strategies and forecast outcomes without disrupting actual production. When these tools are integrated with real-time analytics, operators get a clearer view of moisture profiles, CD basis weight variations and drying efficiency, enabling precise interventions that reduce variability.

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Papermaking is a complex process, and in our experience, the most persistent variability is usually seen in stock preparation, basis weight control, moisture profile, refining, headbox consistency, drying and reel operations.

The shift, therefore, is not simply about adding more automation. It is about using connected, data-driven systems to understand the process better, respond earlier and keep improving control over time.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?

PROCESS VARIABILITY MINIMISATION

DIGITAL TWIN Connecting the physical and digital worlds REAL-TIME DATA Sensors

Physical Asset → Digital Twin Operational / sensor data

loT Temperature Pressure Vibration Energy

Digital Twin → Physical Asset

Production

PHYSICAL ASSET

Insights / optimisation / actions

DIGITAL TWIN

Equipment status

Virtual representation continuously updated with real-world data

Machine • Equipment • Process • Facility

MONITOR

ANALYSE

See current operating conditions

Physical Asset

Live Data

SBT: Advanced Process Control (APC) and Model Predictive Control (MPC) are becoming an important part of modern papermaking, going beyond traditional PIDbased systems. These advanced strategies are now widely applied in stock preparation, paper machines, recovery boilers and energy systems. The key advantage of MPC is that it uses dynamic process models to look ahead and predict how the system is likely to behave. Rather than reacting after a deviation has already occurred, MPC proactively calculates optimal control actions, balancing multiple variables and constraints simultaneously. In stock preparation, MPC helps maintain consistent fibre quality by adjusting refining energy and chemical dosing in real-time, based on incoming furnish variability. On paper machines, it stabilises basis weight and moisture profiles by coordinating headbox consistency, drying sections and CD profile actuators. Recovery boilers benefit from MPC through improved combustion stability, reduced emissions, and optimised steam

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SIMULATE

Understand performance and behaviour

Digital Model

PREDICT

Test scenarios without affecting the real asset

Digital Twin

Anticipate failures and future performance

Improve efficiency, reliability and cost

Example

Machine vibration rises → Digital Twin detects abnormal behaviour → Predicts bearing failure → Maintenance is scheduled before breakdown

generation. In energy systems, predictive control balances steam, electricity and heat loads, minimising fuel consumption while maintaining reliability. These outcomes not only improve profitability but also strengthen competitiveness in a market where customers demand consistent quality and sustainable practices.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?

SBT: Artificial Intelligence (AI) and Machine Learning (ML) are transforming papermaking by enabling mills to detect complex patterns that conventional control systems often miss. They excel at analysing large volumes of process data, identifying subtle correlations and predicting outcomes that would otherwise remain hidden. One of the most impactful applications is predictive maintenance. By analysing vibration, temperature and operational data, www.papermart.in

OPTIMISE

AI models can forecast equipment failures before they occur, reducing unplanned downtime and extending asset life. Break prediction is another practical use case; ML algorithms learn from past break events, identifying precursors such as tension fluctuations or moisture imbalances and alerting operators in advance to prevent costly interruptions. Beyond early detection, AI-driven optimisation continuously finetunes process parameters such as refining energy, chemical dosing and drying profiles to achieve maximum efficiency with minimal variability. By integrating these insights into real-time control systems, mills can correct deviations proactively rather than waiting for quality issues to appear in finished rolls.

PROCESS VARIABILITY MINIMISATION

Successful implementation requires strong leadership, comprehensive workforce training and a clear digital transformation strategy SBT: Online sensors, Quality Control Systems (QCS), machine vision, and smart instrumentation have significantly improved process visibility by providing continuous monitoring of critical sheet properties such as basis weight, moisture, caliper, formation, defects and colour. These systems deliver real-time feedback, enabling operators to maintain tighter control over variability and ensure consistent product quality. Machine vision is particularly useful for the early detection of sheet defects and process abnormalities. By analysing high-resolution images of the moving sheet, these systems can identify issues such as holes, streaks, wrinkles or colour variations that may not be visible to the human eye at production speeds. There are, however, still some important gaps. One of the most persistent challenges is the real-time characterisation of fibre quality. While sensors can measure sheet properties, they often lack the ability to fully capture fibre morphology, bonding potential or variability in furnish composition in realtime. Similarly, real-time chemistry monitoring remains limited. Precise control of wet-end chemistry, including retention aids, sizing agents and charge balance, is critical for sheet formation and strength, yet continuous online measurement of these parameters is still evolving. Another gap is the integration of different measurement sources onto one platform. Mills often operate with multiple standalone systems, and without seamless integration, operators may struggle to interpret data holistically or act on it efficiently.

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The next step is to bridge these gaps through advanced analytics, AI-driven integration, and unified dashboards that combine mechanical, chemical and optical measurements into a single decisionmaking platform. By achieving this, mills can move closer to true predictive control, where variability is minimised, efficiency is maximised, and quality is consistently assured across every roll produced.

actuators simultaneously, ensuring that every part of the machine responds instantly to process changes. High-speed communication networks tie these systems together, enabling rapid data exchange and synchronisation across the entire machine line. In practical terms, this creates a more stable operating environment in which disturbances are quickly corrected before they impact production.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most?

SBT: In recent years, mills have adopted variable-speed drives, digital motion control systems and high-speed communication networks. Together, these technologies improve synchronisation, tension control and overall machine stability, which are critical for maintaining consistent paper quality and efficient production. Traditional fixed-speed systems had limited flexibility in dealing with variability in tension and synchronisation, leading to sheet breaks and uneven quality. Modern drives and motion control systems, by comparison, provide precise, real-time adjustments that keep the entire machine running in harmony. They allow each section of the paper machine to operate at optimal speeds, ensuring smooth transitions between wet end, press section, drying and reel operations. Digital motion control systems further enhance this by coordinating multiple motors and www.papermart.in

SBT: One of the biggest changes in modern papermaking is the ability to bring together process data, quality measurements and advanced control strategies into a unified platform. This provides mills with a more practical way to maintain stable operating conditions by continuously monitoring multiple variables and coordinating corrective actions across the entire machine. The quality parameters that benefit most typically include basis weight, moisture, caliper, formation, ash content, strength properties and surface quality. Basis weight control ensures grammage uniformity, reducing raw material waste and improving product consistency. Moisture stability minimises curl, cockle and dimensional defects, while caliper control ensures thickness uniformity across the sheet. Formation improvements enhance fibre distribution, leading to better printability and strength. Ash content optimisation balances filler usage with sheet performance, while strength properties such as tensile strength and burst strength are

PROCESS VARIABILITY MINIMISATION

stabilised through precise refining and chemical dosing. Surface quality, including smoothness and gloss, benefits from tighter control of coating and calendaring operations. When these measurements are integrated with advanced control strategies such as Model Predictive Control (MPC) and Advanced Process Control (APC), mills can anticipate disturbances and adjust operations proactively. For example, refining energy and chemical dosing can be automatically tuned based on incoming furnish variability, while drying and CD profile actuators respond dynamically to moisture imbalances. This predictive capability reduces sheet breaks, improves runnability, and enhances overall machine stability.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?

SBT: As control systems become more intelligent, the role of operators is undergoing a fundamental transformation. Instead of constantly making manual adjustments to valves, drives or setpoints, operators are increasingly taking on the role of process supervisors and decision-makers. This shift is driven by the rise of intelligent automation, which now handles routine adjustments and stabilises day-to-day operations. Automated systems continuously monitor variables such as basis weight, moisture, caliper and formation, applying corrective actions in real-time. As a result, operators are freed from repetitive manual tasks and can focus on higher-level responsibilities such as optimisation, exception management and continuous improvement. Data-driven dashboards are one of the main enablers of this change. These platforms consolidate information from online sensors,

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QCS, machine vision systems and advanced control strategies into a single, operator-friendly interface. Instead of interpreting fragmented data from multiple sources, operators now have a holistic view of the process, complete with predictive analytics and actionable insights. This helps them make faster, betterinformed decisions, whether that means fine-tuning energy, adjusting chemical dosing or responding to anomalies in moisture profiles and machine speed.

SBT: While the potential is significant, legacy automation remains a major obstacle because older platforms often lack the flexibility, connectivity and computational power needed to support advanced process control, model predictive control or AIdriven optimisation. These outdated systems can limit integration with newer technologies and slow down digital transformation efforts. Poor instrumentation and inconsistent data quality also undermine the reliability of measurements, making it difficult to achieve stable control or predictive insights. Without accurate, real-time data, even the most sophisticated algorithms cannot deliver meaningful improvements. Another common barrier is the lack of system integration. Many mills operate with fragmented platforms where data, quality measurements and maintenance information are stored in separate silos. This prevents operators from having a unified view of operations and limits the effectiveness of advanced analytics. Cybersecurity concerns add further

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complexity, as increased connectivity and cloud-based solutions expose mills to potential risks. Ensuring secure data exchange and protecting critical infrastructure are essential for building trust in digital systems. Equally important are human factors. Limited digital skills among the workforce can slow adoption, as operators and engineers may be unfamiliar with advanced analytics, dashboards or AI-driven decision support. Inadequate change management adds to the challenge because cultural resistance to new technologies can prevent successful implementation. Employees may be hesitant to rely on automation or may fear that digitalisation will reduce their roles, unless clear communication and training are provided. From our experience, successful implementation requires strong leadership, comprehensive workforce training and a clear digital transformation strategy. Leadership must articulate a vision that emphasises the benefits of automation and ensures that employees are empowered rather than displaced. Training programmes should build digital literacy, enabling operators to transition from manual control to process supervisors and decision-makers. Finally, a structured strategy ensures that investments in sensors, automation, and analytics are aligned with business goals, creating a roadmap for continuous improvement.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next? SBT: A recent mill automation modernisation project highlighted the tangible benefits of Advanced Process Control (APC) across both pulp and paper operations. In the pulp mill, APC was applied to

PROCESS VARIABILITY MINIMISATION

bleaching processes, ensuring tighter control of chemical dosing and reaction conditions. This stabilised pulp quality and reduced variability in brightness and strength. On the paper machine, APC was used for furnish blend optimisation, balancing fibre types and filler content to achieve consistent sheet properties. Additionally, Quality Control System (QCS) optimisation improved basis weight and moisture uniformity, while machine condition monitoring provided predictive insights into mechanical health, reducing unplanned downtime. The project resulted in improved

basis weight consistency, reduced quality variability, reduced waste generation and increased Overall Equipment Effectiveness (OEE). By stabilising critical parameters, mills achieved smoother operations, fewer sheet breaks, and higher production rates. Waste reduction not only lowered costs but also supported sustainability goals, while enhanced OEE reflected better utilisation of assets and improved reliability across the production line. Looking ahead, mills should prioritise AI-driven optimisation, which can identify relationships in process data and provide

predictive recommendations beyond conventional control strategies. Digital twins will allow mills to simulate process scenarios, test strategies and forecast outcomes without disrupting actual production. Advanced analytics will further enhance decision-making by integrating historical and real-time data to identify root causes of variability. Finally, next-generation sensing technologies will close existing gaps in fibre quality characterisation and real-time chemistry monitoring, enabling even tighter control of furnish and wetend conditions.

Satia Industries Plans to Incur a Capex of INR 4-5 Billion for Capacity Expansion Backed by a multi-year capex plan of INR 4-5 billion, Satia Industries is gearing up to expand paper production capacity and modernise its operations, with the investment expected to enhance efficiency and support future volume growth. Jul 29, 2026 atia Industries Limited (SIL) is set to invest INR 4-5 billion in capex over FY27-FY29 to enhance paper production capacity and improve operational efficiencies, according to India Ratings & Research (Ind-Ra), which has reaffirmed the company’s credit ratings.

The expansion is likely to incur investment for the upgradation of one of its paper machines (PM-3), along with a chemical recovery plant and boiler, investment property, and routine maintenance over a six-month period starting June 2026. The upgrade is expected to add 18,000-20,000 TPA to the existing installed capacity of over 200,000 TPA by the end of Q3 FY27, increasing overall capacity by around 10 percent. While the temporary shutdown of PM-3 is likely to impact production volumes in FY27, the remaining three paper machines will continue operations, with volume growth

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expected to pick up from FY28. According to Ind-Ra, although the ongoing investments and temporary production disruption may increase leverage and moderate earnings in the near term, the additional capacity and efficiency improvements are expected to strengthen the company’s operational performance from FY28 onwards. The agency noted that Satia Industries remains focused on improving returns through operational efficiency rather than undertaking large-scale expansionary projects in the near to medium term.

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PROCESS VARIABILITY MINIMISATION

Ruchira Papers:

Process Stability and Intelligent Control in Modern Paper Manufacturing

Ms. Ruchica G Kumar, Director, Ruchira Papers Limited Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains. Ruchica G Kumar: The two process parameters with the greatest impact on both product quality and overall mill performance are basis weight (GSM) stability and moisture stability. Basis weight (GSM) stability, particularly in the headbox/approach flow section, affects fibre consumption and product quality. Improving basis weight control can typically reduce fibre consumption by 0.3-0.8%, while also improving GSM uniformity, reducing broke, and ensuring

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In an exclusive interview with Paper Mart, Ms. Ruchica G Kumar, Director, Ruchira Papers Limited, shares how the shift from traditional PID-based feedback control in PLC/ DCS systems towards Advanced Process Control (APC), predictive analytics, and intelligent control is helping paper mills achieve greater process stability and quality consistency. The integration of APC, MPC, AI/ML, QCS, online measurement systems, smart instrumentation, machine vision, and condition monitoring is enabling mills to proactively identify process deviations and optimise operations. At Ruchira Papers, the installation of a Bellmer dilution control headbox, a Tri-Nip Press with shoe press, and the Honeywell Calcoil system has contributed to improved basis weight uniformity, dewatering, brightness, moisture consistency, and caliper profile control, demonstrating the measurable benefits of intelligent process control.

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PROCESS VARIABILITY MINIMISATION

Artificial Intelligence (AI) and Machine Learning (ML) are enabling paper mills to move from reactive process control to predictive and proactive optimisation. consistent paper quality. Similarly, moisture stability in the press and dryer section plays an important role in influencing energy consumption, machine runnability, and final paper quality.

PM: How has the approach to controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples. RG: Traditionally, paper mills relied on PID-based feedback control in PLC/DCS systems, where corrective actions were taken only after a process deviation was detected. While effective for basic control, this approach often reacted too late to prevent quality variations. Today, mills are adopting Advanced Process Control (APC), predictive analytics, and Artificial Intelligence (AI)/ Machine Learning (ML)-based optimisation to minimise variability before it impacts production. These systems continuously analyse data from process sensors, quality scanners, and equipment condition monitoring systems to predict disturbances and optimise control actions in real time, enabling mills to achieve greater process stability and more consistent production performance.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?

RG: Advanced Process Control (APC) and Model Predictive Control (MPC) are increasingly being used in paper mills to optimise multiple interacting process variables simultaneously. Unlike conventional PID control, MPC predicts future process behaviour and proactively adjusts control actions while considering process constraints. Key applications include basis weight control, moisture control, refining optimisation, recovery boiler and evaporator operations, and chemical dosing. The application of advanced control strategies has delivered measurable gains, including 0.3–0.8% reduction in fibre usage, 2–8% reduction in steam consumption, and 1–3% reduction in refining energy. They have also resulted in reduced process variability and off-spec production, improved machine runnability with fewer sheet breaks, higher product quality, and improved Overall Equipment Effectiveness (OEE).

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PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality? RG: Artificial Intelligence (AI) and Machine Learning (ML) are enabling paper mills to move from reactive process control to predictive and proactive optimisation. By analysing large volumes of historical and real-time process data, AI and ML models can identify patterns, predict deviations, and recommend corrective actions before product quality or production is affected. Practical applications include predictive quality control, where AI predicts variations in basis weight, moisture, and caliper, allowing operators or APC systems to make adjustments before off-spec paper is produced.

Predictive maintenance uses ML to analyse vibration, temperature, and motor current data to detect early signs of bearing, roll, or pump failures, potentially reducing unplanned downtime by 20–40% in many applications. AI also supports process optimisation by continuously optimising refining energy, steam usage, and chemical dosing, which eventually led to improved efficiency while reducing operating costs. In addition, ML plays an important role in anomaly detection; it identifies abnormal process behaviour that may not trigger conventional alarms, allowing early intervention before a process upset occurs.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant measurements or data gaps remain?

RG: Modern paper mills are using online measurement systems, smart instrumentation, machine vision, and Quality Control Systems (QCS) to continuously monitor critical process parameters, enabling the immediate detection of process deviations and automatic corrective action. Key technologies include Quality Control System (QCS), smart instrumentation, machine vision systems and online condition monitoring. Despite these advances, several measurement and data gaps remain; online measurement of fibre quality, including fibre length, fibrillation, and fine content, is still limited. Similarly, real-time monitoring of wet-end chemistry and retention efficiency is not yet widely

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available, and pitch, stickies and deposits are difficult to detect before they impact the process. In addition, many mills still operate with isolated DCS, QCS, PLC, and condition monitoring systems, limiting the use of integrated analytics and plant-wide optimisation.

PM: Drives and motion control directly influence speed, tension, synchronisation, and machine stability. How are newer drive and control technologies helping mills reduce variability across the paper machine and associated processes? RG: Modern paper mills adopt high-performance AC drives, digital servo systems, and integrated motion controllers to achieve precise speed, tension, and synchronisation across the entire paper machine. Unlike conventional drive systems, these technologies provide faster response, higher accuracy, and seamless coordination between multiple machine sections. Key improvements include: • Electronic line shafting replaces mechanical line shafts, ensuring precise synchronisation between the headbox, press, dryer, calendar, and reel sections. • Advanced tension control maintains stable web tension throughout the machine, reducing wrinkles, web breaks, and reel defects. • High-speed drive communication (e.g., Ethernet/IP, PROFINET, EtherCAT) enables real-time data exchange between drives, PLC/DCS, and QCS for coordinated control. • Adaptive drive control automatically compensates for changes in roll diameter, machine load, and production speed, maintaining stable operation during grade changes. • Integrated diagnostics and condition monitoring continuously monitor motor health, vibration, temperature, and torque, enabling predictive maintenance and reducing unexpected failures.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most? RG: Modern paper mills combine automation such as PLC/DCS, Advanced Process Control (APC), Quality Control Systems (QCS), and integrated process data to continuously monitor, analyse, and optimise production. By integrating process measurements with quality data, control systems can automatically adjust operating parameters before quality deviations occur, resulting in

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more stable operation and reduced process variability. The key improvements include real-time process optimisation using APC and QCS to automatically adjust headbox flow, stock consistency, steam pressure, and moisture control. Similarly, integrated process data from DCS, QCS, machine vision, and condition monitoring systems provides a complete view of machine performance, enabling faster decision-making and root cause analysis. Predictive analytics and AI further help to identify trends and recommend corrective actions before quality is affected at mills. The quality parameters that have benefited most include basis weight (GSM), moisture, caliper (thickness), ash and coat weight, formation, and defect detection. Basis weight (GSM) control has improved MD and CD profile control with a 20–50% reduction in profile variation. More uniform moisture profiles help reduce curls, wrinkles, and dimensional instability, while better caliper consistency improves printability and converting performance. More accurate control of ash and coat weight contributes to improved product uniformity, while optimised stock preparation and headbox control support better fibre distribution and formation. In addition, machine vision systems identify holes, spots, streaks, and edge defects in real time, helping to reduce customer rejects.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing? RG: As paper mills adopt Advanced Process Control (APC), AI, and intelligent automation, the operator’s role is shifting from manual process control to process supervision and decision support. Instead of continuously adjusting process variables, operators now monitor system performance, validate automated recommendations, and manage abnormal situations.

The key changes include a shift from reactive to proactive operation, as operators receive predictive alerts before process deviations affect production or quality. A greater focus on optimisation, with routine control actions being handled automatically, allowing operators to focus on production efficiency, energy optimisation, and quality improvement. Data-driven decision-making is further supported by integrated dashboards that combine data from DCS, QCS, machine vision, and condition monitoring systems, enabling faster and more informed decisions. The other important changes are exception-based management and improved collaboration, with operators intervening primarily during process upsets, equipment faults, or grade changes, while normal operations are maintained automatically. Also, with improved

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Future investment priorities should focus on Advanced Process Control (APC), AI-based process optimisation, online quality measurement (QCS), machine vision systems, and predictive maintenance, enabling mills to further reduce process variability, improve quality consistency, and enhance overall production efficiency. collaboration, operators work more closely with process engineers and maintenance teams by using real-time analytics and predictive maintenance information.

robust cybersecurity are essential for connected automation systems but are often overlooked during modernisation.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next?

RG: While advanced automation and intelligent control technologies offer significant benefits, many paper mills face practical challenges that limit their full potential. The most common barriers include: • Legacy Control Systems: Older PLCs, DCSs, and drives often have limited communication capabilities, making it difficult to integrate modern APC, AI, and IIoT platforms. • Poor Data Quality: Inaccurate or unreliable measurements due to sensor drift, calibration issues, or missing data reduce the effectiveness of advanced control algorithms. • Limited System Integration: Process data is often distributed across DCS, PLC, QCS, machine vision, historians, and condition monitoring systems, preventing a unified view of plant performance. • Instrumentation Gaps: Many critical process variables, particularly in the wet end and chemical dosing systems, are still measured manually or infrequently, limiting real-time optimisation. • Workforce Skills: Successful implementation requires personnel with expertise in automation, data analytics, APC, and cybersecurity. A shortage of these skills can slow adoption and reduce long-term benefits. • Change Management: Operators and maintenance teams may be hesitant to rely on automated decisionmaking without adequate training and confidence in the system. • Cybersecurity and IT Infrastructure: Secure network architecture, reliable data storage, and

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RG: A recent improvement at our mill was the installation of a Bellmer dilution control headbox along with a Tri-Nip Press incorporating a shoe press. The dilution control headbox provides precise cross-direction (CD) basis weight control by adjusting stock consistency across the machine width, resulting in improved fibre distribution, better sheet formation, and reduced profile variation. In addition, the shoe press significantly improved dewatering efficiency in the press section. This increased sheet dryness and enhanced paper brightness from approximately 39% to 43–44% before entering the dryer section. The improved dewatering also contributed to more stable machine operation, better moisture uniformity, and reduced steam demand in the dryer section. Another key initiative was the installation of the Honeywell Calcoil system for caliper profile control. The system continuously monitors and adjusts the crossdirection caliper profile, resulting in a 50% reduction in 2-sigma variation, significantly improving sheet thickness, uniformity, product consistency, and overall quality. The key results achieved include improved fibre formation and CD basis weight uniformity, increased press section brightness from 38% to 44–45%, and a 50% reduction in caliper profile 2-sigma variation following the installation of the Honeywell Calcoil system. Also, better moisture consistency entering the dryer section and improved sheet quality and machine runnability were achieved. Future investment priorities should focus on Advanced Process Control (APC), AI-based process optimisation, online quality measurement (QCS), machine vision systems, and predictive maintenance, enabling mills to further reduce process variability, improve quality consistency, and enhance overall production efficiency.

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Pakka

Shift From ‘Individual Loop Control To Process-Wide Optimization’

Mr. Jagjeet Singh Khanna, Paper Machine Head, Pakka Limited

Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains. Jagjeet Singh Khanna: The highest process variability is typically seen in stock preparation (freeness, consistency and furnish mix), wet-end chemistry and ash control, headbox consistency, and CD/MD basis weight and moisture profiles across the paper machine. Variations in these areas directly impact formation, basis weight, moisture, caliper, strength

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In an exclusive interview with Paper Mart, Mr. Jagjeet Singh Khanna, Paper Machine Head, Pakka Limited, shares that traditionally, paper mills depended on operator intervention and PID-based feedback control during the paper production process. Today, the focus is on predictive and integrated control, feedforward strategies, and real-time process data to identify and correct disturbances before they impact product quality. Pakka, with its integration of DCS, QCS, APC and process data, is positioned well to take faster corrective action and achieve more stable operation. Looking ahead, the company prioritises investment in reliable instrumentation, online quality measurement, and control systems to improve machine efficiency and profile stability, reduce fibre giveaway, and enhance overall reel quality.

properties, reel quality and overall machine runnability. The greatest measurable gains usually come from tighter control of headbox consistency, CD basis weight profile and final moisture profile. These parameters have a direct influence on fibre consumption, steam usage, product quality and customer specifications. In most mills, even a 1–2% reduction in basis-weight or moisture variability (2σ variation) can translate into meaningful reductions in fibre, energy and chemical giveaway while improving quality consistency and reducing off-spec production.

PM: How has the approach to

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controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples. JSK: Traditionally, mills used to depend on operator intervention and PID-based feedback control. Today, the focus is on predictive and integrated control using APC, MPC, feedforward strategies and real-time process data. Instead of reacting to variability, mills are increasingly predicting and correcting disturbances before they impact quality. For example, QCS,

PROCESS VARIABILITY MINIMISATION

APC and MPC are being used primarily for basis-weight and moisture-profile control, refining optimization, headbox stability, and steam-condensate management. The most visible benefits are tighter CD/MD profiles, improved grade-change performance and lower break frequency. Mills typically see 20–40% reduction in profile variability along with measurable steam and energy savings. DCS and APC systems now work together to optimize basis weight, moisture and dryer performance in real time, resulting in improved stability and consistency. This shift from individual loop control to process-wide optimization is delivering significantly better process stability and product quality.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?

JSK: APC and MPC are being used primarily for basis weight and moisture profile control, refining optimization, headbox stability, and steam-condensate management. The most visible benefits are tighter CD/MD profiles, improved grade-change performance and lower break frequency. Mills typically see 20–40% reduction in profile variability along with measurable steam and energy savings.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality? JSK: Today, AI is creating value mainly through break prediction, predictive maintenance, anomaly detection and soft-sensor based quality prediction. Its biggest contribution is providing

early warning of developing process deviations, giving operators and APC systems time to take corrective action before quality or production is affected.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant measurement or data gaps remain?

JSK: Modern QCS scanners, machine vision systems, and smart instruments provide real-time measurements of basis weight, moisture, caliper, consistency, and ash, enabling faster correction of process variations and tighter quality control. Key gaps remain in online measurement of fibre quality, strength properties, furnish composition, and wet-end chemistry, where mills still rely heavily on laboratory testing and inferred values.

JSK: Modern drive systems have significantly improved machine stability through better speed synchronisation,

tension control and sectional coordination. This has helped reduce sheet breaks, tension-related defects and variability during grade changes, particularly on higher-speed machines. In addition, drive diagnostics provide early warning of mechanical issues before they impact production.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most?

JSK: The biggest improvements have been in basis weight, moisture, caliper and ash consistency. Integration of DCS, QCS, APC and process data enables faster corrective action and more stable operation. In practice, tighter CD basis weight and moisture profiles deliver the most visible quality improvements and material savings.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing? JSK: The operator’s role is increasingly shifting from routine control to process supervision and exception management. As APC and automation handle normal process variations, operators can focus more on troubleshooting, grade changes,

QCS, DCS and APC systems now work together to optimize basis weight, moisture and dryer performance in real time, resulting in improved stability and consistency.

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abnormal situations and continuous improvement initiatives.

PM: What typically prevents a mill from achieving the full benefits of advanced automation and intelligent control? Please tell us more about issues such as legacy systems, data quality, system integration, instrumentation, workforce capabilities, etc. JSK: The biggest barriers are usually poor data quality, ageing instrumentation, inadequate sensor maintenance, fragmented systems and limited in-house expertise. Most mills do not face an automation gap; they face a measurement and data-

quality gap. APC and AI can only be as effective as the quality of the data feeding them.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next?

JSK: One of the most impactful improvements in our mill was the installation of an automatic headbox integrated with the QCS system. This enabled continuous correction of basis weight variations and tighter CD profile control based on real-time measurements.

After implementation, we achieved a 20–25% reduction in CD basis weight variation, a 2–3% improvement in machine efficiency, and a noticeable reduction in off-spec production and operator interventions. Improved profile stability also helped reduce fibre giveaway and enhance overall reel quality. Looking ahead, the mills should prioritise investment in reliable instrumentation, online quality measurement, and control systems. Once the measurement backbone is strong, technologies such as APC, MPC, and AI can deliver substantially greater value.

AI is creating value mainly through break prediction, predictive maintenance, anomaly detection and soft-sensor based quality prediction.

NEWS

Dev Priya Industries Commissions New Anaerobic Reactor ETP Plant Dev Priya Industries has successfully commissioned a new state-of-the-art Anaerobic Reactor Effluent Treatment Plant (ETP), with a treatment capacity of 7,200 m³ of wastewater per day. Jul 01, 2026 ev Priya Industries has announced the successful commissioning of its new state-of-the-art Anaerobic Reactor Effluent Treatment Plant (ETP), with a treatment capacity of 7,200 m³ of wastewater per day. The facility is producing approximately 11,000 Nm³ of biogas daily, converting wastewater into a valuable renewable energy source while significantly reducing our environmental footprint.

This milestone fulfills the company’s commitment to a water discharge policy, reinforcing its focus on sustainable manufacturing, responsible resource management, and environmental stewardship. ‘’We remain committed to investing in technologies that

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drive both operational excellence and a greener future,’’ posted the company on its social media handle.

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Jani Sales

Optimises Chemical Consumption and Stabilises Paper Quality Through Online Chemical Dosing Monitoring System

Mr. Pradip Patel, Deputy General Manager, Jani Sales Private Limited

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As paper manufacturing becomes automated and data-driven, maintaining process stability is critical to achieving consistent quality, higher efficiency, and lower operating costs. In an exclusive interview with Paper Mart, Mr. Pradip Patel, Deputy General Manager, Jani Sales Private Limited, discusses how paper mills are moving from reactive to more proactive and predictive operations to reduce process variability across stock preparation, the wet end, press section, and dryer section. He emphasises the role of Advanced Process Control (APC), Model Predictive Control (MPC), AIbased analytics, Machine Learning (ML), and predictive maintenance. He also highlights the mill’s implementation of an online chemical dosing monitoring system to optimise chemical consumption and maintain stable paper quality, while noting that improving online measurement in key processes will be the next step towards achieving even greater process stability. www.papermart.in

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Pradip Patel: Process variability is most persistent in stock preparation, the wet end, the press section, and the dryer section. Key parameters include pulp consistency, refining, basis weight, moisture, pH, retention, and steam pressure. These variations affect paper quality, machine runnability, energy consumption, and overall production efficiency. By improving process stability through advanced automation, APC/ MPC, and real-time monitoring, mills can reduce breaks and waste, improve quality consistency, lower operating costs, and increase overall productivity.

adjustments before they impact quality. For example, MPC can control basis weight and moisture simultaneously, while AI can predict sheet breaks or equipment issues in advance. This helps improve process stability, reduce waste, increase machine efficiency, and maintain consistent product quality.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?

PP: Advanced Process Control (APC) and Model Predictive Control (MPC) help reduce process variability by controlling multiple process variables simultaneously and making adjustments before deviations occur. In paper mills, they are commonly used for basis weight, moisture, refining, and steam pressure control. This results in more consistent paper quality, fewer sheet breaks, lower energy and chemical consumption, and higher machine efficiency. Many mills have achieved measurable improvements such as reduced quality variation, increased production, and lower operating costs after implementing APC and MPC.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?

PP: Artificial Intelligence (AI) and Machine Learning (ML) are helping paper mills move from reactive to predictive operations. They analyse real-time process data to identify patterns that may lead to quality issues, sheet breaks, or equipment failures. Instead of waiting for a

Modern drive and motion control systems provide more accurate speed, tension, and synchronisation across the paper machine. Compared to older systems, they respond faster to process changes and maintain stable operation even at high machine speeds.

problem to occur, AI provides early warnings and recommends or automatically makes process adjustments. For example, it can predict felt or bearing failures, optimise chemical dosing, or detect variations in moisture and basis weight before they affect production. This helps improve product quality, reduce downtime, and increase overall process stability.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant measurement or data gaps still remain? PP: Today, paper mills use online sensors, QCS (Quality Control System), smart instruments, and machine vision to monitor important parameters such as basis weight, moisture, caliper, ash content, sheet defects, and paper profile in real time. This allows operators and control systems to detect process variations immediately

Artificial Intelligence (AI) and Machine Learning (ML) are helping paper mills move from reactive to predictive operations. They analyse real-time process data to identify patterns that may lead to quality issues, sheet breaks, or equipment failures.

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and make automatic corrections to improve paper quality and reduce waste. However, some gaps still remain, particularly in the online measurement of fibre quality, refining efficiency, wet-end chemistry, and sheet formation. These areas still rely on laboratory testing or operator experience. Therefore, improving online measurement in these processes is the next step towards achieving even better process stability.

PP: Automation, advanced process control, and integrated process data help mills maintain stable operating conditions by continuously monitoring the process and making real-time adjustments. This reduces process variation and improves product consistency. The quality parameters that benefit the most include basis weight, moisture, caliper, ash content, formation, thickness profile, and reel quality. As a result, mills achieve fewer quality complaints, lower waste, and more consistent paper production.

PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?

PP: Modern drive and motion control systems provide more accurate speed, tension, and synchronisation across the paper machine. Compared to older systems, they respond faster to process changes and maintain stable operation even at high machine speeds. Features such as servo drives, vector control, and integrated automation help reduce sheet breaks, improve reel quality, maintain consistent tension, and increase overall machine efficiency. This results in better product quality, less downtime, and more stable production.

PP: As control systems become more intelligent, the operator’s role is shifting from manual process control to process supervision and decision-making. Instead of constantly adjusting machine settings, operators monitor realtime dashboards, analyse alarms and AI recommendations, and focus on optimising production. Automation handles routine control tasks, while operators use their experience to solve complex problems, improve performance, and make strategic decisions. This leads to safer operations, greater efficiency, and more consistent product quality.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most?

PM: What typically prevents a mill from achieving the full benefits of advanced automation and intelligent control? Please tell us more about issues such as legacy

systems, data quality, system integration, instrumentation, workforce capabilities, etc.

PP: The biggest challenges are legacy control systems, poor-quality or missing process data, outdated instrumentation, and a lack of integration between DCS, QCS, and other plant systems. In many mills, sensors are not accurate or properly maintained, which affects automation performance. Another challenge is workforce readiness— operators and maintenance teams need training to effectively use advanced automation and AI tools. To achieve the full benefits, mills need reliable instrumentation, clean and integrated data, modern control systems, and skilled personnel who can work with these technologies.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next? PP: In our mill, we implemented an online chemical dosing monitoring system. We continuously monitor chemical consumption and process parameters in real time. Using historical trend data for each paper grade, we optimise the chemical dosage instead of using fixed set points. This has reduced chemical consumption, improved dosing consistency, and maintained stable paper quality. Going forward, I believe mills should invest more in AI-based optimisation and predictive analytics to further improve process stability and reduce operating costs.

Going forward, I believe mills should invest more in AI-based optimisation and predictive analytics to further improve process stability and reduce operating costs.

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JMC Paper Tech: The Road Ahead from Automation to Optimisation Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance?

Sneh Patel: Process variability remains one of the biggest challenges in papermaking because the process involves continuously changing raw materials, water systems, mechanical conditions, chemistry, steam, vacuum, speed, and operator interventions.

Mr. Sneh Patel, Chief Operating Officer, JMC Paper Tech Private Limited

In an exclusive interview with Paper Mart, Mr. Sneh Patel, Chief Operating Officer, JMC Paper Tech Private Limited, explains the shift in modern paper mills from reactive control towards predictive and coordinated process control. He highlights the growing integration of DCS, QCS, PLCs, APC, MPC, drives, AI, machine learning, and smart instrumentation to understand the relationship between multiple variables and reduce process variability. Mr. Patel also discusses JMC’s vision of creating a digital intelligence layer through MillMind™, where AI supports operators, engineers, and management in moving from automation and integration towards prediction and optimisation, with greater process stability and reduced variability at the core of performance improvement.

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In our experience, the most persistent variability starts in the stock preparation and the approachflow system. Changes in furnish composition, recycled-fibre quality, consistency, freeness, ash content, temperature, pH, chemical dosage, and refining directly influence machine performance. On the paper machine, variability occurs across several critical areas include headbox consistency and pressure, basis-weight profile, forming and drainage, vacuum, press loading, moisture entering the dryer section, steam pressure, condensate removal, dryer temperature, sizepress operation, moisture profile, caliper, reel tension, and machine speed. For recycled-fibre mills, furnish variability is particularly important because every incoming batch can behave differently. Tighter stability and control of stock consistency, basis weight,

PROCESS VARIABILITY MINIMISATION

Automation has significantly improved consistency in important paper-quality parameters such as GSM/basis weight, moisture, caliper, formation, strength, Cobb, RCT, burst, tensile and reel quality. However, the greatest improvement occurs when quality information is connected with process information. moisture, steam and condensate, refining, vacuum and machine speed can deliver measurable improvements in production, fibre and energy consumption, paper quality, machine runnability, and reduction in sheet breaks. The objective should therefore not simply be to operate the machine faster. The objective should be to operate it steadily at the optimum operating point.

PM: How has the approach to controlling process variability changed in recent years?

SP: Traditionally, paper mills depended heavily on operator experience and conventional feedback control. When a parameter deviated, the operator would observe the change, identify the probable cause, and then make a correction. Modern mills are moving from this reactive approach toward predictive and coordinated process control. DCS and QCS remain fundamental, but mills are increasingly integrating information from PLCs, drives, QCS, laboratory systems, energy meters, vibration monitoring, and production databases. The important change is that we can now examine the relationship between multiple variables rather than controlling each parameter independently. For example, a moisture deviation may not simply be

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a dryer-steam problem. It can originate from furnish consistency, drainage, press dryness, vacuum, machine speed, or steam/condensate performance. At JMC, we see the next stage as creating a digital intelligence layer over the existing automation infrastructure. This is also the philosophy behind MillMind™—bringing operating, production, consumption, quality, and equipment information together so that management and operating teams can obtain useful insights from data rather than looking at isolated numbers. The future is therefore moving from automation → integration → prediction → optimisation.

PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability?

SP: Advanced Process Control (APC) and Model Predictive Control (MPC) are particularly valuable in papermaking because many variables interact with one another and because there are significant process delays. Traditional PID control generally reacts to an individual

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Ultimately, the future paper mill will not simply be more automated. It will be more connected, more predictive and more self-optimising, while keeping experienced operators and process engineers at the centre of decision-making. deviation. MPC can consider several process variables simultaneously, understand their interactions, and calculate corrective actions while respecting operating constraints. Potential applications include basis-weight control, moisture control, stock consistency, refining, steam and condensate optimisation, dryer control, approach-flow stability, broken management, and energy optimisation. For example, instead of waiting for final-sheet moisture to move outside its target, an advanced control system can consider machine speed, press-section moisture, steam pressure, dryer differential pressure and other variables, and adjust the process proactively. The greatest benefit is often not simply a higher average production rate. It is the reduction in standard deviation around the target. When variability decreases, mills can operate closer to their quality and process limits without increasing the risk of off-spec production. This can result in higher production, reduced fibre usage, lower steam consumption, and fewer breaks.

PM: What practical role are AI and machine learning playing in predicting and correcting process deviations?

SP: AI and machine learning are becoming practical tools for identifying patterns that conventional control systems may not recognise easily. A paper machine generates enormous amounts of data every day. Historically, much of this data has been stored but not fully utilised. AI can analyse relationships between hundreds of parameters and identify patterns that occurred before a sheet break, quality deviation, excessive steam consumption, abnormal vibration, loss of drainage, poor formation, or other operating problem. The real value of AI, is therefore not merely generating reports after an event, but providing early warning before the deviation becomes a production problem. At JMC, through our work with MillMind™, our philosophy is that AI should support operators, engineers and management rather than replace their experience. For example, instead of an engineer manually searching

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historical trends, an intelligent system should eventually be able to answer questions such as: What changed before the last five sheet breaks? Why has steam consumption increased? Which parameters correlate with lower RCT? What operating conditions produced our best-quality reel? This is where AI becomes genuinely useful for the mill.

PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control?

SP: You cannot effectively control what you cannot reliably measure. Modern QCS and smart instrumentation provide continuous information on basis weight, moisture, caliper, ash, temperature, pressure, flow, consistency, vibration, steam, condensate, vacuum, and energy consumption. Machine vision is also becoming increasingly valuable. High-speed cameras can help identify sheet breaks, edge problems, wrinkles, defects, contamination, and abnormal web behavior that are difficult for operators to continuously observe. However, one of the biggest problems we still see is not necessarily the absence of automation, but measurement quality. A sophisticated control algorithm cannot compensate for an incorrectly calibrated consistency transmitter, unreliable flowmeter, damaged pressure transmitter, or poor-quality laboratory data. Therefore, before investing heavily in AI or advanced controls, mills should ensure that critical instrumentation is properly selected, installed, calibrated, and maintained. Our approach is simple: first create trustworthy data, then integrate it, and finally apply intelligence to it.

PM: How are newer drive and motion-control technologies helping mills reduce variability?

SP: Modern sectional drive systems have significantly improved paper-machine stability. A paper machine contains multiple mechanically connected but independently controlled sections. Small speed differences between the forming, press, dryer,

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inspection to quality prediction. The long-term objective should be to establish a digital operating window for every grade: the combination of process parameters that repeatedly produces the desired quality at the lowest practical fiber, chemical, steam, and electrical consumption. That can become a powerful competitive advantage.

PM: As control systems become more intelligent, how is the operator’s role changing?

SP: The operator’s role is becoming more important, but different. size press, calendar and reel sections can create tension variations, wrinkles, sheet instability, and breaks. Modern AC drives, vector control, high-resolution feedback, synchronised control architecture and faster PLC communication allow much tighter coordination between machine sections. Advanced systems can maintain accurate speed ratios, draw, and web tension while responding rapidly to acceleration, deceleration and process disturbances. This becomes increasingly important as machine speed increases because the tolerance for synchronisation error becomes smaller. Drive-system health should also become part of predictive maintenance. Motor current, torque, speed error, bearing temperature, and vibration can provide early indications of mechanical or process abnormalities. Therefore, the drive system should no longer be viewed only as a means of rotating equipment; it is an important source of process information and machine-health data.

PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? SP: Automation has significantly improved consistency in important paper-quality parameters such as GSM/ basis weight, moisture, caliper, formation, strength, Cobb, RCT, burst, tensile and reel quality. However, the greatest improvement occurs when quality information is connected with process information. For example, if RCT decreases, looking only at the laboratory result tells us what happened, but not why.

When quality data is integrated with furnish composition, refining, consistency, basis weight, moisture, press loading, steam conditions and chemical dosage, the mill can start identifying the process conditions responsible for that result. This allows mills to move from quality

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In traditional mills, operators spend considerable time watching individual parameters and manually correcting deviations. As automation becomes more intelligent, routine adjustments can increasingly be handled automatically. This allows operators to concentrate on process supervision, abnormal-condition management, optimisation, and decision-making. However, automation should not become a black box. Operators need to understand why the system is recommending or making a particular change. Therefore, future operator interfaces should provide not only alarms, but also context and possible causes. The best result comes from combining experienced operators with intelligent digital systems. AI has tremendous analytical capability, while experienced papermakers possess practical process knowledge developed over years. Combining the two creates a much stronger operating environment than either one working independently.

PM: What typically prevents a mill from achieving the full benefits of advanced automation? SP: The biggest limitation is often not technology itself. Common barriers include legacy PLC/DCS systems, disconnected databases, poor instrumentation, inconsistent tag naming, unreliable sensors, insufficient historical data, manual laboratory records, weak network infrastructure, and lack of integration between production, quality, and maintenance systems. Another major issue is organisational. Production, electrical, instrumentation, quality, maintenance, and management teams sometimes operate with separate information systems. The result is multiple versions of the same operating reality. Workforce capability and acceptance are equally important. If operators believe that automation or AI is

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PROCESS VARIABILITY MINIMISATION

being introduced to replace them, adoption becomes difficult. They should instead be involved from the beginning and shown how technology can make their jobs easier and decisions better.

of MillMind™, which is designed as an intelligence and information layer around mill operations. Instead of replacing existing PLC, DCS or QCS infrastructure, the objective is to extract more value from the data that mills already generate.

Cybersecurity and data security must also be considered as connectivity increases.

For future investment, we believe mills should prioritise in the following sequence:

For many mills, therefore, the correct first investment is not necessarily the most sophisticated AI platform. It may be better instrumentation, standardised data, connectivity, and system integration.

Reliable instrumentation AI-assisted Decision-making.

PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? Where should mills prioritise investment next?

Data Connectivity

DCS/QCS Optimization

Advanced Analytics

Predictive Control

Integrated Historian/ Data Platform

The industry should also focus increasingly on measuring success through variability, not only averages. Two machines may both average the same GSM, moisture, or production, but the machine with the smaller standard deviation will generally have better quality consistency, lower waste and greater opportunity for optimisation.

SP: At JMC, our practical approach is strongly influenced by operating experience from paper-machine projects and by implementing digital solutions in a real mill environment. One important learning has been that meaningful improvement comes from connecting production, quality, consumption, and equipment information rather than treating them as independent systems. This philosophy has contributed to the development and implementation

NEWS

Khanna Paper Mills Win CII Award for Energy Efficiency Khanna Paper Mills Ltd. has been awarded first runner up in the Best Energy Efficient Organization category at the 10th CII National Energy Efficiency Circle Competition 2026. Jul 08, 2026 hanna Paper Mills Ltd. has announced that it has been awarded as the first runner up in the ‘Best Energy Efficient Organization’ category at the 10th CII National Energy Efficiency Circle Competition 2026.

Competing with 25 organizations from across India, this award recognition reflects the company’s commitment to energy efficiency, sustainable manufacturing and operational excellence. It is a testament to their dedication, innovation and collaborative spirit of the team as they continue advancing towards a low-carbon, resource efficient future. ‘’We thank the Confederation of Indian Industry (CII) for this recognition and congratulate the entire Khanna Paper team on this success,’’ posted the company on its social media handle.

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GLOBAL COLLABORATION

Rinheat, OrbiGreen Techsource Unite for Advancing Energy-Smart Paper Mills & Sustainable Industrial Solutions

Finnish industrial engineering company Rinheat Oy and India-based OrbiGreen Techsource have joined hands to enhance energy efficiency and performance across Indian pulp and paper mills. Rinheat brings decades of expertise in heat recovery, heat transfer, and evaporation processes, while OrbiGreen serves as a sourcing, engineering, and execution partner. Together, they aim to help Indian mills reduce their carbon footprint and achieve more stable operations. In an exclusive interaction with Paper Mart, Mr. Ville Mäkinen, Managing Director & CEO of Rinheat Oy, and Mr. Manish Sharma, Founder & CEO of OrbiGreen Techsource, discuss their partnership. Paper Mart: Could you introduce Rinheat? Ville Mäkinen: Rinheat Oy is a Finnish industrial engineering company based in Espoo that specializes in heat transfer, heat recovery, and evaporation technology. Founded in 1986, the company has been with its current owners since 1993. We primarily serve the pulp and paper, energy, biofuels, food, and pharma industries, while also delivering custom thermal solutions for other process-engineering sectors.

With over 40 years of experience, more than 200 global references, and long-standing relations with many customers, Rinheat combines agility with highly experienced personnel and fast response times.

Mr. Manish Sharma, Founder & CEO, OrbiGreen Techsource

Mr. Ville Mäkinen, Managing Director & CEO, Rinheat Oy

PM: Could you give us a brief overview of OrbiGreen TechSource and its role as a sourcing partner for the pulp and paper industry in India?

Manish Sharma: OrbiGreen TechSource is a new-age sourcing and modernization partner delivering sustainable industrial solutions across India’s pulp & paper, energy, food, pharma, bio fuels and textile sectors. We bring specialized

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GLOBAL COLLABORATION

engineering capabilities and futureready global technologies to India and the Asia-Pacific region, enabling mills to enhance energy efficiency, strengthen thermal performance, and optimize critical processes with proven, high-impact solutions.

By reusing cleaner secondary condensate, mills can reduce rawwater consumption. The low internal pressure drop improves the effective delta-T across evaporation trains, while the lightweight construction lowers manufacturing costs.

We operate at the intersection of technology sourcing, engineering consultation, and project execution. We identify best-in-class global technologies and adapt them to Indian or local operating conditions through strong local partnerships, supplier networks, and on-ground technical support.

Heat recovery is another important area, where contaminated process steam or vapour can be recovered to produce clean steam or hot water. We also have our own patented technology, which has been proven globally.

As the industry is evolving, driven by packaging growth, energy cost pressures, and sustainability expectations, mills need partners who can offer retrofit solutions. OrbiGreen Techsource meets that need.

PM: Why is the Indian market strategically important to you?

VM: We had been exploring opportunities in new markets for many years and found the ideal partner in OrbiGreen Techsource through our network. India is the fastest-growing market in the world today and offers immense potential. Manish has a strong background in the pulp and paper industry and a long history of working with global companies. He also has a good understanding of local supplier networks, project management, and engineering. OrbiGreen Techsource is the perfect partner to drive our expansion.

PM: Which Rinheat technologies do you see having the strongest potential in India?

VM: I would say our evaporation technology is a key differentiator. Our proven solutions include condensate segregation, compact equipment footprints designed for tight spaces, and small internal pressure drop in evaporation effects.

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PM: How will you support Indian mills beyond supplying the technology? MS: We begin by working closely with mills to understand their current thermal performance and bottlenecks. This includes assessment of steam load, evaporation and condensate systems, heat recovery, and energy efficiency. Such upfront engineering ensures that every solution is customized to the mill’s operating reality. OrbiGreen Techsource manages the execution lifecycle, including detailed engineering coordination with Rinheat, manufacturing and fabrication oversight, quality assurance and inspection, and on-site installation planning and supervision. During commissioning, we jointly work with Rinheat’s engineers to oversee start-up, validate performance parameters, optimize steam balance, and stabilize evaporation and heat-recovery systems. We remain engaged long after commissioning through routine performance reviews, troubleshooting and technical guidance, spare-parts support, and training for mill operators and maintenance teams. This long-term

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engagement ensures mills maintain high uptime, stable operations, and sustained energy savings.

PM: How are you helping customers improve energy efficiency?

VM: Like I said, having the better condensate segregation reduces the mill’s use of raw water. Smaller internal pressure drops inside the evaporation effects, recovering heat from process steam, and addressing heat exchangers that are not operating well can also improve efficiency. It depends on the customer and what the actual challenges are in the mill. We have innovative designs that reduce equipment weights and footprints.

PM: What are some of the key challenges faced by pulp and paper mills today, and how does OrbiGreen Techsource help customers address them?

MS: Pulp and paper is one of India’s energy-intensive industries, with mills facing excessive steam usage in evaporation, drying, and inefficient heat-recovery systems. OrbiGreen Techsource addresses these challenges through high-efficiency equipment, including evaporators, condensers, and air-heaters from Rinheat, along with optimized heatrecovery and condensate systems. Our solutions enable steam‑load reduction of 10–20%, lower fuel consumption, and improved thermal balance. Many mills also operate ageing evaporation plants and heatrecovery units, resulting in poor condensate quality and low dry-solids levels. Retrofitfriendly solutions suited to Indian operating conditions can improve condensate quality and evaporation performance. Thermal inefficiencies can also lead to higher downtime. Data-driven diagnostics, technical audits, and

GLOBAL COLLABORATION

engineering interventions help improve operational stability and reliability. Finally, mills need to upgrade their systems without long shutdowns. Retrofit-based execution, strong Indian fabrication and installation capabilities, and tight project management help minimize disruption to ongoing production.

PM: What differences do you see in the needs and priorities of Indian pulp and paper mills compared with customers in other markets?

VM: In the Nordics and Europe, there is high dependency on virgin softwood and hardwood fibres sourced through sustainable, FSCand PEFC-certified forestry networks, alongside highly structured recycled paper loops. India relies more on non-wood agroresidues such as bagasse, straw, and bamboo, as well as domestic and imported recovered paper, and limited wood supply. Priorities focus on handling high silica content, raw-material yield consistency, and moisture variations. There are also differences in sustainability and regulatory drivers. The Nordics and Europe have stricter

environmental policies, with priorities including decarbonization, fossil-free energy, chemical recovery efficiency, and zero-waste side streams. In India, priorities include water conservation, Zero Liquid Discharge, and cost-effective compliance to reduce water, energy, and chemical footprints per tonne.

OrbiGreen Techsource and Rinheat in the coming years?

The scale and investment landscape also differ. Europe has many highly capital-intensive, megascale integrated mills, with strong emphasis on digital transformation, advanced process control, predictive maintenance, and Industry 4.0 automation. India has a mixed landscape of large integrated mills alongside SME mills, where priorities favour fast return on investment, low upfront capital expenditure, modular machine upgrades, and versatile equipment.

PM: What are the principles that you believe will guide the two companies as you build this relationship?

When it comes to energy priorities, the Nordics are totally shifting toward energy self-sufficiency through bioenergy, green-grid integration, and recovering surplus process heat, while India focuses on boiler efficiency, cogeneration systems, and energy-cost containment to protect mill margins.

PM: What can the Indian industry expect from both

MS: World-class European thermal technology, strong Indian execution capability, a long-term modernization roadmap, and our deep, sustained partnership to help them fully prepare for the next decade of growth.

VM and MS: We are united by five core principles: engineering integrity, transparency, sustainability, local capability, and long-term partnership. We listen to each mill’s unique challenges and design solutions that fit their operating realities. Our technologies and execution approach are aligned with long-term ESG goals – reducing steam consumption, lowering emissions, and improving resource efficiency. These principles guide how we work together and how we help Indian mills become more future-ready. Every solution we deliver must be capable of producing real, quantifiable performance gains. We combine Finnish innovation with strong Indian execution, skill development, and lifecycle support to ensure mills benefit not just today, but for decades to come.

What excites us most is the chance to combine Finnish innovation with Indian execution strength to deliver real, measurable improvements for mills. We share the same values — engineering integrity, transparency, and a commitment to long-term customer success. Together, we are building a partnership that is not only technically strong, but genuinely meaningful for the future of the Indian pulp and paper industry.

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NEW BEGINNINGS

Oryx Kraft Mill to Push UAE’s Circular Economy and Downstream Manufacturing Ecosystem In an exclusive interaction with Paper Mart, Mr. Nikhil Jham, Director, and Mr. S. Venkatesh, Director - Project & Operations, Oryx Kraft Mill Industries Limited, UAE, discuss Oryx Kraft Mill Industries’ plans to establish a modern, integrated kraft paper manufacturing facility with a capacity of 150,000 tonnes per annum at KEZAD Al Ma’mourah in the UAE, with commercial production targeted for Q1 2028. The project is aimed at serving the growing demand for kraft and packaging papers across the UAE, GCC and wider Middle East. They share insights into the project’s vision, sourcing strategy, approach to automation and AI, and expectations for the region’s packaging market.

Mr. Shiraz Gulam Hussien Hamirani, Managing Director, Oryx Kraft Mill Industries Limited, UAE

Ms. Farah Hamirani Jham, Managing Director, Oryx Kraft Mill Industries Limited, UAE

Paper Mart: Oryx Kraft Mill Industries has signed an agreement with KEZAD Group to establish a 107,309 sq.m. paper manufacturing facility in KEZAD Al Ma’mourah. Could you tell us more about this project, including its vision, key objectives and how this facility will contribute to the UAE’s downstream manufacturing and paper industry ecosystem? Nikhil Jham: Oryx Kraft Mill Industries’ project in KEZAD is

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Mr. Nikhil Jham, Director, Oryx Kraft Mill Industries Limited, UAE

envisioned as a modern, integrated kraft paper manufacturing facility serving the rapidly growing packaging and converting industries across the UAE, GCC and wider Middle East. The facility will focus primarily on producing high-quality kraft and packaging papers for applications such as corrugated packaging and industrial packaging. Our objective is not only to establish a competitive paper mill, but also to become

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Mr. S. Venkatesh, Director- Project & Operations, Oryx Kraft Mill Industries Limited, UAE

an important part of the UAE’s circular economy and downstream manufacturing ecosystem. The project will strengthen local and regional supply chains by increasing the availability of locally manufactured kraft paper, reducing dependence on imports and supporting the growth of paper converters, packaging manufacturers and other downstream industries. The location within KEZAD also provides excellent connectivity to

NEW BEGINNINGS

The initial production capacity is planned at approximately 150,000 tonnes per annum, with a paper machine designed for high efficiency and flexibility across a range of kraft paper grades. ports, logistics infrastructure and industrial customers, enabling us to efficiently serve both the domestic UAE market and export markets.

PM: What is the planned capex and production capacity of the mill, and do you foresee any phased expansions in the near future? By when is the mill expected to commence commercial production?

Venkatesh Subbiah: The project is being developed as a major industrial investment, with the final project capex being aligned with the detailed engineering, equipment and infrastructure scope. The initial production capacity is planned at approximately 150,000 tonnes per annum, with a paper machine designed for high efficiency and flexibility across a range of kraft paper grades. The facility has been planned with future expansion and product diversification in mind. As market demand develops, we will evaluate additional capacity and downstream integration in phases. Commercial production is targeted by Q1 2028 following completion of construction, installation, commissioning and performance testing of the plant. Our priority is to ensure a safe and technically robust start-up.

PM: Which paper grades are you planning to produce initially, and how did you decide on those product segments? VS: Our initial product mix is planned around fluting paper and test liner, covering a broad range of packaging applications. We have decided on these product

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segments based on three factors: Firstly, the rising demand for sustainable paper-based packaging; secondly, the continued growth in e-commerce, food and beverage, retail, logistics and industrial packaging; and thirdly, the changing customer requirements for paper. The strong and growing demand for sustainable paper-based packaging across the GCC and Middle East is driving the need for these products. The region is experiencing continued growth in e-commerce, food and beverage, retail, logistics and industrial packaging. These sectors are further driving demand for corrugated boxes, paper bags and other fibre-based packaging solutions. We also want the mill to have sufficient flexibility to respond to changing customer requirements in terms of basis weight, strength characteristics and end-use applications.

PM: Can you tell us why you chose the specific location for the mill and how the UAE fits into your long-term strategic vision?

NJ: Our Promoter & Managing Director, Mr. Shiraz Hamirani, has been running his company, Paper Chase International, in the UAE and many other GCC countries for more than 35 years, which is now being jointly steered by our Managing Director, Ms. Farah Hamirani Jham. Paper Chase International is one of the largest collectors and exporters of waste paper in the Gulf. Our Managing Director’s experience in running the business in the Gulf for so long and his vision of the future growth potential

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of this region have been one of our major guiding forces in our selection of this location in the UAE. Hence, the UAE was a natural strategic choice because of its excellent industrial infrastructure, logistics connectivity and position as a gateway between Asia, the Middle East, Africa and Europe. KEZAD Al Ma’mourah offers several important advantages, including proximity to major ports, road connectivity, availability of industrial infrastructure and access to a growing base of manufacturing and packaging customers. The UAE is also developing rapidly as a manufacturing and logistics hub. Establishing the mill here allows Oryx Kraft Mill Industries to be close to our customers while also providing an efficient platform for exports across the GCC and other international markets. Our long-term vision is to establish the UAE as an important production and distribution base for kraft paper and related packaging products in the region.

PM: How do you plan to source your raw materials–will you rely more on local supplies, imports, or a mix of both?

NJ: The recovered fibre will be sourced mainly through local supplies, which will be collected through our parent company, Paper Chase International. Some quantity of high-strength recovered fibre will be imported from Europe and the USA through our network. For other raw materials, we plan to follow a balanced sourcing strategy, combining local and imported raw

NEW BEGINNINGS

Automation and digitalisation will be important components of the mill’s operating philosophy. Modern process control systems will be used to monitor and optimise critical parameters across stock preparation, approach flow, paper machine operations, finishing and utilities. materials depending on availability, quality, consistency and commercial competitiveness. A diversified sourcing model is particularly important for a large paper mill because raw-material availability and quality can vary between markets. Our objective is therefore to build a reliable and flexible supply chain rather than depend on a single geography. Over time, we also expect the UAE’s recycling and recovered-paper ecosystem to develop further, creating additional opportunities for local sourcing and supporting the country’s circular-economy objectives.

PM: With over a decade of working in Indian paper mills and now moving from the Indian paper industry to setting up a mill in the UAE, what have been some of the biggest challenges so far? What are you most excited to work on in the future?

progress in a coordinated manner. At the same time, this is what makes the project exciting. The opportunity to build a modern paper mill from the ground up gives us the ability to incorporate the best practices we have learned from our experience in the Indian paper industry while adapting them to the requirements of the UAE and GCC markets. I am particularly excited about building a strong technical and operational team in the UAE and creating a mill that can benchmark itself against the best kraft paper producers in the region.

PM: With rapid digital transformation across industries, how do you plan to leverage automation and AI in mill operations to improve efficiency, quality, and cost control? VS: Automation and digitalisation will be important components of the mill’s operating philosophy.

VS: Setting up a greenfield paper mill is always a challenging exercise, irrespective of the geography. Moving into a new country adds another dimension because we have to understand a new regulatory environment, develop local supply chains and establish relationships with contractors, suppliers and service providers.

Modern process control systems will be used to monitor and optimise critical parameters across stock preparation, approach flow, paper machine operations, finishing and utilities. The objective is to achieve consistent product quality while improving energy efficiency, productivity and Overall Equipment Effectiveness (OEE).

One of the biggest challenges is bringing together the various elements of a large project – engineering, technology, procurement, construction, utilities, logistics, manpower and regulatory approvals – and ensuring that they

We also see significant potential for AI and advanced analytics in areas such as predictive maintenance, process optimisation, quality monitoring, energy management and production planning.

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Rather than treating AI as a www.papermart.in

standalone technology, we intend to integrate digital tools into the overall operating system of the mill. Reliable real-time data, disciplined process control and experienced operators will remain the foundation, with AI and analytics providing additional decision-support capabilities.

PM: Looking ahead, how do you envision the demand for kraft paper evolving in the Middle East, and what role do you see your mill playing in that growth? NJ: We are very positive about the long-term outlook for kraft paper in the Middle East.

The region is experiencing structural growth in packaging demand, supported by population growth, urbanisation, e-commerce, food and beverage, logistics and industrial development. At the same time, there is a clear global and regional movement towards replacing plastic and other less sustainable packaging formats with recyclable paper-based alternatives. We expect demand for kraft paper and containerboard products to continue growing over the next decade, particularly in the GCC. Oryx Kraft Mill Industries aims to participate in this growth by providing reliable, consistent-quality paper from a strategically located manufacturing base. Our objective is to serve UAE customers efficiently while building a strong export presence across the GCC and wider Middle East. Ultimately, we want Oryx Kraft Mill Industries to become a dependable

NEW BEGINNINGS

A successful paper mill is not built around one machine, one process or one individual. It is the result of disciplined operations, reliable equipment, good raw-material management, strong people and continuous attention to quality and cost. regional partner for packaging manufacturers rather than simply another paper supplier.

PM: A transition is often enriched by learning. Could you please share what has been your biggest learning so far in the paper industry as you move ahead to take on new roles and challenges?

VS: One of the biggest lessons I have learned from the paper industry is that consistency is more important than short-term performance.

A successful paper mill is not built around one machine, one process or one individual. It is the result of disciplined operations, reliable equipment, good raw-material management, strong people and continuous attention to quality and cost. Over the years, I have also learned that every mill and every market is different. Experience gives us a strong foundation, but we must always be willing to learn, adapt and adopt better technologies and practices.

The Oryx Kraft Mill project provides an opportunity to bring together that experience with a new environment, new technology and a new team. My biggest focus going forward will be to build a culture of safety, operational excellence, teamwork and continuous improvement. For me, the most rewarding part of this project will be seeing the mill progress from engineering and construction into a stable, efficient operation and ultimately becoming a recognised kraft paper producer in the GCC.

Oryx Kraft Mill Partners with Alliance International to Commission State-of-the-Art 180,000 TPA Packaging Paper Production Line Oryx Kraft Mill Industries Limited has officially announced a strategic partnership with Alliance International to deploy a highly advanced, integrated corrugated packaging paper production line. Backed by 37 years of pulp and paper industry expertise, Alliance International will deliver an end-to-end manufacturing solution designed to optimize production efficiency, drastically reduce energy consumption, and secure long-term operational profitability for Oryx. Following rigorous technical evaluations and multiple on-site factory verifications, Oryx selected Alliance International as its trusted partner for this foundational venture into raw paper production. The project features a cutting-edge production line designed and manufactured by Sichuan Chengfa Paper Machinery Factory, China’s premier paper machinery manufacturer equipped with large-scale, advanced CNC tool capabilities. Machinery delivery is officially scheduled for mid-2027. The new line will have an annual capacity of 180,000 tons of premium corrugated packaging paper, with a daily output of 550 tons. Featuring a wire width of 4,850 mm and a design speed of 1,000 m/min, the machine will incorporate advanced shoe press technology. In a significant shift from costly European imports, the project will introduce a highly mature, Chinese-manufactured shoe press, delivering world-class operating efficiency and low energy consumption at a significantly lower capital expenditure (CapEx). This is expected to accelerate Oryx’s return on investment while enhancing the overall efficiency and competitiveness of its operations.

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INDUSTRY INSIGHTS

Where Is Global Pulp & Paper Capacity Headed?

n industry outlook by ResourceWise, based on insights from FisherSolve’s global mill intelligence, highlights the capacity, investment and strategic shifts shaping the pulp and paper industry through 2030.

time, mature markets continue to optimize their manufacturing footprint by rationalizing older assets through closures, converting grades, and modernization projects where it makes sense.

The global pulp and paper industry is entering a new investment cycle-but unlike previous expansion periods, growth is becoming increasingly selective.

For producers, suppliers, and investors, the opportunity isn’t simply in tracking new mill announcements; it’s in understanding the broader investment patterns shaping the industry’s competitive landscape.

Rather than broad-based investment across every region and grade, producers are concentrating capital in markets where fiber availability, production costs, export opportunities, and long-term demand create a competitive advantage. At the same

Using FisherSolve’s® global mill database, we analyzed announced capacity additions, site changes, and investment activity through 2030 to identify where the industry is heading— and what those trends may signal for future market dynamics.

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INDUSTRY INSIGHTS Global Growth Is Becoming Increasingly Concentrated

Announced Pulp and Paper Capacity Additions by Region

The industry’s investment story isn’t one of broad global expansion. Instead, capital is flowing toward a relatively small number of regions that offer the strongest combination of demand growth, cost competitiveness, and long-term strategic value.

Announced Pulp and Paper Capacity Additions by Region

The regional investment pipeline shows a pronounced concentration of new capacity in Asia-Pacific, particularly in projects scheduled to come online over the next several years. While North America, Latin America, Europe, Middle East continue to see investment activity, their pipelines are considerably smaller by comparison.

Source: FisherSolve

Where Producers Are Placing Their Long-Term Bets

Investment by product grade offers another important signal.

This isn’t simply a reflection of population growth. Producers are making deliberate decisions about where they can manufacture most competitively in the long term.

Rather than spreading capital evenly across all product categories, producers continue to focus on grades supported by long-term demand fundamentals.

Several factors continue to influence these decisions:

Announced Pulp and Paper Capacity Additions by Major Grade

•

Access to cost-competitive fiber

•

Modern infrastructure

• • • •

Availability and cost of energy Export potential

Long-term regional demand Regulatory certainty

The implication is clear: competitive advantage is becoming increasingly regional. Companies operating in lower-cost regions with access to expanding demand are likely to strengthen their position, while producers in higher-cost markets will face pressure to differentiate through efficiency, specialization, or modernization. For suppliers, these regional investment trends provide an early indicator of where future demand for equipment, chemicals, automation systems, and engineering services is likely to emerge.

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Packaging grades account for a significant share of announced investments, reflecting continued confidence in global corrugated and consumer packaging demand. Market pulp also remains an area of sustained investment as producers position themselves to serve

growing global fiber requirements. Meanwhile, printing and writing grades continue to represent a much smaller portion of announced projects, reinforcing the structural transition that has been underway for years.

More important than the absolute volume of new capacity is what these investments communicate about executive confidence. Capital projects typically require years of planning and significant financial commitment. They represent long-term expectations— not short-term reactions. Where companies choose to invest today provides one of the clearest signals of where they expect demand to exist tomorrow.

Announced Pulp and Paper Capacity Additions by Major Grade

Source: FisherSolve

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INDUSTRY INSIGHTS Industry Transformation Is Happening Through Both Expansion and Rationalization

Pulp and Paper Site Changes by Region

Focusing exclusively on announced capacity additions tells only part of the story. Every new machine startup exists alongside facility closures, machine conversions, and permanent shutdowns that continue reshaping the industry’s production footprint.

Pulp and Paper Site Changes by Region

FisherSolve data shows this dynamic playing out across multiple regions. While AsiaPacific continues adding sites, Europe experiences continued rationalization, with additional closures reflecting efforts to reduce excess capacity and improve overall competitiveness. North America presents a more balanced picture, where investment increasingly focuses on optimizing existing assets rather than broad expansion. Across much of the industry, producers are replacing smaller, older, higher-cost assets with larger, more efficient operations capable of delivering stronger long-term returns. For investors, these closures often reveal where assets have become structurally uncompetitive. Producers highlight how competitors are reshaping their manufacturing footprint to remain cost-competitive. Suppliers identify where maintenance spending may decline—and where modernization activity is likely to increase.

Modernization Is Becoming a Preferred Investment Strategy Perhaps the clearest signal of today’s investment environment

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Source: FisherSolve

is how companies are choosing to deploy capital. Rather than pursuing large-scale greenfield developments, many producers are extending the life of existing assets through machine conversions and modernization projects. Conversions offer several advantages, including lower capital requirements, faster implementation timelines, reduced project risk, and greater flexibility to respond to changing market conditions. This approach reflects a more disciplined investment strategy compared with previous expansion cycles. Instead of adding capacity simply because demand exists, producers are increasingly asking whether existing assets can be upgraded to meet future market needs more efficiently. That shift is likely to continue as companies balance growth opportunities with higher capital costs, sustainability objectives, and shareholder expectations.

Three Strategic Takeaways

Looking across the global investment pipeline, three themes stand out. 1. Investment Is Becoming More Selective

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Capital is increasingly flowing toward regions that combine favorable economics with long-term demand potential. Future competitiveness will depend as much on location as production capability. 2. The Industry Is Prioritizing Efficiency Over Expansion Growth is no longer measured solely by new mills. Modernization, conversion, and asset optimization are becoming equally important strategies for maintaining competitiveness. 3. Investment Decisions Offer a Window into Future Markets Capacity projects are among the strongest leading indicators of where producers expect future demand, margin opportunities, and competitive advantage to exist. Monitoring these investments helps companies anticipate market shifts well before they appear in production or trade data.

Looking Ahead

The next five years are unlikely to resemble previous investment cycles. Rather than widespread expansion, the industry is entering a period of targeted capital deployment focused on efficiency, resilience, and longterm competitiveness. Companies are investing where they believe they can secure lasting advantages, not

INDUSTRY INSIGHTS

simply where demand is strongest today. For producers, suppliers, and investors, understanding these trends before new capacity comes online creates a meaningful strategic advantage. Knowing where capital is

flowing, which grades are attracting investment, and how competitors are reshaping their asset base can inform everything from commercial strategy to procurement planning and investment decisions. FisherSolve’s global mill intelligence

enables you to move beyond individual announcements and see the larger story: one in which capital allocation, regional competitiveness, and operational efficiency are redefining the future of the pulp and paper industry.

NEWS

Andhra Paper Restores 93% Production Capacity at Kadiam Unit Andhra Paper Limited has resumed operations of its second paper machine at its Kadiam Unit, taking the facility’s operational capacity to around 93 percent of normal levels. The company said it continues to work towards full stabilization and restoration of manufacturing activities following the disruption caused by contract workers’ demands for revised contractual terms. Jul 24, 2026 ndhra Paper Limited has announced the resumption of its second paper machine, with a production capacity of 55 MT per day, at its Kadiam Unit in Andhra Pradesh, effective July 23, 2026. With this development, the unit’s overall operational production capacity has increased from nearly 70 percent to approximately 93 percent of its normal output.

The company stated that it is implementing necessary operational measures to progressively stabilize operations and restore full production at the earliest. The disruption at the Kadiam Unit was attributed to demands raised by contract

workmen regarding revisions to certain contractual terms, although the company clarified that no physical damage occurred to its assets.

Crown Paper Mill Commissions Saudi Arabia Tissue Paper Mill Crown Paper Mill has successfully commissioned its CPM Saudi Arabia Tissue Paper Mill and started up a high-speed Valmet tissue paper machine. Sep 9, 2026 rown Paper Mill (CPM) has announced the successful commissioning of its Saudi Arabia Tissue Paper Mill, marking a significant milestone in the company’s growth and expansion journey.

The facility has commenced operations with the start-up of a high-speed Valmet tissue paper machine operating at 2,200 m/min. The commissioning follows the earlier progress at the CPM4 project in Jubail and brings the new production facility into operation. According to the company, the milestone reflects the combined dedication, technical expertise and teamwork of the project team involved in developing and commissioning the

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new tissue paper mill. The successful start-up of the new machine marks another step in strengthening Crown Paper Mill’s tissue paper manufacturing operations in Saudi Arabia.

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INTERVIEW

Parason

Commissions 400–450 TPD Recycled OCC Stock Preparation Line to Suchonski Pulp & Paper Mill in Europe

Mr. Madhure Desarda, Director—Business Development, Parason Machinery Private Limited

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In an exclusive interview with Paper Mart, Mr. Madhure Desarda, Director—Business Development, Parason Machinery Private Limited, shares that the company has successfully designed, supplied, commissioned, and handed over a complete stock preparation line to Suchonski Pulp & Paper Mill in Eastern Europe, engineered to process 400– 450 TPD of recycled Old Corrugated Containers (OCC). Designed to maximize fiber recovery, ensure consistent stock cleanliness, and adapt to incoming raw material variation, the line provides the mill with a stable and reliable OCC processing platform, operating as an integral part of the mill’s daily production. The new installation enables Suchonski Pulp & Paper Mill to scale its operations while meeting the growing demand for recycled-fiberbased packaging solutions.

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INTERVIEW

Paper Mart: Parason has successfully commissioned a complete stock preparation line for recycled OCC in Eastern Europe. Can you tell us about the new line and its technical specifications?

Madhure Desarda: Parason has designed and delivered a complete stock preparation line for 400–450 TPD of recycled Old Corrugated Container (OCC) furnish, specifically engineered for Russian OCC (ROCC) — a fiber grade known for its variability in cleanliness, fiber length, and contaminant load. The line was executed as a wastepaper pulping and stock preparation project, combining Parason’s core engineering strength and stock preparation expertise accumulated with hand over experience of the last 5 decades. The system integrates a full suite of Parason equipment engineered to work as a single, optimized process package: AFS-15 pulper for highconsistency pulping for efficient defibering of OCC bales; ragger / rope cutter for continuous removal of long-strand contaminants (wires, ropes, plastics); junk trap for heavyreject removal (stones, metals, wire fragments); trommel screen for rotary coarse screening for large debris separation; pressure screens for fine screening for stock cleanliness ahead of the paper machine; and cleaning & screening systems for integrated multi-stage cleaning package. The line is engineered to maximize fiber recovery, deliver consistent stock cleanliness, and provide the mill with a stable, reliable OCC processing platform that adapts to variations in incoming raw material quality.

PM: In which paper mill is the new stock preparation line commissioned? Did you encounter any challenges while commissioning the line and how

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did you overcome them?

MD: The line has been successfully commissioned at Suchonski Pulp & Paper Mill in Eastern Europe, executed as part of a waste paper pulping and stock preparation project. The installation includes the AFS-15 pulper, junk trap, trommel screen, pressure screens, ragger/rope cutter, and associated cleaning and screening systems, all delivered as an integrated package. Commissioning approach: As with any large-scale industrial project, a system of this complexity demands precise engineering coordination between the design, project, and site teams; proactive planning to sequence civil, mechanical, and electrical work efficiently; strong on-ground technical support during equipment installation, alignment, and start-up; and close collaboration with the customer and local partners to resolve site-specific challenges in real time. Through this integrated approach — combining Parason’s engineering strength with the customer’s operational team — the line was successfully commissioned, tested, and handed over, now running as part of the mill’s daily production operations.

PM: When will this new line commence operations?

MD: The line is already in operation. The commissioning has been successfully completed and the system is fully integrated into the mill’s daily production from June 26, 2026. The line is engineered to deliver reliable performance, high-yield fiber recovery, and consistent stock quality, supporting the mill’s day-to-day production requirements and longterm operational stability.

PM: How will the new stock preparation line strengthen the mill’s manufacturing capabilities, optimizing its fiber utilization?

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MD: The new stock preparation line significantly strengthens the mill’s manufacturing capabilities by enabling efficient processing of recycled OCC at 400–450 TPD, a substantial addition to the mill’s production platform. The impact spans multiple dimensions: •

Advanced pulping & cleaning technology: The AFS-15 pulper, junk trap, trommel screen, pressure screens, and ragger works as an integrated package.

•

Maximised fiber recovery: With this new stock line, every usable fiber is captured, and reject rates minimised.

•

Effective contaminant removal: A multi-stage cleaning removes plastics, wires, stones, metals, and fines.

•

Consistent stock quality: The stable pulp characteristics feed downstream operations reliably.

TECHNOLOGY IN SPOTLIGHT TECHNOLOGY INTRODUCED Complete stock preparation line MILL Suchonski Pulp & Paper Mill in Eastern Europe STATUS Successfully commissioned and operational RAW MATERIAL Recycled OCC (Old Corrugated Containers) — Russian OCC / ROCC COMPONENTS AFS-15 pulper, ragger/rope cutter, trommel screen, pressure screens, and cleaning & screening systems PRODUCTION CAPACITY 400–450 TPD

INTERVIEW

•

Reduced raw material losses: The line produces better yield per tonne of incoming OCC.

•

Improved operational efficiency: The stable line ensures fewer stoppages and better paper machine runnability.

•

Sustainability gain: It generates higher recovered fiber utilisation, and supports circular economy goals.

Together, this integrated approach to pulping, cleaning, and screening gives the mill a stable, highperformance recycled fiber platform

— supporting better product quality, more efficient operations, and more sustainable use of recycled fiber resources. The line positions the mill to meet current market demand and to scale confidently as recycled-fiber packaging demand continues to grow.

The line is engineered to maximize fiber recovery, deliver consistent stock cleanliness, and provide the mill with a stable, reliable OCC processing platform that adapts to variations in incoming raw material quality. NEWS

Paperboards Expansion Key to ITC’s INR 20,000 Crore Manufacturing Plan ITC will strengthen its paperboards business through capacity expansion, sustainability initiatives and import substitution under its INR 20,000 crore manufacturing plan. Jul 27, 2026 TC Ltd. has announced an INR 20,000 crore capital expenditure plan over the medium term to expand its manufacturing footprint, with paperboards, paper and sustainable packaging emerging as key focus areas. The investment aims to strengthen domestic manufacturing capabilities, enhance export competitiveness and accelerate import substitution.

Speaking about the company’s paper business, ITC Chairman and Managing Director Sanjiv Puri said the proposed acquisition of Century Pulp and Paper will further reinforce the company’s leadership in the segment, increasing its paper and paperboards production capacity by more than 50 percent to 1.5 million metric tonnes. The company has also commissioned a state-of-the-art moulded fibre products facility to manufacture engineered compostable alternatives to single-use plastics for both domestic and export markets. Puri added that ITC’s distributed manufacturing network is increasingly powered by digital technologies, with an AI-first backbone improving operational efficiency, responsiveness and cost optimisation across facilities. Several manufacturing units now meet nearly 100 percent of their electricity requirements through renewable energy, while others have achieved platinum-rated green building standards and global

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Alliance for Water Stewardship (AWS) benchmarks. He also noted that women now constitute the majority of the workforce at several manufacturing facilities. Highlighting the company’s import substitution strategy, Puri said ITC pioneered the Bharat Fibre value chain for its paperboards business, helping green nearly 1.5 million acres while generating more than 270 million person-days of employment. He added that investments in domestic pulp, capsule manufacturing and decor paper production are expected to generate foreign exchange savings of over INR 17,500 crore over the next decade.

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NEWS

JK Paper’s BCTMP Plant Surpasses Design Capacity Within Four Months of Commissioning JK Paper’s BCTMP plant surpassed its designed production capacity to 418 ADMT/ day within just four months of commissioning, marking a significant milestone in operational efficiency and project execution.

Aug 04, 2026 K Paper’s BCTMP ( Bleached Chemi-Thermo Mechanical Pulp) plant has successfully completed its startup and commissioning, achieving a production rate of 418 ADMT/ day within just four months, surpassing its designed capac-

ity of 400 ADMT/day. The milestone reflects the successful execution of the commissioning process and the operational readiness of the facility. The achievement was attributed to the collective efforts, technical expertise, and dedication of the project team.

Kuantum Papers Plans 50% Capacity Increase Through Debottlenecking and Mill Upgradation Kuantum Papers Ltd. is pursuing a growth strategy focused on debottlenecking and upgrading its manufacturing operations, with plans to increase production capacity by around 50%. The company is also diversifying into specialty and tissue papers while adopting Industry 4.0 technologies. Aug 13, 2026 uantum Papers is planning to increase its production capacity by approximately 50% through debottlenecking and upgrading its plant operations. The company currently operates at an approved capacity of 540 TPD, with four paper machines.

As part of its mill upgradation, the company has commissioned a Displacement Digestor System (DDS) for wood pulping to optimise pulp quality and yield while reducing utility and pulp costs. Native starch systems have also been commissioned on Paper Machines 2 and 3. Meanwhile, Paper Machine 3 has been shut down for a major rebuild aimed at

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enhancing production and quality. Kuantum is also exploring specialty and tissue paper technologies to diversify its product portfolio and plans to leverage IoT, AI and cloud computing for operational efficiency and resource optimisation.

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NEWS

TNPL Commissions 100 TPD Tissue Paper Facility with INR 350 Crore Investment TNPL has commissioned a 100 TPD tissue paper production facility at its Unit-II in Kagithapuram, Tiruchirappalli district, marking the company’s entry into the tissue paper segment. The facility was inaugurated by Tamil Nadu Chief Minister C. Joseph Vijay during the Vettri Tamil Nadu Investment Conclave 2026 in Chennai. Aug 14, 2026 amil Nadu Newsprint and Papers Limited (TNPL) has developed a state-of-the-art facility with an investment of INR 350 crore. The investment marks a significant milestone in TNPL’s diversification into the tissue paper segment, strengthening its commitment to innovation, value-added manufacturing and sustainable growth.

Tamil Nadu Chief Minister C. Joseph Vijay inaugurated TNPL’s 100 TPD tissue paper facility at Unit-II, Mondipatti, Tiruchirappalli, during the Vettri Tamil Nadu Investment Conclave 2026 in Chennai. The new facility will manufacture tissue paper grades ranging from 13 GSM to 40 GSM, primarily using high-quality inhouse hardwood pulp. The tissue products will be marketed under LUMEA, enabling TNPL to extend its established exper-

tise in paper manufacturing into the tissue paper segment. The facility will cater to the growing demand for tissue paper and everyday hygiene and tissue applications.

Rajasekar Veerichetty Elevated to Deputy Managing Director of Al Jawdah Paper Rajasekar Veerichetty has been elevated to Deputy Managing Director of Al Jawdah Paper, bringing over three decades of experience in paper manufacturing, operations, projects, and business leadership. Sep 8, 2026 ajasekar Veerichetty has been elevated to the position of Deputy Managing Director at Al Jawdah Paper, bringing over three decades of experience across paper manufacturing operations, projects, commercial strategy, business development, and administration.

At Al Jawdah Paper, he has played a key role in driving the company’s operations and growth, supporting its advanced paper mills producing 100 percent recycled Kraft JAPLINER (Testliner) and JAPFLUTE (Fluting) for markets across Saudi Arabia and the wider MENA region. He has been involved in greenfield projects, large-scale paper mill commissioning, operational excellence, innovation, and sustainable manufacturing initiatives.

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Mr. Rajasekar Veerichetty, Deputy Managing Director, Al Jawdah Paper

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NEWS

Kay Power and Paper Plans 75,000 TPA Kraft Paper Plant Kay Power and Paper plans to establish a new kraft paper manufacturing plant with an installed production capacity of 75,000 TPA, targeted for commissioning in FY2027-28. Aug 12, 2026 ay Power and Paper Ltd. has proposed setting up a stateof-the-art kraft paper manufacturing plant through its wholly owned subsidiary, Kay Pulp and Paper Mills Private Limited. The facility will be equipped with modern machinery and advanced manufacturing technology and is planned to have a capacity of 75,000 TPA.

The project is expected to be commissioned during FY202728, with commercial production anticipated thereafter. The company estimates first-year revenue from the project at approximately INR 200 crore. The project is currently at the planning and development stage.

JMC Paper Tech Strengthens Technology Partnership with Kawanoe Zoki for Advanced Tissue Solutions JMC Paper Tech Pvt. Ltd. has strengthened its technology partnership with Japan’s Kawanoe Zoki Co., Ltd., following a recent visit by the latter’s senior leadership to India. The discussions focused on advancing tissue paper manufacturing through Kawanoe Zoki’s Best Former technology and JMC’s engineering and project execution capabilities.

Aug 29, 2026 MC Paper Tech Pvt. Ltd. recently welcomed a delegation from Kawanoe Zoki Co., Ltd., Japan, including President Mr. Takahiro Shinohara, Mr. Masamichi Sugi and Mr. Shungo Yokouchi, as part of efforts to further strengthen the companies’ technology partnership. The visit included detailed technical discussions and visits to select JMC customers.

A key focus of the discussions was Kawanoe Zoki’s Best Former technology for tissue paper manufacturing. The teams

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exchanged technical insights on its potential to enhance tissue quality and formation, improve operational efficiency, and ensure consistent production performance. The partnership combines Kawanoe Zoki’s Japanese tissue-making technology with JMC’s engineering, manufacturing and project execution expertise, aiming to deliver advanced and reliable tissue-making solutions to customers in India and international markets.

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NEWS

ITC Closes Acquisition of Century Pulp & Paper On August 01, 2026, ITC Limited completed the acquisition of Aditya Birla Real Estate’s Century Pulp and Paper Business on a going concern basis. The decision marked the expansion of ITC in the pulp and paper sector. Aug 01, 2026 TC Limited notified the completion of the acquisition of Century Pulp & Paper (CPP) from Aditya Birla Real Estate Limited (ABREL) to the National Stock Exchange of India Ltd and BSE Ltd on August 01, 2026. The decision marks one of the largest consolidation moves in India’s paper industry through strategic integration. The acquisition involved a slump sale on a going concern basis.

Under the transaction, the Century Pulp and Paper business has been transferred to ITC Limited in accordance with the terms of the Business Transfer Agreement. This involved ownership of the entire Century Pulp and Paper’s operational business, including its existing infrastructure, contractual relationships, liabilities, and staff, enabling continuity of operations following the transfer.

The acquisition significantly strengthens ITC’s Paperboards & Specialty Papers Business by adding substantial manufacturing capacity and expanding its geographical presence in the country.

Voith Launches ‘PluraMaze’ Refiner Filling To Reduce Energy Consumption in Paper Sector Voith has recently launched ‘PluraMaze’, a new generation of refiner fillings, designed to significantly improve energy efficiency during paper manufacturing. Jun 25, 2026 oith introduces PluraMaze, a new generation of refiner fillings designed to significantly improve energy efficiency and lifetime. The new solution addresses key challenges faced by paper manufacturers worldwide, including rising energy costs, increasing pressure on efficiency and changing raw material qualities.

The energy savings are the result of a newly developed filling geometry based on a labyrinth-like structure. The patent-pending application design reduces internal backflow and significantly lowers no load power.

The new PluraMaze refiner filling

PluraMaze is available in three variants for different requirements: PluraMaze 5.3 for customers with a primary focus on refining results and energy efficiency, PluraMaze 5.6 for a balanced combination of energy efficiency and lifetime, and PluraMaze 6.5 optimized for maximum lifetime. This modular approach allows paper manufacturers to select the ideal type depending on their operational priorities.

The new PluraMaze 5.6 variant optimized for European and Asian OCC pulps enables enhanced fiber treatment and delivers a longer lifetime. PluraMaze can deliver a 70 to 80 percent increase in lifetime compared to Pluralis, Voith’s previous filling generation under comparable operating conditions. This performance directly reduces annual wear-part costs and the frequency of filling changes.

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NEWS

Om Sree Papertek Commissions PM-2 for Lighter GSM Kraft Paper Production Om Sree Papertek (P) Ltd. has successfully commissioned its PM-2, a new paper machine dedicated to manufacturing lighter GSM kraft paper. The commissioning follows 13 months of planning, development and sustained efforts by the company’s team. Aug 24, 2026 m Sree Papertek (P) Ltd. has commissioned PM-2 with a specific focus on manufacturing smell free lighter GSM kraft paper. The new paper machine is designed to cater to the growing demand from the paper bag industry as well as the requirement for high-strength fluting media for corrugated boxes and wrapping paper.

The product mix will cover 60 GSM to 120 GSM, with a strength range of 18 BF to 35 BF, catering to the requirements of corrugated packaging, wrapping paper and other allied applications. The machine has been specifically selected and configured to produce high-tear-factor kraft paper, making it particularly suitable for the rapidly growing paper bag market. The focus is to make the paper smell free to ensure the product acceptability in the market. PM-2 is a combination of Chinese and European technology and equipment. The machine is equipped with a CD-controlled headbox from the reputed MCN, ensuring better profile control and consistency across the paper web. The high-speed paper machine is of Chinese manufacturer and is complemented by a high-speed rewinder and a steam condensate system. The combination of these technologies has been selected to achieve efficient production, improved paper quality and consistency across the targeted product

range. The ETP is a mix of Indian procurement and Chinese engineering suitable for making the paper smell free using the anaerobic digestion technology. With the increasing emphasis on reducing single-use plastics, the shift towards paper bags and other paper-based alternatives is expected to gain significant momentum. The demand for paper bags and allied sustainable packaging products continues to grow, and we believe this segment has the potential to develop into a sizable and sustainable market. PM-2 is strategically positioned to capitalize on this opportunity by producing high-strength, lightweight smell free kraft paper specifically suited for paper bags and other applications where strength-to-weight ratio is critical.

Aryan Paper Mill Achieves Record Single-Day Production of 480 MT Aryan Paper Mill has achieved its highest-ever single-day production of 480 MT, marking a significant milestone in operational performance. Aug 24, 2026 ryan Paper Mill Pvt. Ltd. has recorded its highest-ever single-day production of 480 MT, reflecting the collective efforts and operational commitment of its team. Sharing the achievement, Mr. Sanjay Sharma, Vice President at Aryan Paper Mill Pvt. Ltd., congratulated the team and highlighted its continued focus on maintaining high energy levels and improving performance. The company aims to build on this milestone and set new production records in the future.

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NEWS

Kuantum Papers Successfully Restarts Rebuilt Paper Machine–3 Kuantum Papers has successfully restarted PM3 at its manufacturing facility in Saila Khurd, Hoshiarpur, Punjab, following a major technological upgradation and rebuild, including modern features like top former and film press, aimed at enhancing paper quality, operational efficiency, and product diversification. Aug 26, 2026 uantum Papers Limited has successfully restarted its PM3 at the company’s Saila Khurd manufacturing facility in Hoshiarpur, Punjab, on 26 August 2026, following the completion of a major technological upgradation and rebuild project and several trials. The PM3 rebuild forms part of the company’s strategic capacity and efficiency enhancement plan, with a focus on improving paper quality, operational efficiency, product portfolio versatility and production throughput.

The rebuilt machine incorporates modern features including a top former, film press, improved automation and enhanced drying capability. These upgrades are expected to strengthen the machine’s capabilities and support Kuantum Papers’ future diversification into higher-value writing and printing paper and specialty grades.

Voith Develops MegaDrive Rubber Wire Drive Roll Cover to Reduce Wear and Maintenance Voith has developed MegaDrive, a rubber wire drive roll cover designed to improve traction, reduce wear and minimise maintenance in paper and board machine forming sections. The solution aims to support stable machine runnability under varying operating conditions and extended runtimes. Jul 18, 2026 ire drive rolls transfer drive power to the forming fabric at the wet end of paper machines, operating at high and variable speeds under wet and abrasive conditions. Consistent contact between the roll cover and forming fabric is essential to prevent slippage, maintain sheet formation and ensure machine runability.

According to Voith, conventional wire drive roll covers can lose their performance over time due to hardening, surface cracking and continuous exposure to high mechanical loads. MegaDrive has therefore been developed using a hardwearing yet flexible rubber compound, with the surface profile customisable according to individual operating conditions. MegaDrive uses a hardwearing yet flexible rubber compound, with a customisable surface profile to suit individual operating conditions. It is designed to maintain reliable grip under varying speeds, temperatures, moisture levels and mechanical loads. The solution also addresses process variability in the forming section, where changing operating conditions can affect traction and machine stability. By maintaining consistent

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Voith’s Next-Generation Rubber Wire Drive Roll Cover grip under these conditions, MegaDrive can help reduce one potential source of operational variation and support more stable runnability. MegaDrive combines reliable traction, high wear resistance and extended operating performance. The company can also integrate the cover with a suitable Voith forming fabric based on machine configuration, operating speed, furnish properties and production requirements.

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NEWS

Pakka Progresses Project Jagriti; PM 4 Commissioning and FlexC Development on Track Pakka is progressing with Project Jagriti, with major equipment work substantially completed and key commissioning milestones ahead. The company is targeting September 2026 for power and recovery boiler start-up and November 2026 for PM4 commissioning, alongside FlexC development. Aug 18, 2026 akka Limited is progressing with Project Jagriti, with around 85 per cent of major equipment work completed. The new power and recovery boilers are targeted for start-up in September 2026, while PM4 start-up is planned for November 2026.

Alongside the expansion, Pakka is developing its flexC base material, with pilot trials nearing completion for applications including confectionery wraps, snack pouches, sachets, medical packaging, seed packs, release liners, dry-food liners and tea pouches. The company has also committed to es-

tablishing a Material Science Centre as part of its innovation programme.

Emami Paper Mills Invested INR 30.29 Crores in FY 2025-26, Upgraded PM-2 Emami Paper Mills Limited made a capital investment of INR 30.29 crores during FY 2025-26, with a substantial focus on strengthening its manufacturing infrastructure and upgrading PM2. The PM2 modernisation has improved paper quality, machine speed and operational efficiency, while enabling the company to shift pharma-grade paper production from PM3 to PM2. Aug 10, 2026 uring FY 2025-26, Emami Paper Mills continued its focus on modernisation and strategic capital expenditure to strengthen manufacturing capability and long-term competitiveness. In the year, the company’s capital investment stood at INR 30.29 crores, following INR 20.50 crores invested in FY 2024-25 across paper machines, control systems and downstream processing infrastructure.

Among the significant initiatives undertaken during the year was the upgradation of PM-2 through installation of a new headbox & calendaring system with advanced equipment. The upgradation of PM2 involved the installation of a stateof-the-art auto slice control headbox with MLF for better paper formation, along with a new calendaring section featuring a thermo-roll for uniform caliper and improved smoothness. A CD profiler was also added to maintain uniform basis weight, moisture and caliper across the deckle. In addition, the fan pump capacity in the approach-flow system

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was increased from 2,200 LPM to 2,600 LPM, while a new tail-feeding system was installed from the calendar to the pope reel for faster paper passing. The upgradation also contributed to an increase in PM2’s operating speed from 510 metres per minute (mpm) to 550 mpm, alongside improvements in product quality. The

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NEWS upgrade provided tangible benefits, including improved sheet formation, better surface finish, enhanced printability, smoother runnability and stronger machine productivity, establishing the quality benchmark. The modernisation also enabled the successful transition of pharma-grade paper production from PM3 to PM2, with the company reporting improved product quality and stronger

market demand following the transition. It signifies expansion of presence in speciality papers. The PM2 upgradation and other strategic initiatives are expected to strengthen product quality, machine efficiency, operational reliability and long-term cost competitiveness, while supporting the company’s broader manufacturing and sustainability objectives.

Satia Industries Advances Capacity Expansion and PM3 Upgrade Satia Industries is strengthening its paper manufacturing capacity through continued expansion and modernisation, with installed capacity now exceeding 200,000 MTPA. As part of its latest investment programme, the company has undertaken a major upgrade of PM3, which is expected to enhance capacity, product quality and operating efficiency. Aug 14, 2026 atia Industries Limited continues to expand and modernise its manufacturing capabilities, with total installed paper production capacity now exceeding 200,000 MTPA, and added five more cutlery machines taking the total to 14.

The company has undertaken a major modernisation and upgradation programme for Paper Machine 3 (PM3). The machine was shut down from June 1, 2026, with refurbishment work expected to continue for 4–5 months. The programme is expected to increase production capacity, improve product quality and strengthen operating efficiency. The planned shutdown impacted production volumes during Q1 FY27, contributing to a 2% YoY decline in revenue to INR

3,618 million. However, upon completion, the PM3 modernisation is expected to support Satia’s future capacity growth and strengthen its overall manufacturing platform.

JK Paper Completes Acquisition of Radhesham Wellpack JK Paper has acquired the remaining 20% stake, comprising 25,000 equity shares, in Radhesham Wellpack, making the packaging company its wholly owned subsidiary. Sep 10, 2026 K Paper Limited acquired the remaining 20% shareholding in Radhesham Wellpack Private Limited (RWPL) on September 9, 2026, for a total consideration of approximately INR 44.02 crore. The acquisition comprises 25,000 equity shares of INR 100 each. Following the transaction, RWPL has become a wholly owned subsidiary of JK Paper.

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NEWS

Raghav Paper Mills Produced Its First 32 GSM Poster Paper Reel Raghav Paper Mills has successfully produced its first paper reel, a 32 GSM poster paper, marking an important milestone in the company’s manufacturing operations and its efforts towards consistent quality and import substitution. Aug 20, 2024 aghav Paper Mills Pvt. Ltd. has achieved its first paper production milestone with the successful manufacturing of a 32 GSM poster paper reel. The company described the development as a significant step towards operational excellence, consistent paper quality and import substitution.

The achievement follows the successful efforts of the company’s technical team and project partners involved in establishing the manufacturing operations.

Urvashi Pulp and Paper Mills Achieves Successful Machine Restart with CN Automation Urvashi Pulp and Paper Mills has successfully restarted its paper machine following major technological upgradation. The step marked an important milestone in its efforts to enhance operational performance and automation capabilities. Aug 08, 2026 rvashi Pulp and Paper Mills Pvt. Ltd. collaborated with CN Automation, which served as the automation solution provider for the implementation of major technological upgrades to the mill’s paper machine. The up-gradation involved the integration of advanced automation solutions aimed at strengthening machine performance, process control and operational efficiency.

Following the completion of the upgradation work, the machine was successfully restarted, marking an important milestone for the mill. The project reflects the collaborative efforts of Urvashi Pulp and Paper Mills and CN Automation in

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implementing the upgraded automation systems and bringing the machine back into operation.

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NEWS

Parason Strengthens Its Finnish Presence Through Induro Oy Partnership Parason has partnered with Induro Process Solutions (Induro Oy) as its Sales Associate in Finland, strengthening its presence in the Finnish paper industry. The collaboration will combine Parason’s engineering expertise with Induro’s local market knowledge and customer support capabilities. Aug 21, 2026 arason Machinery (India) Pvt. Ltd. has partnered with Induro Process Solutions (Induro Oy) as its Sales Associate in Finland, marking a step towards strengthening Parason’s presence and customer reach in the Finnish paper industry. Through the partnership, Parason will combine its engineering expertise and paper-industry technologies with Induro’s local market knowledge and customer support capabilities.

The collaboration will enable customers across Finland to access Parason’s solutions, including stock preparation systems, refiner and wear parts, molded fibre solutions, and spare parts and upgrades. The companies will work together to provide reliable technology solutions and local support to paper industry customers in Finland. Through the partnership, Parason aims to build stronger, long-term relationships with customers in the Finnish market while expanding the availability of its technology and support services.

Kuantum Papers Doubles On-Site PCC Capacity to 50,000 TPA Kuantum Papers has expanded its on-site Precipitated Calcium Carbonate (PCC) capacity from 25,000 TPA to 50,000 TPA. Aug 24, 2026 uantum Papers Limited has doubled the capacity of its on-site Precipitated Calcium Carbonate (PCC) plant from 25,000 tonnes per annum to 50,000 tonnes per annum as part of its ongoing manufacturing and capacity expansion initiatives.

The PCC plant was established in collaboration with Specialty Minerals Inc., USA, and supplies high-quality PCC, which is used as a filler in paper manufacturing. The company describes the facility as a first-of-its-kind on-site PCC plant. The capacity enhancement forms part of Kuantum Papers’ broader modernization programme. In 2026, the company also received approval to increase paper production capacity

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from 450 TPD to 540 TPD, alongside upgrades to its paper machines and other manufacturing systems.

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NEWS

Pakka Approves Restart of US Subsidiary with USD 1 Million Investment Pakka Limited has approved the restart of operations at its wholly owned US subsidiary, Pakka Inc., with an aggregate financial outlay of up to USD 1 million. The move aims to clear outstanding liabilities, provide working capital and support the subsidiary’s project. Aug 14, 2026 akka Limited has approved the restart of operations at Pakka Inc., USA, with an aggregate financial outlay of up to USD 1 million. The approved amount will cover investment and working capital requirements, statutory severance obligations, and other necessary costs related to Pakka Inc. and Pakka Guatemala.

Pakka Inc., a wholly owned subsidiary incorporated in the USA, operates in the sustainable and compostable food-packaging sector for the North American market. The investment is also intended to clear outstanding liabilities and support the project undertaken at the subsidiary.

The investment is expected to be completed in one or more tranches by December 31, 2026, subject to applicable approvals and compliances.

Dev Priya Industries’ Paper Passes Odorless Test and Meets FoodGrade Standards This test ensures that the end products retain their natural scent and taste profile without contamination and the paper is of premium quality. Jul 23, 2026 ev Priya Industries Pvt. Ltd. has announced that our paper has officially passed the odorless test and food grade, confirming that it meets the highest standards for food-grade safety.

scent and taste profile without contamination.The paper is of premium quality, backed by rigorous testing so you can build and package with total confidence.

This test ensures that the end products retain their natural

‘‘A huge thanks to our R&D and quality assurance team for their relentless dedication to excellence.,’’ says Mr. Amit Gupta, Technical Director, Dev Priya Industries Pvt. Ltd.

Orient Paper & Industries Limited Appoints Yogendra K. Varshney as COO Orient Paper & Industries Limited has appointed Mr. Yogendra K. Varshney as the Chief Operating Officer, with effect from June 30, 2026. Jun 30, 2026 rient Paper & Industries Limited has appointed Mr. Yogendra K. Varshney as the Chief Operating Officer with effect from June 30, 2026. He succeeded Mr. C.S. Kashikar after his resignation from the position.

Newsprint and Papers Ltd. He has also undertaken successful leadership roles at Genus Paper & Boards, Kauntum Papers, and Century Pulp & Paper.

Mr. Yogendra Varshney brings over 30 years of experience in manufacturing operations, production operations, and project management. Prior to this, he held the position of Executive Director (Operations) & Chief Risk Officer at Tamil Nadu

He is a Mechanical Engineering Graduate from the Institute of Engineering & Technology, Lucknow University.

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Vol.: 01 / No.: 02

Event Calendar ABTCP 2026 6-8 Oct, 2026 São Paulo, Brazil www.abtcp2026.org.br India Paper Expo 2026 14-16 Oct, 2026 Mumbai, India www.indiapaperexpo.com ProPaper Dubai 2026 20-22 Oct, 2026 Dubai, United Arab Emirates www.propaperdubai.com Paper & Tissue Show London 2026 11-12 Nov, 2026 London, UK www.london.paperoneshow.net Paper Arabia 2026 16-18 Nov, 2026 Dubai, UAE www.paperarabia.com PulpFor Expo 2026 24-26 Nov, 2026 Saint-Petersburg, Russia www.en.pulpfor.ru Paperex South India 3-5 Dec, 2026 Chennai, India www.india.paperex-expo.com Paper & Tissue Show 16-18 Mar, 2027 Abu Dhabi, UAE www.paperoneshow.net

Aug-Sep, 2026 Editor & Publisher

Parveen Kumar Jain – pkj@tulip3pmedia.in Deputy Editor Geetika Jain – gjain@papermart.in Consulting Editor Dhananjay Kumar – desk@tulip3pmedia.in Assistant Editor Kannupriya Mehta – desk5@tulip3pmedia.in Sr. Graphic Designer Girish Garg – design@tulip3pmedia.in Graphic Designer Tajinder Singh – design3@tulip3pmedia.in Support Team Kushagra Mehrotra Sandeep Kumar Deepak Kumar admin@tulip3pmedia.in Chief Executive Officer Priyank Jain pj@tulip3pmedia.in Correspondence Address: Tulip 3P Media Pvt. Ltd. 501-502, ABW Tower, MG Road, IFFCO Chowk, Gurugram, Haryana-122003, INDIA, Tel.:0124 447 0798 / 99 E-mail : info@papermart.in / info@tulip3pmedia.in International Sales: RNP Nicolas Pelletier 16, rue Bannier 45000 Orleans, France Tel.: +33 682 25 12 06, Fax: +33 238 422910 Printed by: Parveen Kumar Jain Published by: Parveen Kumar Jain On Behalf of: Parveen Kumar Jain Printed at: Royal Offset, Plot No. 6, F.I.E. Patparganj Industrial Area, New Delhi Delhi-110092 Published From: L-15/6, DLF Phase 2, Sector 25, Sikanderpur Ghosi (68), Gurugram, Haryana - 122002 Editor: Parveen Kumar Jain

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Paper Mart Emagazine Aug-Sept Issue 2026