CE_21_09

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We’ve taken our most practical, most popular PLC family and supercharged it with features you wouldn’t expect from a simple low-cost controller. Data logging, Wi-Fi connectability, MQTT communication and increased security measures are just a few of the impressive features offered with the new CLICK PLUS PLC series. With a starting at price of only $89.00 and free easy-peasy programming software, CLICK PLUS PLCs are a “must have” for simple, affordable control...with a kick!

ON THE COVER: The Engineering Leaders

Under 40 program recognizes manufacturing professionals under the age of 40 who are making significant contributions to their companies and control engineering and/or plant engineering professions. See how the Class of 2021 is advancing the future of smart manufacturing on page 19 with much more at www.controleng.com/EngineeringLeaders.

INSIGHTS

ANSWERS

19 |

SEPTEMBER 2021

ANSWERS

32 | Five more days of PDH online credits

33 | Understanding the matrix for APC

36 | Factory of the future: Digital transformation

38 | Motion control standard: Design, effectiveness

41 | Exploring industrial wireless best practices

INSIDE PROCESS

P1 | Benefits of auto-tuning VFDs

ONLINE | For links to all posts at www.controleng.com during August 2021, pages 6, 7.

• Can you improve ROI using Industry 4.0? - FactoryEye

• Great smart manufacturing; great funding - Grantek

• Unlocking smart manufacturing ROI - LTTS

• How to find the ROI in smart manufacturing - Maverick

• Scaling machine learning for manufacturing - Seeq

• Off-site experts, 3D digital twin - ARC Advisory Group

• Engineering document management: Tags - Idox

• Are linear servo motors the right choice? - Yaskawa

• Motion control, positioning - Physik Instrumente

• Energy management via networks - PI North America

• Power over Ethernet benefits - University of New Hampshire InterOperability Laboratory

• Flow measurement technology - Leomi Instruments

• Video interview: More automation software, more productivity - Aveva

• Investing in automation - White Oak Global Advisors

• Effective process control system migration, Part 1: Planning advice - Maverick Technologies

• Effective process control system migration, Part 2: Open standards - Collaborative Systems Integration

• Effective process control system migration, Part 3: Poll results, answers

CONTROL ENGINEERING (ISSN 0010-8049, Vol. 68, No. 8, GST #123397457) is published Monthly except in November by CFE Media, LLC, 3010 Highland Parkway, Suite #325 Downers Grove, IL 60515. Periodicals postage paid at Downers Grove, IL 60515 and additional mailing offices. POSTMASTER: Send address changes to CONTROL ENGINEERING, PO Box 348, Lincolnshire, IL 60069. Jim Langhenry, Group Publisher/Co-Founder; Steve Rourke CEO/COO/Co-Founder. CONTROL ENGINEERING copyright 2021 by CFE Media, LLC. All rights reserved. CONTROL ENGINEERING is a registered trademark of CFE Media, LLC used under license. Circulation records are maintained at 3010 Highland Parkway, Suite #325 Downers Grove, IL 60515. Telephone: 630/571-4070. E-mail: ctle@omeda.com. Publications Mail Agreement No. 40685520. Return undeliverable Canadian addresses to: PO Box 348, Lincolnshire, IL 60069. Email: ctle@omeda.com. Rates for nonqualified subscriptions, including all issues: USA, $165/yr; Canada/Mexico, $200/yr (includes 7% GST, GST#123397457); International air delivery $350/ yr. Except for special issues where price changes are indicated, single copies are available for $30 US and $35 foreign. Please address all subscription mail to CONTROL ENGINEERING, PO Box 348, Lincolnshire, IL 60069. Printed

USA. CFE Media, LLC

and hereby disclaims any liability to any person for any loss or damage caused by errors or omissions in the material contained herein, regardless of whether such errors result

INNOVATIONS

NEW PRODUCTS FOR ENGINEERS

49 | Electronic circuit breaker system, Sinusoidal pump for pharmaceutical manufacturing, Customized switchgear simulators, Integrated motor drive, Radar level transmitter, Decentralized I/O system, Digital signal processing managed switch, Robot control system More New Products for Engineers: www.controleng.com/NPE.

BACK TO BASICS

51 | Making industrial control system solutions more adaptable Industrial control system (ICS) solutions need a new architecture and philosophy is required to be more adaptable to changing environments. Six methods are highlighted.

NEWSLETTER: Industrial Networking

• Device type manager changes for IIoT applications

• Researchers use Minecraft to advance AI programs, thinking

• Profibus PA overview and description

• Exploring industrial wireless best practices: More answers

• Understanding HART status information

Keep up with emerging trends: subscribe. www.controleng.com/newsletters.

CFE EDU: Virtual Training Week On-Demand

Virtual Training Week fall edition is planned for Oct. 18-22; Learn more on page 32.

Register and receive full access to exclusive content planned and on-demand offered by industry experts with Q&A sessions!

https://cfeedu.cfemedia.com/learning-paths/ cfe-media-technology-virtual-training-week

Control Engineering eBook series: System Integration

Summer Edition

System integration is a crucial aspect of manufacturing for control engineers. They help companies become more efficient, streamlined and smarter in day-to-day operations. Featured eBook articles include questions to simplify system integration, automotive system integration and how PLCs power industrial data integration. Learn more at

www.controleng.com/ebooks

Global System Integrator Report

Advice from system integrators, System Integrator of the Year, System Integrator Giants, automation and control case studies. Next edition will included with Control Engineering and Plant Engineering November/December editions.

www.controleng.com/GSIR

Control Engineering

digital edition

The tablet and digital editions provide links to additional article images and text online and links to other related, useful resources.

www.controleng.com/magazine

controleng.com provides new, relevant automation, controls, and instrumentation content daily, access to databases for new products and system integrators, and online training.

Control Engineering hot topics, July 2021, https://www.controleng.com/articles/control-engineering-hot-topics-july-2021/ Getting connected: interface options for motion control, https://www.controleng.com/articles/getting-connected-interface-options-for-motion-control/

The best engineers are going to the competition, and here’s why, https://www.controleng.com/articles/the-best-engineers-are-going-to-the-competition-and-heres-why/

Top 5 Control Engineering articles July 26 to August 1, 2021, https://www.controleng.com/articles/top-5-control-engineering-articles-july-26-to-august-1-2021/ How to protect OT/ICS systems from ransomware attacks, https://www.controleng.com/articles/how-to-protect-ot-ics-systems-from-ransomware-attacks/ Three ways to ensure collaborative robot success, https://www.controleng.com/articles/three-ways-to-ensure-collaborative-robot-success/

Single blade rotary knife: Application overview, https://www.controleng.com/articles/single-blade-rotary-knife-application-overview/

AMRs have a big future in manufacturing production, https://www.controleng.com/articles/amrs-have-a-big-future-in-manufacturing-production/ 7 things required for a successful cobot deployment, https://www.controleng.com/articles/7-things-required-for-a-successful-cobot-deployment/

Profibus PA overview and description, https://www.controleng.com/articles/profibus-pa-overview-and-description/

Successful IoT adoption requires iteration, learning, https://www.controleng.com/articles/successful-iot-adoption-requires-iteration-learning/

Upgrading industrial PC cybersecurity in manufacturing, https://www.controleng.com/articles/upgrading-industrial-pc-cybersecurity-in-manufacturing/ Three ways to ensure and optimize cybersecurity maturity, https://www.controleng.com/articles/three-ways-to-ensure-and-optimize-cybersecurity-maturity/ Actuators explained: Types of actuators, application choice, maintenance, https://www.controleng.com/articles/actuators-explained-types-of-actuators-application-choice-maintenance/ How to achieve effective process safety, https://www.controleng.com/articles/how-to-achieve-effective-process-safety/ Exploring industrial wireless best practices: More answers, https://www.controleng.com/articles/exploring-industrial-wireless-best-practices-more-answers/ Making industrial control system solutions more adaptable, https://www.controleng.com/articles/making-industrial-control-system-solutions-more-adaptable/ System integrators and serial communication monitoring: Why it matters, https://www.controleng.com/articles/system-integrators-and-serial-communication-risks-why-it-matters/

The role of the system integrator in the digital transformation, https://www.controleng.com/articles/the-role-of-the-system-integrator-in-the-digital-transformation/ Top 5 Control Engineering articles Aug. 2-8, 2021, https://www.controleng.com/articles/top-5-control-engineering-articles-august-2-8-2021/

Seven reasons to invest in smart factory technology, https://www.controleng.com/articles/seven-reasons-to-invest-in-smart-factory-technology/ Engineers develop COVID-19 saliva test, https://www.controleng.com/articles/engineers-develop-covid-19-saliva-test/

How tomorrow’s automation technology will transform workforce, https://www.controleng.com/articles/how-tomorrows-automation-technology-will-transform-workforce/

What IEC 61499 means for the PLC, https://www.controleng.com/articles/what-iec-61499-means-for-the-plc/

Digital transformation’s role in manufacturing workforce evolution, https://www.controleng.com/articles/digital-transformations-role-in-manufacturing-workforce-evolution/ 4 variables to consider before applying new automation technologies, https://www.controleng.com/articles/4-variables-to-consider-before-applying-new-automation-technologies/ System trains drones to fly around obstacles at high speeds, https://www.controleng.com/articles/system-trains-drones-to-fly-around-obstacles-at-high-speeds/

Training the next generation of cybercops,

https://www.controleng.com/articles/training-the-next-generation-of-cybercops/ Faster path planning for rubble-roving robots, https://www.controleng.com/articles/faster-path-planning-for-rubble-roving-robots/ Research building offers hypersonic testing, materials development,

https://www.controleng.com/articles/research-building-offers-hypersonic-testing-materials-development/ Rethinking the way industrial products are purchased, https://www.controleng.com/articles/rethinking-the-way-industrial-products-are-purchased/ Ignoring cyber risk is dangerous to society and your bottom line, https://www.controleng.com/articles/ignoring-cyber-risk-is-dangerous-to-society-and-your-bottom-line/ What OT teams can learn from IT strategies and structure, https://www.controleng.com/articles/what-ot-teams-can-learn-from-it-strategies-and-structure/ Making the case for full automation, https://www.controleng.com/articles/making-the-case-for-full-automation/ Choosing the right robot for warehousing, manufacturing operations, https://www.controleng.com/articles/choosing-the-right-robot-for-warehousing-manufacturing-operations/ How the American Jobs Plan could improve critical infrastructure cybersecurity, https://www.controleng.com/articles/how-the-american-jobs-plan-could-improve-critical-infrastructure-cybersecurity/ Top 5 Control Engineering articles August 9-15, 2021, https://www.controleng.com/articles/top-5-control-engineering-articles-august-9-15-2021/

An MIT-developed inflatable robotic hand gives amputees real-time tactile control. The smart hand is soft and elastic, weighs about half a pound, and costs a fraction of comparable prosthetics. Courtesy: Massachusetts Institute of Technology www.controleng.com/articles/inflatable-robotic-hand-provides-real-timetactile-control-for-amputees/

Learn more daily at...

Heat transfer experiment arrives at International Space Station, https://www.controleng.com/articles/heat-transfer-experiment-arrives-at-international-space-station/

On pages 6 and 7 are articles posted in August 2021, in case you missed something. Links are live in the digital edtion at www.controleng.com/magazine.

Researchers use Minecraft to advance AI programs, thinking, https://www.controleng.com/articles/researchers-use-minecraft-to-advance-ai-programs-thinking/ Cybersecurity maturity model certification (CMMC) for the U.S. DoD supply chain, https://www.controleng.com/articles/cybersecurity-maturity-model-certification-cmmc-for-the-u-s-dod-supply-chain/ IoT group rebrands, shifting focusing toward marketplace maturity, https://www.controleng.com/articles/iot-group-rebrands-shifting-focusing-toward-marketplace-maturity/

Five trends of Industry 4.0 outline the future of flexible factories, https://www.controleng.com/articles/five-trends-of-industry-4-0-outline-the-future-of-flexible-factories/

On the edge: Smartening up sensors, https://www.controleng.com/articles/on-the-edge-smartening-up-sensors/ AI process optimization platform receives funding, https://www.controleng.com/articles/ai-process-optimization-platform-receives-funding/

The IPC requirements of complex control, https://www.controleng.com/articles/the-ipc-requirements-of-complex-control/

Testing the physical infrastructure with industrial Ethernet, https://www.controleng.com/articles/testing-the-physical-infrastructure-with-industrial-ethernet/

Applying automation: The right infrastructure for the best results, https://www.controleng.com/articles/applying-automation-the-right-infrastructure-for-thebest-results/

The IT/OT convergence conundrum, https://www.controleng.com/articles/the-it-ot-convergence-conundrum/

Printed hybrid electronics: 4 new things you need to know, https://www.controleng.com/articles/printed-hybrid-electronics-4-new-things-you-need-toknow/

An overlooked ICS cybersecurity gap for companies, https://www.controleng.com/articles/an-overlooked-ics-cybersecurity-gap-for-companies/

Managing the costs of OT cyber insurance, https://www.controleng.com/articles/managing-the-costs-of-ot-cyber-insurance/

Top 5 Control Engineering articles August 16-22, 2021, https://www.controleng.com/articles/top-5-control-engineering-articles-august-16-22-2021/

Can you improve ROI using Industry 4.0?, https://www.controleng.com/articles/can-you-improve-roi-using-industry-4-0/

While manufacturing investments in digital technology is growing, the potential cybersecurity threat is also growing, and the pace is faster than what manufacturers are doing. Courtesy: Fortinet/Dragos

www.controleng.com/articles/importance-of-operational-resilience-in-a-threat-landscape

Inflatable robotic hand provides real-time tactile control for amputees, https://www.controleng.com/articles/inflatable-robotic-hand-provides-real-time-tactile-control-for-amputees/

Artificial intelligence researchers receive Federal funding, https://www.controleng.com/articles/artificial-intelligence-researchers-receive-federal-funding/

What to know if conducting business with the U.S. DoD, https://www.controleng.com/articles/what-to-know-if-conducting-business-with-the-u-s-dod/ Semiconductor sales remain strong in July, https://www.controleng.com/articles/semiconductor-sales-remain-strong-in-july/

Secure device onboarding for manufacturing supply chain, https://www.controleng.com/articles/secure-device-onboarding-for-manufacturing-supply-chain/ Built-in vibration control can help soundproof rooms, vehicles, https://www.controleng.com/articles/built-in-vibration-control-can-help-soundproof-rooms-vehicles/ Metamaterial reconfigured to modify its thermal, electromagnetic properties, https://www.controleng.com/articles/metamaterial-reconfigured-to-modify-its-thermal-electromagnetic-properties/ Importance of operational resilience in a threat landscape, https://www.controleng.com/articles/importance-of-operational-resilience-in-a-threat-landscape/ Improve legacy critical infrastructure protection, https://www.controleng.com/articles/improve-legacy-critical-infrastructure-protection/ Power over Ethernet benefits, applications and certifications, https://www.controleng.com/articles/power-over-ethernet-benefits-applications-and-certifications/ Flow measurement technology advances, https://www.controleng.com/articles/flow-measurement-technology-advances/ How serial-to-Ethernet converters help attackers breach cyber-physical assets, https://www.controleng.com/articles/how-serial-to-ethernet-converters-help-attackers-breach-cyber-physical-assets/

Investing in automation: Strategies manufacturing companies need to know, https://www.controleng.com/articles/investing-in-automation-strategies-manufacturing-companies-need-to-know/

Takeaways from 2020 ICS vulnerabilities report, https://www.controleng.com/articles/takeaways-from-2020-ics-vulnerabilities-report/ Engineering document management: Paying Formula 1 money for Uber-ride tasks, https://www.controleng.com/articles/engineering-document-management-paying-formula-1-money-for-uber-ride-tasks/

Top 5 Control Engineering articles August 23-29, 2021, https://www.controleng.com/articles/top-5-control-engineering-articles-august-23-29-2021/

Study finds manufacturers willing to implement data-driven and AI initiatives, https://www.controleng.com/articles/study-finds-manufacturers-willing-to-implement-data-driven-and-ai-initiatives/

How do you break the trap of IIoT development?, https://www.controleng.com/articles/how-do-you-break-the-trap-of-iiot-development/

Break the IIoT development trap

Streamlined tools and industry knowledge can help with faster, more effective Industrial Internet of Things (IIoT) implementations.

Development of the industrial internet

is in full swing. At the industrial level, according to statistics, more than 1,900 platforms support Industrial Internet of Things (IIoT) worldwide. Of course, “The value of the industrial internet’s existence is not limited to a platform. Its most important value is to empower all real industries and bring efficiency improvements to all businesses of enterprises,” according to Cai Qinan, general manager of Advantech (China) Industrial Internet of Things Business Group.

Three categories of IIoT platforms

Industrial Internet platforms can be grouped into three main categories. One is the proprietary platform used within large enterprises. This type of platform application can only serve single enterprises.

Another category is the industry platform, such as construction machinery and home appliance manufacturing enterprises, which develop platforms. These are used by and provided to enterprises in the same industry.

MMore INSIGHTS

KEYWORDS: Industrial Internet of Things (IIoT), industrial internet

The third category is the general platform, which is suitable for various industries. These platforms are not built based on a certain enterprise or industry. They only provide application development for various industries, have strong openness and versatility and support multiple applications in multiple industries.

Learn how industrial Internet platforms can be grouped into three main categories. See advantages of IIoT that focuses on field interconnections.

Examine how IIoT can break the trap of industrial internet with industry expertise

CONSIDER THIS

Have you identified roadblocks in the way of more effective IIoT Industrial Internet of Things implementations? Have your competitors?

ONLINE

www.controleng.com/ international

www.cechina.cn

www.controleng.com/ iiot-industrie-4-0

IIoT field interconnections

An industrial Internet platform should interconnect field equipment, collect field data and then transmit data in various ways to reach the cloud for analysis and processing. At present, many IIoT solution providers are keen on building platforms, especially with cloud and communication devices as the core, without paying attention to connecting:

1. All production aspects of customer enterprises

2. The special situations and requirements of the customer’s industry.

This IIoT development trap focuses on platform building rather than value creation. The IIoT development trap mainly results from wide use of information technology (IT) and cloud platforms in recent years, little differentiation among platforms in the cloud

technology, and from serious fragmentation of interconnections of field layer equipment and data collection information. IT companies generally are not good at integrating decades of fragmented field equipment. Industrial internet can focus on those challenges and create value.

The industrial Internet platform from operational technology (OT) manufacturers usually have inherent IIoT advantages. For example, Advantech has been engaged in automation for more than 30 years, developing more than 10,000 models of data acquisition (DAQ) and data transmission products. These industrial communication products include various data acquisition modules, remote input/output (I/O) devices, wireless intelligent sensors, edge programmable controllers, edge intelligent gateways, intelligent terminal remote terminal units (RTUs), industrial switches and others.

Automation products require field-level equipment interconnection of various industries, such as intelligent manufacturing, intelligent equipment, smart city and infrastructure. Neither software nor hardware need to be provided by third-party cooperative manufacturers. Because of experience with field equipment, networking and data collection, the industrial internet solution creates value for end users.

“Unlike other IIoT platforms, Advantech’s development on the industrial internet is bottom-up. On the basis of strong data collection and transmission, we developed the industrial platform as a service (PaaS) so field equipment data can be more complete and reliably transmitted to the cloud platform. This is one of the characteristics and advantages of our industrial internet platform,” said Cai Qinan.

An industrial internet solution needs to be deeply cultivated in the industries it serves. There is no general scheme that can be implemented across industries without change. Cai Qinan believes the manufacturing industry’s needs are ever-changing and diverse. Each industry has specific industry knowledge. To implement IIoT in various industries, the needs, working methods and industry rules of each enterprise must be understood to carefully form industry-based IIoT customer solutions. System integrators and customers need to participate the design and implementation. ce

Stone Shi is executive editor-in-chief, Control Engineering China; Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com.

INSIGHTS MARKET

Semiconductor sales remain strong in July

North America-based semiconductor equipment manufacturers posted $3.86 billion in billings worldwide in July 2021 (three-month average basis), according to the July Equipment Market Data Subscription (EMDS) Billings Report published today by SEMI. The billings figure is 4.5% higher than final June 2021 billings of $3.69 billion and 49.8% higher than July 2020 billings of $2.57 billion.

The SEMI Billings report uses three-month moving averages of worldwide billings for North American-based semiconductor equipment manufacturers. Billings figures are in millions of U.S. dollars.“The

start of the second half of 2021 further extends a robust sales uptrend for North America-based semiconductor equipment manufacturers,” said Ajit Manocha, SEMI president and CEO in a press release. “Capacity demand across the semiconductor manufacturing supply chain continues its strong growth, reflecting the role of semiconductor equipment as a key engine of digital transformation globally.” ce

- Edited from a SEMI press release by CFE Media and Technology. SEMI is a CFE Media content partner.

How the American Jobs Plan could improve critical infrastructure cybersecurity

Some of the key provisions of the American Jobs Plan that support critical infrastructure cybersecurity include:

• Make $20 billion in energy infrastructure investments for state, local and tribal governments contingent on cyber modernization

• Create a new tax credit for transmission infrastructure that will help finance cyber technologies for the electric grid

• Improve security monitoring and incident response activities [by providing an additional $650M in funding to the Cyber Security and Information Agency (CISA) for the stated purposes]

If carried out as described, the actions proposed in the American Jobs Plan will help bolster the cybersecurity posture of American critical infrastructure. However, they do not go far enough to address the vast scale and scope of the problem we are facing. While the disruption of the Colonial Pipeline was certainly significant, as reported the attack was simply commoditized ransomware –nation states and cybercriminals currently have the capability to destroy and disable critical infrastructure for far longer than we saw with Colonial by targeting OT systems rather than IT systems.

As information technology (IT) and operational technology (OT) systems have converged, cyber adversaries have become increasingly aggressive in pursuing cyber-physical effects, such as critical infrastructure downtime, asset dam-

age, and process manipulation. This has put business continuity and human safety at risk, and further ensured that adopting zero-trust visibility at every level of the industrial control system (ICS) is critical to an organization’s security posture.

While the described block grant and tax credit programs are certainly needed, smaller critical infrastructure organizations often lack sufficient expertise in OT security best practices to properly monitor and defend their critical assets. These programs also must be followed up with technical assistance beyond existing government frameworks (such as NIST’s Guide to Industrial Control System Cybersecurity) that recommends specific technology stacks so that recipients can most effectively leverage these programs.

The scope of potential recipients of block grant programs should be expanded to ensure that small privately-owned utilities and rural electric co-ops are included. These organizations are critical to our nation’s energy infrastructure, yet only municipal public utilities appear to be included as eligible for the DOE-administered block grants. By helping state, local, and tribal governments as well as privately-owned critical infrastructure organizations secure adequate resources, develop domain expertise, and procure effective technologies, the Biden Administration hopes to encourage robust adoption that helps to enhance the cybersecurity posture and resiliency of the nation’s critical infrastructure. ce

Robert Fairfax is a financial officer with Cynalytica, a CFE Media content partner.

‘Up 4.5% from June; nearly 50% up from July 2020: North American-based semiconductor global billings.’

‘Cyber adversaries have become increasingly aggressive in pursuing cyber-physical effects, such as critical infrastructure downtime, asset damage, and process manipulation.’

: Take flight with flying motion technology!

Flying 2D product transport with up to 6 degrees of freedom

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For use across all industries: assembly, packaging, food/bev, pharma, laboratory, entertainment, …

input #6 at www.controleng.com/information

Research building offers hypersonic testing, materials development

Imagine an aircraft flying 2,800 miles across the United States in only 15 minutes. A state-of the-art building ready for construction at Purdue University will provide the facilities to explore that idea through advanced hypersonic research.

The planned 65,000-square-foot Hypersonic Applied Research Facility (HARF) will house two cutting-edge wind tunnels, enhancing Purdue’s capabilities in hypersonics evaluation and testing. The $41 million facility will house the only Mach 8 quiet wind tunnel in the world as well as a hypersonic pulse (HYPULSE) shock tunnel. The tunnels recreate different scenarios such as spacecraft re-entry or missile flight through the atmosphere as well as replicating engine conditions for extremely high-speed propulsion.

The Mach 8 quiet wind tunnel and the HYPULSE tunnel offer controlled environments to research facets of high-speed

flight. The new Mach 8 quiet wind tunnel more closely simulates flight and provides more accurate data than conventional hypersonic wind tunnels. The HYPULSE tunnel uses a shock wave of high-temperature air to recreate specific hypersonic flight conditions. It will allow flight simulations at speeds ranging from Mach 5 to as high as Mach 40. Purdue will be second U.S. university to offer HYPULSE test capabilities. The university has one of two working U.S. Mach 6 quiet tunnels.

Flow physics, heat transfer

National pursuit of hypersonics systems by government and industry has intensified during the last few years. Hypersonic vehicles can travel more than five times the speed of sound and fly in the upper reaches of the atmosphere. Hypersonics-related research is included in the FY22 President’s budget request at $3.8 billion, up by 20%

IoT group rebrands, shifting focusing toward marketplace maturity

The Industrial Internet Consortium (IIC) announced a new direction and a new name, Industry IoT Consortium (IIC), to help expand its mission to transforming business and society by accelerating the Industrial Internet of Things (IIoT). The consortium’s new mission is to bring transformative business value to organizations, industry, and society by accelerating the adoption of trustworthy IoT systems. The group’s focus will drive technology innovation that fosters business transformation for a return on IoT investments.

“We recognized the need to focus on technology deployments to solve technical problems,” said Dr. Richard Soley, executive director, Industry IoT Consortium, in a press release. “We’re applying technology to address customer pain points and improve business results. Industry organizations and technology providers turn to IIC and its members for IoT support and guidance. Now we’ll guide them on the application of IoT technology and digital transformation enablers to achieve positive business outcomes.”

New programs combine several approaches to digital transformation, identify customer pain points, improve go-to-market abilities, and enhance business outcomes. Existing programs will change to reflect this focus, and new initiatives will emerge to help members reach more customers. IIC will continue work on best-practice frameworks, innovative testbeds, and providing standards requirements to standards development organizations. It targets IT, networks, manufacturing, energy, utilities, healthcare markets, academia and research.

- Edited from an IIC press release. The IIC is a CFE Media content partner.

from a $3.2 billion request in FY21.

This potential increase in funding would build on previous investments by federal agencies and industry to help better integrate hypersonic systems with the U.S national security strategy. The new HYPULSE tunnel is a donation from Northrop Grumman Corp. In 2019, Purdue received a contract from the Air Force Research Laboratory to support the development of the first quiet Mach 8 tunnel in the world, the first facility of its kind capable of collecting data at speeds greater than Mach 6. Collecting data at higher Mach numbers is critical to extending the understanding of flow physics, especially heat transfer and flight control effectiveness, as Department of Defense programs continue working to fly faster and farther.

Purdue’s recent investments in hypersonics help to position the university as a partner for national defense projects from industry and government. The building will feature advanced facilities to study high-temperature materials applications. Hypersonic flight can create air friction above 1,000 °C, requiring processes and materials for such conditions. ce

BrianHuchel, PurdueUniversity. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

Students work during the summer with Purdue’s Mach 6 quiet wind tunnel. A more advanced Mach 8 quiet wind tunnel will be part of the new hypersonics research building to be constructed at Purdue. Courtesy: John Underwood, Purdue University

Digital edition? Click on headlines for more details. See news daily at www.controleng.com

Metamaterial reconfigured to modify its thermal, electromagnetic properties

NorthCarolinaStateUniversity researchers created a vascular metamaterial that can be reconfigured to modify its thermal and electromagnetic properties.

“We drew inspiration from the network of tiny vessels found in living organisms and have incorporated such microvasculature into a structural epoxy reinforced with glass fibers – essentially vascularized fiberglass,” said Jason Patrick, corresponding author of the research paper. “And we can control multiple characteristics of the composite material by pumping different fluids through that vasculature. This reconfigurability is appealing for applications ranging from aircraft to buildings to microprocessors.” Patrick is an assistant professor of civil, construction and environmental engineering at North Carolina State University.

The metamaterial is made using 3D printing technologies. This allows engi-

neers to create networks of tiny tubes, known as microvasculature, in a wide variety of shapes and sizes. The microvasculature can be incorporated into a range of structural composites, from fiberglass to carbon fiber to other highstrength materials for body armor.

Researchers infused the vasculature with a room-temperature liquid metal alloy of gallium and indium. This allows researchers to control the electromagnetic properties of the metamaterial by manipulating the microvessel architecture. Controlling orientation, spacing and conductive liquid metal in the vasculature gives control over how the material filters certain electromagnetic waves in the radio spectrum. Reconfiguration holds potential for tunable communications and sensing systems capable of operating in different parts of the spectrum on demand.

“The ability to dynamically reconfig-

SCIENTISTS AT the U.S. Department of Energy’s Argonne National Laboratory are advancing material technologies for printed electronics. Four details for engineers are highlighted.

1. Printed hybrid electronics combine modular components with printed circuitry on thin, flexible material. They are helping to create next-generation lightweight sensors, phones, wearables, radio frequency antennae and flexible displays.

2. Engineers create these electronics using various printing technologies. This tends to waste less material, reduce costs and help manufacturers create prototypes more quickly compared to standard methods.

3. Manufacturers face material challenges for printed hybrid electronics. They need high-performance conductive, semiconductive, and dielectric ink materials that are compatible between each other and also are printable and durable.

4. Despite these challenges, the global market for printed electronics rose 22% at a compound annual growth rate (CAGR) over the past five years. This trend could continue due to the strong demand in mobile, flexible, and sensor devices spurred by the fifth generation (5G) of communication technology. Argonne has more information on the topic in a related webinar. Yuepeng Zhang is a principal materials scientist at Argonne National Laboratory. Edited by Chris Vavra, web content manager, Control

cvavra@cfemedia.com.

Engineering, CFE Media,

ure electromagnetic behavior is really valuable, particularly in applications where size, weight, and power constraints highly incentivize the use of devices, which can perform multiple communication and sensing roles within a system,” said co-author Kurt Schab, an assistant professor of electrical engineering at Santa Clara University. Researchers circulated water through the same vasculature and demonstrated that they could manipulate the material’s thermal characteristics.

“This could help us develop more efficient active-cooling systems in devices such as electric vehicles, hypersonic aircraft and microprocessors,” Patrick said. “Batteries in electric vehicles currently rely on aluminum fins with simple microchannels for cooling. We believe our metamaterial would be as effective at dissipating heat and could also maintain structural protection of the power source – but would be substantially lighter .... 3D printing allows us to create more complex, optimized vascular architectures.” ce

Matt Shipman, North Carolina State University. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com

Headlines online

Top 5 Control Engineering articles

August 9-15, 2021

Featured articles included effective process safety, optimizing manufacturing processing, serial communication monitoring, HMI and SCADA design and what IEC 61499 means for PLCs.

AI process optimization platform receives

funding

Recent $30 million growth round led by Zeev Ventures and Insight Partners, with participation from Spider Capital and UpWest. Testing the physical infrastructure with industrial Ethernet

The role of Ethernet continues to expand, supporting the high speed transfer of data and certification will play a larger role in this expansion.

Printed hybrid electronics: 4 new things you need to know

INSIGHTS

Smarter manufacturing

Smart manufacturing is impressive. Learn from these examples.

Nine online examples below and five more in this issue show how smart manufacturing technologies add intelligence, speed, economy and safety. Think again about how intelligence in software can improve hardware, processes, and people.

Smarter communications

Smart manufacturing can improve with time-sensitive networking (TSN), controller-to-controller communications and safety networks, edge computing and vertical integration, advanced physical layer (APL), and fifthgeneration cellular (5G) technologies. PI North America

Can you improve ROI?

Returnoninvestment (ROI) is a hot topic for midsized manufacturers interested in investing in operational improvements on the factory floor. FactoryEye by Magic Software Enterprises

Smart manufacturing funding

How to present a business case to get smart manufacturing projects successfully approved and implemented. Grantek

Unlocking smarter ROI

Asystemintegratorexplainssix industrial data requirements for factories of the future using an apple-pie baking example. L&T Technology Services

How to find the ROI

Whether it’s called smart manufactur-

More INSIGHTS M

www.controleng.com/iiot-industrie-4-0

MESA, a Control Engineering content partner, has more on smart manufacturing. Smart manufacturing model production lifecycle benefits.

Bridging the Smart Manufacturing gap for users.

The practical side of Smart Manufacturing.

ing, Industry 4.0, or the Industrial Internet of Things, (IIoT), installing a smart platform for the sake of implementing new technology doesn’t produce the desired result; it must be practical, usable and focus on business benefits. Maverick

Scaling machine learning

Enabling access to machine learning (ML) algorithms in easy-to-use advanced analytics applications accelerates insights in process data. A specialty chemical manufacturer used ML tools to predict over 90% of quality deviations and save more than $500,000 per year in quality downgrades. Seeq Corp.

3D digital twin, AR

For operations, a 3D digital twin of a plant can be used to navigate augmented reality to access information about real assets. ARC Advisory Group

Digital twin tags

Digital twin: An interactive, oneto-one scale digital replica of the asset and every component, system or piece of equipment within it, updated in realtime gives the asset owner a powerful monitoring tool and testbed. Idox

Power over Ethernet benefits

Power over Ethernet (PoE) technology has been around nearly 20 years, but there’s still confusion about what it can and can’t do for end users and what the certifications mean. University of New Hampshire InterOperability Lab

More, in this issue

In this issue, on this topic, see: How do you break the trap of IIoT development? Finding the ROI in smart manufacturing, digital transformation; How to calculate digital transformation ROI; Factory of the future: How to vitalize digital transformation; and Exploring industrial wireless best practices: More answers. ce

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Gary Cohen, Senior Editor GCohen@CFEMedia.com

Chris Vavra, Web Content Manager CVavra@CFEMedia.com

Contributing Content Specialists

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Ekaterina Kosareva, Control Engineering Russia ekaterina.kosareva@fsmedia.ru

Agata Abramczyk, Control Engineering Poland agata.abramczyk@trademedia.pl

Lukáš Smelík, Control Engineering Czech Republic lukas.smelik@trademedia.cz

Aileen Jin, Control Engineering China aileenjin@cechina.cn

Editorial Advisory Board

www.controleng.com/EAB

Doug Bell, president, InterConnecting Automation, www.interconnectingautomation.com

David Bishop, chairman and a founder Matrix Technologies, www.matrixti.com

Daniel E. Capano, senior project manager, Gannett Fleming Engineers and Architects, www.gannettfleming.com

Frank Lamb, founder and owner Automation Consulting LLC, www.automationllc.com

Joe Martin, president and founder Martin Control Systems, www.martincsi.com

Rick Pierro, president and co-founder Superior Controls, www.superiorcontrols.com

Mark Voigtmann, partner, automation practice lead Faegre Baker Daniels, www.FaegreBD.com

CFE Media and Technology

Contributor Guidelines Overview

Content For Engineers. That’s what CFE Media stands for, and what CFE Media is all about –engineers sharing with their peers. We welcome content submissions for all interested parties in engineering. We will use those materials online, on our website, in print and in newsletters to keep engineers informed about the products, solutions and industry trends.

www.controleng.com/contribute explains how to submit press releases, products, images, feature articles, case studies, white papers, and other media.

* Content should focus on helping engineers solve problems. Articles that are commercial or are critical of other products or organizations will be rejected. (Technology discussions and comparative tables may be accepted if non-promotional and if contributor corroborates information with sources cited.)

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Meet the engineers who are exceeding expectations and improving operations

Amanda Pelliccione, Project Manager

The Engineering Leaders

Under 40 program recognizes manufacturing professionals under the age of 40 who are making significant contributions to their company’s success and to the control engineering and/or plant engineering professions. The Class of 2021 includes 46 well sought-after individuals with high ethical standards who prefer to go above and beyond to ensure success for their customers. These advanced strategists enjoy getting down and dirty with designs in an effort to avoid unnec-

essary downtime, keep production booming and strengthen their own reputations, as well as that of the companies they work for.

View the Engineering Leaders Under 40, Class of 2021, in the following section and read about their industry contributions online at www.controleng.com. CFE Media and Technology aims to honor these individuals at the annual Engineering Awards in Manufacturing dinner in spring 2022 in downtown Chicago. Congratulations to the Class of 2021!

• For information on how to nominate for 2022, visit: www.controleng.com/EngineeringLeaders.

Jeff Baldwin, 37 Director of Engineering Sealevel Systems

Liberty, SC, United States

BS Electrical Engineering, Clemson University

—Jeff has designed more than 60 industrial computer systems for leaders in defense, energy, public safety and transportation; his favorite being the “extreme rugged” designs and those that focus on functional density.

Nicholas Bell, 25 System Integrator InterConnecting Automation

Milwaukee, WI, United States

BS Electrical Engineering, University of Wisconsin-Platteville

—As a system integrator and consultant, Nicholas has traveled to various sites across the U.S. to assist in replacing aging controls systems and is a co-creator of a one-on-one PLC training/mentoring program.

Cameron Bolton, 25 Hardware Design Engineer

Sealevel Systems

Liberty, SC, United States

AS Science, Trident Technical College

BS Electrical Engineering, Clemson University

—Cameron led the development of an industrial SuperSpeed USB 3.1 hub, taking it upon himself to become immersed in a comprehensive understanding of USB specifications and protocols as he set out to create the best-inindustry hub.

Allison Buenemann, 28 Industry Principal - Chemicals Seeq

Seattle, WA, United States

BS Chemical Engineering, Purdue University

MBA, Louisiana State University

Jake Beck, 32 Controls Engineer Syscon Automation

Sandy, UT, United States

AS Electrical Automation & Robotic Technology, Utah Valley University

—Jake is a leading controls engineer for battery handling machines that support the EV industry, a task for which he has developed several programming standards that have contributed to Syscon’s re-use code library.

John Binion, 35 Process Safety Engineer

Hargrove Controls + Automation

Baton Rouge, LA, United States

BS Computer Engineering, Louisiana State University

—John is a licensed Professional Engineer and TÜV Rheinland-certified Functional Safety Engineer who embraces the highest ethical standards while fulfilling the spirit of his client’s needs, rather than just the required task.

Joshua Bozeman, 37 Operations Manager

Maverick Technologies

Webster, TX, United States

BS Chemical Engineering, Louisiana State University

—Josh has worked his way from process control engineer to project manager and now business manager; he recently moved to the Houston office to take over a struggling project portfolio for a critical customer, strengthening the relationship and profiting the company.

Anthony Carannante, 26 Automation Validation Engineer

Panacea Technologies

Montgomeryville, PA, United States

BS Chemical Engineering, University of Pittsburgh

—In her current role, Allison is shaping the go-to-market strategy, developing account-based expansion strategy, guiding the product development roadmap and growing new and existing chemical industry business at Seeq.

account-based expan-

—Anthony led the effort to design strategies and educate a pharmaceutical company’s engineering team on how to comply with data integrity standards; he worked to educate them and give them the tools to perform the work on their own.

it upon himself

Functional Safety Engi-

Baron Carleton, 36 Chief Operating Officer

Avalon International Aluminum

Tualatin, OR, United States

BS Nuclear Engineering, MS Nuclear & Radiological Engineering, Georgia Institute of Technology

—Baron developed and patented a new product that has revolutionized the interior glazing process in the interior aluminum door frame industry; the product allows Avalon to solve glazing issues with non-standard walls.

Briana Chamberlain, 27 Systems Engineer

Malisko Engineering

Denver, CO, United States

BS Chemical & Biological Engineering, Colorado State University

—As Senior Project Leader, Briana was a key contributor on the design and build out on a project for Colorado State University that featured a brewery on campus in support of the science and fermentation program.

Dominique Dangerfield, 32 Project Manager

Maverick Technologies

Baton Rouge, LA, United States

BS Chemical Engineering, Louisiana State University

Nayeli Castruita, 36 Sr. Controls Engineer

Wunderlich-Malec Engineering

Houston, TX, United States

BS Electrical Engineering, University of Texas at San Antonio

—Nayeli has developed her technical, people and management skills by traveling internationally and working in several industries, while also successfully managing a growing team, multiple projects and clients for Wunderlich-Malec.

Jonathan

Clark, 34 Operations Manager

Maverick Technologies

Pensacola, FL, United States

AS Science, Pensacola Junior College

BS Electrical Engineering, University of West Florida

—Jonathan leads and continues to grow a team of engineers, project managers and subject matter experts, supporting them in execution of controls and systems integration projects, while driving business growth in targeted areas.

Aaron Esselman, 30 Senior Hydro Engineer

Mechanical

Yuba Water Agency

Dobbins, CA, United States

BS Mechanical Engineering & Sustainable Manufacturing, California State University, Chico

matter experts,

Matthew Fether, 37 Department Manager Matrix Technologies

Maumee, OH, United States

BS Electronics Engineering Technology, University of Toledo

MBA, Bowling Green State University

and Triconex, Domi-

—While leading successful migrations as lead on projects for Honeywell and Triconex, Dominique developed an HMI [human-machine interface] Best Practice Wiki for Maverick, a guide that has helped others successfully plan and execute graphic migrations.

—Aaron takes pride in mentoring and successfully advocated for Yuba Water Agency’s internship program in 2020, providing on-the-job engineering training for several interns during an otherwise dark year for many college students.

Kyle Finkbeinier, 39

Sr. Electrical Engineer

Dart Container Corp.

Mason, MI, United States

BS Electrical Engineering, Michigan State University

—Matt recently oversaw the automation development and assisted with the execution for a project that doubled a customer’s capacity to produce household cleaning products during the worldwide COVID-19 pandemic.

execution for a

—Kyle has completed several projects, including upgrading the obsolete controls package on different machine with modern controls; such projects improved machine safety, quality of the product produced and machine throughput.

Bob Frey, 35 Project Engineer Plus Group

Cincinnati, Ohio, United States

BS Electrical Engineering, University of Cincinnati

—Bob was instrumental in the upgrade of an automotive production-critical machine, including safety upgrades and an all-new design for mechanical clamps; he developed a phased plan to install all upgrades during the nonproduction time.

Christopher Gonzalez, 32 Project Manager

Maverick Technologies

Webster, TX, United States

BS Chemical Engineering, Louisiana State University

—Chris is a trusted advisor to his clients, particularly for high-performance graphic development and implementation; he has selflessly delivered results and is often sought out by clients who would “pay 10% more to have him on the project.”

Kaleigh Hatfield, 35 Senior Manager, Assembly Manufacturing and Maintenance, Nissan North

Powertrain Plant

America

Decherd, TN, United States

MS Industrial Engineering & Engineering Management, University of Tennessee at Knoxville

—Kaleigh manages over 300 personnel and is responsible for three assembly lines that produce nearly 500,000 engines and electric motors per year on a multiple-shift operation.

Michael Horth, 30 Sr. Controls Engineer Applied Manufacturing Technologies

Orion Charter Township, MI, United States

BS Mechanical Engineering, Ohio Northern University

—Michael developed a standard controls package for PLC, HMI and robots for palletizing applications, as well as a custom AOI for Rockwell Automation PowerFlex drives; his biggest contribution has been in the development of other employees through mentorship.

Tim Garnett, 37 Senior Systems Engineer Malisko Engineering

St. Louis, MO, United States

BS Industrial & Manufacturing Systems Engineering, University of Missouri (Columbia)

—Due to successful project execution since 2010, Tim was recently requested by name for project work at a specific client; with many interfacing systems to consider when installing a process line, Tim is careful to view every angle and address inconsistencies early.

Robert

Harman, 38 Senior Control System Engineer/Project Engineer Plus Group

Cincinnati, Ohio, United States

BS Chemical & Biomolecular Engineering, Ohio State

—Robert helped design the Automation Plus Metrix365 data collection platform written in .NET Core, which operates within the ISA95 security model and features agnostic edge agents, key performance indicator (KPI) analytics and integration to enterprise systems.

Alex Head, 28 Engineering Team Leader

Maverick Technologies

Tinley Park, Illinois, United States

BS Chemical Engineering, Auburn University

—As part of a leadership development team at Maverick, Alex took on a yearlong project with a goal of improving company efficiency; he spent time learning from various business units to provide experience beyond the level of an individual contributor.

Jess Ingrassellino, 40 Engineering Manager InfluxData

San Francisco, CA, United States

BS Music Education, University of Vermont; MS Music Education, Teachers College of Columbia University; MBA, Quantic School of Business and Technology; EdD, Teachers College of Columbia University

—Jess manages the Telegraf project at InfluxData, which has produced over 300 plugins that makes real-time access to OT data easy; she also teaches management courses.

written in .NET

Hannah Kelly, 33 Lead Controls Engineer Strike

The Woodlands, Texas, United States

BS Electrical Engineering, Louisiana Tech

—Hannah is involved in developing remotely controlled stations that are involved in the safe movement and monitoring of hydrocarbons across Texas; she holds a patent from when she developed offshore control systems early in her career.

Michael Lehrich, 26 Automation Validation Engineer

Panacea Technologies

Montgomeryville, PA, United States

BS Chemical Engineering, University of Delaware

—Mike led a company effort to evaluate IIoT platforms and edge devices using MQTT and other communication protocols. His efforts led to Panacea adopting a new philosophy and nudged them towards cutting edge deployment methodologies.

Michael Mast, 31 Lead Systems Engineer

Honeywell Aerospace

Phoenix, AZ, United States

BS Aerospace Engineering, Arizona State University

MS Aerospace Engineering, Arizona State University

—Mike oversees automatic flight and thrust control functions as part of the Integrated Flight Systems team at Honeywell Aerospace; he has been a part of developing new and novel aerospace technology in addition to cutting-edge designs.

Ben Meise, 28 Systems Engineer Malisko Engineering

Denver, CO, United States

BS Chemical & Biological Engineering, Colorado State University

—Ben has led the effort on the Ramskeller project, a unique and highly automated brewing system at Colorado State University; the system provides students an example of controls, electrical, chemical and mechanical engineering design.

Jeffrey Kutz, 37 Vice President of Global Engineering Operations Bridge Gap Engineering

Northampton, PA, United States

BS Mechanical Engineering, Pennsylvania State University

—In his current role, Jeffrey is responsible for all engineering and execution activities throughout BGE’s global office network; he has regularly contributed to IEEE/PCA conference as a presenter of industry relevant topics

Kevin Martinez, 34 Project Engineer Applied Control Engineering

Taunton, MA, United States

BS Mechanical Engineering, Worcester Polytechnic Institute

execution activities

—Kevin is a go-to for out-of-the-box and unusual projects at ACE due to his ability to learn and figure out new and old technologies; he enjoys leading by example and mentoring young engineers on technical and people skills.

Ryan McSherry, 32 Manager, Business Development IAPS Products

Yokogawa

Newnan, GA, United States

BS Biomolecular & Chemical Engineering, Georgia Institute of Technology

—Ryan is a certified Product Manager, an engineer-in-training and an expert in the field of laser analytical gas measurement with the ability to communicate a complex subject with a wide range of coworkers and clients.

Raju Nair, 36 PLC Applications Engineering Manager

Tesco Controls

Sacramento, CA, United States

BS Electrical & Electronics Engineering, California State University Sacramento

—As a manager of two departments at Tesco, Raju leads a team of 30 PLC engineers working on critical infrastructure projects as well as a team to develop devices specifically designed for the water/wastewater industry.

thrust control func- expert in the field of laser engineers on criti-

Jason Pharo, 33 Technology Lead Team Manager

Maverick Technologies

Pensacola, FL, United States

BS Chemical Engineering, Auburn University

—Jason was the technical lead for a greenfield automation project beginning with functional development through commissioning for the scale up of a pilot plant for a customer’s cutting-edge precursor material.

Alan Raveling, 39 OT Architect

Interstates

West Chester, OH, United States

BS Computer Science, Iowa State University

MS Information Assurance, University of Dallas

—When customers began asking about cybersecurity, Alan took it upon himself to expand his expertise into understanding standards from NIST and ISA and developed training programs to help customers meet compliance requirements.

Deepak Sharma, 39 Principal Process Engineer

Bayer U.S.

Creve Coeur, MO, United States

MS Chemical Engineering, Illinois Institute of Technology

—Deepak manages a multimilliondollar infrastructure project supporting Bayer’s production of the SARS-COV-2 vaccine; his implementation will enable timely delivery of vaccines that will save lives.

Ryan Slayton, 30 Engineering Manager Quantum Automation

Anaheim, CA, United States

BS Mechanical Engineering, Cal State Fullerton

—Ryan oversaw the design and improvement of pharmaceutical conveyor belts via RFID technology such that blood samples are more readily processed and errors are minimized; patients are able to get results and proper care faster as a result.

Daniel Ragozzino, 26 Controls Engineer

Patti Engineering

Indianapolis, IN, United States

BS Electrical Engineering Technology, Indiana University–Purdue University

Indianapolis

—Dan has developed expertise with UHF RFID for manufacturing and asset tracking applications and has implemented RFID systems in multiple industries; he also has participated and spearheaded UHF RFID application engineering studies.

Sam Russem, 34 Director, Smart Manufacturing Grantek Systems Integration

Allentown, PA, United States

BS Systems Engineering, University of Pennsylvania

—As lead for Grantek’s Smart Manufacturing Practice, Sam is responsible for identifying and developing solutions for customers by working cross functionally across all departments; in two years Sam has doubled this initiative’s revenue.

Pratul Singh, 35 Senior Controls Engineer

Masimo

Irvine, CA, United States

BS Electronics & Communication Engineering, National Institute of Technology, Nagpur;

MS Electrical & Computer Engineering, Rutgers University

—Understanding machine safety, industrial communications and controls, Pratul has led integration of collaborative robots into a manual assembly line and current materials flow.

Doug Sumpter, 37 Controls + Automation Leader of Projects Hargrove Controls + Automation

Mobile, AL, United States

BS Electrical Engineering, Auburn University

—As Leader of Projects, Doug uses his project management skills to lead other project managers on profitable and successful projects; his unique skill to communicate his vision while remaining focus on individual needs benefits his teams.

with functional devel-

SARS-COV-2 vaccine; his

Alan management

Ankita Thakur, 32 Lead Process Engineer CertainTeed

Buchanan, New York, United States

MS Science, Arizona State

—Ankita led a project to reduce dryer jams resulting in more than $116,000 in annual savings; she was also key support for Burn/Wet/Peel and Cupping projects that accounted another $500,000 in combined savings.

Jeniffer Vesga, 36 ESP Surveillance Engineer

Schlumberger

Houston, TX, United States

MS Oil, Gas & Petrochemicals, Universitat Guillermo Marconi

—Jeniffer has made important contributions to the remote control and monitoring of oil and gas well production using electro-submersible pumps; she has also been involved in the development of software that has greatly improved the remote control of wells in production.

Michael Williams, 38 Engineer Applied Control Engineering

Houston, TX, United States

BS Electrical Engineering, Lamar University

—Mike shows an eagerness to dive into projects and master them by understanding the problem and developing solutions that are robust and well executed; he actively listens and seeks solutions that go beyond the obvious to anticipate and prepare for eventualities not presented in the problem description.

Kaishi Zhang, 34 Global Director, Product Management

Schneider Electric

Andover, MA, United States

BS Electrical Engineering, Zhejiang University, China; MS Electrical Engineering, University of Minnesota

—Having worked closely with customers in different functions, Kaishi has been leading a team to define the next generation of automation platform; his dedication to bringing innovative products to the market is recognized by customers, partners and peers.

Janika Tyagi, 36 Proposal & Estimating Group Team Leader

Maverick Technologies

Houston, TX, United States

BS Chemical Engineering, Texas A&M University

—Janika is a dependable leader who is strongly oriented towards supporting and mentoring her direct reports. As a working/functional team leader, she seeks solutions to problems and looks for opportunities to increase efficiencies.

Thomas Wenning, 36 Program Manager

Oak Ridge National Laboratory

Oak Ridge, TN, United States

BS Mechanical Engineering, University of Dayton

MS Mechanical Engineering, University of Dayton

and mentoring her

—Under Thomas’ leadership, the U.S. Dept. of Energy Better Plants program has grown to more than 250 industrial partners, generating over $8.2 billion and 1.7 QBtu in cumulative energy savings.

Engineering Leaders Under 40

Know someone who qualifies as an Engineering Leader Under 40? Help give them the recognition they deserve.

The Engineering Leaders Under 40 program recognizes manufacturing professionals under the age of 40 who are making a significant contribution to their plant’s success, and to the control engineering and/or plant engineering professions. Our research shows that finding, training and retaining workers is the biggest issue facing manufacturing today.

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SMART MANUFACTURING, IIoT, INDUSTRY 4.0

Paxton Shantz, Beckhoff Automation

How to calculate digital transformation ROI

Simplify and prioritize the digital vision for smart factory upgrades and consider hard and soft savings in the return calculations.

While smart manufacturing and digital transformation continue to gain traction in intralogistics, packaging, process control, assembly and manufacturing, many facilities are still resisting change and using with the same old equipment and processes. The main reason? There is not readily available information about return on investment (ROI) or time to value (TTV) to support investing in it.

Sometimes, project champions push to get approval on the merit of the project’s technological advantages. Most engineers and plant managers need to provide more traditional justification. If ROI or TTV data is needed to advance Industry 4.0 plans, here is some advice and research to help get things moving.

ROI for digital transformation?

Keep in mind that for many chief financial officers (CFOs), the responsibility of making forwardlooking strategy investments is relatively new. Prior to recent years, their focus was more about financial reporting, stewarding the company’s assets and ownership of cash management. By coupling this understanding with the CFO’s fiduciary responsibility, it becomes clear why the CFO wants concrete data to justify any technology investment decisions.

Of course, there is no shortage of anecdotal information that promises a slow death to companies that

do not transform quickly enough. And countless graphs forecast the exponential growth Industry 4.0 will provide. But a lot of this information has been in circulation for years. Has it stood the test of time? Is real ROI and TTV data available?

If we take a step back, growth forecasts from 2017 estimated Industry 4.0 would experience a 37% compound annual growth rate (CAGR) from 2017 to 2023 ($47 billion to $310 billion). When compared to a similar report from 2019, which began its study in 2016, the CAGR has been re-forecasted to 14.6% from 2020 to 2027.

Although these two data points support the fact that expectations for Industry 4.0 may have been too optimistic, they also illustrate how a lot of misinformation is making the digital transformation more complicated and difficult than it needs to be. This misinformation often stems from companies selling unnecessary hardware and software solutions meant to lock users into a unique solution. The real end goal of these new technologies and concepts – the digital vision – is something broader, more open and more powerful.

Simplify 3 parts of the digital vision

Figure 1: Choose partners for your digital transformation that prioritize open technologies, including horizontal communication to all open fieldbus systems and vertical communication via OPC UA, MQTT, AMQP, etc. Courtesy: Beckhoff Automation

To avoid such complications and inaccurate ROI and TTV calculations, it is important to simplify and prioritize the digital vision into a plan that can be incrementally implemented. Going through this process supports a better understanding of the requirements and makes companies better prepared to select the right technology partners for each step.

To simplify and prioritize the digital vision, first consider how digital transformation for manufacturing integrates three key business components:

• Supervisory control and data acquisition (SCADA), programmable logic controller (PLC) and control (machine automation)

• Manufacturing execution system (MES), including part traceability, machine monitoring and machine management, recipes, etc.

• Enterprise resource planning (ERP), which includes: (AP/AR, raw materials, purchase orders, inventory, scheduling and tracking).

Achieving large profitability and competitive gains requires seamless integration of three business components. However, it is important to begin at the machine automation level, then incorporate the MES and finally the ERP. The reason for following this path is based on data requirements but also because it is the easiest path for development.

ROI for PLC/control technologies

Because the PLC/control is one of the best-known and understood components in manufacturing, many very good Industry 4.0 solutions exist that can be added to an existing PLC/control platform. A good example is Caron Engineering. Founded in 1986, Caron Engineering has partnered with machine tool users for 36 years to digitize their machines.

With a focus on unattended operation, Caron Engineering provides an off-the-shelf offering called tool monitoring adaptive control (TMAC). With more than 5,000 installations, this technology has proven to be easy to integrate into any type of computer-controlled cutting machine tool for about $10,000 to $20,000. TMAC provides an average ROI of 28% and a TTV that is immediate by using advanced sensors to provide machine health information that allows maintenance departments to predict potential downtime.

This example is relatively typical of how easy it can be to calculate an attractive ROI and TTV for digitally transforming the PLC/control. Whether working to integrate a turnkey solution, working with an integrator or working with an automation supplier, it is easy to target and quantify the investment required to obtain certain benefits. However, moving upstream to integrate the MES and ERP, the ROI and TTV values become much more difficult to quantify.

ROI for MES and ERP upgrades

ROI is more difficult to calculate for MES and ERP systems because estimating the ROI requires detailed information about the costs and benefits –and this can be challenging for these systems. For each of these, users can be certain the digital transformation is going to provide benefits, but there is uncertainty about what the actual benefits will be. In addition, there can be many soft returns an ROI calculation will miss.

If the MES and ERP systems are complex, consider an incremental and iterative process that allows better benefit targeting. This process allows users to focus on a specific problem and uncover immediate hard and soft savings.

A typical place to start for the MES hard savings is poor quality, and for the ERP it is inefficient scheduling. These two issues result in excessive cost due to rework, scrap and lost production time. Properly quantifying these costs will provide a welldefined and meaningful investment target for MES and ERP.

Figure 2: Caron Engineering’s TMAC solution offers multi-channel monitoring to help increase machine and tool health, providing a 28% ROI and simple integration for cutting machines that use PCbased control. Courtesy: Caron Engineering

The next step is to evaluate the potential soft savings. This is where MES and ERP systems thrive and realize the real purpose of digital transformation. In this phase, it is important to identify and quantify manual tasks that can be automated. It is about eliminating the time, challenges and limitations of human intervention by allowing the MES and ERP systems to immediately make key decisions. The automated decision making will advance a company’s competitiveness. For the ROI calculation, however, companies should focus on the time saved and redundant tasks that can be eliminated.

Industry 4.0 ROI Problems

While going down the path of iterative ROI estimates, stay focused on the immediate problems and their solutions. The digital transformation will certainly provide benefits in the long term, so avoid the trap of trying to accommodate every aspect of Industry 4.0. Work to find technology partners that can help navigate the company’s transformation. Partners may differ for each stage.

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KEYWORDS: digital transformation, Industry 4.0 Digital transformation growth is not being realized by many companies because they don’t see the return on investment (ROI) returns.

Prioritizing the digital vision requires focusing on control system and asset management systems. Manufacturing execution system (MES) and enterprise resource planning (ERP) upgrades can help companies realize ROI returns.

ONLINE

www.controleng.com/ iiot-industrie-4-0/

CONSIDER THIS

What is holding your company back from taking the next step in the digital transformation?

ONLINE EXTRA

Learn more from Beckhoff about Industry 4.0: www.beckhoff.com/industrie40

Select partners focused on unifying the PLC/ control, MES and ERP system data into information that will address manufacturing inefficiencies, continue to support employee involvement for innovation and be built on standard industry hardware, software and communication protocols. ce

Paxton Shantz, digital manufacturing industry manager, Beckhoff Automation LLC. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

ANSWERS

SMART MANUFACTURING: DIGITAL TRANSFORMATION

Matt

Matt Newton, Aveva

Find smart manufacturing ROI

Smart manufacturing and digital transformation continue to gain traction.

The COVID-19 pandemic forced radical lessons on companies about how to run and optimize systems in unpredictable times. Global organizations have been compelled to put technology at the heart of their businesses, speeding up digital transformation. As companies and industries work to hire and retain appropriate staff after a disruptive year, questions around return on investment for future projects are expected.

IDC estimates that spending on Industry 4.0 technologies, such as augmented reality (AR), virtual reality (VR) and robotics will surpass $1 trillion in revenue, led by the manufacturing and transportation industries. Digital transformation can advance business strategy, improve operations, and uncover new opportunities for sustainability, efficiency and productivity. To be successful, a company needs to improve profitability and return on capital across the asset and operations value chains.

Support business strategy

MMore ANSWERS

KEYWORDS: digital transformation, asset analytics

Digital transformation is about advancing and uncovering new opportunities for sustainability, efficiency and productivity.

By outlining clear financial and operational aspirations, teams can demonstrate how the investment creates real business value. A McKinsey & Company report looked at industry-leading manufacturers using digital transformation to enhance operations. Company benefits recorded include 30 to 50% reductions in machine downtime; 15 to 30% improvements in productivity; and 10 to 20% decreases in the cost of quality. By aligning technology solutions with business needs, it can clarify how the transformation supports company-wide priorities and brings into focus why investments should be made.

The overall tactical objective in achieving digital transformation is creating a real-time operational control loop that manages based on information and analytics. An open, system-agnostic approach provides long-term values and lowers total cost of ownership (TCO) for the user.

ONLINE

See more on digital transformation at www.controleng.com, including “More automation software, more productivity: Expert interview series, John Krajewski, Aveva.” www.controleng.com/ iiot-industrie-4-0

CONSIDER THIS

How is your company achieving digital transformation?

For example, Duke Energy implemented predictive analytics software as part of its program to avoid catastrophic failures at power plants. The software leverages high fidelity data from more than 30,000 sensors to develop more than 10,000 models to catch asset failures long before they occur. More than 500 finds over three years has helped to avoid more than $100 million in repair costs.

Every digital transformation journey needs to begin with the critical understanding that information and data have

become a priceless and strategic asset to the enterprise. The faster a team can collect, visualize and analyze data, the faster it can take action that benefits operations and customers. The overall tactical objective in achieving digital transformation is to create a real-time operational control loop that manages an enterprise based on information and analytics.

For example, one of the world’s largest industrial gas manufacturers closed its data loop with predictive asset analytics. Prior to a scheduled maintenance outage, the plant identified a vibration sensor anomaly. This allowed technicians to investigate a turbo engine compressor further and discover a cracked impeller. This early catch prevented reactive maintenance and unplanned downtime for a total savings of $500,000.

Catch asset failures in advance

As supported by the examples above, a study of common failure patterns by ARC Advisory Group found 82% of failure types are random. Only 18% are predictable and can be prevented using traditional maintenance methods.

Machine learning helps identify inefficiencies and abnormalities in equipment operation long before regular inspection. Engineers can reference operational models and digital twins for recent abnormalities in design versus operational performance. This capability becomes increasingly powerful when combined with advanced visualization and control technologies, such as web-based human-machine interfaces, supervisory control and data acquisition systems and AR/VR.

In a large regulated and non-regulated utility with more than 60 plants in six states, including coal, simple cycle combustion turbines, combined cycle and integrated gasification plants, predictive analytics software was applied to helps monitor and optimize the maintenance of critical power generation. An early warning of a crack in a turbine rotor saved the utility more than $34.5 million.

Digital solutions enable companies to enhance capabilities, increase reach and maximize returns. An open, system-agnostic approach drives longterm value and lower total cost of ownership. ce

Matt Newton is director, asset performance portfolio, Aveva. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

Peter Galan, retired software engineer

Control system improvements: Feed-forward, adaptive, fuzzy control

Control methods that can be more effective than proportional-integralderivative (PID) controllers, include feed-forward control, disturbance compensation, adaptive control, optimal PID control and fuzzy control.

Aproportional-integral-derivative (PID) controller has limits and can be improved and optimized. Expansion of other control architectures doesn’t mean PID-based control systems are dying. Control systems are advancing with other technologies. Examples of control system advances follow.

Feed-forward control

Feed-forward control itself is another name for an open loop control. Such a control is not precise and cannot cope with the system disturbances, so it is very rarely used. However, it can be combined effectively with feedback control.

There are actually two options of the feed-forward combined with feedback control. They differ based on a variable, which is processed by the feedforward path. Figure 1 shows both possibilities of feed-forward control (compensation).

The first feed-forward compensation applies to a reference signal, r(t) with two blocks, Fy and Fu The second feed-forward compensation applies to a disturbance signal, d(t). Such a feed-forward and feedback control arrangement is sometimes called a control system with disturbance measurement/ compensation.

Feed-forward compensation

The first option under feed-forward compensation is explained below and shown in Figure 2.

In the simplified block diagram (Figure 2) the individual blocks represent transfer functions in the s-domain, omitting the s argument. The output-toreference transfer function is expressed as

By choosing F u = 1 and F y = S, the response to the reference will be simplified to S, so it will not depend on C at all. This is great, as it’s possible to optimize control coefficients for minimizing disturbances, for example, without accounting for a response to the reference. However, the result is the same (slow) response time to the reference as the controlled system itself. In some cases, this does not matter, especially if the reference (set point) value rarely changes, or if such a slow reaction to the reference value change is even required. If this is not the case, then choose F y to be a first order low-pass filter with a time constant, which can be, let’s say, 10 times shorter than the sum of the controlled system time constants. This is what the feedback control targets. Because F y will not be identical to S, in this case a response to the reference value will remain dependent on the C parameters, but the sensitivity towards those control parameters/coefficients will be much lower, so it’s possible to optimize

Figure 1: A feedback control system can be enhanced with feed-forward compensation to enhance control system effectiveness. All courtesy: Peter Galan, a retired control software engineer

Figure 2: A simplified block diagram combines feedback control and feed-forward compensation.

ANSWERS ADVANCED PROCESS CONTROLS

them to minimize the disturbance impact on the output variable. Usually, F u and F y are first-order filters (high-pass and low-pass respectively) with suitable time constants.

Disturbance compensation

Adisturbancecompensationissometimes referred to as a feed-forward compensation applied to the disturbance signal. Look at the simplified block diagram of a combined, feed-back and disturbance compensation control system in Figure 3.

The output-to-disturbance transfer function, in this case, is By choosing Fd = S1-1, the output variable will not depend on a disturbance at all. However, such implementation is not as simple as it sounds. If S1 represents a low-pass filter (which is almost always the case), the Fd should have the transfer function 1+sτ1, which must contain a derivative. It’s even worse if S1 contains some transportation delay. In such a case, Fd should be able to predict the disturbance behavior in advance.

That’s possible in some applications. For example, if the controlled system is a multi-zone heat chamber maintaining a certain temperature profile, current temperature can be measured at neighboring zones, and if they change, the control system can immediately act without waiting until they affect (disturb) this particular heat zone control.

Adaptive control

While feed-forward or disturbance compensations are more or less well-defined additions to a feedback control, adaptive control has rather a vague meaning. Basically, the purpose of an adaptive control is to monitor control system and its environment and modify either the structure, or more likely the parameters of a (PID) controller. Figure 4 shows a block diagram of a generic adaptive control system.

EXAMPLE: Adaptive control can work in a temperature control system that has continuously changing time constants of the heater. By analyzing the controlled system (the heater), it’s possible to measure its time response and calculate, for example, three pairs of its τ1 and τ2 constants, one taken at around the ambient temperature (τ a1,2), the other one taken at the so called balanced temperature (τ b1,2) , at roughly 50% of the output power, and the last one taken close to the maximum temperature (τ m1,2). Figure 5 shows those time responses are changing exponentially with the rising (falling) output variable: temperature.

It’s possible to linearize time responses’ dependence on temperature, for example, as it is shown in

Figure 4: Block diagram shows an adaptive control system.

Figure 3: A simplified block diagram combines feedback control with disturbance compensation.

Figure 5: Heater time response is graphed as a function of temperature.

Figure 6: Linearized time responses are graphed as a function of temperature.

Figure 6, which can simplify calculations provided by the adapter block.

It is evident both time responses are functions of a difference between the actual temperature (an output variable) of the heating system and the ambient temperature. So, those two variables have to be inputs to the adapter block. Another information required by the adapter is the sign of actuating variable, u(t), because those time responses depend on whether the current process is heating or cooling. The adapter continuously calculates values of the controlled system time responses and calculates the optimal PID coefficients based on those values.

Optimal control

Optimally tuned PID parameters provide an optimal transfer function for a certain, reasonably selected time response (settling time) of an entire PID control system. However, the settling time, with which an output variable reacts to the step change of a reference value, even though it can be a “reasonable” short, it will not be automatically optimal, that is a shortest settling time possible. Further increasing the KI value may decrease the settling time. With continued increasing of the KI value, at some point the output variable will start to oscillate, which means the system is not optimally tuned and is unstable. To get optimal system behavior, for example, the fastest possible reaction to the reference value, a different control method is needed than a simple, closed-loop control system with PID compensation.

Optimal control has been a subject of extensive research for many decades, beyond the scope of this article, but below see some basic ideas about optimal control.

EXAMPLE: A direct-current (dc) electrical servomechanism requires control. Such a servo system is very often used, for example in robotics. The servo requires control to reach a new reference point in the shortest possible time. An optimally tuned PID controller would not achieve this goal. Applying the maximum possible voltage to the dc motor runs the motor at full speed forward. At a certain time, changing voltage polarity, would start to de-accelerate the motor at the maximum possible rate. When the motor speed is zero, voltage is reduced to zero. By changing voltage polarity at the right time stops the servo at the desired position at the desired time. This is called optimal control, more specifically, time-optimal control.

Figure 7 explains the above-described time-optimal control process in the state space, which, in this case, is a two-dimensional space (area). One dimension is an output variable and the other dimension is its (time) derivative. At the moment, when a new reference value is applied, the output variable is shifted along horizontal axis, so it actually represents the regulation error – difference between the reference

and the actual output. At the same time, t0, a maximum voltage is applied to the dc motor. The servo leaves its initial position, P0 and starts to accelerate. At the time t1 the controller changes voltage polarity, and the motor speed decreases. At time t2 , just as the motor speed is zero and the desired position P2 has been achieved, the actuating variable – voltage is turned off. While this seems straightforward, knowing the switching curve’s shape is not so simple.

If the controlled system is a servomechanism with a simplified transfer function – the angular displacement over the voltage in the s-domain is:

where K and T include all the electro-mechanical constants of the servomechanism. A complete time optimal control system is shown in Figure 8.

This is a different control scheme from PID control. It is non-linear control, and because the second non-linearity, N 2 , represents a relay, such a control is called the bang-bang control. Regarding the non-linearity N 1 , which represents the switching curve, the “sqrt” (square root) function will provide reasonable results. There are known graphical methods based on the isoclines

and some computational methods, which can be used to get a more precise switching curve. In

Figure 7: Time optimal control in state space is graphed with derivative of output variable on the vertical axis, and output variable on horizontal axis.

Figure 8: Time optimal control system for servomechanism is shown.

ANSWERS ADVANCED PROCESS CONTROLS

M

More ANSWERS

KEYWORDS: Control methods, advanced process control, feedforward control

Examine advanced process control (APC) methods extend beyond PID control to include feed-forward control, disturbance compensation, adaptive control, fuzzy control and others.

Compare diagrams that offer examples of APC methods.

Consider what control method might best fit various applications.

CONSIDER THIS

If your control systems rely on decades-old control methods, are you getting decades-old results?

ONLINE

With this article online, see many details about FUZZY CONTROL with 7 more graphics. www.controleng.com/control-systems/pid-apc

Also see: From simulation to computer-aided design of control systems

practice, it is difficult, and the control process will likely be switching the driving voltage between its maximum and minimum forever. To avoid this, try to increase the dead zone of the relay. However, then the system may end up with a relatively high steady state error.

Another complication or limitation is the fact that not every controlled system exhibits “astatism” (meaning it contains an integral member) like a servomechanism. Such a system requires actuating the variable to be zero when the output variable matches the reference value. For example, a temperature control system maintaining certain temperature requires permanent presence of a non-zero value of the actuating variable.

In such cases, the time optimal control has to be combined, for example, with a feed-forward subsystem. The feed-forward will continuously provide some constant actuating value, which matches to

Virtual Training Week, Fall 2021 edition

a desired output value. The optimal control subsystem will act only as a booster during the transitions from one output value to the other.

An entirely different class of bang-bang control systems should be rather called on-off control systems. They are among the simplest systems, where the actuating variable changes its value between 0 and U max forever. Their relay characteristics is a simple on/off with a small hysteresis in some cases. They are used in simple applications, such as electric range heaters. ce

Peter Galan is a retired control software engineer. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com.

5 days of PDH online credits

Virtual Training Week from CFE Media and Technology, Oct. 18-22 (and archived thereafter), has five days of professional development hour instruction at https://cfeedu.cfemedia.com/pages/virtual-training-week. More details and registration information is available at CFE EDU’s URL above (or will be shortly).

Learning is expected to include 20 hours of sessions. Below are tentative details as of Aug. 25.

General topics including digital transformation and future manufacturing technologies; electrical and power innovations; control systems, networking devices and plant safety; effective maintenance strategies and productivity; and motors and drives.

Companies and organizations expected to provide expert instruction are: Advanced Energy, Applied Manufacturing Technologies, Cirrus Link Solutions, Cummins, Festo Didactic, GE Digital, Industry IoT Consortium, Jacobs; Lockwood, Andrews & Newnam Inc.; MIMOSA, Motion, Nissan-USA, Page, PI North America, SEW Eurodrive, Stratus, Wago, Wood and Yaskawa.

Topics (as of this writing) are: Engineering educators: Are you leveraging the power of the digital transformation in the classroom? Mission critical system installations; Transfer switch application and operations; Specifying gaseous generator sets; Industrial control system networks: Keys to reliability and security; How open, real-time location services helps manufacturers; Safety validation in an IIoT, Industry 4.0, smart manufacturing world; Standards-based interoperability for digital transformation in asset lifecycle management; How digital transformation accelerates predictive maintenance, production quality; How control systems and AI add productivity, make maintenance smarter; Total motion system efficiency; and Back to basics: Electric motors.

CFE Media and Technology maintains accreditation with The American Institute of Architects (AIA) and with the Registered Continuous Education Program (RCEP). Control Engineering, Consulting-Specifying Engineer, Plant Engineering, IIoT for Engineers, Oil & Gas Engineering and Industrial Cybersecurity Pulse are part of CFE Media and CFE Technology. ce

‘

To get optimal system behavior, a different control method is needed than a simple, closed-loop control system with PID compensation.

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ADVANCED PROCESS CONTROL

Allan G. Kern, P.E., APC Performance LLC

Understanding the matrix for APC improvements

The dominant aspect of process control activity for the next couple of decades will (most likely) be multivariable control. This is the next logical step in process automation progress. Better tools are making advanced process control (APC) methods available to more applications.

After several decades of multivariable control activity, the conventional multivariable control paradigm – model-based control (MPC) and real-time optimization – has never evolved into the multivariable control core-competency the process industry needs. It is evident much work remains to be done (“APC’s missing metric”) and more agile tools are needed to do it (“Multivariable control as core-competency.”)

A modern multivariable control paradigm will combine enduring single-loop process control principles that pre-date the MPC era with key multivariable control lessons that have emerged from the MPC era (Table 1). The surviving core multivariable control principles and lessons will be important to know for control engineers. Chief among them is the concept of the matrix for its role in multivariable control, and also for its role in the bigger picture of effective process operation, constraint management, and process optimization.

APCconnections, directions

The first things to know about any controller, whether single-loop or multivariable, are its connections and directions.

In single-loop control, “connections” refers to which transmitter (or other process measurement) and which valve (or other final control element) are connected to the controller. These are often shown on piping and instrument drawings (P&IDs), control system graphics, and in many other types of process documentation. Each context may include additional controller details, but a controller’s connections are always the minimum information necessary to grasp the role of the controller at a glance,

that is, which variable is being controlled by which valve (or by which “handle”).

A matrix diagram provides the same information for a multivariable controller (Figure 1). It shows which manipulated variables (MVs) are connected to which controlled variables (CVs), which MVs can be used for constraint control and which CVs can be optimized. As in single-loop control, this is the starting point in understanding the role in process operation of any multivariable controller.

Understanding APC control action

The next most essential piece of information is control direction, which is the sign of the process gain. For example, if a single-loop controller output or a multivariable controller MV is increased,

connections and directions of a multivariable controller,

Figure

comprise the basic information necessary for all members of the operating team to collaborate on constraint control and optimization objectives. A plus or minus sign indicates the control direction of each manipulated variable/controlled variable (MV/CV) connection for control and optimization purposes. All graphics courtesy: APC Performance LLC.

More agile tools are helping multivariable control become more effective for advanced process control and other applications than traditional model-based control (MPC) and real-time optimization. Learn where the matrix can help.

1: A matrix diagram shows the

which

ADVANCED PROCESS CONTROL

does the controlled variable increase or decrease in response?

In single-loop control, this is also known as control action (reverse or direct, respectively). In multivariable control, it is also known as gain direction (positive or negative, respectively). Knowing control direction is necessary to understand the possibilities, limitations and competing interests of utilizing each MV/CV connection for control and optimization purposes.

collaborate effectively in multivariable constraint management and process optimization.

Matrix diagrams go beyond APC

In the MPC era, matrix diagrams have often been hidden from view and of interest primarily to APC engineers. Experience has revealed matrix diagrams are an effective tool to concisely diagram the multivariable nature of any process operation. This makes matrix diagrams of primary interest to the entire operating team, including process engineers, operations personnel, distributed control system (DCS) and APC engineers, and all other process operation and optimization stakeholders.

Figure

Control direction is the most enduring aspect of a process model. A single-loop controller may be retuned many times in its life, but its control direction never changes – it is a fundamental consequence of the process design and the controller’s connections. MPC experience also has shown that other model aspects, such as dynamic timing and gain magnitude, may change frequently, but gain direction never does.

Connections and directions together define the basic mechanics and capabilities of a controller. The rest is tuning. Control engineers will often be interested in additional controller details, but connections and directions, in the convenient form of a matrix diagram, comprise the basic information necessary for all members of the operating team to

Matrix diagrams have proven to be one of the most effective and appropriate tools to bring all these stakeholders onto the same page when it comes to managing process constraints and achieving process optimization.

In the modern multivariable control paradigm, the genesis of matrix diagrams changes. Instead of originating within APC projects, they originate with process engineers, also known as production or operation engineers, who often have the lead role in steering day-to-day operation towards greater reliability and optimization.

Process engineers also can use matrix diagrams as a communication and discussion tool with the rest of the operating team. Beginning as working sketches developed by process engineers, matrix diagrams can logically migrate into process manuals, training materials, operating procedures, control system graphics, and ultimately into automated multivariable controllers (Figure 2). Not incidentally, as the matrix diagram evolves, it becomes refined and proven in use, so it becomes sanctioned among the operating team before it becomes deployed as an online controller.

Multivariable constraint control and optimization has always been an inherent aspect of nearly all process operations, whether it is carried out manually by the operating team or with the aid of automated multivariable controllers. But prior to the MPC era, industry lacked an effective tool and best practice to capture and share this crucial operating information in a practical and concise format. Bringing the matrix into the mainstream lexicon of process automation may ultimately prove to be the single most important contribution of the MPC era (not models or optimizers: See “Changes in store for APC”).

Theoretical vs. operational matrix

In conventional MPC practice, matrix design has usually included essentially all MV/CV process interactions as identified through a comprehensive plant step test. Every process interaction, however small or potentially problematic in use, becomes a connection in the matrix. But from an

‘

Connections and directions together define the basic mechanics and capabilities of a controller –the rest, it could be said, is just tuning.

2: The genesis of matrix diagrams changes in the modern multivariable control paradigm, where matrix design begins with operating team collaboration and ultimately may be deployed as an automated multivariable controller.

experienced process operation standpoint, a more limited number of MVs are usually known to be effective and proven in operation for the various constraint control and optimization purposes, while many others are known to be problematic and are avoided in operation based on experience and various process and equipment operational considerations.

This is the difference between theoretical and operational matrix design (see “Operational matrix design”). Discussion with process and operation personnel will usually readily reveal which are which – especially if everyone understands the basics of matrix diagrams!

Operational matrix design generally results in multiple, smaller, less dense matrix designs, rather than one large matrix as has been common practice under the theoretical approach of MPC. For example, process engineers and console operators can often explain directly, based on experiences and knowledge, without a plant test, which MVs to use for which constraints and optimization objectives. Process engineers and console operators will rarely mention (or sanction the use of) more than two or three handles for any one purpose; usually it is one or two. As the matrix becomes less dense from this paring of ineffective or problematic handles, it becomes more easily divided into smaller and more manageable parts. This is reflected in Figure 2, which (at a matrix size of 5x8) is smaller and less dense than typical MPC matrix designs (which often have dozens of variables and hundreds of models).

Operational matrix design tips

A good rule of thumb in operational matrix design is if there are more than three models (or connections) in any one matrix column, further review is warranted. There is no hard reason for this, but experience has shown the realities of industrial process and equipment operation tend to have the ultimate effect that more than two or three useful handles for any one objective is rare (except in cases of multiple “parallel handles,” such as heater pass balancing). The bad actor loop metric also can be utilized to help identify existing manual multivariable control practices that have become established within ongoing operation.

APC example: Multivariable control in unexpected places

Example: With the emergence of multivariable control as a core-competency and more efficient and reliable control algorithms, multivariable control can migrate from the supervisory control layer into the base layer. This brings important performance and reliability improvements, especially controller redundancy and high execution speed.

Figure 3: This matrix design for heater control includes fuel gas, draft, and pass balancing. This application can run at the redundant control layer with fast execution speed so that it can accommodate both fast and slow controlled variables. In model-less multivariable control, the matrix includes gain direction rather than detailed dynamic models.

Redundancy means that the question “What if APC is off or unavailable?” no longer needs to be a complicating factor. Instead, small, fast APC applications can be designed to run continuously in the base layer, just like other base layer single-loop or advanced regulatory controls (ARC).

High execution speed means multivariable controllers in the base layer can combine fast controlled variables (CVs) with slow CVs. Conventional APC at the supervisory level often executes at 30 or 60 seconds and only can accommodate correspondingly slow CVs, but many process variables respond much faster than this. APC in the base layer can execute at 1 to 5 seconds, so it can combine fast and slow CVs in one multivariable control matrix design.

Fired heater control, one of industry’s most common multivariable control applications, provides an example (Figure 3).

In the past, fast or critical CVs, such as burner pressure, need to remain in the base layer, while slower CVs, such as excess oxygen or pass balancing, are typically implemented in conventional model-based multivariable controllers at the supervisory level. This split scheme is complex to implement, maintain and operate, and it compromises performance. With APC in the base layer, the entire multivariable control application can be implemented in one combined matrix, bringing significant reliability and performance improvements. ce

Allan G. Kern, P.E., is owner and consultant at APC Performance LLC. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com.

MMore ANSWERS

KEYWORDS: Matrix, advanced process control (APC)

Learn about a controller’s (singleloop or multivariable) connections and directions.

Review theoretical vs. operational matrix design and design tips for all process interactions. Examine an APC example of fired heater control.

CONSIDER THIS

Should you be using a matrix to optimize more processes?

ONLINE

www.controleng.com/ control-systems/pid-apc/

Also read: Multivariable control as a core competency

INDUSTRY 4.0, AUGMENTED REALITY

Vinay Bhanot, L&T Technology Services

Factory of the future: How to vitalize digital transformation

See five attributes of the factory of the future. IT and OT organizations, hardware and software synergy should be part of the roadmap.

Automation remains a critical part of the designs for factories of the future. If you observe that industrial digital transformation has stalled or just hasn’t taken off, motivation and advice follow to apply intelligent automation, Industrial Internet of Things (IIoT) technologies and cybersecurity.

The global industrial automation market is projected to be worth $326.14 billion by 2027, growing at a compound annual growty rate (CAGR) of 8.9% in the forecast period, according to Fortune Business Insights June 22 report on Intrado GlobalNewswire. While this surge in the growth rate has been triggered by the COVID-19 pandemic, it is amply clear that factories will not be the same again.

In the next few years, enterprises may rely on machines to perform more than half of all tasks, which means the operating processes that govern them will become critical. This bodes well for the process industry, but there are lingering questions to address first.

Are businesses prepared for the factory of the future that is heavily reliant on artificial intelligence/machine learning (AI/ML), process automation, and Internet of Things (IoT)? How far along are they on their digital transformation journeys?

(OT) to optimize costs, reduce time to value and improve efficiencies.

Factory of future transition: Five areas

Five focus areas can help enterprise make the transition to the factory of the future:

• Intelligent automation

• Internet of Things (IoT)

• Data analytics

• Digital twin

• Cybersecurity.

Intelligent automation: Humans, robots

Enterprises across industries, particularly in manufacturing, are heavily investing in automation. Since the dawn of Industry 4.0, business leaders have turned to emergent technologies such as AI/ML and robotic process automation (RPA) to build ecosystems that minimize human intervention. With intelligent automation, repetitive or predictable work can be performed faster while human resources focus on higher-order tasks such as monitoring, troubleshooting, and decision-making.

As AI/ML evolves, robots will become smarter and will soon “learn” from their tasks and responses. With the growing use of RPA on factory floors, robots can easily take over repetitive tasks in the assembly line with precision and speed. Large-scale robot use will require process evolution and intelligent, insightful decision-making. To make this happen, enterprises will need to upgrade infrastructure and ensure seamless process support and operational continuity.

Using real-time operational intelligence

What are the necessary process evolutions for future readiness? Most importantly, what are the key principles upon which to base future factories?

A good place to start is building a clear picture of the current scenario, the existing manufacturing processes and an enterprise’s near- and long-term business objectives.

Once the roadmap and strategy are clear, enterprises must work towards synergizing information technology (IT) and operational technology

IoT devices equipped with smart sensors transmit and share data in real time through high-speed, secure, and reliable networks. Data analytics that emerge from such smart, connected systems yield key operational and business intelligence, all of which can be viewed on user-friendly dashboards. Enterprise leaders can then use these insights to drive decisionmaking and achieve growth objectives.

An IoT ecosystem gives enterprises end-to-end, round-the-clock visibility into operations. This

‘A process digital twin enables people and machines to work in tandem independent of location.’

ensures safety, transparency, optimal productivity and a smooth functioning of the supply chain. Moreover, high visibility allows human resources to preempt possible issues and take proactive, corrective measures. Process efficiency soars, which results in seamless operations, reduced costs, and improved productivity.

In manufacturing units that deal with hazardous materials, chemical plants for instance, employees and systems need to follow the strictest safety protocols; failure to do so could pose significant health risks. With the use of IoT, enterprises can strengthen operating processes and deliver optimal safety and business value. IoT-enabled devices and smart sensors can be programed to trigger alerts when operations reach certain pre-determined hazard levels. The operations team can preempt and prevent disasters, protecting lives and saving recovery costs.

Data analytics: Informed decisions

Data analytics is critical to process engineering evolution. With advanced analytics, enterprises can have real-time insights into processes, meaning operational intelligence is always accessible. Advanced analytics automatically analyze data, ensure proactive monitoring and predictions, and enable process simulation and optimization.

In a hyper-connected enterprise environment, data analytics is critical for decision-makers to factor in all possibilities and prepare for any eventualities. Through advanced analytics, enterprises can optimize processes by making informed and timely decisions. This also helps integrate operations and make the best use of engineering talent.

Digital twin: Effective process models

While the digital twin has disrupted the manufacturing industry in the last few years, its application has mostly revolved around product lifecycle optimization. In its evolved state, the digital twin today has a crucial role to play in process modeling. In the Industry 4.0 spectrum, digital twin capabilities are not limited to visualization and collaboration; they now can be used to understand manufacturing operations as a whole and create a manufacturing process digital twin.

This is valuable for the process industry as it redefines processes. In the food processing industry, digital twin technology can help enterprises remodel operating processes by initially replicating physical processes in a virtual scape and making necessary adjustments to see where greater value can be generated.

When combined with AI/ML, IoT, and augmented reality/virtual reality (AR/VR), the digital twin allows enterprises to create holograms that enable collaboration between physical and virtual models. A process digital twin enables people and machines to work in tandem independent of location. This radically improves process efficiency, reduces time to value, and accelerates digital transformation.

Predictive maintenance is important area for digi-

tal twins. Digital twins increase plant reliability by proactively monitoring equipment, identifying issues, and offering vital insights to mitigate the problem areas before they can cause operational disruptions.

In the process industry, digital twins help manufacturers recognize possible irregularities in plant operations. Doing so enables preventive and predictive maintenance, which results in reduced maintenance costs and improved uptime and productivity.

Cybersecurity: Safe, confidential data

Today and in the factory of the future, cybersecurity cannot be a secondary consideration. Smart manufacturing is inherently dependent on secure and reliable digital networks. Robust cybersecurity is a foundational element of industrial communications.

A cybersecurity breach in a smart factory can have devastating consequences that can, at best, stall production, and at worst, cause losses in intellectual property (IP) and brand reputation, requiring years of recovery. Breaches of confidential or sensitive data can result in serious ramifications for regulatory compliance. As governments, enforcement bodies, and regulatory institutions emphasize the need for watertight data security, failing to comply with those requirements may result in hefty fines and long-term penalties.

As technology evolves, so do the sophistication levels of cyberattacks. A strong cybersecurity foundation that is constantly monitored and upgraded can help companies mitigate cyber threats. Process evolution is paramount for cybersecurity. By bringing in process developers with capabilities in cybersecurity modules, enterprises can benefit immensely from holistic process upgradation and integration.

Driving value, partner with experts

As enterprises progress on the digital transformation journey and work towards building factories of the future, the need for careful thought and planned processes grows. To get there, enterprises must find innovation partners who can offer the technological knowhow and engineering prowess across domains and processes. This is critical for the process industry, which tends to rely too much on technology solutions providers for digital transformation needs.

This creates a gap between technological implementation and process engineering. By forging a knowledge partnership with process specialists, enterprises can achieve composite IT and OT excellence. Specialists help make use of mature and nascent technologies and build secure, hyper-connected and automated factories that provide a competitive edge. ce

Vinay Bhanot is executive vice president (North America), L&T Technology Services. L&T Technology Services is a Control Engineering content partner. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com.

ANSWERS M

KEYWORDS: Industry 4.0, digitalization, augmented reality Learn five areas to help with transition to factory of the future, digitalization. See how intelligent automation includes humans, robots, and software empowering each other.

Examine how augmented reality and digital twins enable wider, more efficient collaboration, optimization.

CONSIDER THIS

Are Industry 4.0 and Industrial Internet of Things automation technologies increasing operational effectiveness?

ONLINE

www.controleng.com/ iiot-industrie-4-0

More

‘Smart manufacturing inherently depends on secure and reliable digital networks.’

ANSWERS

SERVO CONTROL

Eelco van der Wal, PLCopen

Motion control standard simplifies machine designs

function

Due to changing user requirements, new machine design concepts are needed: mechanic components are being replaced by mechatronic systems. To simplify the application of mechatronic systems by machine builders and system integrators and to give the users a better understanding, PLCopen and its members developed a set of standard motion control function blocks combined with a state diagram. [Mechatronic systems combine mechanical and electrical designs.]

PLCopen Motion Control: High functionality, abstraction

The PLCopen Motion Control group specified an independent library of building blocks. This provides a standard command set while hiding the underlying architecture and complexity to the user. This is called abstraction.

This structure can be used on many platforms and architectures. The application may be developed independent of control architecture or brand,

state

and the developer can decide which architecture will be used at a later stage of the development cycle. Advantages for the machine builder are, among others, lower costs for supporting different platforms and freedom to develop application software in an independent way, without destroying productivity. In addition, system maintenance is easier, and the education period is shorter.

Moving from mechanical to mechatronic machine designs

An important user group is the machine manufacturing group, with the packaging industry being the most active. The packaging industry must react quickly to changes in consumer behavior by providing alternative packaging technologies. This must be done by more flexible machines in their production lines. And to provide this flexibility, one must go beyond mechanical solutions, to mechatronic alternatives. Of course, this includes adaptable software which plays a key role.

The acceptance level of the Motion Control Function Block specification is high, and European suppliers of the packaging industry are especially progressive. Packaging machines are exported all over the world, and this means, different regions ask for different brands of controllers. Even though these controllers are used on the same machine and provide the same functionality, several different brands of controllers must be implemented for global export.

Changing consumer needs increase the need for flexible machine designs

Changing consumer needs translates into a need for more flexible manufacturing and packaging. Coffee is a simple example. We all are familiar with the vacuum-sealed pounds packs, the bricks. They have been on store shelves for ages. Supermarket shows have an enormous variety, with different tastes and different packaging technologies. The basics of coffee are not changed. The process side is

Standardized motion control

blocks combined with a

diagram from PLCopen are helping to shift mechanical machine designs to more efficient and effective mechatronic designs, helping machine builders, users.

Figure 1: Moving from mechanical to mechatronic machine designs using a control architecture instead of mechanical designs can improve machine performance and decrease machine complexity. Images courtesy: PLCopen

finalized and cannot provide much more efficiency. This means attention is focused to the presentation in the market, and so to the consumer.

Another example is knäckebröd (Swedish flatbread), and similar items, containing smaller entities within the same package to guarantee product freshness. To realize this change, the infrastructure in the production environment must be changed: a packaging function must be added.

The same production lines need to perform these and other sometimes temporary changes.

More user requirements require new machine concepts

A new generation of a packaging machine must fulfill two requirements for the user: maintenancefree machines (or at least low and predictable maintenance) and easy-to-clean for maximum hygiene. If you take these two goals for new packaging machine development, what will be the outcome?

They require the machine builder has to remove all mechanical parts that can attract dust or needs oil: Items like pullies, belts, gearboxes and mechanical cams.

In practice, this means a conventional machine (Figure 3) with 118 functional units will be reduced to 23 function units, providing an 81% reduction.

How to move to a mechatronic machine design

Moving to a more mechatronic design from a traditional mechanical design results in fewer components and it is easier to clean. A mechatronic operated system also is cleaner, more simple, more transparent, faster and cheaper. This is what the end user wants.

With a mechatronic solution, the control system and its software take essential roles. It is about the software in the control system and not the quality of the mechanics anymore. This often results in a different problem within the average machine manufacturer, on average, in business for from 50 to 100

years and family owned, with a mechanical design background. It is extremely difficult to change from an organization with a classic mechanical mindset, into one focused to software and control, with mechanics coming at a later stage.

Within PLCopen motion control this is recognized, and a tight coupling between logic and motion tasks is realized. Control software is playing an ever-increasing role in the success of the packaging machine. Machine designs contained almost no software 30 years ago. Now software represents about 50% of the total cost on a production line.

Motion control standard unites varied machine architectures

The motion control market has a variety of motion systems. All have their own proprietary technology, languages, dialects, buses, development environments and other variances. Despite the need for standardization, it was unavailable.

The machine manufacturer wants to serve a broad market with a reusable application. Normally, the machine builder supports multiple levels: highend machines, middle-end machines and low-end machines. The machine builder doesn’t want to be involved in three types of application development. Why are 10 descriptions needed to move an axis when one will do? Why do we

Figure 2: Hiding the complexity of the software architecture from the end user is called abstraction. Machine builders are using abstraction to improve mechatronic machine designs.

MMore ANSWERS

KEYWORDS: Motion control, servo control, machine builder standards

PLCopen Motion Control standards deliver high functionality, abstraction for machine design. Machine designers are moving from mechanical to mechatronic machine designs to better serve customers.

PLCopen motion control standards can unite varied machine architectures.

CONSIDER THIS

Are your machine designs including motion control standards to reduce machine complexity and maintenance? ONLINE www.PLCopen.org

www.controleng.com/ discrete-manufacturing/ cnc-motion-control

‘Standard benefits: A conventional machine with 118 functional units will be reduced to 23 function units, 81% reduction.

SERVO CONTROL

have to know which motor, control or encoder is already used in an application phase?

Address such a user on a different level, where all the system aspects are implemented in the motion control functionalities, and, as such, hardware independent. PLCopen Motion Control standards do this.

with other, user-defined blocks, and can be added to the company own library. This registration function can be used company wide, and the source is usable on different platforms. This saves time and money in the next machine.

Motion control standards: Supply chain market acceptance

PLCopen Motion Control standards provides a solution to a supply chain challenged. The supply chain consists of independent software suppliers, control hardware suppliers, the machine manufacturers and their end-user customers.

Software suppliers are content with using motion control standards, which makes it easier for software suppliers to talk to their (potential) users – the control suppliers. They only need to implement the motion control standard once, with only small changes regarding the underlying architecture.

PLCopen motion control suite of specifications

The first part of the PLCopen motion control specification includes motion functionality for single axis and multiple axes, several administrative tasks and a state diagram. The latter is for control and safety aspects: Not every command can be issued to a machine at all times; one has to go through a certain routine.

Solution independence is shown in testing a newly-connected axis. Whatever system is used, the user only needs a few steps to rotate the axis: turn the power on, start the home procedure, and finally give the axis a move command like “moveabsolute.” With these three simple steps, the axis has to move.

One does not want to know what network is behind the interface. That is something the supplier has to do. The standard supplies the buildings blocks called in a small program. Compile the code, download it and play it. If the axis doesn’t turn, the supplier has a problem, not the user.

PLCopen has defined a suite of motion control specifications. Part 1 – Basics includes the original extensions as defined in Part 2. Part 3 - User Guidelines, Part 4 – Interpolation (read: robotics) and Part 5 covers homing extensions.

Part 3 - User Guidelines shows how the user can create a set of building blocks based on the IEC standard and the PLCopen Motion Control function blocks. These blocks can be reused across projects and platforms.

For example, in part 2 a registration function is defined, without giving the used input. Sensor inputs may be from an unknown location (directly or networked) and/or the sensor needs to be compensated. This functionality consists of standard blocks, in which the registration function is defined

The hardware suppliers with new systems also see this as an important step forward: They do not have to develop their own specifications anymore. The motion suppliers with a longer existence were a little skeptical to accept the motion control standard because they were afraid their possibilities for differentiation would be restricted.

That fear is unfounded. There are different networks, control systems, operating systems, installation and maintenance tools, ranges of drives, motors and encoders. Diversification is applicable. An absolute movement remains an absolute movement in any environment. It’s best not to change that. Diversification is possible with the supplied building blocks, the software suite of tools, the range of servos, encoders, the tuning, and other design elements. Motion suppliers are willing to integrate their existing platforms into one environment while merging the know-how of their different motion control groups to increase synergy. The motion control standard offers a potential way out of a tangle of different implementations.

The next link in the chain is the machine builder. With some, there’s a clear technology break with the past. They are working with knowledge centers that develop mechatronic solutions. This trend resulted in mergers and acquisitions, creating bigger operations to enlarge and broaden the market by offering a new generation of machinery.

At the end of the chain are end users that buy and use the machines. They want flexibility and less downtime: faster, better and cheaper. PLCopen motion control standards support this. ce

Eelco van der Wal is managing director, PLCopen, a CFE Media content partner. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com.

Figure 3: Moving to a mechatronic machine design reduces machine parts by 81% in this example, which strengthens machine design by lowering complexity and decreasing maintenance.

Mark T. Hoske, Control Engineering

Exploring industrial wireless best practices: More answers

Learn more on industrial wireless, including wireless sensors, wireless reliability and wireless technology selection.

More industrial wireless best practices were provided by speakers from a Control Engineering webcast, “Exploring industrial wireless best practices.” Laurie Cavanaugh, business development manager, E Technologies, and Dean Fransen, Applied Intelligence, Wood, answered more industrial wireless audience questions below that were submitted but not answered in the one-hour July 8 webcast. Answers below include information on wireless sensors, wireless reliability and wireless technology selection.

Question: If wireless is the industrial communication choice, how do you help clients decide among technologies? What are criteria used?

Cavanaugh: The very first thing is to determine what problem you’re trying to solve. And what is the perception that wireless will be the answer? Answer will definitely include these criteria: Range, speed/performance, reliability, cybersecurity, cost to implement, cost to support and maintain, compatibility with existing systems, lifecycle?

Fransen: Additional criteria to ask yourself, what am I using wireless for? Data collection? Streaming? Discrete data? Location/mobile? Time sensitivity/latency. The answers to these questions will help provide some answers.

Q: Are wireless communications more likely to require updates in hardware or protocols than wired industrial communications?

Cavanaugh: Wired devices in a control infrastructure have always communicated across multiple firmware levels, so updates are not required, and having the ability to put in a new controller and talk to a 20-year-old controller on the same wired network is doable. This was driven by certain industries that required validated systems so applying firmware updates, SCADA or other application updates, and even adding a wireless option requires

significant planning and is expensive to modify after the initial installation due to the need to revalidate those systems.

Fransen: This depends on the wireless infrastructure. For example, an Internet of Thing (IoT) solution using 2G cellular may be impacted by carriers migrating to 4G/5G only.

Q: Is the wireless lifecycle generally longer or shorter than industrial-wired applications?

Cavanaugh: Wired communication, when installed well and with environmental factors taken into consideration, can be stable, reliable and last a long time – and even provides a path for replacement of equipment on either end without changing wireless infrastructure. It is easier to secure. Wired does involve multiple players for implementation

Industrial Internet of Things (IIoT) sensors and wireless mesh network can notify maintenance there is a problem. Courtesy: Control Engineering webcast on “Exploring industrial wireless best practices.”

Industrial Internet of (IIoT) and wireless mesh network

INDUSTRIAL WIRELESS

and maintenance – a direct correlation with the harshness or complexity of the environment.

Q: Is wireless reliability a concern compared to wired communications?

Cavanaugh: Wireless reliability is the key factor; that’s why you have to understand the application. There are also issues with interference, ensuring you’re on the right license bandwidth, etc. There are have been advancements to reduce environmental impact to strength and reliability, but it’s still a consideration during design and planning.

Q: Are retrofits more often from wired to wireless or older wireless to newer wireless?

Cavanaugh: From what I see, there is not so much a replacement as an augmentation or adaptation. If new equipment has wireless sensors, but also a wired controller, there will be an opportunity for creating a hybrid wireless and wired communication and information sharing network. Fortunately, the ability to use an existing Wi-Fi network, add an Edge Industrial Internet of Things (IIoT) device to collect wireless sensor data, wire in the new controller to an existing control network, and add a switch into the new panel to connect to the network allows for that evolution into the adaptation into a hybrid wireless architecture. It’s an evolution, not a revolution.

Q: Does a customer ever start with one wireless technology in mind, then change because the application needs something else?

Cavanaugh: This is absolutely a real possibility, and for that reason, we start with a pilot project to prove what is unknown and can’t be determined during a design phase. Design only gets you so far. And everyone may think they’re solving the root cause problem at first, but the pilot project should flush out the real root cause.

Q: Does industrial wireless advice differ from a couple years ago?

Cavanaugh: It is critical to evaluate wireless within the organization to determine whether (a) wireless has or will be part of a long-term information exchange direction for the overall organization or (b) is more of an opportunistic and case-based solution consideration. If it is (a) then I’d propose a corporate wireless strategy needs to be developed and maintained as part of the overall information technology / operational technology (IT/OT) Strategy. If (b) then having an identified “Task Force” as part of the IT/OT group would be sufficient to plug into the discussion on how/where wireless would be

used as part of a specific project initiative.

Q: Are there industries that should be using more industrial wireless, but aren’t? Why?

Cavanaugh: The process industries: Life sciences, food and beverage, and consumer packaged goods. Due to their heavy reliability on equipment, they can really start to build analytics based on the higher volume of real-time data.

Q: What’s next for industrial wireless?

Cavanaugh: The evolution because of the volume of data collected would be closed-loop decision making to correct or adjust equipment without operator intervention. In addition, as less operator and worker involvement drives using machine learning and AI models, the integrity of that machine learning would be driven by models for compliance safety and quality. Machines need calibration, not motivation.

Fransen: With greater access to broadband, industrial wireless will go beyond traditional controls and data collection. Add connected operators and maintenance with augmented reality (AR) to support manufacturing processes. Think about real-time access to data for trouble shooting, drawings, visualization of assembly processes.

Q: How do you recommend we advance our industrial wireless maturity level?

Cavanaugh: Understand your organization’s “real” maturity level. Take some of the learnings here to do a little more self-education so that you can ask deeper questions in the organization and identify where wireless may be in use. Knowing what “smart questions” to ask will help to quickly determine opportunities to advance using wireless solutions. Depending on what you learn, you may reevaluate where you are on the maturity spectrum. Once you’ve assessed your current state, and learned about what is possible and how to help the organization operationally and financially, you’ll be in a better position to propose use cases and determine if there is traction to evolve.

Q: Any industrial wireless lifecycle advice?

Cavanaugh: I think the advice would be that wireless lifecycle or end of life announcements aren’t necessarily as scary as they may have been several years back, because there are technologies being developed to bridge that gap and provide a middleware translation. There are solutions out there to bridge that gap so that you can put together

Continued on page 44

‘

With greater broadband access, industrial wireless will go beyond data and controls.

Augmented reality will support manufacturing.’

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More ANSWERS

KEYWORDS: Industrial wireless, system integration

Industrial wireless webcast included audience questions, with more answers here.

Wireless sensors, wireless reliability and wireless technology selection are among topics.

E Technologies and Wood provide system integration services, including industrial wireless communications.

CONSIDER THIS

Are you questioning where to add wireless industrial communications?

ONLINE

www.controleng.com/ networking-and-security/ wireless

Continued from page 42.

a more tactical strategy to address aging technology over time.

Q: Are there vulnerabilities of cellular networks vs private?

Cavanaugh: Yes. Cybersecurity or wireless security is not a given, so there has to be a well thought-out security strategy for wireless integration. That will be called out in corporate IT standards. That’s why there’s either a task force or strategy already developed. That strategy has to be maintained against current threats.

Q: Have you seen 5G and AI applications?

Cavanaugh: The adaptation of AI into the manufacturing space has been slow. I’ve seen it in other distributed industries like water/ wastewater, where there are multiple locations.

Q: What about wireless cybersecurity?

Fransen: How will your solution manage protecting access to the network? Can you

MOVE SECURELY INTO THE CLOUD

FIELD TO CLOUD CONNECTION

restrict access once on the network? Is the data moving across the network encrypted? Hiding the service set identifier (SSID) of the wireless network are a few considerations.

Q: Can you discuss virtual private networks (VPNs) over carrier-based networks?

Fransen: Wireless connected devices using VPN for connectivity to corporate domain is commonplace for employees using laptops and tablets. A similar strategy can be used to IoT devices if direct connection to corporate networks is required.

Q: What are pros/cons of IEEE 802.11 Wi-Fi grid vs. Zigbee mesh network?

Fransen: Zigbee is a short range, small data, low power, mesh network. Each node can connect to the network directly or via another node (passthrough). This helps extend range and adds some reliability as nodes have multiple paths to connect to the network. Wi-Fi has longer range, large amounts of data, much higher power consumption. ce

Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media, mhoske@cfemedia.com.

• IIoT-ready with Sparkplug, native MQTT and TLS encryption

• Built-in VPN and Firewall for increased network security

• Run Docker Containers in parallel with PLC logic

• Interface with existing controls via onboard fieldbus gateways

www.wago.us/IIoT

ANSWERS

Paul Avery, Yaskawa America Inc.

Benefits of auto-tuning VFDs

Variable frequency drives (VFDs) make applications all over the world work better, at higher efficiency and make the equipment easier to interact with via keyboard displays. Manufacturers of these devices recommend users perform an auto-tune.

An auto-tune helps the VFD control the motor with specific motor settings. Just like the automotive companies not knowing where to put the adjustable seats in a new car, the VFD manufacturer can’t guess what the best default settings for motor information. As a result, they default to an industry standard.

For example, the manufacturer of a 40 HP 480 V drive might default its motor full load amp setting per NEC table 430.250 and set it at 52 A from the factory. That would probably not match the new premium efficiency motor. Setting the amps correctly is the start to getting proper performance. Performing an auto-tune is easy, so let’s discuss the what needs to be done and why, when auto-tuning VFDs.

VFDs are not like servos

There are other auto-tuning functions. As the name auto-tune implies, any operation that calculates and adjusts things automatically at the user’s behest can be called an auto-tune function. With servo motors and amplifiers (close cousins of the VFD and induction motor), the auto-tuning function will probably have more to do with tuning the servo pair to their loads. The tuning will help adjust gains for positioning and speed loops. The VFD auto-tuning asks the load is detached from the motor when the auto-tune is performed.

The reason for the difference is servo motors and their amplifiers are always bought together from one manufacturer. A simple motor code is all the amplifier needs to know everything about the connected motor. Conversely, the VFD and motor are only sometimes manufactured by a com-

mon company. It is more the norm that brand A motor will probably be used with brand B VFD. Because of this unfamiliarity between the motor and the VFD that auto-tuning becomes the bridge by which good motor information can be passed to the drive.

Getting value from auto-tuning: Benefits

Any time spent improving a VFD’s performance better be worth the time invested. If done correctly, a properly autotuned VFD will be more efficient (lower current for the same torque) and better performance (more linear and stable operation).

By giving the VFD the actual electrical specifications from the motor nameplate, the VFD will not have to assume generic values and produce excess motor flux and possibly even saturate the motor’s magnetic field, which won’t produce more motor torque but probably will produce more motor losses (heat). The flipside of the equation is how much time does it take to perform an auto-tune?

An auto-tune helps a variable frequency drive (VFD) control the motor with specific motor settings, and there are many ways to get the best results for a specific setting and situation. See five auto-tuning tips.

Figure 1: An auto-tune helps the VFD control the motor with specific motor settings. Images and graphics courtesy: Yaskawa

Figure 2: Auto-tune implies any operation that calculates and adjusts things automatically at the user’s behest.

ANSWERS

INSIDE PROCESS: AUTO-TUNING VFDS

makers will allow the user to view a list of modified parameters so it can be simple to do a before and after check of the list to see what was entered and what was measured or calculated. Items that are typically adjusted include:

• Line-to-line resistance

• Motor rated current

• Motor no-load current

• Motor rated slip

If there’s a good picture of the motor’s specs, say from the motor nameplate, it will probably take about 90 seconds to enter the information and an additional minute to run the auto-tuning.

What gets changed through auto-tuning

Noteverymanufacturer does auto-tuning the same, but there are common adjustments they all make. It’s a mistake to assume the VFD is does all the work. The person performing the auto-tune routine is actively involved. When the auto-tune function is initiated on the keypad, the drive user needs to enter typical motor nameplate information. There isn’t really a need to measure or calculate the full-load amps if the user can just enter it. Some specs like slip frequency and leakage inductance are only alluded to on the nameplate and are best calculated by the drive.

Once the user enters the relevant motor information, the drive prompts the user to start the autotuning process during which the drive runs and tests the motor to calculate motor specifications not readily found on the nameplate.

After the auto-tune is completed, most VFD

• Energy savings coefficient

• Leakage inductance

• Saturation compensation

• Motor iron loss

• Motor-rated power.

Some of the measured values are used to populate a single-phase induction motor circuit model as seen in Figure 3. All three phases should be the same.

For instance, by applying a dc voltage to the stator and measuring the created current with dc current transformers (DCCTs), the drive calculates the line-to-line resistance, which would be RS in the model. The rest of the model can be calculated using other techniques and measurements and then extrapolated into three phases. This can help the drive better anticipate and compensate for changing loads on the motor and lead to more efficient regulation of motor operation.

What to do when auto-tuning goes wrong

As with any VFD and motor operation, there can be pitfalls that can trip up the auto-tuning. Manufacturers have a separate list of faults that can occur during an auto-tuning routine. The most typical error happens before the auto-tune begins. Any values input during the auto-tune are checked against the values allowed for the size of drive being auto-tuned and against each other.

If the full-load amps are 100 A, but the entered motor size is 40 HP, the drive will throw a fault to stop the routine. Even if the horsepower and FLA are reasonable, but exceed the rating of the drive, the drive will stop the auto-tune and display an error code regarding a data entry error.

Because a VFD’s auto-tuning routine is to probe the motor and not the load, most auto-tunes that require rotating the motor to make measurements also require the motor and load are discon-

Figure 3: Some of the measured values are used to populate a singlephase induction motor circuit model.

Figure 4: By applying a dc voltage to the stator and measuring the created current with dc current transformers (DCCTs), the drive calculates the lineto-line resistance.

Figure 5: Any values input during the auto-tune are checked against the values allowed for the size of drive being auto-tuned and against each other.

nected during the auto-tune. The VFD can tell by the amps drawn during rotation whether the load has been detached and may fault with a load fault rather than complete and accept the auto-tuning adjustments.

Types of auto-tunes for VFDs

The most effective version of an auto-tuning routine for VFDs and motors requires the motor shaft to be rotated while unloaded. There just isn’t any replacement for actual measurements that can be made while the motor is turning its own shaft. However, not all VFD and motor applications allow for easy uncoupling. Using sophisticated calculations, some of the motor model information can be estimated using an auto-tune method that does not require motor shaft rotation.

These non-rotational auto-tunes sometimes are referred to a stationary auto-tuning. Some auto-tunes are very basic and require little information to be entered and take only a few seconds. For the most part, the auto-tune will just measure the resistance that is inherent in the windings of the stator and the motor cable.

This goes back to the line-to-line resistance. The advantage of such a simple auto-tune is the VFD can then compensate for the reduced magnetic field strength due to voltage loss.

There also are auto-tuning routines specifically for permanent magnet (PM) motors in many of the same VFDs. Some of what the PM

auto-tuning routines do is common with what is done with induction motors. However, even more specific information necessary for a proper auto-tune of a PM motor and wider variety of characteristics are measured, as well.

Five VFD auto-tuning tips

Most VFD auto-tuning is straightforward and doesn’t require tremendous expertise. However, there are some things that may improve VFD auto-tuning.

1. Some motor characteristics – specifically, resistances – will change as the temperature of the copper windings increases.

Since the motor will be warm to hot during normal operations, the auto-tune should reflect that state. The tip is either run the auto-tune multiple times or let the motor run for a while, even unloaded, before performing your rotational auto-tune.

2. Because it is simpler to do a stationary autotune, it is tempting to settle for the stationary autotune. While convenient, it’s a mistake. Always insist on the uncoupled rotational auto-tune.

3. The auto-tune often can be run before the

Figure 6: With drive tools software baselines, they help with seeing any differences in performance and can be a benchmark for future comparisons.

‘Do not settle for the simpler, stationary auto-tune. It is a mistake. Always insist on the uncoupled rotational auto-tune.’

INSIDE PROCESS: AUTO-TUNING VFDS ANSWERS

KEYWORDS: variable frequency drives, VFDs

Auto-turning is a good best practice when it comes to getting the most from variable frequency drives (VFDs).

A properly auto-tuned VFD will be more efficient (lower current for the same torque) and better performance (more linear and stable operation).

There are many auto-tune types for VFDs for specific applications.

ONLINE

www.controleng.com/ discrete-manufacturing/ motors-drives/

CONSIDER THIS

What challenges do you face with auto-tuning VFDs?

application is fully assembled. Sometimes, it is easier to do the full rotational auto-tune when the motor is only 20 ft apart and have a relatively short motor cable. Later when the application is fully assembled and the motor is 75 ft away from the drive and already coupled to the load, a simple line-to-line resistance can be run. This non-rotational resistance tune will not affect the motor measurements but will re-test and update the increased resistance due to a longer motor cable. Viewing the modified VFD settings can confirm the new resistance measurement.

4. It also may be helpful to perform pre-tune and post-tune measurements. Try using the VFD’s built-in monitoring displays to complete a table with preand post-monitor values.

If the user is successfully auto-tuning from factory default settings, all the VFD’s values in the post-tune will be lower than the pre-tune, with the exception of the dc bus voltage, which will mostly stay constant at a steady state.

5. Another way to compare pre- and post-tun-

ing performance is through free trending software offered by many manufacturers with drive tools software. These baselines help with seeing any differences in performance and can be a benchmark for future comparisons.

Auto-tuning is worth the time and money

Auto-tuning is a good best practice when it comes to getting the most from VFDs. The investment is a few minutes of time usually and the differences can be well worth the effort. The better and more accurate the motor model the VFD has, the better and more efficient the motor control will be. ce

Paul Avery, senior product training engineer, Yaskawa America Inc. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

‘It may help to perform pre-tune and post-tune measurements using built-in VFD monitoring displays.’

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Electronic circuit breaker system

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Input #203 at www.controleng.com/information

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The VT971 is a rugged conduction cooled module which follows the VITA specification for environmental (see ordering options). The module accepts 32 high-speed SERDES to the field programmable gate array (FPGA), which is supported by two 64-bit wide banks for DDR4 memory for the total of 16GB of memory. The FPGA is integrated with a Layer 3 managed Gbe/10GbE Ethernet switch, which provides 26 egress port via front of the module. The module supports 24 GbE through RJ-45 (10/100/1000Base-T) and dual 10GbE via SFP+.

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Input #207 at www.controleng.com/information

MEDIA SHOWCASE F OR E NGINEERS

BACK TO BASICS: INDUSTRIAL CONTROL SYSTEMS INNOVATIONS

Bridget Fitzpatrick, Wood

Adaptable industrial control systems

Industrial control system (ICS) solutions need a new architecture and philosophy is required to be more adaptable to changing environments. Six methods are highlighted.

Dynamic and intuitive machines are transforming the way businesses function in every industry. Industrial control solutions have traditionally not been known for easy adaptation or inexpensive changes. Part of this has been related to the legacy structure of layered control technology. The existing technology monolith has dramatically improved overall performance but has also added a complexity that needs to be managed. To flexibly adapt, a new architecture and philosophy is required.

Control systems have played a crucial role in manufacturing, providing advancements in mechanical and or pneumatic systems. Now, Industry 4.0’s digitalization relies on intelligent, connected systems and has a potential to generate $3.7 trillion over the next decade. The companies that embrace and actively manage digitalization will succeed and find ways to add value to the enterprise. New technology is not the solution. The key is to find the transformations that add value and then leverage technology intelligently.

Six ways to turn digital transformation into business value

The inability to adapt to changing conditions, difficulty in managing multiple optimization goals and inconsistency are some limitations of existing control systems. Translate digital transformation into significant business value in six ways.

1. Using control templates: We identify the control strategies to meet client functional requirements and leverage these as flexible templates to right size the engineering effort. We worked, for example, with Suncor on well pad development using modular type package (MTP) concept resulting in an estimated cost savings of more than 50%. This project also was a winner of two Suncor President’s Operational Excellence awards.

2. Reinventing control algorithms: We are systems integrators but, more importantly, process control experts. We are active members of varied industry groups. There is a strong need for open systems with re-engineered solutions and have established a function block library, leveraging decades of experience over a wide range of vertical markets.

3. Using real-time cost control: Nothing stimulates highly effective decision making quite like

an informed workforce. Integrating real-time variable costs into operations screens results in a step change in cost performance and an understanding of cost drivers. In places where the costs can be highly variable like power and natural gas, this can be very valuable.

4. Using the digital twin: Companies that leverage and actively maintain engineering design data use data in more innovative ways. They can provide easy access for ongoing learning and integrate it into optimization and simulation models to apply and grow intelligence.

5. Using machine learning (ML) and artificial intelligence (AI): Machine learning and artificial intelligence (AI) can be applied effectively to transform data into actionable intelligence and into autonomous operations. Leveraging AI to support intelligent control systems is key to realizing the opportunity that Industry 4.0 brings. A recent study confirms 50% of companies that embrace AI over the next 5 to 7 years may double their cash flow. And manufacturers that implement intelligent systems achieve 17% to 20% productivity gains.

6. Using operations as process managers: The operations team is shifting to manage the process, beyond operating the process. When a product is manufactured in multiple locations, sharing technical and business data can optimize assets globally.

Ecosystems, faster advances

An ecosystem of operating companies, technology providers and service companies need to identify and execute breakthrough shifts in how the process and manufacturing industries are managed. This thinking is underway and gaining traction. For this new industrial revolution, only reinvention will suffice; these are not simple incremental changes. ce

Bridget Fitzpatrick is the global technical lead for process automation at Wood, a CFE Media content partner. This article originally appeared on Wood’s website. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

More INNOVATIONS M

KEYWORDS: Industry 4.0, industrial control system

A new architecture and philosophy is required for industrial control solutions in the Industry 4.0 age.

Reinvention is needed because of Industry 4.0’s potential to change how information is processed and gathered. Using digital twins, machine learning (ML) and artificial intelligence (AI) can help leverage digital transformation.

ONLINE

www.controleng.com/iiot-industrie-4-0

CONSIDER THIS

How quickly is your company changing industrial controls in the Industry 4.0 era? Is it fast enough?

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