Automation World September 2020

SEPTEMBER 2020 / www.automationworld.com

28 MAKING SENSE OF THE DATA ANALYTICS MARKET 22 08 33 10 14 18

Paying for Performance How COVID-19 is Impacting Automation Decisions Data Analysis Helps Glassmaker See Through Its Processes The Pandemic is Shaping the Future Supply Chain Automating Additive Manufacturing More Disinfecting Robots Come to Market

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2 CONTENTS

AW SEPTEMBER 2020

SEPTEMBER 2020 | VOLUME 18 | NUMBER 9

22

Paying for Performance

28

Making Sense of the Industrial Analytics Market

The new automation model focuses on services that reduce a manufacturer’s financial risks by shifting the responsibility of asset acquisition and management to the OEM or technology supplier via performance-based service level agreements or cloud-based subscription offerings.

As organizations continue to see the value in industrial analytics, making sense of the sheer amount of data produced can be a difficult task. Finding the right product and developing a proper workflow is important to get long-term use out of the system.

Analysis Helps Glassmaker See Through Its Processes 33 Data By using OSIsoft’s PI to monitor thousands of data points across a high-intensity float glass production system that runs 24/7, AGC has been able to reduce downtime and improve operations.

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4 CONTENTS

AW SEPTEMBER 2020

EDITORIAL

ONLINE 6

Exclusive content from AutomationWorld.com: videos, podcasts, webinars, and more

INDUSTRY DIRECTIONS 8

How COVID-19 is Impacting Automation Decisions

BATCH OF IDEAS 10

The Pandemic is Shaping the Future Supply Chain

NEW TECHNOLOGY SPOTLIGHT 12 Integrated Motion Technologies

PERSPECTIVES 14

David Greenfield Director of Content/Editor-in-Chief dgreenfield@automationworld.com / 678 662 3322 Luis Rodriguez Managing Editor lrodriguez@automationworld.com / 312 205 7910 Stephanie Neil Senior Editor sneil@automationworld.com / 781 378 1652 Aaron Hand Editor at Large ahand@automationworld.com / 312 222 1010 x1180 Jim Chrzan VP/Content and Brand Strategy jchrzan@automationworld.com / 312 222 1010 x1470 Kim Overstreet Content Strategist koverstreet@pmmimediagroup.com James R. Koelsch, David Miller, Lauren Paul, Jeanne Schweder and Beth Stackpole Contributing Writers

ART & PRODUCTION

Automating Additive Manufacturing Workers Wanted? Contact the Robot Employment Agency

Filippo Riello Art Director friello@pmmimediagroup.com / 312 222 1010 x1200 George Shurtleff Ad Services & Production Manager gshurtleff@pmmimediagroup.com / 312 222 1010 x1170

NEWS 18

ADVERTISING

More Disinfecting Robots Come to Market Belden and Honeywell Expand Cybersecurity Protections PMMI News

INDUSTRY-SUPPLIED CONTENT 35

Death by a Thousand Spreadsheets: The Simple Yet Insidious Nature of Time Series Data

Kurt Belisle Publisher kbelisle@pmmimediagroup.com / 815 549 1034 West Coast Jim Powers Regional Manager jpowers@automationworld.com / 312 925 7793 Midwest, Southwest and East Coast

AUDIENCE & DIGITAL

NEW PRODUCTS 38

David Newcorn Senior Vice President, Digital & Data Elizabeth Kachoris Senior Director, Digital & Data Kelly Greeby Senior Director, Client Success & Media Operations Jen Krepelka Director, Websites & Digital Design Strategy

HMI Software Platform for OEMs and Discrete Part Manufacturers T1 Industrial Connector for Industrial Single Pair Ethernet SCARA Robots And more...

PMMI MEDIA GROUP

Kurt Belisle Publisher kbelisle@pmmimediagroup.com / 815 549 1034 Jake Brock Client Success Manager jbrock@pmmimediagroup.com / 312 222 1010 x1320 Sue DaMario Director of Marketing damario@pmmimediagroup.com / 312 222 1010 x1710 Amber Miller Marketing Manager amiller@pmmimediagroup.com / 312 222 1010 x1130 Sarah Loeffler Director, Media Innovation sloeffler@pmmimediagroup.com / 312 205 7925 Janet Fabiano Financial Services Manager jfabiano@pmmimediagroup.com / 312 222 1010 x1330

FINANCE VIEW 40

Industry 4.0 Capabilities Come to Enterprise Finance By Larry White

IT VIEW 41

Securing Your On-Premise or Cloud Industry 4.0 Systems By Larry Grate, GICSP

ENTERPRISE VIEW 42

The Prescription for Transformation is Clear: Better Analytics By Diane Sacra

KEY INSIGHTS 44

All Automation World editorial is copyrighted by PMMI Media Group, Inc. including printed or electronic reproduction.

Magazine and Web site editorial may not be reproduced in any form without the written permission of the publisher.

Automation World | PMMI Media Group 401 N. Michigan Avenue, Suite 300, Chicago, IL 60611 Phone: 312 222 1010 | Fax: 312 222 1310 www.automationworld.com PMMI The Association for Packaging and Processing Technologies 12930 Worldgate Dr., Suite 200, Herndon VA, 20170 Phone: 571 612 3200 • Fax: 703 243 8556 www.pmmi.org

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6 ONLINE

AW SEPTEMBER 2020

LEADERSHIP IN AUTOMATION Vote Now for Your Favorite Suppliers

If you have a supplier that goes above and beyond, here’s your opportunity to say thank you.

Recognize the companies that have demonstrated excellence in automation technology or services.

Voting is now open for 2021 Honorees. We’ll acknowledge the top companies in our annual Leadership in Automation feature article published in the January issue of Automation World. And don’t forget to enter your name for a drawing to receive a $200 American Express gift card.

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AUTOMATION WORLD TV Automation World’s YouTube site offers relevant videos on the latest industrial automation insights, trends, and news. Check out our videos and subscribe to keep up with the latest technology and application developments.

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PODCAST SERIES How Much Cybersecurity Do I Really Need?

In this episode, we connect with Brandon Bohle of Interstates to discuss control system cybersecurity in light of increasing remote connections use in response to COVID-19, as well as general cybersecurity best practices moving forward.

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ON-DEMAND WEBINARS OT Cybersecurity Secrets: Tips and Tricks for Little or No Cost

In today’s constantly connected world, most would agree the need for cybersecurity is real and growing.

In this webinar, you’ll learn how cybersecurity is about more than technology and why information and operation technology collaboration is the keystone of a successful strategy. You’ll leave the webinar with an understanding of how to prioritize next steps and take actions to improve the security of your operation.

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Struggling to Achieve Production Agility and Right First Time Quality?

In this webinar, Rajant, Velodyne, and Mov.ai discuss each of their technologies in detail and show how Rajant solves WiFi coverage issues in warehouses by enabling M2M communications, Velodyne provides light detection and ranging to improve warehouse robotics localization and worker safety challenges, and Mov.AI provides robot operating system and fleet management of any robot, in particular the TUGBOT, designed to automate the movement of industrial carts.

ON-DEMAND WEBINARS • Balancing Employee Health and Safety With Business Continuity During a Pandemic • Industry 4.0: Thriving Through Transformation • The Importance of Material Tracing • Protect Your Staff, Protect Your Clients • The Value of a Peer Group

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8 EDITORIAL

AW SEPTEMBER 2020

INDUSTRY DIRECTIONS

How COVID-19 is Impacting Automation Decisions

By David Greenfield

dgreenfield@automatioworld.com Editor-In-Chief/ Director of Content of AutomationWorld

T

he COVID-19 pandemic has changed virtually everything about our business and personal lives this year, and automation is certainly no exception. To better understand how COVID-19 is affecting industrial companies and their decisions around automation, we connected with Dan Malyszko of Malikso Engineering, a system integration company, for a recent episode of the “Automation World Gets Your Questions Answered” podcast series (http://awgo.to/1090).

Like most everyone, Malisko Engineering experienced “a bit of a lull in terms of any active project work” in the first months of the pandemic, said Malyszko. “But during that time, it was interesting to see how things evolved. With traditional automation projects, we’re now seeing people thinking more about the data side. For example, as projects ramp back up, people are asking: ‘Can we add some reports to that? Because so-and-so is remote, and they’re going to want to be able to see what’s going on.’ I think we’re going to see more and more of this as people get used to this new normal.

We’re going to have to be able to provide more remote access to production and efficiency data in real time and make it a very clean, easy experience for the user.”

As automation projects slowly begin to ramp back up, Malyszko said he’s seeing more planning for 2021. Specifically, he’s seeing clients not just looking to what’s next, but

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“what’s after next?” People are increasingly talking about things they weren’t talking about before. And a lot of those have to do with things like remote monitoring,” he said.

Malyszko said the uptick in remote access interest from so many manufacturers has allowed Malisko Engineering to flex its OT (operations technology) expertise when talking to the IT (information technology) departments about bringing remote connectivity and other collaboration technologies down to the plant floor.

“What we’ve found is that this is one of those areas—securing endpoints and data— that IT is really, really good at, and they’ve been doing it for years,” said Malyszko. “So if there’s one benefit from all this that we’ve seen is that this [pandemic] is facilitating new digital conversations. Everybody talks about having a digital roadmap or a digital strategy, and this notion of remotely connecting to the plant floor is now driving that conversation.”

He also noted that every company they’re working with has some sort of a COVID-19 committee focused on figuring out how to return people safely to work. This discussion “can’t be just about behavior modification for right now. It really needs to be about how can we promote longer-term behavior modification and new ways of doing things in the plant,” Malyszko said. Following this new line of thought, we’re seeing “requests for various social distancing technologies that you might wear, like a Bluetooth device; we’re also seeing interest in ultra wideband. This has traditionally been used to track assets, but now we’re looking at it to track people within a resolution of about one foot. And we’re also dealing with an increase in interest around connecting people from corporate headquarters to the plant floor. In the past, these people would have been able to jump on a plane and help out, but now they’re having to do that remotely. That’s

driving interest in technologies like Cisco’s Remote Expert to connect people in real time using video headsets and being able to see, remotely, whatever the operator is seeing in front of them on the line.”

These factors are now driving a lot of conversations about plant Wi-Fi, according to Malyszko. Up to now, we’ve seen Wi-Fi be “kind of hit and miss in plants,” he said, but interest in all of these “new remote technologies is driving new conversations about putting in more Wi-Fi on the plant floor.

And we see that opening up a lot more doors to other, more advanced technologies, down the road, once we get past this [pandemic]. With this move toward more Wi-Fi, the notion of people walking around with iPads and going paperless, that starts to become more of a reality.”

Malyszko said he hopes this heightened interest in remote connection technologies continues to drive a bigger portion of the industry toward greater levels of digital transformation. “I hope that it’s a longer-term response to getting IT departments and corporate more involved [in plant technologies].

Once we prove what can be done with remote connectivity to keep people connected, what about connecting all those assets and really start looking at the Industrial Internet of Things. Once we have all this connectivity in place, manufacturers and processors will more easily be able to see that we can do other things, like grabbing data from all of the plants and aggregating it so that they can have better KPIs (key performance indicators).”

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10 EDITORIAL

AW SEPTEMBER 2020

BATCH OF IDEAS

The Pandemic is Shaping the Future Supply Chain

By Stephanie Neil

sneil@automatioworld.com Senior Editor of AutomationWorld

W

e’ve learned a lot during the COVID-19 pandemic, but one ubiquitous underlying understanding that has resulted from this firsthand experience is that the world can be impacted in a very short period of time. And we—as individuals, as businesses, and as a culture—have to be agile and adept enough to react quickly.

The pandemic is a crisis that caused us to step back and rethink the way we interact and work as it affects public health and the economy. But it also serves as a great reminder that it is during times of disruption that some of the greatest innovations happen. For example, the electric razor, the car radio, and the very important chocolate chip cookie were all developed in the 1930s during the Great Depression. During World War II, the world was introduced to radar technology, penicillin, jet engines, and more.

In 2020, a decade that is dedicated to digitization, it is the supply chain that will be an area of innovation as a result of COVID19 disruptions. That was the message that came out of a virtual symposium sponsored

by Siemens Financial Services that focused on adapting the supply chain in an age of uncertainty. The speakers addressed how businesses can cope with unplanned global risks that threaten the future of societies, and how technology can help as we rethink our supply chain strategies.

According to Bruce McIndoe, president of

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McIndoe Risk Advisory, there are five megatrends that will shape the future of business and the world: globalization, demographics, climate change, resource scarcity, and technology innovation. Each are interlinked and influence global supply chains as the world supports a growing global population.

McIndoe briefly described these trends: Globalization: As a result of an uncoupling movement between the U.S. and China and vulnerabilities in the global supply chain that the pandemic exposed, there will be a shift to deglobalization via onshoring or nearshoring.

Demographics: As we add two billion more people in the next 30 years, we’ll need more water, food, and housing to support them.

It’s estimated that 80% of these new citizens will live in cities and by 2050 we’ll see cities with 50-to-100 million people. Based on urban density, growth of the middle class, and climate change, we’ll need to build an excess of one billion more housing units. “In the next 30 years, we essentially will need to rebuild the entire global housing stock since the beginning of mankind. That is a huge demand,” McIndoe said.

Climate change: This can ultimately become the weak link in the supply chain.

The greater frequency and severity of climate hazards create more disruptions in the global supply chain by interrupting production, hampering transportation, raising prices, and ultimately hurting corporate profits.

Resource scarcity: Here, we are the issue— humans are massive consumers of natural resources, and by 2050 we will consume 140 billion tons of minerals, ore, fossil fuels, and biomass per year. That’s three times the current consumption rate. We must decouple economic growth from massive resource use, McIndoe said. In addition, water and food are life or death resources for all of us. Lack of access to water has been catalyst to war and will be a major driver for human migration—which creates friction and unrest. Lack

of access to food, too, can drive people to be aggressive which can evolve into civil unrest.

Technology innovations: The good news is, most of the solutions for long term human sustainability rely on technology innovations.

Most of the technology we need for water, advanced farming, power generation, materials advancement, and modular recyclable materials, exist now or are in development.

And so there’s hope for the future, McIndoe said. “There’s no questions humankind will become more reliant on technology to sustain our population growth and raise the standard of living globally. And it is technology like robotics, artificial intelligence, and additive manufacturing that will make onshoring and nearshoring a reality for developed countries where labor costs are high,” he said.

He also said that access to always-on, highspeed broadband will change the nature of work—that is when and where work is done—as society eventually sheds its 9-to-5 work week tethered to the office. It is the pandemic that opened our eyes to the realization that many workers can be productive from home, and home can be anywhere on the planet.

Siemens USA CEO Barbara Humpton summed up what’s happening in the world right now in one word, “antifragility,” an idea explored in a book called “Antifragile: Things That Gain From Disorder” by Nassim Nicholas Taleb. The book describes how systems can increase in capability and thrive as a result of stressors, shocks, and volatility. It is the ability to respond, recover, and reinvent to get stronger from disruption. “We can experience antifragility during a crisis,” Humpton said. “We are looking for ways we can use today’s tools in different ways for a future that is more sustainable and resilient and more productive for all of us.”

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12 EDITORIAL

AW SEPTEMBER 2020

NEW TECHNOLOGY SPOTLIGHT

Integrated Motion Technologies

By Luis Rodriguez

lrodriguez@automatioworld.com Managing Editor of AutomationWorld

I

nstallation of a new motion control device can be a demanding task following the often arduous process of choosing the product that best fits your production operations. But, with more products coming to market touting a simpler installation process, this doesn’t have to be the case.

Take, for example, the TSM14POE StepServo from Applied Motion Products, which combines motor, encoder, drive, and controller into a single integrated motor package with Power over Ethernet (PoE), allowing it to be installed in tighter locations.

Similarly, there is the Kinetix 5100 servo drive from Rockwell Automation, which bundles the drive, motor, and cable into a smaller package. And then there is the Melservo MR-J4 amplifier series from Mitsubishi Electric Automation, which offers a plug-and-play concept and multi-network interface that makes it easier for international manufacturers to install. The amplifier’s built-in positioning function also allows positioning systems to be configured without a positioning module to simplify system cost and bills of material.

Though simplified installation is an important part of deciding which product to choose, performance and efficiency remain critical factors. And these new products don’t skimp in these areas either. For example, the TSM14POE is said to offer greater torque and higher acceleration rate than

2009_E3.indd 12

conventional open-loop step motor systems, while the Kinetix 5100 offers a large power range of 50W to 2kW at 120 to 230V and 3 to 15kW at 230V. These three new automation products, by offering their capabilities in a single package, not only simplify the design of the products as whole, but ease aspects of installation while delivering high performance.

Following are more highlights of these devices: • By combining a motor, encoder, drive, and controller in a single integrated motor package, the TSM14POE StepServo is said to eliminate the need to connect motor power and feedback cables to an external motor controller. The integrated motor receives its power and Ethernet communications over a single cable for greater design modularity and installation simplicity.

The motor uses Applied Motion Products’ StepServo closed-loop stepper technology, which is the factor the company notes as providing higher torque and greater efficiency when compared to conventional, open-loop step motor systems. Other highlights of the device include its compact size and integrated control electronics that allow motor mounting almost anywhere. It also reportedly delivers better efficiency, decreased motor heating, and less audible noise than traditional, open-loop step motor systems.

• The Kinetix 5100 servo drive can run without a controller to meet a variety of application requirements. For example, the drive has multiple control modes to support a wide range of high-speed, low-power motion control applications.

It can be used with a Micro800 controller, a Logix controller or even by itself, allowing OEMs to choose how the product best functions in their applications.

Bundling the drive, motor, and cable together creates more competitive system pricing. With built-in safe torque off, users can remove motor torque without removing power from an entire machine, allowing a machine to restart faster after it has reached a safe state.

• The Melservo MR-J4 amplifier series incorporates a multi-network interface called “Servo Open Network” that works with CC-Link IE Field, Profinet, EtherCAT, and EtherNet/IP. Mitsubishi Electric Automation says this multi-network interface makes it simpler for equipment manufacturers to offer their products globally and helps make OEM support available globally. The amplifiers’ plug-and-play concept reportedly makes network protocol selection user-friendly, and a quick start guide is available for each of the networks, as are sample projects and function blocks supplemented by flexible connection options. The servo systems cover the power range from 0.05 to 22 kW and are highly compact, occupying less than 50% of the volume of comparable products. The amplifiers are also supported by a large selection of motors with high power densities, offering flexibility in design and efficiency with a minimum footprint.

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14 PERSPECTIVES AW SEPTEMBER 2020

Automating Additive Manufacturing

By David Greenfield,

Director of Content/Editor-In-Chief

A

s more companies add 3D printing/additive manufacturing technologies to their production operations, it’s not unusual for volume bottlenecks to grow. And like any piece of equipment, there are the inevitabilities of equipment downtime and failed print jobs. All of which can lead to production deadlines being missed. One way of addressing this would be to add more 3D printers, but as Scott Crump, inventor of FDM (fused deposition modeling) and founder of Stratasys says, that “would not be considered a best-practice response in traditional manufacturing operations, and it shouldn’t be the first choice in additive operations either.”

Crump adds that “additive manufacturing is likely never going to produce the volume scale of traditional manufacturing techniques like injection molding or CNC machining. However, the COVID-19 pandemic has shown Stratasys that the additive production process can benefit from more automation.”

Key to understanding how this works is to recognize the typical constituent components of additive manufacturing: • Print properties selection; • Print preparation and orientation; • Managing in-print queue; • Initiating printing; • Removing parts from the 3D printer; • Post-processing; and • Finished part retrieval.

Stratasys learned about the value additional automation can bring to 3D printing through the launch of its “COVID Coalition” earlier this year. Comprised of more than 100 organizations (including colleges and manufacturing companies) to achieve the 3D print production of thousands of face shields each week, the complexities of this dispersed production project was streamlined with the use of Stratasys’s GrabCAD Shop workflow software.

Crump says that, a year ago, without this software, “we couldn’t have done it. The complexity of the task

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Continuous Build 3D printer modules. Source: Stratasys would have overwhelmed our ability to manage the initiative.”

Using GrabCAD Shop in combination with GrabCAD Print to manage printing on each machine enabled Stratasys to “set up each organization as a 3D print shop, with an ability to assign jobs to each location,” says Crump.

“And each location has the ability to assign jobs to specific 3D printers. We’ve been able to connect orders from our CRM (customer relationship management) system with clouddistributed production capacity to know who is doing how much, where, and when things should be done.”

Based on what Stratasys learned about automating the additive manufacturing production process in the “COVID Coalition” project, the company is now taking automation of 3D

printing to the next step to further scale 3D printing at higher volumes. Using Stratasys Labs Skylab server software, accessible via a web interface, Crump says that “virtually everything gets automated and centralized from a control center, allowing an operator to monitor incoming part requests, the master queue, available printer resources, printer status, and even business analytics.”

Crump noted a key factor Stratasys discovered during these efforts to add more automation to the 3D printing is to use file analysis to auto-select default print properties. “By assessing orientation, fill styles, color and material availability, and resolution requested, the system can automatically set up the job, along with a start time, build time, and material volume,” Crump says.

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Explaining how Stratasys uses this approach, Crump says the Stratasys Labs operation linked 60 of its Continuous Build 3D printer modules.

“These systems are essentially towers of three stacked FDM 3D printers designed to continuously execute jobs one after another and run 24/7 without requiring anyone to remove finished parts or otherwise touch the machines,” says Crump. “All that’s needed is a worker to periodically harvest jobs from baskets in front of each machine.”

Crump says that automating production across these machines has enabled Stratasys to produce 20,000 face shields per month.

This production rate reflects a significant increase in utilization rates. A typical additive manufacturing service bureau, with one FTE for about every ten 3D printers, usually has an FDM utilization rate close to 70%. But the Stratasys Labs operation has been running its 60 printers at 95% utilization, with just one full-time employee.

“By using cloud-based software to automate additive manufacturing work, combined with lowcost 3D printers optimized for this software, we can ultimately achieve extraordinarily high utiliza-

Scott Crump, founder, Stratasys. no staff. This can open up new application opportunities for 3D printing in the future.”

tion rates 24/7 with limited staffing required resulting in a low cost per part and without tooling,” says Crump. “We recently 3D printed 500 visors for face shields overnight with the lights out and

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Workers Wanted? Contact the Robot Employment Agency

By Stephanie Neil, Senior Editor

R

obots are often welcome on the factory floor to do some heavy lifting or to perform high-speed pick-andplace activities on production or packaging lines. But sometimes robots get a bad rap, like when people think they’ll be replaced by these moving machines. So, when startup MusashiAI, a joint venture between SixAI based in Israel and Musashi Seimitsu of Japan (a Honda Motor Corporation affiliate), launched a robot employment agency, alarms went off. Does this mean machine operators will soon lose their jobs?

Well, yes and no. Some people in the factory may be displaced, but the goal is to give the robots the rigorous, repetitive tasks and redeploy their human counterparts to more value-added jobs.

“Our mission is to redistribute human labor, not take it away and make people redundant,” said Ran Poliakine, co-founder of MusashiAI. “The goal of the joint venture has always been to work towards our vision of Industry 4.0, where human workers do human jobs and are not trapped in manual industrial jobs.”

The robot employment agency is actually a robots-as-a-service (RaaS) business model that gives industrial manufacturers the option to source needed labor instead of investing

significant capital in purchasing the robots.

Robot labor is charged by the hour or on a task-completed-based salary.

MusashiAI’s robot employees for hire are the company’s autonomous Visual Quality Control Inspector and the autonomous Forklift Driver, which uses an artificial intelligence (AI)-enabled mobile robots fleet management system, all of which MusashiAI officially rolled out in July.

Human workers have traditionally been relegated to do visual quality control inspection of final industrial products because robots

MusashiAI autonomous Forklift Driver with an artificial intelligenceenabled mobile robots fleet management system. Source: MusashiAI

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have not been able to surpass or even match the human ability to detect and identify surface defects quickly and accurately. But MusashiAI’s autonomous robotic in-line visual quality control inspection system uses stateof-the-art image processing and a deep learning algorithm for rapid “new parts” learning.

“We believe that we are one of the first to bring to market autonomous AI robots capable of out-performing human workers in speed and accuracy in detailed visual inspection,” Poliakine said. “Most visual inspectors look at large geometric defects, our robots are capable of detecting surface level defects as small as 50 micrometers.”

In addition, the autonomous forklift holds up to a 1,500 kg load capacity and continuously self-optimizes. It navigates the warehouse or factory floor using MusashiAI’s proprietary fleet management system which employs sophisticated perception and decision-making software in combination with inexpensive industry-standard HD cameras. “Our robotic forklift driver comes with an advanced fleet management system which uses AI to predict accidents or obstacles before they happen,” Poliakine said. “These drivers are safer than human drivers and bring massive efficiencies to the factory floor at very little cost, because their hardware is not expensive at all—it’s all done by the software.”

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Smart business when you have to social distance

Aside from relieving people from performing monotonous and tedious tasks, the autonomous robots are gaining traction due to the social distancing rules resulting from the COVID-19 pandemic.

In addition to its initial commitment with advance payment of $10 million, Musashi Seimitsu is willing to expand the deployment of MusashiAI’s autonomous quality control inspectors and autonomous forklift drivers in its factories globally, subject to the company meeting certain development milestones.

MusashiAI has also secured a proof of concept (POC) for its autonomous Quality Control Inspector with one of the world's largest bearing manufacturers. In addition, MusashiAI will conduct three POCs for the autonomous Forklift Drivers and central management system with leading Israeli retail and fast-moving consumer goods groups starting in Q4 this year. These agreements will be the first times the robots are being tested outside of the Musashi Seimitsu group.

“Globally, nearly 30 million people work in grueling visual inspection jobs. Many of these people suffer chronic health condiMusashiAI’s tions from this work, autonomous such as carpal tunnel Visual Quality syndrome. No doubt a Control Inspector. large number of them Source: have been furloughed MusashiAI because many industrial settings are unsafe now due to the are designed with people in mind. The vision coronavirus. These people are not key workis that they integrate easily onto the producers, but what they do is essential,” Poliakine tion floor where there will still be some human said. “Businesses will need their final prodworkers, but release other workers from this ucts inspected, and we are offering the world particular drudgery. They are friendly looking a solution which can shield employees from and easy to deploy wherever they are needed. this deadly virus and the chronic health probOur OpEx model means clients can deploy rolems associated with their work, [as well as] bots when and where they need them, withthe major economic danger of stalling busiout extensive CapEx.” ness for much longer.”

In addition, it’s a relatively risk-free business move Poliakine noted. “These robots

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More Disinfecting Robots Come to Market

By David Greenfield

Director of Content/Editor-In-Chief Since the early stages of the COVID19 pandemic, robots have been seen as an answer to associated social distancing and workforce issues. They have also been eyed as a solution to the near-constant disinfecting processes required to keep areas as virus-free as possible. Automation World first reported on this in April 2020 in the article COVID19 Provides Use Cases for Mobile Robotics (http://awgo.to/covid19robots).

Now Fetch Robotics has announced the release of its SmartGuardUV disinfecting autonomous mobile robot, built in cooperation with Piedmont National, a supplier of packaging equipment and services, and Puro Lighting, a supplier of disinfection UV lighting. According to Fetch Robotics, the SmartGuardUV is an autonomous, broad spectrum UV disinfection robot that eliminates up to 99.9% of viruses and bacteria with UV-C, UV-B, and UV-A. It also reports on the results of the disinfection.

Designed to autonomously disinfect hightraffic areas ranging from assembly and warehouse facilities to hospital rooms, the SmartGuardUV combines Fetch Robotics’ cloud robotics platform, Puro Lighting's pulsed Xenon UV fixtures, and Piedmont National’s 4Site cloud analytics platform.

The SmartGuardUV uses mapping technology and 3D camera vision to autono-

The SmartGuardUV autonomous mobile robot at work in a warehouse facility. Source: Fetch Robotics mously direct broad-spectrum UV light from a pulsed Xenon lamp to disinfect priority areas within a facility. Puro Lighting says its pulsed Xenon UV lamp fixture requires as little as 90 seconds to disinfect a 10-ft. workstation and as little as six minutes to disinfect priority areas of a personal office.

The pulsed Xenon UV lamp technology used in SmartGuardUV has been tested by independent accredited third-party testing labs and is registered with the EPA. Piedmont National’s John Garlock says, “Legacy autonomous disinfection robotic solutions can only operate for two to two-

and-a-half hours on a single charge, whereas the pulsed xenon light engines on the SmartGuardUV—which precisely targets UV rays at high touch surfaces—can operate for 8 to 10 hours on a single charge.”

Prior to the release of the SmartGuardUV, Fetch released the Breezy One, chemical disinfection autonomous mobile robot designed for large spaces over 100,000 sq. ft. According to Fetch Robotics, the Breezy One is designed for wide area deep cleaning, while the SmartGuardUV is designed for targeted cleaning.

Belden and Honeywell Expand Cybersecurity Protections

By David Greenfield

Director of Content/Editor-In-Chief

A

s the COVID-19 pandemic accelerates the digital transformation of industry with more employees working remotely and more remote connections to equipment being deployed to reduce the

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need for in-person repairs and maintenance, the cybersecurity threat vector for industry is increasing. Amid this increase in remote connectivity, Belden and Honeywell have announced expansions to their industrial cybersecurity offerings.

In Belden’s case, the company has partnered with Forescout, a provider of technology for device visibility and control, to

advance cybersecurity for industrial organizations and critical infrastructure. Joint offerings from Belden, along with its Tripwire and Hirschmann brands, and Forescout will focus on industrial network segmentation and threat detection to maintain visibility to and protection from cyber events that threaten safety, productivity, and quality.

According to the Belden and Forescout,

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integration of the Forescout platform and Belden’s Hirschmann network infrastructure makes segmentation an immediate, viable defense against cyber incidents by allowing for rapid implementation over heterogeneous automation networks to minimize disruption and downtime. Forescout’s eyeSegment reportedly simplifies the initial creation and ongoing lifecycle management of segmentation policies at scale, while also providing simulation of enforcement before implementation to avoid disruption to mission-critical operations. Integration across Forescout, Tripwire, and Hirschmann products also enhances threat detection and response.

“Network segmentation will be imperative to meet availability requirements for real-time, next generation industrial automation networks,” said Ashish Chand, executive vice president,

The Honeywell Forge Cybersecurity platform.

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Pandemic Cancels In-Person PACK EXPO International

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fter thoughtful consultation with the PMMI Board of Directors, PMMI, The Association for Packaging and Processing Technologies, has made the difficult decision to cancel its in-person PACK EXPO International and Healthcare Packaging EXPO in Chicago this year. The PMMI Board determined that, due to the evolving COVID-19 pandemic and current state and local regulations, it was not possible to have a safe and productive event for attendees and exhibitors.

To ensure this essential industry remains connected, PMMI Media Group is using its digital marketing expertise and extensive industry knowledge to launch a brand new live, web-based event, PACK EXPO Connects 2020 on Nov. 9-13, complete with live chats, live product demos and equipment, and engaging educational opportunities.

“For over six decades, PACK EXPO has been here to serve and connect the industry, and while the pandemic makes it impossible to meet in person this year, connecting the industry is still our top priority. PMMI Media Group is putting all of the power of the PACK EXPO brand into fostering connections between consumer-packaged goods companies (CPGs) and suppliers by driving

the entire industry to PACK EXPO Connects,” says Jim Pittas, president and CEO, PMMI. PACK EXPO Connects will facilitate exhibitor and attendee interaction while continuing to provide the ability to see machinery in action through this new platform. This exciting online experience will also offer worldclass educational opportunities, including daily Jumpstart sessions on hot topics from industry thought leaders along with the Innovation Stages, a staple at previous PACK EXPO events. The new Solution Room will feature expert-led education sessions, and PMMI Media Group editors will discuss highlights via Daily Download sessions, bringing attendees up to speed on the latest and greatest solutions on display at PACK EXPO Connects. A special Packaging and Processing Women’s Leadership Network event will feature an address from Jan Tharp, president and CEO at Bumble Bee Foods.

“Connecting the industry has never been more essential as packaging addresses the critical needs of this pandemic,” adds Laura Thompson, vice president, trade shows, PMMI. “While nothing can replace an in-person event, PACK EXPO Connects will push digital boundaries of virtual to provide the resources the industry needs to solve today’s

PMMI Media Group is putting the power of the PACK EXPO brand into connecting CPGs and OEMs via PACK EXPO Connects. unique packaging challenges.”

For more information on exhibiting or attending PACK EXPO Connects, visit packexpoconnects.com. For any additional questions or concerns, contact the PMMI Show Department at expo@pmmi.org or by phone at 571.612.3200.

2020 Processing and Engineering Scholarships Awarded

T

he PMMI Foundation has awarded three $5,000 scholarships to university students at four-year PMMI partner schools who are studying for a career in the packaging and processing industry. PMMI, The Association for Packaging and Processing Technologies, supports packaging and processing education at North American colleges, universities and technical schools through the PMMI Foundation.

The recipients of these scholarships are: • Electrical Engineering Scholarship o Jordan Wolf, Penn State York, ElectroMechanical Engineering

2009_News.indd 20

• Mechanical Engineering Scholarship o Eric Almberg, University of Iowa, Mechanical Engineering • Processing Scholarship o April Johnson, University of NebraskaLincoln, Food and Science Technology “Our goal is to recognize the leading students in our industry, providing them with necessary resources so they can transfer academic success into professional excellence,” says Kate Fiorianti, senior manager, workforce development, PMMI. “The motivation and achievements of these students

represent a positive outlook for the next generation in transforming the packaging and processing industry.”

With a commitment to developing future leaders in the industry, the PMMI Foundation has awarded academic scholarships each year to students enrolled in PMMI Education Partner programs since 1998.

For more information about the PMMI Foundation, go to pmmi.org/foundation.

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CONTINUED FROM PAGE 17 industrial automation at Belden. “Belden and Forescout will allow operators to begin segmenting their networks today with existing infrastructure, while also providing a trajectory for additional controls as next generation networks are deployed over time.”

Meanwhile, Honeywell has released the latest version of its Forge Cybersecurity Suite—R200—which includes new features such as enhanced industrial-grade remote access, increased asset discovery capabilities with active and passive functionality, and improved cybersecurity risk monitoring. To date, Honeywell Forge Cybersecurity technology has been installed more than 4,000 times worldwide.

Honeywell Forge Cybersecurity Suite provides users with a single dashboard to centralize security operations and asset security management. According to Honeywell, the newest release addresses common pain points in operations technology domains, including:

2009_News.indd 21

• Safely moving and using operations data; • Strengthening endpoint and network security; and • Improving cybersecurity compliance.

“As more operators move to support remote work, they’re increasingly vulnerable to cybersecurity issues,” said Jeff Zindel, vice president and general manager, Honeywell Connected Enterprise Cybersecurity. “The Honeywell Forge Cybersecurity

Suite helps customers increase productivity by providing the next level of protection required for more secure remote operations and better securing operational technology environments with asset discovery, inventory and continuous monitoring, as well as risk and compliance management.”

Application of Hirschmann switches and routers with Forescout.

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The new automation model focuses on services that reduce a manufacturer’s financial risks by shifting the responsibility of asset acquisition and management on to the OEM or technology supplier via performancebased service level agreements or cloud-based subscription offerings.

By Stephanie Neil, Senior Editor

2009_F1.indd 23

I

n February 2020, Robex, an automation and robotics integrator for the food, beverage, building, and container industries, rolled out a unique offering that delivers its custom-made robots in a use-based finance model. This Machine-as-a-Service (MaaS) offering is a flexible way to install automation on the factory floor without having to invest capital upfront. Instead, the customer pays for a successful outcome based on a predetermined agreement around productivity.

The service, called Robex Flexx, is powered by Steamchain, a blockchain-based software used to measure a variety of critical machine productivity parameters in realtime which then calculates transactional payments based on a machine’s overall performance. Robex also throws preventative maintenance into the contract. “If we see a robot is not performing or part of the solution is not working, we are on it right away,” said Craig Francisco, vice president of automation at Robex. “Probably before a customer even picks up the phone, we know there’s an issue and we will fix it immediately.”

Robex is both an OEM and a system integrator. Its history of providing products and services to manufacturers helped the company recognize the need to build out new aftermarket offerings to help its customers deal with industry obstacles—ranging from a skills shortage to the need to improve machine uptime during a pandemic.

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“We took action pre-pandemic but I think the concept will gain more traction now as people are open to new ideas and ways of trying to automate,” said Francisco. “The customer is limiting their risk using the Flexx program because we are taking on responsibility.”

And while the risk shifts to Robex, the rewards will be a great, new revenue stream— if they deliver on what is promised.

According to a report from Deloitte called “Aftermarket Services Transforming Manufacturing in the Wake of the COVID-19 Pandemic,” changes in customer demands, increasing market maturity, cyclical fluctuations in new equipment sales, and pressure on pricing are among the major factors driving many manufacturers to seek new aftermarket services revenue opportunities. This shift is taking place because customers are emphasizing service level agreements (SLAs) that guarantee product uptime. These customers are also looking for partners who can proactively support their equipment before it is out of service. In return, the customers are willing to pay a price premium.

For this new business model to work, new kinds of partnerships between machine builders and technology suppliers are emerging. “In many cases, the most significant competitor within the aftermarket business is the customer who may handle maintenance and repairs,” said Joe Zale, principal with Deloitte Consulting LLP. “Addressing this requires an ecosystem to work cooperatively and collaboratively with all the players, including hardware and software technology providers, more traditional channel partners, and customers.”

Robex, for example, partnered with Steamchain—a company founded in 2017 by engineers from Rockwell Automation who experienced the need to align relationships between OEMs and end users through accountability. By partnering with Steamchain, a ripple effect was created, putting Robex in a position to form closer relationships with its customers.

“Robex offers Machine-as-a-Service and includes onsite service, so it’s like contract manufacturing under your own roof,” said Michael Cromheecke, co-founder and CEO of Steamchain. “And in this market, it’s not so much about when a machine breaks, but what happens if a machine can run at 200 [parts] per minute and an end user is only

2009_F1.indd 24

achieving 100 per minute, who is responsible for that?”

Many times, it’s not the machine that’s to blame, but the operators, and therefore education becomes an important aspect of aftermarket service. And OEMs are uniquely capable of educating people on their equipment. “The end user wants more support from OEMs, but there’s no model in place today that creates the right linkage, other than to block off time or pay by the hour. We solved that by making it easier to bring automation into play.”

In addition, Steamchain does its part to support its OEM customer, whether it’s having a conversation with the manufacturer’s finance and procurement teams, designing the terms and conditions of the MaaS, or educating the sales and marketing teams to help create awareness, or offering financial services—which is brand new.

“When we sign on a new OEM partner, we are partners for life,” Cromheecke said.

“Our interest is the same as theirs—to sell more machines on MaaS terms.”

Within the ecosystem of partners, industrial control system (ICS) suppliers offer a lot of value to OEMs and end users alike when it comes to delivering aftermarket services.

The power of partners

If you take a quick glance around the ICS landscape, you’ll notice some unique partnerships emerging. There’s Rockwell Automation and PTC, for example, where Rockwell made a $1 billion equity investment in PTC to have a seat on the board of directors and to create a joint technology road map. In addition, Rockwell recently acquired Kalypso, a software delivery and consulting firm specializing in the digital evolution of industrial companies, as well as Italy-based ASEM S.p.A., a provider of digital automation technologies including industrial PCs, human-machine interface (HMI) hardware and software, remote access capabilities, and secure Industrial Internet of Things (IIoT) gateways. And, earlier this year Rockwell announced it will acquire Avnet Data Security, an Israelibased cybersecurity provider.

In November 2019, Rockwell announced its Digital Partner Program designed to streamline IIoT implementations and connect manufacturers to a variety of digital expertise from companies including Accenture, Microsoft, PTC, Ansys, and Eplan. For

example, Accenture can work with companies to create a business plan and develop use cases with return on investment (ROI).

Microsoft can help manufacturers access high-quality data from an intelligent edge to the cloud to drive better companywide decisions. PTC can help connect devices and systems from the edge to the cloud and provide augmented reality (AR) technology to solve problems in new ways. And Ansys and Eplan can solve complex challenges related to creating a digital thread, which helps in design, operations, and maintenance activities.

“We are going through our own transformation as a company,” said Tom O’Reilly, vice president of global business development at Rockwell Automation. “Different partnerships will play a bigger role as we transform ourselves in order to help our customers transform themselves. We don’t say [we are an] industrial software company, we now say we are an industrial productivity company.”

And new services that Rockwell rolls out will be valuable to both OEMs and end users.

“We believe there is benefit to both, and we are working on doing things with Microsoft later this year that will enable machine builders and others to participate in a broader way to provide value,” O’Reilly said.

One such offering that has already rolled out is Factory Insights as a Service, a turnkey cloud offering from Rockwell powered

by PTC and Microsoft, that delivers realtime production performance monitoring, asset monitoring and utilization, connected work cells, and digital and augmented work instructions.

At your service

The industry is seeing similar offerings from other industrial technology suppliers, like Hilscher, which launched a new way for OEMs to service and monitor equipment at customer installations.

Hilscher makes edge gateways, and the recurring theme from the OEM market and large end users has been how to maintain these devices, how to upgrade when a new release comes out, and how to change what they do with the applications that run on them. “It became evident that having devices in the field only maintained locally—as in walking up to the device and using a USB stick to load firmware to get another level of features—required another way of doing

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The Robex Staxx palletizer is offered on the Flexx Machine-as-a-Service program.

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it,” said Craig Lentzkow, business development manager for Hilscher’s IoT solutions.

The Hilscher platform, called netField, brings intelligence to field devices, providing the ability to update firmware from a remote location via a container-based management system. Hilscher created an IIoT operating system, called netField OS, that runs containers in a Docker runtime environment (Docker is an open source software platform; a Docker container is a lightweight, standalone, executable package of software that includes everything needed to run an

application, including code, runtime, system tools, system libraries, and settings.) To that end, netField OS also includes a self-service management portal, called netField Portal, as an interface for local or remote set up. And then there’s the edge gateway.

The edge gateways are set up to be information-gathering devices, not controlling devices, and, for security protections, the customer does not get access to the programmable logic controller (PLC) via the edge gateway. The device sits on a machine and monitors the controller and,

in some instances, the I/O to gather the status of the machine. The goal of the edge gateway is to stream data in real time to where that data needs to be acted upon.

Data can be streamed from the edge gateway to cloud-based AI applications, such as prescriptive maintenance software that predicts device failures, or the data can be acted on in the edge gateway by containerized applications—often referred to as edge computing.

“We call it ‘no touch’ because you don’t have to be physically present, just physi-

Siemens’ Manage MyMachines securely connects CNC machines to the cloud and all of these machines, connected to MindShpere, can be managed around the world.

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cally connected to the device,” Lentzkow said. “The goal of the open environment is that it is highly customizable by the customer. We provide 85% of the necessary software framework so the customer can focus on applications and what they want to run. Millions of devices can be monitored on a system like this.”

Similarly, Siemens recently rolled out its new Manage MyMachines, a cloud-based Platform-as-a-Service (PaaS) that, combined with edge technology, enables data tracking of machine kinematics as well as production data.

As a MindApp within the Mindsphere portfolio, Manage MyMachines is integrated in the cloud-based, open Internet of Things (IoT) operating system and it allows access to all critical machine tool information, from bearing temperature to production by shift or job, all in a selectable priority scale based on user needs. Unexpected line downtimes and off-normal machine kinematic conditions can be quickly identified and corrected. Predictive maintenance can be programmed, so an upcoming failure can be anticipated, with alerts sent to a local distributor, for example, to deliver the needed components.

“Simply stated, this concept will be a gateway to the digital factory for all of our associates in the machine tool world, including builders, integrators, and end users,” said Sascha Fisher, head of the machine tool systems group at Siemens in the U.S. The industry is currently seeing a surge in “as a service” offerings due in large part to COVID-19, which has disrupted business.

“It has become challenging to dispatch field service technicians, and advanced remote diagnostics and assistance capabilities have helped to ensure business continuity,” said Deloitte’s Zale. Nevertheless, “the move to pay-for-performance designs has been long anticipated in manufacturing, but has had a mixed record of conversion, with most companies’ business models moving slowly from capital to solution-based, outside of a few, unique segments. Like many trends that have seen massive acceleration in this crisis, the conversion to more creative contract designs that balance risk between equipment/service providers and customers could quickly become the norm in a broader set of use cases and segments.”

But it’s not only the coronavirus that is acting as a catalyst for technology sup-

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pliers to deliver more creative aftermarket services. There are industry initiatives like the Open Process Automation Forum (OPAF), which is focused on developing a standards-based, open, secure, and interoperable process control architecture that allows integration of different control systems and components.

And that means ICS suppliers must build a new business model that is not reliant on “vendor lock-in” associated with proprietary control architectures.

The impact of OPAF

In the summer of 2020, the Open Process Automation Standard (O-PAS) version 2.1 went into final review and is expected to become available in October 2020.

It builds on O-PAS 2.0 which focuses on configuration portability—the first steps toward the ultimate goal of plug-and-play of control equipment. Version 2.1 adds in function block definitions and includes the process automation device information model (PA-DIM) from FieldComm and the OPC Foundation.

“It’s bringing together the data models from all the different field networks for a unified information model,” said Dave Emerson, vice president of the U.S. Technology Center at Yokogawa and co-chair of the OPAF enterprise architecture working group. “This has plagued the industry for a long time…everyone did the same thing but called it something different. We are working on a common set of terminology, data fields, and data links. In some ways this is small, which is why it’s 2.1, but it will give us a unified platform to build on.”

In the long term, this means that a manufacturer could use control function blocks from different suppliers, and they would work together. In the short term, this means process control suppliers will need to differentiate product offerings in new ways.

“Going forward, as a supplier, we realize with open technology coming from the IT (information technology) world it is inevitable that we will need to change where we are going to add value and where we can help the customer the most,” said Emerson.

Yokogawa, for example, offers lifecycle services, which are currently helping businesses impacted by COVID-19 through remote support for operations and maintenance via the company’s Cloud Enabled Execution infrastructure and SensPlus tool,

which uses AR and video communication to connect with subject matter experts. In the future, Yokogawa could use its lifecycle services to act as the main service provider for an Open Process Automation (OPA) system. Acting as a partner to the end user, its role could be to layer innovative technology on top of the system as needed.

“Advanced control is still productive but has reached a saturation level for users.

Now, with machine learning and artificial intelligence, people want to explore what these can do,” Emerson said.

To that end, Yokogawa recently acquired a Danish startup called Grazper Technologies that has developed advanced artificial intelligence (AI) for analyzing images. The company aims to use this technology to improve recognition accuracy for moving imagery as a way to open up new security applications related to image analysis on production lines.

Machine builders are also looking at building more functionality into machines— like AI—but only turning it on as needed.

“This feature management allows the end user to buy a [basic] machine, but there are features built-in that can be turned on later, which creates more revenue [for the OEM],” said Steamchain’s Cromheecke.

Of course, all of this requires a new mindset around machine automation as it relates to buying a service rather than a product. “We are careful with our customers,” Robex’s Francisco said. “We want someone who sees the value and wants us to be a partner. This is a win/win if we can be open and honest and grow together.”

The good news is, manufacturers are waking up to the possibilities, especially as more factories lack the level of in-house technician expertise they had a decade ago, Francisco said. “We believe for us to reach our goals and bring as much value as we can to the market and to customers, we have to do something different. And this to me is a phenomenal way to offer a flexible solution to our customers. And it’s limitless what we can do with it.”

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28 INDUSTRIAL ANALYTICS AW SEPTEMBER 2020

Making Sense of the Industrial Analytics Market As organizations continue to see the value in industrial analytics, making sense of the sheer amount of data produced can be a difficult task. Finding the right product and developing a proper workflow is important to get long-term use out of the system.

By Beth Stackpole, Contributing Writer

C

ollecting and analyzing data from industrial assets on the plant floor hardly registers as cutting edge. For years, plant floor managers and their counterparts have analyzed industrial machine data to be alerted to production snafus, identify quality glitches, or as a guide for tweaking assets with the goal of boosting performance.

As industrial assets are digitized with sensors and connected via the Industrial Internet of Things (IIoT), manufacturers still want to analyze machine data to create production

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efficiencies, reduce downtime, rein in costs, and promote better decision making. Yet the goal posts have shifted significantly when it comes to scale. Instead of a plant manager or maintenance worker analyzing historical data from a specific asset in a spreadsheet to make a modest change down the road, today’s manufacturers are striving for wholesale transformation. Their aim is to create flexible and intelligent operations where networks of assets and systems can be holistically automated and optimized in near-real-time.

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INDUSTRIAL ANALYTICS 29 AW SEPTEMBER 2020

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The engine for such intelligent operations in areas like predictive maintenance, realtime quality control, and scenario testing for root cause analysis is advanced analytics, powered by artificial intelligence (AI) and machine learning. While the analytics category remains somewhat nebulous in the industrial world, use cases are already sparking huge interest and growth. According to IoT Analytics, the industrial AI and analytics market hit $15 billion in 2019, with the top use cases being predictive maintenance, cited by nearly a quarter of respondents (24.3%), followed by quality inspection and assurance (20.5%), manufacturing process optimization (16.3%), and supply chain optimization (8.4%).

The surge in industrial analytics use is rooted in the desire to capitalize on the sheer amount of data generated by plant floor or field-based industrial assets, including robots, automation cells, oil rigs, and wind turbines.

As manufacturers across industries ramp up digitization efforts, IDC Insights estimates

that the typical plant is generating more than a terabyte of data a day with expectations that the number will multiply by a factor between five and 10, depending on industry, over the next five years.

“That’s what’s driving companies to develop or buy these [analytics] tools—without them, there’s nothing else to do with the data,” says Kevin Prouty, group vice president, manufacturing insights and energy insights at IDC. “It’s too much data for an engineer with an Excel spreadsheet to analyze.”

Enterprise analytics vs. industrial analytics

Most manufacturers agree with the notion that the bounty of data can be leveraged for bottom line impact, whether that’s increasing profits, productivity, or both. The problem is the data is scattered across silos, in different formats, without context, and with much of it stored as time-series data, which isn’t handled adequately by most enterprise analytics

and Big Data tools designed for structured and unstructured data. In addition, Excel has been the analysis tool of choice in this space for decades, but it’s inefficient and any insights remain isolated to a single engineer tackling one specific problem.

There are also differences in the approach enterprise information technology (IT) and operations technology (OT) groups take for data collection and analysis. Most enterprise analytics efforts involve ingesting data, normalizing it, and putting it in a centralized repository or data lake, most likely in the cloud, to make it accessible to a variety of business users for different types of analysis.

From an OT perspective, the data collection and analytics efforts have been mostly local and tactical. “OT people know how to build an analytical model for a single machine in a single factory for a single problem and they do it in Excel or by hand with an open source platform,” says Marcia Walker, global industry principal for the manufacturing practice

With data analytics, industrial organizations can capitalize on the IoT opportunity, optimize operations, and generate greater profitability.

Image courtesy of GE Digital.

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at SAS. “When you ask them how they’re going to take that and apply it to all the machines in a factory and to their factories across the globe, they stare at us like deer in the head lights.”

Another big gap between industrial analytics and general enterprise analytics is an understanding of the specific nature of the machines and the ability to provide context to the data collected in historians and supervisory control and data acquisition (SCADA) systems. Unlike structured content from financial systems, time series data lacks context for understanding how the raw data set relates to a specific process or condition—for example, what factors might be present to impact the operation of a pump. Without the proper context, it’s impossible to fully leverage data to drive operational performance, condition monitoring, or predictive or prescriptive maintenance applications.

“Context is required for problem solving,” says Bry Dillion, vice president of cloud, community, and channels for OSIsoft, which markets the PI System for collecting and centralizing time series data from diverse sources.

“If you’re streaming data associated with a pump, you have to understand how the data set relates to the process to get that context.

If you just optimize the flow through pump and don’t know the calibration or throughput, you could potentially optimize the pump to the point where the pump breaks. You can’t just bring in raw data and expect machine learning to figure it out.” (Editor’s note: At press time, Aveva had just announced its pending acquisition of OSIsoft. Read more at http:// awgo.to/bSDYc.)

Core components

Industrial analytics can take a variety of forms, but there are core components and attributes that seem to be universal across platforms. While a lot of the heavy lifting in enterprise analytics happens in the cloud, industrial analytics software requires significant edge processing capabilities given the need to process and analyze data in nearreal-time and close to the source to avoid latency and security issues.

“When you are talking about the industrial space, you are almost always talking about something that has a combination of on-premise and cloud,” says Ed Cuoco, vice president of analytics for PTC. “You need a solution that’s balanced and that can send data to the cloud for processing along with

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Advantech’s MIC-720AI is an ARM-based system integrated with the Nvidia Jetson Tegra X2 System-on-Module. According to Advantech, it is suited for AI inference at the edge and deep learning applications. an edge ability to drive insights very close to or within the machine.”

Advantech makes the case that AIenabled edge processing delivers better performance than cloud-based industrial analytics while also ensuring a higher level of security. Advantech’s Edge AI Systems, powered by the Nvidia Jetson platform, can serve as a replacement for traditional visual quality inspections performed by plant floor workers. In one such scenario, an edge server system, buttressed with various AI models, performs real-time inspection on baked goods in a cookie factory, automating the process of setting bake times and oven temperatures to ensure more consistent, high-quality cookie production.

“We’re focused on the edge instead of the cloud so we can protect data and keep it secure and confidential,” says James Yung, product manager of Advantech’s servergrade products. “If you send data to the cloud, it can take a long time to come back with a response.”

Given the heterogeneity of plant floor data, an industrial analytics platform must have both an ability to ingest disparate information types with some means of normalizing and contextualizing data. Specifically, customers need to know the context at the moment when data is generated from a device or a production line, however, it remains difficult to gather high-speed OT

contextual data from different edge devices let alone package it in a structured way to pair with third-party industrial data sources or send it upstream to IT applications for enterprise-wide insights.

To solve this problem, automation partners Rockwell Automation and PTC have created smart objects, a flexible data model that automatically discovers and gathers high-speed OT data with rich context, allowing it to be consumed by upstream IT applications like enterprise resource planning and product lifecycle management systems. “Smart objects unlock the contextualized OT data you’re gathering at the edge in a fast manner and makes it compatible with all IT apps downstream,” explains Gaurav Verma, director, digital transformation at Rockwell Automation. “IT apps can glean a lot of business insights at the enterprise level, but without smart objects, it’s not possible.”

Sight Machine also leans heavily on a modeling layer to differentiate its manufacturing analytics platform. The software performs an automated and continuous data intake process, which includes employing expert systems and machine learning classifiers to prepare and contextualize process and product data. The end result is a digital twin of the plant floor, which using machine learning and advanced analytics, can surface anomalies and provide insights to help reduce

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32 INDUSTRIAL ANALYTICS AW SEPTEMBER 2020

Seeq enables the complete lifecycle of advanced analytics, from connecting to disparate time-series data to enabling rapid investigation and analysis. Image courtesy of Seeq.

downtime. “We apply data models and put common structures in place to harmonize data,” says Jon Sobol, Sight Machine’s CEO. “It’s the application of structure to data so you can analyze it effectively that’s been so difficult for people.”

Regardless of their different approaches, most, if not all, industrial analytics tools and platforms incorporate some form of AI and machine learning to help uncover patterns in the deluge of asset data to build models of assets and production floor processes and to automate processes as part of more intelligent operations. The AI-driven analytics model can become a mission-critical element in the production line, creating a digital twin that allows, for example, a brewery to simulate, test, and optimize its processes as well as analyze hundreds of thousands of parameters to understand and predict influences on beer quality, explains Henning Ochsenfeld, head of data science and machine learning engineering at Siemens

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Digital Industries. “It’s nothing a human could do,” he explains. “You need to model the relationship between existing key performance indicators and the huge amount of data acquired on the production line.”

Another element of emerging industrial analytics platforms that is proving to be critical is some semblance of citizen developer capability that allows OT professionals, not just IT and data scientists, to easily model problems and visualize insights. Siemens’ Mendix low-code platform serves that role in its industrial analytics portfolio.

Differing from the platform approach, Seeq bills its data analytics software as being specifically designed to help process engineers and subject matter experts interact with and model time series data at scale.

Instead of competing with some of the large industrial analytics platforms, Seeq connects to data stored in variety of process historians and SCADA systems as well as IIoT platforms like PTC ThingWorx and Siemens Mindsphere,

according to Michael Risse, Seeq’s vice president and CMO. Given the complexity of factory automation and the diversity of industrial data, there will be no one analytics product that fits the bill for all use cases and all scenarios.

Rather, experts say organizations need to consider the long-term strategy and the questions they’re looking to answer to line up the right tools for the job. “Don’t draw a bright line between tool sets—it’s important to put everything on table and see how they play together,” says Jennifer Erickson, vice president of product management for power and the oil and gas business unit at GE Digital. “Don’t look at industrial analytics as a side project because, if you do, you’ll be spending a lot of time and energy on a cool engineering project, but not necessarily changing how the business works.”

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Data Analysis Helps Glassmaker See Through Its Processes Using OSIsoft’s PI to monitor thousands of data points across a high-intensity float glass production system that runs 24/7, AGC has been able to reduce downtime and improve operations.

By Aaron Hand, Editor at Large

T

he world’s largest glass company, AGC, makes glass for nearly everything, from “skyscrapers to microwave windows, automobiles, and everything in between,” said Bradley Willson, electrical engineer for AGC Glass North America. The company has facilities around the world and has been optimizing operations at its float glass manufacturing operations in Spring Hill, Kan., Richmond, Ky., and Church Hill, Tenn., using OSIsoft’s PI system for production data analyses. (Editor’s note: At press time, Aveva had just announced its pending acquisition of OSIsoft. Read more at http://awgo.to/bSDYc.) AGC Glass North America has been using OSIsoft’s PI System since 1996 to help make sense of its production data. But while attending a recent PI World event, AGC learned about PI’s move from data historians to a data infrastructure, giving AGC new ideas for how to improve its production operations.

AGC has been using PI products such as ProcessBook, DataLink, and Manual Logger to help visualize data from PI historian servers and create reports. These tools are largely used for process tuning of PID loops to make sure they’re performing optimally. Now the company is “migrating towards OSIsoft’s

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new product, PI Vision, to build out our asset framework, create notifications, develop complex analyses, and integrate with our ERP system,” Willson said.

PI Vision enables users to analyze data in a number of ways on any device. It can import graphic process monitoring displays created

by PI ProcessBook, for example, and allow them to be viewed in a web browser. It also supports mobile browsers and customized views for small-screen devices to enable easy access from anywhere.

Monitoring multiple processes

AGC uses PI tools to monitor its intense production process. “This furnace is capable of melting roughly 600 tons of batch per day.

And it’ll hold up to 1,700 tons of molten glass within the tank. It is a natural gas furnace that consumes roughly 120,000 cubic feet of natural gas per hour,” Willson said. “The interior temperature of the furnace reaches roughly 3,000°F, and this furnace has been constantly melting batch 24 hours a day, seven days a week for 15-20 years.”

AGC monitors about 1,500 data points on each of its float lines. It also monitors

CASE STUDY 33 AW SEPTEMBER 2020

High-efficiency glass is made possible through a sputter coating line, which adds a metallic film to the glass surface. Source: AGC Glass

auxiliary processes throughout its production facilities, such as its sputter coating line, which produces high-efficiency glass through the application of a metallic film added to glass surfaces. Likening the process to how ships pass through the Panama Canal—but lowering air pressure instead of water level— Willson explained how the glass gets transferred from chamber to chamber about every 20 seconds. “Once the glass reaches roughly 10-6 mbar, it gets transferred into the sputter coating compartments,” he said. “Here, we inject argon and oxygen into each compartment and then ignite a large DC plasma field inside the compartment. The plasma grabs atoms of material from the precious materials, bounces around inside the compartment, and then deposits those precious materials onto the top surface of the glass.”

At AGC’s U.S. manufacturing facilities, data from various automation devices are sent to the PI Vision Data Archive server via OPC and a relational database management system, and from there into the PI Asset Framework server. Both of those servers are located on premise at each site. At this point, a centralized, cloud-based PI Vision data server gathers data from each of the

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34 CASE STUDY AW SEPTEMBER 2020

At AGC’s three U.S. manufacturing facilities, data is pushed into the PI Vision Data Archive server and then into the PI Asset Framework server. A centralized, cloud-based PI Vision data server gathers data from each of the Asset Framework servers for further analysis. Source: AGC Glass Asset Framework servers for further analysis.

The Richmond site stands apart from the other two facilities using these PI technologies because AGC is experimenting with machine learning there. “We’re using the PI OLEDB interface to push data up into the Amazon Web Services (AWS) cloud, where we’re doing some complex analyses and pushing data out through the clients via Tableau (business intelligence and dashboard software),” Willson said.

Implementing new tools

The shift to PI Vision has delivered new tools for AGC’s analytics. Willson’s favorite, he said, are the email notifications. “You set these notifications up once and then PI does the rest of the work,” he said. “It’s completely automated and, most of the time, these emails get sent out even before the operator notifies maintenance that there’s a problem. This helps reduce the amount of downtime and production outage.”

The Greenland facility in Church Hill has begun to add preemptive notifications as well,

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which can tell them when a process is starting to go out of tolerance and notify the team to take action before it becomes an issue.

PI Vision also enables production reporting, making it easy to compare, for example, what gets loaded in with what gets loaded out of a coater. “[We] can see how many square feet was loaded into the coater per hour, how many square feet of glass was loaded into the coater by shift, and how many square feet of glass was actually packed on the unload end,” Willson said. “This could be expanded to a complete material balance as well.”

PI Vision is also being used for troubleshooting. Willson explained how the software was able to discover a seven-year trend in which the temperature on a melter backwall was slowly increasing. Without the long-term trending capability, the changes would’ve been too small to notice. “Due to this long-term trending [capability], we were able to identify that we had a problem, trace the events back to the start, and then install countermeasures to verify that the problem had been corrected—ultimately reducing

downtime,” Willson said. “In this example, we estimated that we would’ve had a two-week downtime if we had not noticed that the backwall was heating up. And that equates to roughly $2 million worth of downtime plus materials and labor.”

What’s next?

AGC plans to continue exploring the additional tools available in PI Vision, with a plan to move progressively toward preventive rather than reactive maintenance. “I’ve seen some really neat use cases for event frames, so I want to learn more about those. And we’re going to continue developing new analyses,” Willson said. “We’ll continue to develop additional PI Vision screens. And then we’re going to begin rolling out these PI tools to our other facilities.”

The facilities also plan to continue their efforts with machine learning, using AWS and Tableau to make even better use of the data.

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INDUSTRY-SUPPLIED CONTENT 35 AW SEPTEMBER 2020

Death by a Thousand Spreadsheets: The Simple Yet Insidious Nature of Time Series Data Despite their many limitations, spreadsheets are the tool of choice for engineers performing ad hoc analytics on time series data. Fortunately, there are better alternatives in the form of advanced analytics software.

I

n the mid-1970s, the process manufacturing industry began its transition to digital infrastructure with the first distributed control system, and this trend accelerated in the 1980s with the proliferation of supervisory control and data acquisition and human-machine interface systems.

Equipped with sensors, digital networks, and programmable logic controllers, companies began generating and collecting massive amounts of data from their operations. And now, 30+ years later, process manufacturing companies generate terabytes of data—1TB/ day for the average plant and perhaps 40TB/ day for a corporation with multiple plants— recording flow, temperature, pressure, level, and everything in between.

This sensor data, technically “time series data,” is the starting point for all analysis and optimization efforts in process manufacturing. However, analyzing time series data is as complex as it is critical, leaving many organizations mired in a web of Excel spreadsheets.

The concept of time series data is simple: the measurement of physical world over a

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period of time stored as a data pair—timestamp: value. But that only scratches the surface. In process manufacturing plants, tens of thousands of sensors are measuring the world at different intervals on any given day.

Companies must be able to analyze all of this data to discover relationships, investigate issues, optimize production, and predict outcomes to prevent catastrophic failures.

In addition, organizations use time series data to support broader business objectives.

Given the rate of change in process manufacturing, all of this must happen quickly if the analytics are to improve operations in a timely manner. And that’s where time series data suddenly becomes very, very complicated.

Time series data storage

Time series data is typically stored in dedicated applications, such as process, data, or enterprise historians. The data may be viewed in “trenders,” which are applications for visual analytics, or copied into spreadsheets for calculation-based analytics. While organizations benefit from consolidating

Michael Risse,

chief marketing officer, Seeq

relational data to enable new and more complex relationships and correlations, time series data doesn’t enable better insights simply because it’s aggregated in one place: user input is required!

This is because calculation analytics with time series data depends on the user to define the critical time periods of interest and relevant context—all at the moment of analysis.

This is why spreadsheets, as time consuming and cumbersome as they are, are still the time series tool of choice for engineers to perform ad hoc analytics. They put the user in control of the questions and investigation, while offering a known path of analysis.

However, spreadsheets bring a new host of issues. Collaboration is difficult as is version control, and new queries must be run as data changes. Data cleansing and contextualization is a slow and manual process.

What one person does on their desktop may not be discoverable by their colleagues. And the basic issues of time series data, like time zones, daylight savings time, and interpolation types and logic, must be addressed

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Process and other manufacturers generate a tremendous amount of data, providing an opportunity for insights and operational improvements. by the user in spreadsheet formulas. The result isn’t just hours in spreadsheet, hell, it’s weeks or months.

Furthermore, time series data is difficult to reconcile and analyze in the broader business context necessary for profitability and efficiency use cases to succeed. Traditional business intelligence (BI) applications are great for relational data sets, but they don’t

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accommodate the dynamic nature of time series data. And data scientists can’t run their algorithms until data is “ready,” which means they must first assemble models of cleansed, calculated, and contextualized time series data. For all their expertise in algorithms, data scientists don’t have the plant, asset, or process expertise to know what they are looking for in the data. This

is why process engineers, subject matter experts with first principles expertise, are required for the data preparation efforts for both business analyst and data science tasks, as well as for process-related analytics.

Regardless of the complexities, time series data is critical for innovation and for achieving business goals. Leveraging time series data to augment and drive deeper

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Process manufacturers can analyze time series data for multiple purposes.

Advanced analytics software designed to work with the time series data generated by process manufacturers is a much better solution than general-purpose spreadsheet software.

context and meaning for process engineers and traditional BI applications is the correct path, but today most analyses begin at the same starting point: the spreadsheet.

Making use of data insights

So how do process engineers and data scientists quickly get the insights they need and collaborate for a better, more optimized future? This is where Seeq advanced analytics software comes in.

Advanced analytics software is as easy to use as time series data is labor-intensive to analyze, enabling process engineers and subject matter experts to cleanse, contextualize, and model operational data to quickly find

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the right insights and make data-based decisions. Data is accessed across silos, is never copied or duplicated, and is used for diagnostic, predictive, and descriptive analytics.

Advanced analytics software empowers collaboration among colleagues with published reports and dashboards for insights across the organization. All without rifling through hundreds of thousands of rows in spreadsheets. With advanced analytics software, it’s possible to quickly get the insights organizations need to realize the full value of time series data.

So, for the process engineers doing their own analytics—or preparing time series data for business analytics using PowerBI, Tableau,

or other BI applications, or for data scientists using their machine learning algorithms— advanced analytics software taps innovation in data science to catch up to the volume and challenges of efficient analytics with time series data. And for those of you who don’t want to give up spreadsheets with their pivot tables and graphing? Seeq has excellent integration with Microsoft Excel, including streaming updates via OData to bridge from calculation to visualization analytics.

With advanced analytics software, time series data finally is as easy to analyze as it is to create.

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38 NEW PRODUCTS AW SEPTEMBER 2020

HMI Software Platform for OEMs and Discrete Part Manufacturers

Adrisa, www.adisra.com Adrisa SmartView Service Pack 1 (SP1) adds new development and usability features designed to make it easier for users to create applications with greater flexibility.

Templating functionality included in the update supports re-use of advanced graphic objects and screens across multiple applications. New features include the ability to use tags to dynamically adjust the file and pathnames for recipes and reports along with the ability to change display resolution of an application to match any target deployment. Other new features include GIF usage, improved button functionality for screen navigation, an added corner radius property for many graphic objects, and a MultiTagViewer object for displaying array data based on offset and size. Secure connectivity is said to have been improved with the ability to integrate the Adrisa SmartView security system with the industry-standard Lightweight Directory Access Protocol. Multiple database connections are now possible, allowing tags and alarms to be logged to multiple databases simultaneously in an intuitive manner, without the need for SQL or other custom code.

T1 Industrial Connector for Industrial Single Pair Ethernet Harting, www.harting.com/US/en The T1 industrial connector features a single twisted pair of wires instead of four or eight and utilizes power-over-data-line technology to bring communication, voltage, and the amperage needed to power a device. This connector’s mating face is standardized according to IEC 63171-6 (formerly IEC 61076-3-125) and meets IEEE 802.3 requirements for Single Pair Ethernet; it also works across common industrial protocols including EtherNet/IP, Profinet, and EtherCAT. With this connector, the number of connections on the device are reduced, eliminating the need for an external power supply, and plant floor devices that traditionally communicate over Fieldbus protocols can join the same IP-based network as the other devices, enabling peer-to-peer communication, open-loop feedback of all devices, and smart functionality from the main control room to the device. The industrial design offers locking lever protection, 360° shielding, and high mating cycles.

SCARA Robots

Epson Robots, www.epson.com/usa LS3-B and LS20-B SCARA robots features batteryless encoder, lower cable duct profile for hardto-reach workcell layouts, built-in camera cable for a simpler vision system setup, and new topof-arm layout for an enhanced equipment mounting process. The LS20-B has a 20 kg payload and available reach of 800mm and 1000mm for higher payload applications, while the LS3-B SCARA robot has a payload of 3kg and a 400mm reach. Both robots include Epson’s proprietary Quartz MEMS technology, a hardware and software system that combines force feedback and position for improved servo performance and are compatible with the new RC90-B controller, a single controller with wiring options for both PNP and NPN.

Compact Safety Magnetic Sensors

Carlo Gavazzi, www.GavazziOnline.com The MC36C Series are for safety-related applications, such as the monitoring of swinging, sliding, or removable safety guards. The magnetically-coded REED safety magnetic sensors monitor the position of sliding, hinged, and removable safety guards, especially in dirty and dusty environments. They can work standalone or in conjunction with a safety module to reach a safety category four, according to the EN ISO 13849-1 Standard. Units measure 36x26x13 mm, are available with two NO or one NO and one NC output configuration and come with 2 m cable or M8 quick disconnect.

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NEW PRODUCTS 39 AW SEPTEMBER 2020

IP65-Rated Stepper Motors

Applied Motion Products, www.applied-motion.com These motors are dustproof and resistant to water pressure impact, making them suitable for use in both wet and dusty applications. Using advanced seal protection technology, the steppers feature sealed laminations, an oil shaft seal, internal corrosion-resistant film coating, gaskets for mechanical joints and an integral 10 ft. shielded cable that offers protection against the ingress of dust as well as resistance to low-pressure water jets. For improved protection in high-humidity environments, an advanced coating is available as an option. Units are available in NEMA sizes 23, 24, and 34. A double-shaft version is available with an optional IP65-rated encoder for applications requiring feedback.

Robot and Controller for Harsh Environments

ABB Robotics, www.abb.com/robotics The IRB 1100 robot comes standard with an IP40 rating; it is also available with an IP67 rating. With the IP67-rated version, the robot can be used in applications generating substantial dust, water, and debris, including 3C polishing, wet grinding, buffing, and deburring. The robot is powered by ABB’s new OmniCore C90XT controller, which is equipped with advanced motion control capabilities for use in rapid assembly, pick-and-place, and material handling applications. The IRB 1100 is also equipped with up to 16 I/O for more sophisticated/complex applications. The unit is the company’s most compact and fastest robot, and is available in two variants—one with a 4 kg payload with 475 mm reach and the second with a 580 mm reach.

Computer for Machine Vision Applications

Matrox Graphics, www.matrox.com/graphics/en/ The Supersight Uno offers I/O capabilities plus direct interfacing with GigE Vision and USB3 Vision cameras. Supported expansion cards include the company’s frame grabbers and third-party boards including high-end graphics cards. Enhanced system reliability and maintenance comes via quick-release, hot-swappable drive bays with redundant array of independent disks (RAID) support. Moreover, this vision controller can power multiple expansion boards— which the company says does not compromise system performance—with the support of its 600 W power supply. With steel construction and 4U rack-mount chassis, the computer supports both horizontal and vertical mounting.

Cellular-Based Transmitter Connects Industrial Sensors to the Cloud

SignalFire Wireless Telemetry, www.signal-fire.com The Ranger cellular-based transmitter meets the need for monitoring isolated measurements where it is cost-prohibitive or complicated to simply get a reading from a sensor. The unit uses LTE CAT M1 technology to connect industrial sensors to the cloud for remote monitoring, control, and alarming. Connecting directly to the cloud bypasses local networks offers a more secure connection without adding more work for information technology departments. The transmitter has two digital inputs, one analog input, and one relay output.

The digital inputs can detect on/off status or frequencies up to 2 kHz. The analog input can be set to 1-5 VDC or 4-20 mA and is powered by the integrated battery pack.

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40 FINANCE VIEW AW SEPTEMBER 2020

Industry 4.0 Capabilities Come to Enterprise Finance

By Larry White

lwhite@rcaininstitute.org

executive director, Resource Consumption Accounting Institute

Traditional nancial accounting information is the product of an analog world and simply is not up to the operational and management challenges of Industry 4.0.

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T

he near century long gap between business metrics, as expressed by financial accounting standards designed for regulated financial statements and audits, and operational information with its focus on real-time quality and efficiency, appears to be the new frontier among major software and systems providers. In July 2020, SAP and Siemens announced a partnership of software offerings to improve product lifecycle, supply chain, and asset management.

Their announcement included an interesting statement: “Silos between engineering and business have existed in enterprises for decades.

This new partnership will help customers to break down these silos so manufacturers, product design teams, and service managers have the information needed to quickly create and manage customer-centric product and service offerings.” I don’t have specific insight into how Siemens and SAP will achieve this. SAP software was originally designed to support German management accounting/controlling techniques that focused on creating a causal monetary model of operations purely for internal decision support and was not used for external financial reporting. Causality is a critical requirement to monetarily reflect operations. The German “controlling” body of knowledge remains very active and continues to focus on internal decision support, though it has expanded beyond manufacturing to other industries and also supports organizational strategy development and execution.

Digitalization is clearly the springboard for changing the nature of information. Traditional financial accounting information is the product of an analog world and simply is not up to the operational and management challenges of Industry 4.0. If a manufacturer’s accountants aren’t designing and creating “fit for digital manufacturing” causal financial information for internal decision support, it appears manufacturing systems providers are ready to develop or find partners that will bring their customers capable Industry 4.0 financial information. This is really a digital steamroller for finance and accounting in manufacturing because it is likely that the internal decision support financial information from these new systems will be completely credible and fully capable to compete in the decision arena with poorly connected, historical regulated financial reporting information.

Continuous, cause-and-effect-based cost information opens up a new world of insight for decision making. Manufacturing costs will be substantially established as the product and production capability will be built on the digital twin, subject possibly to material purchase costs. But manufacturing costs are only part of the story With an organization-wide decision support system, design selling and marketing costs, warehousing and delivery costs, financing and invoicing costs, and warranty service costs could be estimated based on history. Actual process performance or statistical forecasts are then captured for critical evaluation and forecast improvement continuously. Add in-demand and revenue forecasting and evaluation, which is more common than cost forecasting, and manufacturers are looking at continuous profitability analytics.

Accountants can be instrumental in this exciting new world of internal decision support financial information, but the profession must expand its scope inside organizations. Finance tends to be geared toward “up and out”—meaning the C-suite, board, and shareholder. Finance needs to focus on “around and down”—meaning mid-managers and employees who can add tremendous value with high quality, timely financial information. Numerous initiatives exist at the Institute of Management Accountants, International Federation of Accountants, Resource Consumption Accounting Institute, and many other organizations to increase accountants’ focus on internal customers and internal decision support needs which have long gone under-recognized.

Nearly a century ago HL Gantt, an engineer, and Alexander Church, an accountant, debated the role of accounting in improving efficiency in the factory and supporting value creation. The debate centered on the detrimental effect of the existing accounting perspective on the actual operations in the factory and the business decisions of manufacturers. In the end, they agreed that economic reality was more important than accounting standards. This debate is only dimly recorded and often forgotten. Perhaps Industry 4.0 and digital manufacturing systems will bring back this wonderfully old fashioned, but completely relevant agreement between manufacturers and accountants.

8/29/20 10:33 AM

IT VIEW 41

AW SEPTEMBER 2020

Securing Your On-Premise or Cloud Industry 4.0 Systems

By Larry Grate, GICSP director of technology, Premier System Integrators

A

major component of any Industry 4.0 product is getting information from deep within the manufacturing environment out to the enterprise in a contextualized, secure manner. Fortunately, most offerings that have been used in manufacturing for many years are based on Ethernet technology, making them very easy to connect to a plant network. Unfortunately, the protocols used by these systems are typically unencrypted and unauthenticated. As a result, unsuspecting companies often connect these

T�e advantages you get by using a secure cloud provider should be deeper than your in house resources because the costs are spread across multiple clients.

2009_ITView.indd 41

systems in ways that leave them open to outside compromise resulting in downtime, or worse, out-of-spec products that may not be caught by final quality inspections.

There are several cyber standards (as well as best practices) that have been developed by major automation vendors to create a monitored perimeter around these systems, with appropriate security controls in place to allow access to this gold mine of information contained in the control systems. One of these standards is produced by ISA/IEC and is known by many as IEC62443 or ISA S99. When this standard is implemented correctly, the result is a hardened, monitored edge for your manufacturing network, which can provide the contextualized information that artificial intelligence or machine learning products are looking for.

Assuming that the interface to the manufacturing environment is properly secured (unfortunately, this is rarely the case), what is the most secure method to consume that information and begin to use it? The prevalent thought has been that on-premises offerings are more secure because they do not require the internet as a conduit to move data. With that in mind, let’s review the three primary types of offerings and then we can consider the associated risks.

First is a true on-premises offerings in which the tools used to ingest and process the data are located at the same physical location as the manufacturing facility. The second is a hybrid offering that leverages a multiprotocol label switching connection tied back to a private data center where the tools are deployed. This is oftencalled an on-premises cloud offering. The third offering uses a true cloud provider leveraging either software-as-a-service, infrastructure-as-a-service, or platformas-a-service technology. Which of these three cloud offerings you choose is normally driven by the tool you plan to use to ingest the data.

The question then becomes somewhat simplified. Is it more secure for the connection between your Industry 4.0 tool

and your manufacturing environment to be managed by you, or managed by a cloud service provider? It really comes down to how well you manage your own security posture.

The advantages you get by using a secure cloud provider should be deeper than your in-house resources from a security perspective because the costs are spread across multiple clients. The challenge is making sure that the provider is providing a secure service. How well have you vetted their security policies? Are they based on an international standard like ISO 27001?

Do they have an incident response plan that is effective? Are qualified individuals performing the appropriate level of threat hunting to assure your data is safe and secure? If the answers to these questions is yes, and assuming you are already providing similar services for your enterprise information technology strategy, then there is likely no difference in the security posture for cloud-based offerings than the one that you can create on your own in an on-premises environment.

Taking note of the scenarios described above, the next questions you need to ask yourself are: • Do you have the correct skills within your organization to address your manufacturing security posture?

• Have you done your homework creating an appropriate standards-based security offering for your manufacturing environment?

• Do your technology and system integration partners understand the security risks, and are they appropriately positioned to help you make your systems more secure?

• Do you have appropriate controls in place for your enterprise system, whether its located on-premises or is cloud based?

8/29/20 10:34 AM

42 ENTERPRISE VIEW AW SEPTEMBER 2020

T�e Prescription for Transformation is Clear: Better Analytics Diane Sacra

director of marketing, LNS Research

Prescriptive analytics is the only capability that suggests action. However, for it to work, an organiation’s analytics must be reliable and trusted.

2009_EnterpriseView.indd 42

A

mong the most hyped technologies in the industrial landscape today are artificial intelligence, machine learning, and Big Data. At the core of these advancements is analytics, with the ability to glean key information to make better decisions and drive industrial transformation. A recent LNS Research survey of nearly 6,200 plants compared analytical progress among industrial organizations today to efforts two years ago.

The results have shown that there has been a significant increase in formal analytics programs across industrial companies, which is very good news; but the study also reveals that manufacturers still have more data work to do.

As a result of the survey, LNS Research, in conjunction with MESA International, has just released its latest biennial report, “Analytics That Matter in 2020: A New World.” The comprehensive study provides an in-depth analysis on the use of analytics by industrial companies and offers specific recommendations for improvement. Moreover, the study looks at the impact the COVID-19 pandemic has had on manufacturers.

According to the survey conducted this year, among industrial companies, there has been a 52% increase in use of formal analytics programs. Furthermore, there has also been a 102% increase in diagnostic capabilities, and a 66% increase in predictive capabilities. These are significant improvements in the use of analytics, which is critical to developing an industrial transformation strategy and accelerating its success.

While growth in formal analytics and these types of capabilities are promising, one area that continues to lag behind is prescriptive analytics. The LNS Research survey reveals there has only been a 39% increase in prescriptive capabilities in the past two years—well behind the increases

in diagnostic and predictive analytics. Prescriptive analytics differs from its diagnostic and predictive counterparts by offering specific recommendations—i.e., what should we do—with predicted outcomes. This capability makes prescriptive analytics particularly important in readying an organization for future action and if/when situations.

For industrial companies seeking continuous improvement and ways to transform its operations, there are big opportunities within prescriptive capabilities.

Prescriptive is the only type of analytics that suggests specific actions. However, for it to work, an organization’s analytics must be reliable and trusted. Real-time optimization (RTO) in continuous process control is a common example of prescriptive analytics that is based on well-proven, first principle mathematical models that are understood by the process engineers who use them. RTO existed even before analytics was used in manufacturing, and as such, some may not consider it prescriptive. However, RTO provides the much-needed trust in analytics to make prescriptive effective.

The bottom line for manufacturers seeking industrial transformation and operational improvements is that the answers are at your fingertips—in your own data.

The key is to ensure your data is first trustworthy, available broadly, and demonstrates value. Then, employ the various types of analytics—including prescriptive analytics—to create effective action. Utilizing analytics is core to promoting a datacentric and learning-based organization, and is the primary pre-requisite for successful industrial transformation.

8/29/20 10:34 AM

ADVERTISER INDEX 43 AW SEPTEMBER 2020

COMPANY

TELEPHONE

WEBSITE

PAGE #

Automation24

800.250.6772

www.automation24.com

5

AutomationDirect

800.633.0405

www.BRXPLC.com

Digi-Key Electronics

800.344.4539

www.digikey.com/automation

Emerson Industrial Automation

888.889.9170

www.emerson.com/PACMotion

Festo

800.99.FESTO

www.festo.us

Galco Industrial Electronics

888.526.0909

www.Galco.com

15

Hammond Manufacturing

716.630.7030

www.hammondmfg.com

21

Inductive Automation

800.266.7798

www.demo.ia.io/automation

IQMS

866.367.3772

www.iqms.com

Motion Industries

800.526.9328

www.MotionIndustries.com

Opto 22

800.321.6786

www.opto22.com

PE CONNECTS

571.612.3198

www.packexpoconnects.com

13

Telemecanique Sensors

800.435.2121

www.tesensors.com/XXSonic

17

Wago Corporation

800.DIN.RAIL

www.wago.us/touchpanel

9

Winsted Corporation

800.447.2257

www.winsted.com/WELS

19

Cov-2 3 Cov-4 7

1 Cover-wrap 11 Cov-3

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Automation World ® is published 14x a year by PMMI with its publishing office, PMMI Media Group, located at 401 N. Michigan Avenue, Suite 300, Chicago, IL 60611; 312.222.1010; Fax: 312.222.1310. Periodicals postage paid at Chicago, IL, and additional mailing offices. Copyright 2020 by PMMI. All rights reserved.

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8/31/20 9:44 AM

44 KEY INSIGHTS AW SEPTEMBER 2020

The robot employment agency is actually a robots-as-a-service business model that gives industrial manufacturers the option to source needed labor instead of investing significant capital in purchasing the robots.

Stephanie Neil on MusashiAI’s robot employment agency. http://awgo.to/1091

By incorporating operator feedback into the app’s functions, it enables operations, maintenance, and production teams to train the AI (artificial intelligence) engine to adapt to specific implementations.

Luis Rodriguez on Aveva Insights Operations Management Interface app. http://awgo.to/1092

Most algorithms that use depth images from active infrared sensing identify regions of space as either empty or occupied. However, this is inadequate for a safety system because a safety system requires that humans be sensed affirmatively.

David Greenfield on Veo Robotics approach to industrial robot safety for collaborative applications. http://awgo.to/1093

Honeywell estimates its Enabled Services can deliver increased value by reducing the number of incidents per year by 40%, with a net decrease in total cost of ownership of 15%.

Aaron Hand on Honeywell’s array of technologies and services highlighted for industry’s response to COVID-19. http://awgo.to/1094

With an infeed rate of 120 products/min from each of two lanes, the system can load both small shelf-ready packaging cases, as well as larger trays, and reusable plastic crates.

Anne Marie Mohan on mass customization flexibility, featured in Packaging World’s Packaging Robotics Playbook. http://awgo.to/1095

2009_KeyInsights.indd 44

8/29/20 10:37 AM

Full Page Ad.indd 73

8/29/20 11:04 AM

S l bl M Scalable Motion i Solutions for Your High Performance Applications Emerson’s new PACMotion™ portfolio enables you to scale your motion capabilities without sacrificing performance. Our new family of servo motors, servo drives, software and motion controller easily integrates with our PACSystems portfolio for a complete solution for high-speed, high-precision processes in packaging, printing, material handling, semiconductors, food and beverage and manufacturing or other applications where a high number of axes are needed.

Emerson offers end-to-end automation solutions for your high-performance machinery applications. Visit www.emerson.com/PACMotion to learn more. Reach out to us directly at ContactUs@Emerson.com

The Emerson logo is a trademark and service mark of Emerson Electric Co. ©2020 Emerson Electric Co.

Full Page Ad.indd 73

8/29/20 11:05 AM