Automation World July 2021 by PMMIMediaGroup

JULY 2021 / www.AutomationWorld.com

20 WHEN ARTIFICIAL INTELLIGENCE COMES TO CONTROL 23 26 08 14 30 34

Industrial Ethernet Advances Broaden Network’s Value U.S. Air Force Looks to Fly with 3D Printed Parts Cybersecurity Lessons from the Colonial Pipeline Breach Simulation Platform for IoT Network Testing Automation World Exclusive Interview with Beckhoff Hidden Opportunities in Your Order-to-Cash Process

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CONTENTS 3 AW JULY 2021

JULY 2021 | VOLUME 19 | NUMBER 7

When Artificial Intelligence Comes to Control

Industrial Ethernet Advances Broaden the Network’s Value Across Industries

U.S. Air Force Looks to Fly with 3D Printed Parts

Automation World Exclusive Interview with Beckhoff

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Applications of machine learning and other forms of artificial intelligence have been recognized in robotics and analytics. Now the technology is adding some spice to basic control applications.

Recent innovations in industrial Ethernet’s physical layer—Single Pair Ethernet and Ethernet Advanced Physical Layer—are being heralded as game-changers for their ability to extend Ethernet cabling lengths and address hazardous environment concerns.

Metal additive manufacturing is being applied to the production of oil lubrication system parts for the GE F110 engine, which powers the Air Force’s F-16 jet fighter.

An interview with Hans Beckhoff, Beckhoff Automation managing director and founder, and Kevin Barker, president of Beckhoff USA, offers insights into where industry is heading with automation technology.

6/24/21 9:26 AM

4 CONTENTS AW JULY 2021

EDITORIAL

ONLINE 6

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

INDUSTRY DIRECTIONS 8

Cybersecurity Lessons from the Colonial Pipeline Breach

BATCH OF IDEAS 10

Manufacturing Skills Gap Widens in the Wake of COVID-19

PRODUCTION PERSPECTIVES 11

Creating the Digital Thread to Connect OEMs and End Users

PERSPECTIVES 13

David Greenfield Director of Content/Editor-in-Chief dgreenfield@automationworld.com / 678 662 3322 Stephanie Neil Senior Editor sneil@automationworld.com / 781 378 1652 David Miller Senior Technical Writer dmiller@automationworld.com / 312 205 7910 Emma Satchell Managing Editor esatchell@automationworld.com / 312 205 7898 Jim Chrzan VP/Content and Brand Strategy jchrzan@pmmimediagroup.com / 312 222 1010 x1470 Kim Overstreet Senior Content Strategist, Alignment koverstreet@pmmimediagroup.com James R. Koelsch, Lauren Paul, Jeanne Schweder and Beth Stackpole Contributing Writers

ART & PRODUCTION

How Festo Applies Artificial Intelligence for Predictive Applications Simulation Platform for IoT Network Testing

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

NEWS 16

New Tool for Troubleshooting Industrial Ethernet PMMI News Attract and Retain a Quality Workforce, Insights with Gardner Carrick at PMMI’s ELC

INDUSTRY-SUPPLIED CONTENT 28 Analytics Overload: Why You’re Confused

NEW PRODUCTS 33 RFID Handheld Computer Electromagnetic Flowmeter Industrial 5G Router

ADVERTISING

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 Kelly Greeby Senior Director, Client Success & Media Operations Alicia Pettigrew Director, Product Strategy

AUDIENCE & DIGITAL

David Newcorn Executive Vice President Elizabeth Kachoris Senior Director, Digital & Data Jen Krepelka Director, Websites + UX/UI Sarah Loeffler Director, Media Innovation

FINANCE VIEW 34

Hidden Opportunities in Your Order-to-Cash Process By Larry White

PMMI MEDIA GROUP

IT VIEW 35

Smart Manufacturing in a Pandemic By Garrett Clemons

ENTERPRISE VIEW 36

Digital Continuous Improvement Can Deliver the Promise of Industrial Transformation By Diane Sacra

KEY INSIGHTS 38

Kurt Belisle Publisher kbelisle@pmmimediagroup.com / 815 549 1034 Jake Brock Brand Operations Manager jbrock@pmmimediagroup.com / 312 222 1010 x1320 Sharon Taylor Director of Marketing staylor@pmmimediagroup.com / 312 222 1010 x1710 Amber Miller Marketing Manager amiller@pmmimediagroup.com / 312 222 1010 x1130 Janet Fabiano Financial Services Manager jfabiano@pmmimediagroup.com / 312 222 1010 x1330 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 JULY 2021

PODCAST SERIES Is Fieldbus Technology Still Effective?

In this episode, learn about the combined use of fieldbus and Ethernet industrial networking technologies, even as Ethernet increasingly becomes the plant floor network of choice, in this discussion with Duane Grob of system integration company Avanceon.

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AUTOMATION WORLD TV Supply Chain Technology for a Changing World

In the wake of unprecedented supply chain disruption, a new suite of intelligence software products is helping companies to navigate. Watch this Take Five video to learn more.

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THE AUTOMATION PLAYBOOK The Automation Playbook is a useful source of information as you look for guidance in how to approach the Industrial Internet of Things, communication protocols, controls implementation, safety, asset management, predictive maintenance, the mobile workforce, and much more.

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AUTOMATION WORLD E-BOOK

Automation World’s Most Popular Articles Read Automation World’s best-read articles discussing the digitization of discrete manufacturing, how Kellogg manages cybersecurity risks, integrating open-source software with industrial automation, and more.

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SYSTEM INTEGRATOR BLOGS • Is the Pandemic Changing the Client Supplier Relationship? • Automating Industrial Business Processes with Business Process Modeling Notation • Protect OT from Cybersecurity Attacks • Additional Report Parameters Enhance Process Performance • Why IIoT Demand Continues to Grow

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8 EDITORIAL AW JULY 2021

INDUSTRY DIRECTIONS

Lessons from the Colonial Pipeline Breach By David Greenfield

dgreenfield@automationworld.com Editor-In-Chief/ Director of Content, Automation World

ot long ago, most cyber-attacks on industry happened largely behind the scenes. The companies whose systems were breached rarely went public about the event and if information about these events was ever discussed publicly, it was usually years after the event and few specific details beyond the nature of the attack were ever revealed. But that’s been changing as cyber-attacks have become more brazen and threaten the public at large. For example, on February 5, 2021, we learned about the remote access intrusion into the control system at a water treatment facility in Oldsmar, Fla., about 13 miles from Raymond James Stadium in Tampa where the Super Bowl was held just two days later. In May 2021, cyber-crime gang DarkSide claimed responsibility for compromising the Colonial Pipeline Company—one of the largest fuel pipelines in the United States. As a result, fuel outages were experienced across states in the eastern U.S. supplied by Colonial Pipeline.

Advice for industry

Considering the ongoing rise in cyber-attacks on industry, Ron Brash, director of cybersecurity insights at Verve Industrial, a supplier of industrial control system security, highlighted five key areas of focus to help industrial companies mitigate the threat of a cyber breach affecting their operations: Realize that industrial cybersecurity is not IT vs. OT, as operations can be affected by attacks on both sides of the system. “Organizations need to work on bringing these two organizations together to protect the entire

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system. Visibility and protection across the IT-OT landscape is key to protecting operations,” he said. The largest security gaps in industrial companies tend to be in the management and maintenance of security. “Firewalls may exist, but personnel have adjusted rule settings to allow remote access and created servers that route around critical protection layers; patching policies may exist, but the manual tasks that are often standard do not get completed given the urgencies of operations; and standard secure configurations may exist, but exceptions are made, users adjust them, new software is allowed, and ports are opened, leaving gaps in that secure structure,” said Brash. “[But often] there is no central visibility of these gaps.” Brash noted that the ability to consolidate the security status across all systems into a common database to track and ensure protections are maintained is critical to strong cybersecurity protections. “Owners must patch, segment, harden configurations, ensure appropriate backups, and limit access to least privilege,” he said. “These core, fundamental elements of security can be the difference between being a victim or not.” Rapid response and recovery are critical. The real advantage a company can have is the immediate ability to take actions across endpoints—IT or OT—to stop the spread of malware, Brash said. “This integration of detection and response actions allows industrial organizations to significantly reduce the spread—and cost—of ransomware attacks.” Have a plan for a conscious shutdown. “Incidents like the Colonial crisis have become the new norm within the critical infrastructure cybersecurity community,” he said. “As such, organizations should be adequately trained and prepared to handle incidents like this via a well-defined procedure.”

IoT device security

“Good security is rarely retrofittable, especially when it comes to IoT devices. It needs to be built in as a core fundamental and planned for to

exceed the anticipated lifetime of the product it is securing,” said Chris Hickman, chief security officer, at Keyfactor, a supplier of cryptography technology used to prevent network outages and secure machine identities in multi-cloud enterprises and IoT supply chains. Mark Thompson, vice president of product management at Keyfactor highlighted three common mistakes Keyfactor sees being made in industry as they relate to IoT device security, and how to avoid them: • Hardcoding credentials onto the device: Some IoT devices are limited due to hardcoded credentials, Thompson said. “This is a common outcome when manufacturers embed passwords or shared keys into firmware to help simplify development or deployment at scale. If [these keys are] accidentally leaked, threat actors or individuals without proper authority can access an entire fleet of devices.” To avoid this problem, Thompson recommends using strong mutual authentication between any connected devices or applications within the overall deployment. • Unsigned firmware: “It’s strongly recommended that device makers sign firmware with a tightly controlled code signing certificate that only permits access to authorized individuals,” said Thompson. “Another critical step is to keep an internal audit trail of all code signing activities. Using a trusted public-private key pair is the most effective means to secure device firmware and have the ability to check and verify the device’s signature before booting the device or installing firmware updates.” • Weak authentication and encryption: “Implementing strong cryptographic keys and algorithms that match the device’s use case applications are critical to hardening its long-term security,” Thompson said. “Equally important is ensuring sufficient entropy to produce an encryption key; randomness in key generation is a priority through this process.”

6/24/21 9:24 AM

We see connected and smarter operations that prevent equipment failures before they happen. Emerson delivers real-time insight to equipment health, helping detect and prevent asset failures before they impact production. With our advanced analytics and control and monitoring technologies, food and beverage manufacturers can run smarter operations with reduced costs, minimized downtime and access to actionable data. Learn more at Emerson.com/FoodBeverageReliability Video: Digital Transformation Solutions for Food and Beverage Operations

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10 EDITORIAL AW JULY 2021

BATCH OF IDEAS

Manufacturing Skills Gap Widens in the Wake of COVID-19 By Stephanie Neil

sneil@automationworld.com Senior Editor, Automation World

ver the past six years, the manufacturing industry successfully added about 600,000 jobs, making some headway toward solving its biggest challenge of attracting and retaining a quality workforce. But it’s one step forward and two steps back for the industry. That’s because it lost its momentum last year when the pandemic wiped away 1.4 million U.S. manufacturing jobs. While we recouped the majority of those jobs by the end of 2020, about 570,000 jobs remain unfilled according to information released in the 2021 Manufacturing Talent study from Deloitte and the Manufacturing Institute. This is the duo’s fifth manufacturing talent study which was fielded between December 2020 and February 2021 and surveyed more than 800 U.S. manufacturing executives across all sectors. Despite the fact that the unemployment rate remains high, the majority of survey respondents said that finding the right talent is now 36% harder than it was in 2018, with 77% of surveyed manufacturers saying they will have ongoing difficulties in attracting and retaining workers in 2021 and beyond. And, while there’s always a need for engineers, these companies are just trying to fill entry-level positions. All these positions require is a good work ethic and the ability to follow directions. There’s also a need for mid-level skilled jobs, such as welders or CNC machinists, which may require a certification, but not a college education. With so many people displaced from other industries like the hospitality and restaurant businesses, the

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question is: “Where are the people?” If we stay on this track, the U.S. manufacturing skills gap could leave as many as 2.1 million jobs unfilled by 2030, according to the study, which is concerning because manufacturing has the highest multiplier effect of any economic sector. “For every $1.00 spent in manufacturing, another $2.74 is added to the economy. Using this multiplier, leaving the open jobs unfilled in manufacturing could bring a potential negative impact to the U.S. economy of more than $1 trillion by 2030 alone.” There are a few reasons why we are not seeing people lining up to work on the factory floor. First, there’s the old stigma that it’s a dark, dirty, and dangerous place. The study found that the ongoing challenges in attracting entry-level and skilled workers in the right geographic markets are often the result of misconceptions about manufacturing work, especially amongst the younger generations who wonder if it can deliver rewarding career experiences with work-life balance. The other challenge relates to the ongoing digital transformation, which means the skills needed to run a smart factory will be very different than the skills used today. Deloitte developed a series of personas to describe the new kinds of roles that will be required in the future. Titles include: digital twin engineer, predictive supply network analyst, robot teaming coordinator, drone data coordinator, and smart safety supervisor. The good news is, the roles are not mundane. A robot teaming coordinator, for example, is responsible for training humans and robots to work together collaboratively for optimal human-machine interactions. That sounds like an interesting job! However, the manufacturing community will need to change its approach to recruiting to even get folks in the door to become a robot teaming coordinator. Specifically, the report notes the growing need for diversity, equity, and inclusion (DEI). “In manufacturing, DEI is often focused on women because the industry has historically been maledominated. Fewer than one in three manufacturing professionals are women today, despite

representing nearly half of the overall workforce in the United States.” In addition, a separate DEI study by Deloitte and the Manufacturing Institute notes that women are more likely to leave the industry than men. This is partially due to the circumstances of the pandemic, but it could also be due to the way work is organized in manufacturing. The study notes that the lack of work-life balance and flexible work arrangements have been a top reason many women give for leaving the industry. It’s important to have a diverse workforce for a number of reasons. Of course, offering an environment of equity where all people have fair access, opportunity, resources, and power to thrive is the right thing to do. But having DEI in a company has been proven to drive business performance and innovation. According to the study, “An analysis of Fortune 500 manufacturing companies reveals that companies fostering diversity and building inclusive environments are more likely to have stronger financial performance.” In addition, 63% of manufacturers surveyed link the business benefits of DEI to the ability to attract, retain, and develop talent. For more information and recommendations for closing the manufacturing skills gaps, you can find the study at awgo.to/1216.

“’For every $1.00 spent in manufacturing, another $2.74 is added to the economy. Using this multiplier, leaving the open jobs unfilled in manufacturing could bring a potential negative impact to the U.S. economy of more than $1 trillion by 2030 alone.’”

6/24/21 4:34 PM

EDITORIAL 11 AW JULY 2021

PRODUCTION PERSPECTIVES

Creating the Digital Thread to Connect OEMs and End Users By David Miller

dmiller@pmmimediagroup.com Senior Technical Writer, Automation World

he relationship between original equipment manufacturers (OEMs) and manufacturing end-users is undergoing a sea change in terms of how equipment is purchased and maintained. Numerous forces are responsible for this shift. Most prominent among these is the availability of fewer onsite engineers. This operating reality has led manufacturers to outsource much of their maintenance operations, requiring them to rely more heavily on remote condition monitoring and predictive maintenance techniques provided by OEMs themselves. As a result, new business models, bolstered by digital transformation, have begun to spring up among OEMs. For instance, performance-based costing, which bills endusers based on the amount of throughput a machine achieves, has started to usurp the flat-fee model. This not only reduces upfront capital expenditures for manufacturers, but incentivizes OEMs to continuously improve the performance of their equipment, making them more competitive and delivering better results for end-users. In addition, as these machines-as-a-service type arrangements become more prevalent, they are being tapped to provide an end-toend data pipeline between OEMs and endusers that allows those who design and engineer equipment to better understand how their products are used in the field, effectively

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extending the process of asset lifecycle management to the planning and design stage of a piece of machinery. These new partnerships between OEMs and manufacturers are increasingly being made possible by partnerships between OEMs and providers of industrial software. One such example is the recent expansion of a partnership between Siemens and SAP, wherein Siemens will begin offering SAP’s Asset Intelligence Network, the SAP Asset Strategy and Performance Management Application, and the SAP Enterprise Portfolio and Product Management package. In turn, SAP will offer Siemens’ Teamcenter software service lifecycle management portfolio. SAP’s Asset Intelligence Network and its accompanying applications allow end-users to collect and aggregate sensor, time series, and status data from equipment into a centralized repository that can be used to build a digital twin for sharing with others—in this case, an OEM. By studying the digital twin, OEMs will not only make suggestions for maintenance and improving performance, but will be able to learn more about how their equipment is actually used in the field to improve the design of future products. Supporting this data sharing process, Siemens’ Teamcenter software enables engineers to share computer-aided design (CAD) and design data via the cloud for real-time, remote collaboration at the product development stage. Users can view, measure, and markup CAD files, share projects, and review designs via augmented reality on tablets and other mobile devices. According to SAP and Siemens, the integration of this diverse set of offerings will bolster collaboration across the entire supply chain, offering OEMs and manufacturers alike the possibility to discover end-to-end efficiencies that previously would not have been possible. By using SAP’s Asset Intel-

ligence Network and Siemens’ Teamcenter software together, the companies contend that a consistent digital twin of a plant’s operation can be viewed by plant operators, OEM service teams, and engineers working in new product development. “Siemens is helping industrial companies make more confident decisions by closing the loop between IT and OT,” said Cedrik Neike, member of the managing board of Siemens and CEO of Siemens Digital Industries. “Through this partnership, we are enabling a true digital thread that integrates real time operations-based data with virtual product and asset models using components from both Siemens and SAP to provide operational insights. This can accelerate digital transformation for industrial equipment owners, operators, and manufacturers who can offer new business models including performance and usage-based cost, and to more efficiently use assets.”

“According to SAP and Siemens, the integration of this diverse set of offerings will bolster collaboration across the entire supply chain, offering OEMs and manufacturers alike the possibility to discover end-to-end efficiencies that previously would not have been possible.”

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PERSPECTIVES 13 AW JULY 2021

How Festo Applies Artificial Intelligence for Predictive Applications By David Greenfield

Editor-In-Chief/Director of Content, Automation World

s part of Festo’s exhibit at the 2021 virtual Hannover Messe event, the company featured its Festo AX software, developed by Festo and Resolto (a Festo subsidiary specializing in artificial intelligence). Dr. Frank Melzer, member of Festo’s management board for product and technology management, noted that Festo uses condition monitoring and machine learning to monitor the behavior of its customers' components, machines, and systems. “AI is the enabler that takes the automation business to a new level of efFesto uses predictive maintenance in the automotive industry to increase ficiency,” he said. “We continuously efficiency in the maintenance of servo-pneumatic welding guns by avoiding monitor machine data and check it against our AI model, which deunforeseen downtimes and service and complaint costs. Source: Festo. scribes the good state of a comrienced in this company’s production operaHighlighting the open architecture of Fesponent or machine. The AI algotions being avoided and allowing repairs to be to’s AI technologies, Dr. Melzer said Festo's rithms then detect deviations from the normal scheduled during non-production times. AI technologies can “be easily integrated via state and can also predict them. Particularly in In the other application highlighted at the IoT gateways and standardized protocols with industrial intelligence, the mixture of algorithms event, Festo used a predictive energy applicaother components.” paired with the specific expertise of an engineer tion of AI for a customer in the food packagTo help demonstrate how the use of AI can is a decisive success factor for the implementaing industry. Here, the packager's goal was to vary depending on its application, Festo pretion of AI-based automation applications.” reduce the energy consumption of its pneusented two use cases in different matically operated bottling plant to reduce industry verticals. CO2 emissions and costs. After examining In one application for the autothe plant’s compressed air processes, Festo motive industry, Festo explained applied its C2M energy efficiency module to how a German automobile manumonitor compressed air consumption, profacturing customer uses predictive vide information about possible leaks, and maintenance to improve the mainprevent the system pressure from falling betenance and reduce the downtime low a defined standby pressure level. of its servo-pneumatic welding The C2M module includes a pressure reguguns. Data from the welding guns lator, on-off valve, sensors, and fieldbus comis continuously collected and evalmunication in a single unit. According to Festo, uated using Festo’s AI algorithms the application of the C2M module has worked to predict failures of the welding so well for the customer that they now want to guns. Evaluation of this data allows use the data collected by the C2M for potential failures to be identified before Dr. Frank Melzer, member of Festo’s predictive maintenance applications. they occur. According to Festo, management board for product and this translates into about a quarter of the downtimes currently expetechnology management.

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14 PERSPECTIVES AW JULY 2021

Simulation Platform for IoT Network Testing By David Miller

Senior Technical Writer, Automation World

mong the biggest challenges of the Industrial Internet of Things (IIoT) is the installation, management, and integration of an unprecedented array of data-producing connected devices. The increased loads of data created by the IIoT’s

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proliferation of connected devices places a great strain on industrial networks. To date, several technologies are being used to ease this burden. For example, MQTT (message queuing telemetry transport), an industrial communication

protocol which uses a publish/subscribe transmission paradigm to limit the volume of data exchange on a network, has significantly reduced bandwidth usage. In addition, the rise of more sophisticated simulation technology—often driven by artificial

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PERSPECTIVES 15 AW JULY 2021

intelligence (AI) and machine learning—has allowed for explosive advances in the prediction and forecasting of issues that may arise within networked systems as they become more complex. This applies in many areas, including: Supply chain management, in which parallel planning for various possible scenarios has been made possible by virtual optimization models; predictive maintenance, where machine learning algorithms trained on large quantities of data can help operators anticipate equipment failures before they occur; and in the use of interactive digital twins that can help plant managers spatially optimize their facilities. Now, the combined capabilities of simulation and MQTT are being extended to the testing of large-scale IoT networks via the use of Swarm, a new offering from HiveMQ, a provider of MQTT broker software. HiveMQ’s Swarm is a distributed platform that can create hundreds of millions of virtual network connections that simulate devices, messages, and MQTT top-

ics. From there, the Swarm software is able to develop scalable and reusable scenarios that mirror real-world device behaviors. According to Mary Brickenstein Ofschen, technical writer at HiveMQ, the custom scenarios created by Swarm allow end-users to scale the number of devices involved in a simulation by changing simple parameters and observing how individual assets will behave within the overall system as a result. This can help determine how to distribute a load intelligently across a network for the purpose of stress testing. “For many companies, it is very important to understand exactly how their current development plans impact the entire system. For example, what will the backend infrastructure look like if the number of products sold each year doubles. The same is true for the industrial IoT space. Let’s say you want to expand your gateway infrastructure, add a new SCADA system, or increase the primary and secondary applications in your Sparkplug space,” Ofschen

said. “You need to discover the potential bottlenecks in your system, but it’s hard to do. The ability to build reusable, declarative scenarios that HiveMQ Swarm provides [means that you] can build scenarios that truly match your planned use case, put the scenarios on version control, and copy and modify your testing parameters as needed. You can even build your own library of different test scenarios and use them to automate the testing of your entire solution.” Swarm features multi-cloud functionality and can also be deployed on a local machine with no additional requirements. Currently, the software supports up to 10 million MQTT connections. In addition to its simulation capabilities, Swarm offers built-in monitoring, logging, and reporting, as well as REST API compatibility, making it possible to integrate with a centralized infrastructure.

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16 NEWS

AW JULY 2021

New Tool for Troubleshooting Industrial Ethernet By David Greenfield

Editor-In-Chief/Director of Content, Automation World

he growing prevalence of Ethernet on the plant floor has been clear for years now, but the increase in remote work brought on by the pandemic has only served to underscore the importance of Ethernet in industry. Other drivers behind Ethernet’s wider use on the plant floor, such as connectivity to enterprise systems and the ability to transmit greater amounts of data, as well as the general push toward Industry 4.0 and Industrial Internet of Things applications, remain key reasons why Ethernet continues to replace many fieldbus installations.

Like any industrial communications technology, Ethernet requires specific maintenance tools to ensure the network remains up and running with minimal or no downtime. To help address specific Ethernet issues, Fluke Networks recently introduced the LinkIQ-IE Cable+Network Industrial Ethernet Tester, which is designed to troubleshoot network cabling. To understand the effect of Ethernet cabling issues in industry, Indu-Sol, an industrial network support organization, reports that more than half of their industrial Ethernet service calls result from cabling-related issues. Fluke Networks says that, by combining their state-of-the-art cable measurement technology and basic tests for industrial Ethernet switches, LinkIQ-IE speeds and

simplifies the discovery of network failures via a touchscreen interface that’s similar to a smartphone. “Troubleshooting industrial Ethernet problems often involves the use of complex tools such as protocol analyzers that require years of training or trial-and-error approaches such as running bypass cable in the hope of solving the problem,” said Walter Hock, vice president of products at Fluke. “We designed LinkIQ-IE to provide answers to key troubleshooting questions in seconds through an easy-to-use touchscreen interface and a price that puts it in the reach of factory teams.” James Sinn, owner of Sinn Development, an Oakville, Ontario-based provider of design, installation, and troubleshooting services, said, “With the ability to display

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a single-test approach that automatically provides the appropriate measurements based on what’s at the other end of the cable. For an open cable, it shows the length and pairing. If it’s terminated with the supplied remote, the test result shows the maximum data rate the cable can support—up to 10 Gb/s. If LinkIQ-IE Cable+Network Industrial the cable is connected to a switch port, LinkIQ-IE shows Ethernet Tester kit from Fluke. the name of the switch plus the port name, speed, and duplex. If PoE is switch port, VLAN, and PoE (power over used, it will display the power and class (up to Ethernet) information, LinkIQ-IE is a great 90 W or Class 8) and then load the switch to addition to our toolkit. The first thing I did verify the power can be delivered. with LinkIQ-IE was to test the cabling for The LinkIQ-IE has an RJ-45 type conneca face shield production line. It instantly showed me that the cause of the problem tor and includes cabling and adapters for conwas a disconnected shield that made the nection to M12-D, M12-X, and M8-D conneccable susceptible to the EMI (electromagtors commonly used in industrial applications. netic interference) from a nearby machine tool with a large induction motor.” According to Fluke, LinkIQ-IE is based on

LinkIQ-IE Cable+Network Industrial Ethernet Tester from Fluke.

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PMMI Executive Leadership Conference: How to Attract and Retain a Quality Workforce

Attracting and retaining a quality workforce in manufacturing is a systemic key business challenge.

By Melissa Griffen Contributing Editor, PMG

t the 2021 Executive Leadership Conference (ELC) hosted by PMMI, The Association for Packaging and Processing Technologies, Gardner Carrick, vice president of strategic initiatives at The Manufacturing Institute (MI) and National Association of Manufacturers (NAM), presented technical workforce development trends, both in connection to and beyond COVID-19. Results show that since 2010 there has been an increase of nearly a million and a half jobs in manufacturing, which decreased when the pandemic hit. Though recent studies suggest the numbers have rebounded and are returning to previous counts. Beyond COVID-19, the second key business challenge of 2021 is the continuing struggle of attracting and retaining a quality workforce in manufacturing. Research proves that this issue is systemic and not transitory. There’s not a “strong enough pipeline of individuals desiring to go into a career in manufacturing, and not enough breadth of training programs

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to prepare them with skills to be successful in those careers,” said Carrick. MI and NAM prioritize the success of manufacturers and their workforce, whether it be through fighting for manufacturer rights, providing news and intelligence about the industry, or through initiatives to support the diverse American workforce by providing skilled training programs. The MI and NAM efforts, presented at ELC, are: 1. Creators Wanted, which exhibits in towns to invite high school students to enter the manufacturing field post-graduation. MFG Day–when facilities open their doors on the first Friday in October–has been combined with Creators Wanted. It includes virtual tours and 3D maps, as well as an MFG Day webinar series. 2. Military and veteran recruitment starts these brave men and women on their next career. Individuals on their last six months of service can start training in the MI programs, which have recently been modified to include networking days with manufacturers. In addition, both non-commissioned and commissioned officers have shown increased

interest in leadership roles in manufacturing. These programs are available at five U.S. military bases. 3. The STEP Women’s Initiative, which includes training women to be role models in their community. More than 800 women have been recognized so far, with hundreds of companies participating. 4. The NAM Pledge of Action ensures broad-based recruiting strategies “to cast as many nets as wide as possible in order to fill the roles that we need,” said Carrick. This allows for greater diversity in the workforce by reaching out to minority communities. 5. The Second Chance operation is for those with criminal records. Studies done on retention routes and productivity of individuals show that those in the Second Chance program have a competitive drive to keep their positions.

Apprenticeships and credentials

Once a workforce is obtained, however, training is indispensable in making each individual’s manufacturing career a success.

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future workforce. This fund allows companies to work with local education programs to donate money or equipment. PMMI then matches company donations up to $50,000. According to PMMI, this fund is a key component in helping companies build stronger

relationships with local education programs. Learn more about PMMI’s workforce development programs at www.awgo.to/1211.

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Manufacturing-related positions focus on keeping machines working, which requires technical skillsets that go beyond the abilities of technical colleges. Carrick emphasizes that companies, with their up-to-date knowledge, need to be involved in educating future generations as well as the development of scholastic programs every step of the way, including apprenticeships. This is also a great opportunity to offer debt-free education and show the new workforce that the company is invested in them, which Carrick says will help gain their trust. An apprenticeship program highlighted by Carrick at the ELC event is Toyota’s FAME, the Federation for Advanced Manufacturing Education. FAME is a multi-skilled maintenance technical program operated by a group of companies, which promotes professional behaviors in dress and speech, and educates workers on the culture of manufacturing; for example, how to think as a maintenance employee. Another aspect of forming a quality workforce is credentialing. The credentials market is filled with credentials that are lacking, creating confusion on industry standards. NAM and MI have created tools to evaluate individuals and credentials in an attempt to rectify this confusion. Carrick said states are already lining up to back this standardization.

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PMMI efforts to build the workforce

PMMI has invested in a single employer model with Amazon to develop an apprenticeship program. Amazon wanted to develop a program to upskill current employees, which would build a baseline to allow individuals to make a career in the industry. The company had been looking for different models and certifications to provide standards they could follow. PMMI’s mechatronics’ certification program became the base of Amazon’s apprenticeship program, which allows individuals to obtain certifications as well. PMMI saw a huge increase of 223% in utilization of the certification program throughout 2020. This increase is expected to continue as more schools offer the certification program thanks to the Amazon apprenticeship program. Like the miltiary-focused MI and NAM programs mentioned above, PMMI is also working to make the military aware of the industry and become properly trained. PMMI has also created a Skills Fund for the

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When Artificial Intelligence Comes to Control Applications of machine learning and other forms of artificial intelligence have been recognized in robotics and analytics. Now the technology is adding some spice to basic control applications. By James R. Koelsch, Contributing Writer, Automation World

sing your noodle to think things through tends to make things go much more smoothly—even if you’re just a high-speed food packaging machine wrapping instant noodles. That’s an important lesson gained from machine learning technology used by systems integrator Tianjin FengYuLingKong of Tianjin, China. This form of artificial intelligence (AI) allowed the firm’s engineers to develop a multivariable inspection model for one of China’s largest producers of noodles. Relying on this model, the control system for the packaging lines can now deduce whether sachets containing spices and dried vegetables for flavoring were placed correctly on the precooked noodle blocks before each block is individually wrapped. This ability is an example of how machine learning and other forms of AI are moving beyond applications like robotics and analytics and into control applications. In Tianjin FengYu’s case, there was no other cost-effective way to check whether an occasional sachet of flavorings might have slipped between two blocks of noodles and been cut open by a cross-cutting tool. Although cutting a sachet generates measurable signals within the machine, other events such as vibration and changes in packaging material, conveyor speed, and cutting tension also

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affect those signals, making conventional forms of process monitoring unreliable. For this reason, Tianjin FengYu decided to develop, train, and deploy a mathematical model using TwinCAT Machine Learning from Beckhoff Automation. The integrator’s engineers collected sensor data via EtherCAT terminals and TwinCAT Scope View charting software. Then, the data were correlated into

a model using TwinCAT Condition Monitoring, and the model was trained using an opensource framework called Scikit-learn. After being saved as a description file in a binary format suited for serialization in TwinCAT, the trained model was loaded into a CX5100 series embedded PC, which runs the model in real time. This embedded PC is integrated with the main controller on the packaging line.

The control system can run the model in real time as each packaging line wraps about 500 packages of noodles per minute. “A trained model actually runs fairly quickly,” notes Beckhoff’s Daymon Thompson. “And that’s what’s usually running in the controllers.” Training the model is a different story, however. Thompson says that training needs a lot of processing power, as much as 30 minutes to a full day, depending on the model and the computer training it. So, the initial training and any subsequent retraining are often done on a server or an offline controller. Besides in-process inspection, another application for machine learning in controls is the optimization of motion profiles. Consider a conveyor system that carries payloads around corners and coordinates motion with loading and other activities in a demonstration created by Beckhoff using its eXtended Transport System (XTS). “Instead of just running everything around as fast as we can to get in line for the next synchronized event, we want the motion to be optimized to minimize energy consumption and wear and tear on the mechanics,” explains Thompson. The machine learning algorithm figures out exactly what the motion profile should look like. “Because the motors driving the system need to be coordinated in real time, the

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motion profile really needs to be built into the machine control,” notes Thompson. “It can’t be done on a server or even an edge device.”

AI benefits closed-loop control

“Traditionally, PLC programmers would write ladder logic to tune systems with either creative rungs of arithmetic or PID control blocks,” says Kevin McClusky, co-director of sales engineering at Inductive Automation. “Today, closed-loop control with AI allows users to feed data into predictive models that can optimize output based on past performance or cost reduction, allowing far more complex algorithms to be applied to achieve efficiency or productivity goals.” He reports that the catalogs of several PLC manufacturers now offer AI modules for closed-loop control. Although not every application needs the technology, these modules are another set of tools in the toolbox. McClusky compares them to a simple PID block in ladder logic. “It’s not needed in a lot of applications, but it sure is handy in applications that can benefit from it,” he says.

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“Model outputs can be integrated into the control scheme to extend the capabilities of classical control methods,” adds Jennifer Mansfield, marketing manager—analytics at Rockwell Automation. “Challenging problems, like enabling predictive maintenance or dynamic control, are better addressed with machine learning than classical control.” Illustrating her point is the model predictive control (MPC) that EnWin Utilities Ltd. implemented to mitigate pressure spikes in the water distribution system in Windsor, Ontario. These spikes had been contributing to an increasing number of watermain breaks in the aging system. The old control scheme had depended upon PID logic that maintained a flow setpoint based upon outlet header pressure. Pressure would vary whenever operators would start and stop pumps at the two pumping stations and an auxiliary booster station to adjust flows to compensate for fluctuating demand. To even out pressure, EnWin chose an MPC-based system that could handle more variables than just flow and outlet header

pressure. Working with engineers from Rockwell Automation, EnWin began by creating 17 remote pressure stations throughout the water distribution system. The team also installed server-based MPC on its existing supervisory control and data acquisition (SCADA) system. The system now maintains the lowest possible pressure for producing adequate flow as demand changes. To optimize pressure and flow control further, the main campus uses a new ControlLogix controller with onboard MPC. “We knew we could optimize the system by incorporating pump start-stop functionality and flow control valves,” explains Quin Dennis, an application engineer at Rockwell Automation. “But given the existing interval speed, [server-based] MPC would not be able to make system adjustments quickly enough to mitigate the rapid pressure spikes from pump starts or stops.” Onboard MPC, however, reduced the 15 to 16 second interval speed down to 0.5 to 1 second. The system is now responsive enough to regulate the speed of the pumps and adjust

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Real-time inference results

control valves to offset any pressure spikes. By replacing PID logic with MPC at the controller level, as well as at the server level, EnWin was able to reduce watermain breaks by 21%. It also reduced average pressure by 2.8 psi and standard deviation by 29%, saving the company $125,000 in annual energy and leakage costs.

Predictive applications

Another benefit of AI is that it can help users peer deeper into their processes than controllers would otherwise permit. This is especially true in applications that require processing large amounts of data. “AI is now being implemented on the edge in situations where large volumes of data must be analyzed quickly before being sent to the cloud,” observes Joe Berti, vice president of AI applications at IBM Corp. “As a result, smart technology is broadening engineers and technicians’ understanding of their assets’ health by capturing and interpreting more information faster than any human could.” Consequently, Berti thinks that the biggest contribution AI and machine learning are making to controls technology is the ability to streamline detection and resolution of developing problems before they have a chance to escalate. “In the past, an asset might have been inspected on an annual basis,” he says. “Now, IoT sensors and enterprise asset management systems can detect patterns in asset data and then translate those findings into potential problems.” An example of this kind of application can be seen in the use of AI to discover oil degradation on a food packaging line installed by Novate

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Artificial intelligence used on noodle packaging machines by Tianjin FengYu detect an anomaly (highlighted in red). Real-time inference results like these are displayed in TwinCAT Scope View. Image courtesy of Beckhoff Automation.

Solutions Inc., an engineering and technology services firm based in West Sacramento, Calif. The clues to the problem came from IBM’s cloud-based AI technology and Maximo Monitor software, which Novate uses to provide a process monitoring service. The AI noticed that the average torque of a servomotor had been increasing over time, so the Novate solution flagged the equipment for inspection. Upon being alerted by Novate engineers, the production crew at the food producer checked the packaging equipment and found that the oil had not been changed as the maintenance log had suggested. The oil had completely degraded, causing the motor to work increasingly harder over time.

Trained for decision-making

Another application for AI in basic control is the automation of decision-making in continuous processes. “Here, an AI system controls a part of a facility or operation, sending signals to do basic control of different pieces of equipment,” says Inductive Automation’s McClusky. He points to the way a type of machine learning known as reinforcement learning is being deployed by Andritz Automation, a worldwide systems integrator headquartered in Graz, Austria. In reinforcement learning, models are trained to make a sequence of decisions by means of a trial-and-error method that strives to maximize a cumulative score of rewards and penalties. In what may have been the first implementation of this AI technology in continuous industrial processes, Andritz engineers in

Canada and Germany collaborated on developing prototype software. They then implemented the prototype in a pilot program at Newmont GoldCorp., a Vancouver-based goldmining company. This prototype uses the integrator’s process simulation software as the training ground for machine-learning algorithms. The AI engine learns by interacting with several simulations as they run. A user can set up batches of training scenarios, such as particular plant malfunctions that the AI engine needs to know. After the training exercises are performed, the algorithms are stored and used for automatic plant control. A key technology for developing and implementing this AI engine was Inductive Automation’s Ignition development environment for SCADA. Ignition provided a bridge between the AI engine and either the integrator’s process simulation software or the real plant, using scripted HTTP calls on one side and OPC on the other. Ignition’s sequential function charts control the dispatch of training scenarios. All scenario configuration and training results are stored in a SQL database. During the training process, the two teams in Canada and Germany were able to work on the project at the same time because the training environment was deployed on a small virtual network on a Microsoft Azure cloud server in Europe. Each team could run Vision clients simultaneously and access the database gateway and simulation machines.

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Industrial Ethernet Advances Broaden the Network’s Value Across Industries

By David Miller, Senior Technical Writer, Automation World

ot so long ago, many doubted that industrial Ethernet could ever take the place of legacy fieldbus on the plant floor. Prior to the rise of deterministic Ethernet communication protocols such as EtherCAT, EtherNet/IP, and Profinet, Ethernet simply wasn’t capable of accommodating the extremely rapid cycle times mandated by complex motion control applications, which often require control loop updates to take place within the space of mere milliseconds to function properly. However, with these issues solved, Ethernet has increasingly become the preferred industrial network, particularly in discrete manufacturing. According to Michael Bowne, director of technology marketing at PI North America, four Profinet nodes are now sold for every one Profibus node sold; just a decade ago, those numbers were reversed. Despite the rise in preference for industrial Ethernet networks, many fieldbus installations remain in place, particularly in the process industries where the shift to Ethernet has been more challenging. One of the reasons for this is that longer cable runs are often needed in large, outdoor environments common to the oil and gas industry. With typical industrial Ethernet being limited to a maximum length of 100 meters to prevent signal decay, this can present an issue. Moreover, with many process industry applications taking place in areas classified as hazardous zones and divisions by the National Electric Code, costly safety measures that require specific expertise must be undertaken to ensure Ethernet cabling and connectors will not ignite a flame. Recent innovations in Ethernet’s physical layer—the first tier of the Open Systems Interconnection (OSI) model, a conceptual-

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framework used to describe the various functions of a networking system—may help to surmount these obstacles. Single Pair Ethernet (SPE) and Ethernet Advanced Physical Layer (APL) are two Ethernet innovations currently leading the way for greater expansion of Ethernet in industry, and both bring with them an assortment of potential benefits. Simply put, SPE is a form of Ethernet that uses a single twisted-pair of wires, whereas other forms of ethernet use two or three. Similarly, APL is a type of SPE combined with IEC 60079 Two-Wire Intrinsically Safe Ethernet (2-WISE) capable of being deployed with pre-existing Fieldbus Type A cabling for use in hazardous environments. While the distinction may seem minute, many industry insiders are hailing the development as having significant implications for industrial networking deployments. “This is going to be the same type of step change that happened in factory automation when we moved from fieldbuses to industrial Ethernet,” Bowne says. “All those benefits we gained from that—the same thing can happen in process control.”

SPE: Single Pair Ethernet

SPE uses a single twisted pair of wires, as opposed to the two or three used in other forms of industrial Ethernet.

Several qualities possessed by SPE make it ideal for use in process industry environments. First, its maximum length is 1,000 meters—10 times that of previous industrial Ethernet forms. That said, this extension isn’t accomplished without some trade-offs. SPE’s communication speed is 10 Mbit/second, while four- and eight-wire Ethernet can reach speeds ranging from 100 Mbit/second to as high as 10 Gbit/second. Still, this represents a marked improvement over both fieldbus, which has a maximum communication speed of 31.25 Kbit/second, and HART,

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One of SPE and APL’s primary advantages for the process industries is their substantially greater cable length compared to other forms of industrial Ethernet.

which has a maximum communication speed of 1,200 bits/second. In this way, SPE represents a kind of middle-ground between legacy fieldbus and other forms of industrial Ethernet. While fieldbus might not currently offer data transmission speeds that can fully tap the larger quantities of data being produced by Internet of Things (IoT)-equipped devices, four- and eight-wire Ethernet may provide more than is necessary, says Guadalupe Chalas, senior marketing specialist at Phoenix Contact. “For these field devices, you might need longer cable distances but less bandwidth. So, what happens is if you’re talking about bandwidth specifically, you don’t want to put a standard Ethernet connection of 100 Mbit/ second on something that only needs eight or 10 Mbit/second. That would be overdesigned,” Chalas says. “In that case, you’re using an expensive connection on an application that doesn’t need it.” In addition, SPE has swapped the RJ45 connectors native to most Ethernet cables. Not only are SPE’s connectors more rugged, and thus better suited to harsh industrial conditions, but they are significantly smaller and match ports commonly available on existing sensors and other field instrumentation. "The number one reason that standards organizations are heading in this direction is to ensure greater interoperability," says McKenzie Reed, technology manager for standards development at Harting. "The RJ45 is a commercial product that migrated into the industrial market, and that is what standard organizations working on SPE are putting a ton of time and attention into making sure doesn't happen again because of the quality, compatibility, and performance issues that surround the RJ45 connector when used in

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industrial environments.” Finally, SPE enables power over data line (PoDL), which is capable of transmitting up to 50 watts of power over the same twisted pair of wires that transmits data. According to Reed, this can be used to deliver power to small sensors and other forms of simple instrumentation in the field, allowing endusers to further cut costs by eliminating secondary power supplies.

APL: Advanced Physical Layer

APL refers to an installation architecture that can be used to render SPE intrinsically safe for applications in hazardous environments. This is achieved in conformity with IEC technical specification 2-WISE, which defines port profiles for multiple power levels to limit the flow of current in areas where explosions may occur. According to Al Beydoun, president and executive director of ODVA, while other forms of industrial Ethernet can be used in hazardous environments, they require additional precautions be taken, such as installing mechanical cable protections, using shorter cable runs that must be determined using appropriate calculations, and sheltering connections in additional cabinets and enclosures. By eliminating these needs, APL cuts costs, reduces complexity, and allows for longer cable runs without compromising safety. Moreover, APL is designed to be compatible with pre-existing Fieldbus Type A cabling, which may significantly ease the process of adoption. This is possible because, while APL is a change to an Ethernet cable’s physical layer, its increased data transmission capacities are enabled by a compatible device’s network interface controller (NIC) and physical transceiver (PHY), rather than the cabling

itself. As a result, industries such as oil and gas or wastewater management in which existing cabling may be buried, encased in concrete, or otherwise difficult-to-reach locations can easily make the transition by updating devices and connectors without needing to rip and replace their entire cabling infrastructure.

More data for modern applications

Perhaps the greatest benefit of bringing SPE and APL to process industry applications is the ability to transmit larger quantities of richer, more granular data from sensors and devices to higher level systems due to Ethernet’s greater bandwidth compared to fieldbus. In addition, where fieldbus only offers half-duplex or unidirectional communication, SPE and APL, like other forms of industrial Ethernet, are full-duplex, meaning they can simultaneously transmit data to and from connected devices. With this functionality, real-time, continuous visibility for use in digital twins and other advanced technologies can be made possible. SPE and APL are also protocol agnostic, meaning that they can be used in conjunction with any other higher-level industrial Ethernet communication protocol, allowing for top-to-bottom Ethernet use without the need for network gateways or protocol conversion that raise costs and increase complexity. According to Reed, this will also make commissioning easier to manage, especially as fieldbus expertise wanes among newer members of the workforce. However, ubiquitous adoption won’t occur overnight, says Sri Senthamaraikannan, product line manager for industrial Ethernet and electronic cables at Belden. Because devices must be manufactured with the appropriate

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PHY in order to be compatible with SPE and APL, it could take three to five years before deployment gains momentum. That said, the first SPE and APL compatible devices are going into production this year. It’s also important to note that SPE and APL are not replacements for, but rather complements to existing forms of industrial Ethernet, and have been designed specifically to bring Ethernet connectivity to select applications, particularly those in the process industries. “SPE offers many benefits, but it’s not going to [entirely] replace existing four- or eight-wire industrial Ethernet because it still has strong advantages over SPE, such as a higher data transmission rate; but it is definitely going to be the case that SPE will be a cost-effective solution in specific applications where it has an important role to fill,” Senthamaraikannan says. “We see SPE being a critical enabler of adoption of Ethernet in process control environments.”

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SPE and APL use smaller, more rugged connectors, which can result in material footprint reductions of up to 80% over previous RJ45 connectors.

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U.S. Air Force F-16 fighter craft. Source: GE Aviation

U.S. AIR FORCE LOOKS TO FLY WITH 3D PRINTED PARTS Metal additive manufacturing is being applied to the production of oil lubrication system parts for the GE F110 engine, which powers the Air Force’s F-16 jet fighter. By Jeanne Schweder, Contributing Writer, Automation World

dopting new manufacturing technologies has often proven to be a game changer for companies seeking to enter a new market or retain their leadership in an existing one. For GE, 3D printing is the latest tool for staying ahead of its competitors in the aircraft industry. Though GE engineers had originally developed the engine for the B-1 supersonic bomber, by 1970 it was no longer seen as a leading supplier. That opinion changed in the 1980s when GE designed a new engine around the B-1 core to provide the U.S. Air Force with propulsion systems for its F-16 and F-15 fighter

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aircrafts. Decades later, that F110 jet engine still powers most frontline F-16 fighters. To keep its fleet flying, the U.S. Air Force continually searches for the best ways to procure parts, including crucial spare parts for planes that have been in service for decades. That’s why the Air Force’s Rapid Sustainment Office (RSO) was receptive when representatives from GE Additive approached them last year with the idea of making some parts with 3D printing. That collaboration is now bearing fruit. GE’s engineers are building a 3D-printed sump cover for the GE F110 engine. The sump is

part of the oil lubrication system, and the sump cover is basically a cap, yet still a key part of the engine, says James Bonar, engineering manager at GE Additive. “Compared to other parts on the F110 engine, the sump cover might have lower functionality, but it is incredibly important. It needs to be durable, form a seal, and it needs to work for the entire engine to function. That’s critical, of course, on a single-engine aircraft like the F-16.”

Intricate shapes

GE was able to make its case for 3D printing based on its broad expertise with 3D printing

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technology. Also known as additive manufacturing, the process works by fusing thin layers of metal powder with a laser or electron beam to make a final product. The technology allows engineers to create shapes that would otherwise be too expensive, or too intricate, to make by casting or stamping. According to Antroine Townes, site leader for GE Aviation’s Additive Technology Center (ATC), “The beauty and the value of additive manufacturing comes in the flexibility of design and the speed of innovation.” And it has been a particular boon for GE’s work in aviation. Engineers at the ATC, for instance, were able to use the technology to combine more than 300 engine parts into just seven 3D-printed components in the new GE9X engine, which GE claims is the most powerful jet engine in the world. Thanks to 3D printing and other technologies, this engine is 10% more fuel-efficient than its predecessor, the GE90. GE Aviation also relied on 3D printing for its Catalyst, the first “clean-sheet” design of a turboprop engine to make it to the aviation market in more than a half-century, according to GE Aviation. With 3D printing, GE’s engineers distilled about 800 parts down to

a dozen or so, while reducing the Catalyst’s weight and improving its fuel consumption.

3D-printed sump cover

GE’s collaboration with the Air Force RSO builds on this experience. “The Air Force wanted to go fast from day one and gain the capability and capacity for metal additive manufacturing as rapidly as possible in order to improve readiness and sustainability,” says Lisa Coroa-Bockley, general manager for advanced materials solutions at GE Aviation. “Speed is additive’s currency.” The first print run of the sump covers, which are conventionally cast from aluminum, happened at the ATC, where engineers created the parts from cobalt-chrome powder using GE Additive’s Concept Laser M2 machine. “Part of that process involved exploring how to quickly eliminate the associated risks with castings, and how metal additive might replace it for those parts that are either no longer in production or where we need smaller production runs to keep our platforms flying,” explains Melanie Jonason, chief engineer for the propulsion sustainment division at Tinker Air Force Base in Oklahoma.

For this collaboration, the Air Force and GE are using a spiral development model common to fields like software. This process begins with lower functionality individual parts, like the sump cover, and then advances to tackle complex components and systems such as heat exchangers. With Phase 1a of the sump cover project underway, the teams are moving on to Phase 1b, which focuses on a sump cover housing—a family of parts on the TF34 engine. This engine powers the Air Force’s Fairchild Republic A-10 Warthog, which has been in service for more than 40 years. “The program with GE is ahead of schedule and the preliminary work already done on the sump cover has allowed us to move forward quickly,” says Beth Dittmer, division chief of propulsion integration at Tinker Air Force Base. “As we build our metal additive airworthiness plan for the Air Force, the completion of each phase represents a significant milestone as we take a step closer to getting an additive part qualified to fly in one of our aircrafts.”

Additively manufactured cobalt-chrome sump cover for F110 jet engine. Source: GE Additive

F110 engine. Source: GE Aviation

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28 INDUSTRY-SUPPLIED CONTENT AW JULY 2021

Analytics Overload: Why You’re Confused And if you aren’t confused, you aren’t paying attention!

rocess manufacturing operations may be oversimplified as entailing raw materials, a production process, and finished goods. The same model can be applied to using production data to improve process and business outcomes: data, analytics, and insights. The issue is the value of insights is so high that enthusiasm for claiming credit for the “analytics” between data and insights has gotten out of control. Analytics, the systematic computational analysis of data or statistics (according to Merriam Webster), derives from the Greek analýein, which means “to loosen, dissolve, or resolve into constituent elements.” Leave it to marketing to mess up what Aristotle taught almost 2500 years ago. The result is “analytics” is now everything and everywhere in software products, platforms, and cloud services. You’d be hard pressed to find software that doesn’t claim analytics features or benefits as part of its offering. The abuse of this benign word means it’s difficult to tell what analytics means, what’s included, or what’s required. To overcome this, “analytics” is now frequently qualified to

define the exact type of analytics, a trend which can be broken into three categories.

Advanced and augmented analytics

First, there is the trend towards modern analytics that taps innovation in data science and computing resources; for example “advanced analytics,” which has come into use in the last several years. McKinsey & Company defines advanced analytics as “the application of statistics and other mathematical tools to business data in order to assess and improve practices ... [users can use advanced analytics] to take a deep dive into historical process data, identify patterns and relationships among discrete process steps and inputs, and optimize the factors that prove to have the greatest effect on yield. The issue with this definition is that it assumes a user has the skills for the statistics or machine learning or other technologies required to leverage advanced analytics. Therefore, Gartner has begun using the term augmented analytics, which taps the

By Michael Risse, Vice President and Chief Marketing Officer, Seeq Corporation

same innovation themes but puts the analytics in the context of the user experience with business intelligence applications or tools. As Gartner explains: Augmented analytics is the use of enabling technologies such as machine learning and artificial intelligence to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and business intelligence platforms. Perhaps the best example of augmented analytics is the simple Google Search Bar— the user doesn’t have to know what computations are taking place behind the web page they use to get results.

Iteration required

The second transition in analytics language comes from recognizing that analytics is not a static end point or insight. I would get in trouble inserting a graphic from a vendor that uses this approach, but there are dozens of examples. This approach suggests a hierarchy, a “better than” analytics structure which starts with descriptive analytics (i.e., writing reports), then diagnostic analytics (root cause analysis), then predictive analytics (also predictive maintenance), and finally prescriptive analytics to tell the user what to do (see Figure 1). There may be other, intermediate steps included, but the point is there is a fixed path to greater analytics sophistication. This hierarchical view of analytics may make for compelling marketing materials (“Find Your Analytics Maturity!”) but it’s simply not realistic. A realistic view of analytics is an iterative, looping, collaborative process where an engineer starts with one analytics type, switches

Figure 1: Even recognized types of analytics, such as predictive, can be further broken into specific types or methods. Source: Seeq

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INDUSTRY-SUPPLIED CONTENT 29 AW JULY 2021

to another, goes back to the first, then does something else, or otherwise moves among analytics types to accommodate the changes in plant priorities, raw material costs, formula changes, and other factors. Even in the most static environment, process engineers with experience in Lean or Six Sigma techniques knows that good enough today won’t be good enough tomorrow. Again, Gartner is leading the discussion on an iterative approach to analytics. The analytics aren’t static and hierarchical, they are circular and subject to impact from new requirements.

Improved outcomes

The third transition in analytics is in the desired outcome and impact of analytics. The static view, summarized in the prior paragraph, is defined both by its hierarchy and its defined outcome. The highest level, the brass ring, of this approach is “prescriptive” analytics, as if there was a way to define what the user should do given a certain set of data. This is simply not a realistic objective. At any point in time there will be context known only to the user or subject matter expert, and only at the time of the analysis.

This context must be considered when making the right decision for optimizing the production or business outcomes. If the analytic recommends a shutdown of the line when an asset is working but in need of maintenance, how does the decision get made in the context of production objectives and customer commitments? Only the process engineer or plant manager has the right business context to answer this type of question. Therefore, the desired end point of analytics is not “tell me what to do” but instead “give me insights to inform my decision” based on the process engineer’s ability to tradeoff among outcomes. Another critical aspect of this optimization focus is insights must be achieved in time to make a decision that impacts the outcome. The unsatisfactory—and common—alternative occurs when the analytics take longer than the process to complete, with results delivered after the fact. Analytics tools therefore need to be available as self-service, ad hoc solutions to plant personnel, and presented in time to make a difference. The boring and banal “actionable insights” from two decades of automation vendor marketing must give way to a focus on empowering and supporting the process

engineer or subject matter experts inclusion and perspective in the trade-offs required for optimizing higher level outcomes.

Convergence

These three transitions in the language and innovation of analytics are not exclusive to each other; in fact they are converging in a new generation of software applications that assemble the key capabilities as one offering. Thus, innovative augmented analytics accessible to process engineers or subject matter experts in the plant will support all types of analytics—for past, present, and future data— to constantly tune and adjust the analytics to match plant requirements (see Figure 2). And of course, insights from these new software applications will be accessible to end users so they can provide insights in time to improve production and business outcomes. Analytics has had a rough go of it in the last couple of decades with marketing abuse and over-saturation of messaging, but a new generation of solutions will deliver on the promises and potential of innovation.

Figure 2: Modern advanced analytics applications empower engineers to directly interact with data of interest to create insights quickly enough to optimize production outcomes. Source: Seeq

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30 SUPPLIER INTERVIEW AW JULY 2021

Automation World Exclusive Interview with Beckhoff An interview with Hans Beckhoff, Beckhoff Automation managing director and founder, and Kevin Barker, president of Beckhoff USA, offers insights into where industry is heading with automation technology. By David Greenfield, Editor-In-Chief/Director of Content, Automation World

020 was a year of change for everyone, and the industrial automation sector did not escape unscathed. After several years of growth and expansion, many industrial technology suppliers experienced significant downward impacts on sales and revenues. Even those suppliers that managed to have a year with positive earnings still felt the pinch compared to the levels of growth the industry had seen for years prior to the pandemic. Automation World recently had the opportunity to speak with Hans Beckhoff, managing director and founder of Beckhoff Automation, and Kevin Barker, president of Beckhoff USA. The idea behind this interview was to get insights into Beckhoff’s experience as a global supplier of industrial automation technologies during a year that so dramatically changed personal and business perspectives and to get insights into what may lie ahead for the automation industry.

What 2020 wrought

Our discussion began with a review of Beckhoff’s business in 2020. Hans Beckhoff noted that his company had been experiencing an average growth rate of 14% since 2000. However, in 2020, that rate of growth shrank to about 2%, buoyed by a strong performance from Beckhoff China, which grew by 20% in 2020, as well as a good performance in the U.S., where the business grew by 5%. For 2021, Beckhoff sees positive business development worldwide based on its current double-digit growth rate. The company reportedly generates more than $1 billion in revenue worldwide. Barker noted that Beckhoff’s “highly diversified” portfolio of products and industries it serves contributed to the company’s good performance in 2020.

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Hans Beckhoff, managing director and founder of Beckhoff Automation (left), and Kevin Barker, president of Beckhoff USA. “We don't have more than 15% of our business in any one particular vertical,” said Barker, “so when some of our existing customers did not invest in new theme parks or new oil and gas exploration, we still saw new projects with electric vehicles, semiconductor manufacturing, intralogistics, and packaging.” He added that Beckhoff’s technology portfolio, including TwinCAT control software, industrial PCs, I/O, drives and motors, contribute to the company’s ability to address a wide range of specific projects. “In the U.S., it's pretty evenly distributed and that’s because we are working with innovative companies looking to solve really important problems. And that starts at the control architecture and extends to the entire approach to automation. So, when we have these engagements, we see the revenue streams across all our different product families. We are leading the way with emerging technologies—like mechatronics—which have been a growth engine for us. But we see strong growth across all of our different

product families.” Hans Beckhoff added that the Beckhoff automation architecture is “quite unified across I/O, bus terminals, CPUs, motors and drives, and software, which can be used to do very small applications like controlling a conveyor or very complex and big applications like machine building or logistical transportation projects. Regardless of the application, it's always the same hardware with basically the same TwinCAT software.” One differentiator that Beckhoff pointed to is that his company’s automation architecture is software-based and supported by modular hardware. “There are, of course, some differences in the software algorithms for different applications,” Beckhoff explained, “but control can be realized with this unified hardware, which helps us with a lot of different customers in different segments.”

At the IT/OT crossroads

As a supplier and proponent of PC-based control, Beckhoff has long positioned itself

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SUPPLIER INTERVIEW 31 AW JULY 2021

Beckhoff EtherCAT terminals.

at the crossroads of IT and OT (operations technology)—an area that has gained increasing attention as the drive toward Industry 4.0 and Industrial Internet of Things applications brings these two technology worlds closer together. “We’ve been doing PC-based control for almost 40 years, so having IT and OT integrated has been a part of our technology for all these years,” said Beckhoff. “Because we use a PC to control the machine, it's quite normal for us to collect and analyze data. And we are communication specialists; Beckhoff is the inventor of EtherCAT. We introduced the technology in 2003 and we knew that EtherCAT would be the perfect communication system for general automation, especially for demanding high-speed machine control applications with a lot of motion and measurement functions. Today EtherCAT is a global standard and has become the standard fieldbus for many automation architectures

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and device vendors. Nevertheless, Beckhoff supports an open control philosophy, which means that we support almost any communication interface in the industry, such as Profinet, OPC UA, EtherNet/IP, CANopen, and others—all of which is orchestrated through our TwinCAT software.” He contends that Beckhoff’s focus on industrial PCs, I/O communication technology, and its TwinCAT software provide a strong base for delivering edge intelligence, an aspect of Beckhoff’s business that has been growing rapidly as system integrators develop their own edge systems with Beckhoff hardware and “some big machine builders use our hardware to implement their own edge software concepts in different controllers on the machine.” Beckhoff pointed to a particular feature of the company’s controllers as helping position the company well with integrators and OEMs when it comes to edge computing—the Twin-

CAT Analytics Logger inside the controller. “This Analytics Logger works like a flight recorder, in that all signals from the machine are written in real time to a file or can be sent to the cloud. The complete operation of the machine is recorded,” said Beckhoff. “This allows you to do analytics and optimize the machine because you can see how the machine is working from your desk at home. So, if a machine is going down every two weeks in the middle of the night, you can see exactly what is going on. We also have the Analytics Workbench, which incorporates analytics tools like min/max comparisons, fast Fourier transforms, and it even has an interface with MatLab/Simulink for high-end analytics, all of which can be done via standard IEC 61131-3 languages. This means a controls engineer who programs the machine is also able to program the analytics.” Read the full interview at www.awgo.to/1217

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NEW PRODUCTS 33 AW JULY 2021

RFID Handheld Computer

iDTronic, idtronic-rfid.com The M3 SM15 mobile computer is a compact RFID handheld computer for Internet of Things applications. Outfitted with an industrial-grade Qualcomm Snapdragon 625/626 processor, this mobile reader offers sufficient power for applications in warehouse, logistics, or supply chain operations. The device can be used for mobile device management, such as overseeing applications on multiple devices. In addition, the M3 SM15 mobile computer is equipped with a 2D barcode reader and an integrated NFC reader. An optional long-range reader which can capture 2D barcodes on RFID labels and tags at a range of up to 15 meters may also be added.

Electromagnetic Flowmeter

Endress+Hauser, endress.com The Promag W 800 flowmeter with battery-powered operation provides maintenance-free operation for up to 15 years, as well as worldwide secure data transfer via cellular radio, according to Endress+Hauser. In addition, The Promag W 800 electromagnetic flowmeter ensures reliable monitoring of water supply networks and efficient and time-saving maintenance. Leaks can be located, and non-billable water losses (non-revenue water) can be avoided. These flowmeters are suitable for measuring lake, river, spring, or groundwater flows for drinking and process water, as well as for applications in distribution networks subject to fiscal metering.

Industrial 5G Router

Siemens Digital Industries, siemens.com The Scalance MUM856-1 connects local industrial applications to public 5G, 4G (LTE), and 3G (UMTS) mobile wireless networks. The router can be used to remotely monitor and service plants, machines, control elements, and other industrial devices via a public 5G network flexibly and with high data rates. In addition, the device can be integrated into private 5G networks. The Scalance MUM856-1 therefore supports applications such as mobile robots in manufacturing, autonomous vehicles in logistics, or augmented reality applications for service technicians. Due to its IP65 housing, the router can also be used outside the control cabinet under harsh conditions in production or in outdoor facilities in the water industry.

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34 FINANCE VIEW AW JULY 2021

Hidden Opportunities in the Order-to-Cash Process By Larry White

CMA, CFM, CPA, CGFM lwhite@rcaininstitute.org

Executive Director, Resource Consumption Accounting Institute (www.rcainstitute.org)

alk about the ordinary, the routine, the tedious...the order-to-cash cycle is the epitome of all those attributes. It is a ubiquitous process, with an established body of knowledge, solid procedures, and frequent audits. So, where’s the opportunity? Well, it is the culmination of all successful customer interactions. A creative look may yield opportunities to improve business. The order-to-cash process is thought of as an accounting process, but it involves most elements of a manufacturing organization. Communication across the organization can yield the most significant improvements. Let’s examine the key steps. Order management generates valuable information. Sales should be concerned with the selling effort required, customer and market intelligence gained, potential leads, method of customer acquisition, future opportunities with the customer, price, terms, concessions required, etc. Sales, order taking, logistics, and operations should be concerned with influencing customer ordering patterns. Ordering behavior drives inefficiencies and complexity or can simplify many activities; communications and price incentives can often influence customer behavior if information is known across the organization. Orders can range from complex custom orders requiring many approvals for modifications, delivery dates, pricing, etc. to routine orders for standard products at standard prices. One critical, but often overlooked, performance statistic for non-standard orders is the time from order receipt to the final acceptance decision. This is critical to your reputation with customers; metrics and standard processes are key to improving

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or maintaining performance. Credit approval, both for new customers and monitoring the credit worthiness of existing customers, is a strong risk mitigating function. However, it must be done efficiently and consistently with clear policies, rapid notifications to sales and senior management for problems and delays with significant customers, strong cooperation between finance and sales to maintain customer relationships, and clear procedures for rapid action by operations and shipping for serious credit failures with existing customers. A final boring, but important, customer satisfaction issue is accuracy of order entry—terms, pricing, and delivery—which can affect invoicing, customer satisfaction, and the speed and accuracy of payment. Order fulfillment and shipping is primarily an operations and logistics function, but it critically interests customers. Offering visibility into or communication about this process can enhance customer satisfaction. Sending notices of order fulfillment and shipping to sales staff and order takers enables clear, proactive, and positive communications with customers. Invoicing should occur with order shipment unless special arrangements are in place. Accurate invoicing depends on accurate order entry, both initial entries and modifications. For larger customers, send invoices to sales staff so they can communicate with customers. Accounts receivable management, often thought of as purely an accounting activity, is a key enterprise activity and provides critical customer information. Sales and order taking should always have receivables status available and make proactive communications with customers on payment performance. For serious situations, communication channels to manufacturing and fulfillment should enable holding orders for customers that are at high risk of nonpayment. To the extent business permits, prompt paying customers should receive recognition and incentives; and slow-paying customers should see disincentives if their behavior continues. Commissions to sales staff can be paid when collection is com-

plete to ensure their continuing interest. Payment collection & dispute resolution. Reconcile payments received with outstanding invoices and resolve differences. Differences can range from mundane issues resolvable between accounting offices, or may become a customer satisfaction and relationship issue that requires the involvement of sales staff, senior management, and potentially legal. Escalating, addressing, and resolving these issues promptly is good business practice. Confirm payments received a few days after deposit to ensure the customer or credit card company has not stopped them or dishonored a check because of non-sufficient funds. If a customer pulls a payment back, notify production and shipping immediately to hold pending orders while resolving the matter. Also, rapidly notify sales and senior management to manage the customer relationship for the best possible outcome.

e rder t cas process is thought of as an accounting process, but it involves most elements of a manufacturing organization. Communication across the organization can yield the st si niﬁcant improvements.

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IT VIEW 35 AW JULY 2021

Smart Manufacturing in a Pandemic By Garrett Clemons MES Consultant, Rockwell Automation

is ande ic as r t at it is ti e r c anies t in est in t e sel es t eir r rce t eir s l ti ns and in s art manufacturing.

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o say the absolute least, this past year has been brutal. Everything has been impacted. Everyone had to adapt to survive, literally. From an economic perspective, this year required adaptability, agility, reducibility, sustainability, and an extremely focused business strategy just to stay afloat. For those in the manufacturing industries, their workforce, their solutions, their businesses, and their processes were put to the absolute test. Massive fluctuations in supply and demand drove the need for immediate business process analyses with ongoing adaptation and improvement, increased customer support, and the use of remote or cloud-based solutions. These constraints by themselves are challenging, let alone when lumped together. They require extremely robust solutions that provide opportunities for continued analyses around key metrics and business processes, systems that are accessible to their workforce on- and off-site, and artificial intelligence (AI) to offer proactive system maintenance and solution optimization. These types of advancements and opportunities are exactly what smart manufacturing provides. A smart manufacturing solution can be something as small as a piecemeal upgrade or as significant as a new, fully integrated, robust system and solution. The degree or significance of these constraints may lessen but they will not go away. The specific constraints the pandemic has generated will not suddenly disappear. These challenges and constraints will remain. Companies’ current solutions may not be sustainable. This pandemic was proof that it is time for companies to invest in themselves, their workforce, their solutions, and in smart manufacturing. Smart manufacturing solutions were implemented and used throughout the world this past year due to companies being forced to adapt and survive. Pharmaceutical companies started using smart manufacturing solutions to revamp their vaccine production to meet global demands. Without these smart manufacturing solutions, it would have taken a lot longer to meet the challenges and demands that arose from the pandemic. Cloud solutions were implemented for a workforce that no longer went to offices, and smart manufacturing solutions provided an

avenue to keep up with demand while simultaneously supporting the workforce as their needs and locations shifted. Many companies finally got serious about using AI solutions to analyze massive amounts of data. They realized they had more data than they thought they had, and from that data could learn more about what was really going on and what they needed to do about it. AI solutions were the key to that insight. Companies also got serious about new manufacturing approaches. It might have been the limits on the workforce or other constraints, but companies started getting serious about additive manufacturing, cobots, and digital twins. Luckily, we are now seeing the light at the end of the tunnel. Companies are starting to relax, decompress, and celebrate the wellearned victory of continued operation. Some companies had to adapt various areas of their businesses to meet the immense challenges presented during a global pandemic, but now are reverting to their original solution, strategy, or processes. That may be a big mistake. This pandemic required everyone to selfassess and adapt to sustain. Companies need to do the same. They need to assess how their solutions adapted (or did not adapt) to the insane constraints and challenges the pandemic provided, and then find where they can improve, either completely or piecemeal. Smart manufacturing solutions such as AI, augmented reality/virtual reality, Industrial Internet of Things, cloud and edge, digital twins and digital threads, smart AI objects, prescriptive analytics, and closed-loop orchestration and optimization are all real, proven solutions which are not only providing significant economic benefits to the companies who are smart enough to use them but are specifically designed to meet the challenges that we are facing as a result of the pandemic. We may be very close to the end of this pandemic, but by no means should we forget the challenges and constraints we faced. We need to identify and implement more advanced solutions to meet the ever-growing challenges. Going forward, this time should be used to assess our current state, identify where we can improve, and strengthen our resolve.

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36 ENTERPRISE VIEW AW JULY 2021

Digital Continuous Improvement Can Deliver the Promise of Industrial Transformation By Diane Sacra LNS Research

Based on a recent study by LNS Research, there is deﬁnitely a diﬀerence in digital continuous improvement (CI) adoption between industrial transformation leaders versus followers, and the gap is only widening. An average of 40% of leaders are engaged in digital CI as compared to only 16% of followers. Industrial organizations should move toward digital CI as part of their larger IX strategy.

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he concept of continuous improvement (CI) and—more specifically under the umbrella of CI—programs such as total productive maintenance (TPM), world class manufacturing (WCM), and lean are certainly not new; industrial organizations have been utilizing these strategies for the betterment of their operations for many years now. However, a closer look at these continuous improvement initiatives shows that they are in a strong position to deliver on the promise of industrial transformation (IX). According to LNS Research, industrial transformation (IX) is a “proactive and coordinated approach to leverage digital technologies to create step-change improvement in industrial operations.” Moreover, IX can be a subset of the overall trend toward digital transformation that many organizations are working to achieve. At the heart of successful industrial transformation (IX) are three important aspects of any organization: people, process, and technology. Among these three key elements, many would point quickly to process as the place to start when transforming an organization. Not so fast. When looking at manufacturers with a proven background in improvement processes, we often see the focus is actually on people and technology as they are the real enablers to process improvement. In his latest research report, entitled, “Digital Continuous Improvement in an IX World,” LNS Research Principal Analyst, Andrew Hughes, examines the importance of digitizing continuous improvement programs, like lean, as part of a larger, IX strategy. “It is critical to get a balance between the introduction of digital processes and changes made to ongoing continuous improvement programs, such as world class manufacturing and total productive maintenance,” Hughes said. “One advantage of digitizing lean is the ability to add digital tools to existing processes to enhance lean principles without undermining the impor-

tance of traditional lean.” In his report, Hughes further explains that data is the driver of digital continuous improvement, and it must be both highly organized and readily available in order to produce desired results. He also explains that all manufacturers have a starting point from which they can transform their organizations and categorizes companies into five groupings, from the most prescriptive to the most flexible. “It is important to recognize which group you fall within as a starting point,” Hughes said. “This is key to planning your future as you move toward digital continuous improvement, and to ensure that your organization can handle the changes being proposed.” Based on a recent study by LNS Research, there is definitely a difference in digital continuous improvement adoption between industrial transformation leaders versus followers, and the gap is only widening. An average of 40% of IX leaders are engaged in digital CI as compared to only 16% of IX followers. Hughes encourages industrial organizations to move toward digital CI as part of their larger IX strategy. Fortunately, there are many possibilities when it comes to digitizing continuous improvement—some will require only small changes to process and programs, while others may require fundamental, organizational change. This depends on where an organization starts from in their IX and CI maturity. As industrial organizations move further into digital continuous improvement as part of their IX strategy, Hughes cautions organizations to not look at lean too narrowly. “Lean is not just a set of tools, rather it is a way of improving manufacturing with tools to support the program. As we move toward digital lean, keeping the bigger picture in mind is essential.”

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ADVERTISER INDEX 37 AW JULY 2021

COMPANY

TELEPHONE

WEBSITE

PAGE

2021 Healthcare Packaging EXPO

312.222.1010

www.HCPELasVegas.com

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312.222.1010

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Automation Direct

800.633.0405

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Automation24

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Beckhoff Automation

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DELMIA Works

866.367.3772

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Digi-Key Electronics

800.344.4539

www.digikey.com/automation

Emerson

888.889.9170

www.Emerson.com/FoodBeverageReliability

Galco

888.526.0909

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Hammond Manufacturing

716.630.7030

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Maverick Technologies

888.917.9109

www.mavtechglobal.com/goose-automation-world

mk North America

860.769.5500

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Opto 22

800.321.6786

www.opto22.com

Telemecanique Sensors

800.435.2121

www.tesensors.com/XXSonic

Winsted

800.447.2257

www.Winsted.com

Automation World ® (ISSN # 15531244, USPS 22435) is a registered trademark of PMMI, The Association for Packaging and Processing Technologies. 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 2021 by PMMI. All rights reserved. Materials in this publication must not be reproduced in any form without written permission of the publisher. Applications for a free subscription may be made online at www.packworld.com/subscribe. Paid subscription rates per year are $105 in the U.S., $147 Canada and Mexico by surface mail; $250 Europe, South America. $325 Far East and Australia by air mail. To subscribe or manage your subscription to Automation World, visit AutomationWorld.com/subscribe. Free digital edition available to qualified individuals outside the United States. POSTMASTER; Send address changes to Automation World®, 401 N. Michigan Avenue, Suite 300, Chicago, IL 60611. PRINTED IN USA by Quad Graphics. The opinions expressed in articles are those of the authors and not necessarily those of PMMI. Comments, questions and letters to the editor are welcome and can be sent to: editors@automationworld.com. We make a portion of our mailing list available to reputable firms. If you would prefer that we don’t include your name, please write us at the Chicago, IL address. Volume 19, Number 7.

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38 KEY INSIGHTS AW JULY 2021

Approximately 50% of industrial transformation leaders have an autonomous plant initiative formalized, and an estimated 41% of these leaders are accelerating their autonomous plant efforts because of the pandemic. Moreover, more than half of the study’s respondents indicate they will have remote operations centers in place within the next one to two years. Dian Sacra of LNS Research on autonomous and remote operations trends. awgo.to/1206.

This not only reduces upfront capital expenditures for manufacturers but incentivizes OEMs to continuously improve the performance of their equipment, making them more competitive and delivering better results for end-users. David Miller on the effect of performance-based costing as a business model for OEMs enabled by remote monitoring and maintenance. awgo.to/1207.

We can build a program that has cryptic names for all the components in the software and know how it works, but if we handed that to someone else in the plant who has never seen the software, they would have a hard time figuring it out. Integrators must segregate those functions within the code to provide ease of access for those who did not write it. Jeff Allen of system integrator E Technologies Group on practical systems maintenance. awgo.to/1208.

PMMI’s mechatronics certification program became the base of Amazon’s apprenticeship program, which allows individuals to not only finish the program but obtain certifications as well. Melissa Griffen on building a quality industrial workforce. awgo.to/1209.

Troubleshooting industrial Ethernet problems often involves the use of complex tools such as protocol analyzers that require years of training or trial-and-error approaches such as running a bypass cable in the hope of solving the problem. David Greenfield on Fluke’s new LinkIQ-IE Cable+Network industrial Ethernet tester. awgo.to/1210.

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