PE_20_04 by Modiconlv

PlantEngineering.com

COVID-19’s

profound impact on manufacturing & supply chain Also in this issue: • Remote sensors & networks • Troubleshooting AC induction motors • Digital OEE

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479-646-4711 baldor.abb.com input #16 at www.plantengineering.com/information

Rodless Air Cylinders Half the Footprint, 100% of the Value

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All prices are U.S. published prices. AutomationDirect prices as of 02/05/2020. Prices and specifications may vary by dealer. Grainger prices are from http://www.grainger.com 03/16/2020 Prices subject to change without notice.

Features

Rodless air cylinders are robust and compact linear actuators powered by a pneumatic air supply and controlled the same way as a conventional air cylinder. Rodless cylinders can offer the same stroke length as rodded cylinders in a smaller space. All sizes have magnetic pistons and are double acting. NITRA L-Series double-acting rodless cylinders are typically half the cost of those offered by competitors and can be used in place of typical air cylinders or even traditional motion equipment.

• Rodless cylinder design • Double acting with magnetic piston • Front and rear adjustable cushions • Tapped end caps mount • 16mm to 40mm bore sizes available • 100mm to 1000mm stroke lengths available • 2-Year warranty

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input #1 at www.plantengineering.com/information

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seweurodrive.com / 864-439-7537 input #3 at www.plantengineering.com/information

APRIL 2020

SOLUTIONS 9 | Digital twins drive innovation in the energy sector Representations also serve as interfaces to further information

12 | Deploy IIoT sensors and networks in remote locations

IIoT adds value within a plant, but also is a natural fit for field data gathering

16 | An overview of industrial IoT, from edge to cloud

Editor’s Insight 5 | A profound impact on manufacturing

INSIGHTS 7 | Survey results: increased recognition of Covid-19’s adverse impact Digital work from home is fine, but manufacturing takes place in the physical world

SPECIAL REPORT SR 3 | Edge computing offers 4-step pathway to digital transformation

Living on the edge: Putting computing power close to the process reduces control system latency, creates a distributed architecture, and can integrate machine learning (ML) and artificial intelligence (AI) capabilities

SR 7 | Edge computing terms, skills

Six edge computing questions to ask about data collection, networking and control systems

Next generation distributed I/O brings users one step closer to seamless connectivity

20 | Improve plant uptime with advanced sensing systems

What every plant manager must know about today’s sensing systems

25 | Your questions answered: Troubleshooting techniques for ac induction motors

Webcast presenters answer questions on troubleshooting techniques for ac induction motors

27 | Conduct asset performance management with a software-based approach

Unite separate parts of the organization, allowing teams to work collectively

INSIDE: OIL & GAS ENGINEERING Technology transfer

High throughput experimentation for the oil & gas industry

PLANT ENGINEERING (ISSN 0032-082X, Vol. 74, No. 3, GST #123397457) is published 10x per year, monthly except in January and July, by CFE Media, LLC, 3010 Highland Parkway, Suite #325, Downers Grove, IL 60515. Jim Langhenry, Group Publisher /Co-Founder; Steve Rourke CEO/COO/Co-Founder. PLANT ENGINEERING copyright 2019 by CFE Media, LLC. All rights reserved. PLANT ENGINEERING is a registered trademark of CFE Media, LLC used under license. Periodicals postage paid at Downers Grove, IL 60515 and additional mailing offices. Circulation records are maintained at CFE Media, LLC, 3010 Highland Parkway, Suite #325, Downers Grove, IL 60515. E-mail: pe@omeda.com. Postmaster: send address changes to PLANT ENGINEERING, PO Box 348, Lincolnshire, IL 60069. Publications Mail Agreement No. 40685520. Return undeliverable Canadian addresses to: PO Box PO Box 348, Lincolnshire, IL 60069. Email: pe@omeda.com. Rates for non-qualified subscriptions, including all issues: USA, $165/yr; Canada/Mexico, $200/yr (includes 7% GST, GST#123397457); International air delivery $350/yr. Except for special issues where price changes are indicated, single copies are available for $30 US, $35 foreign. Please address all subscription mail to PLANT ENGINEERING, PO Box 348, Lincolnshire, IL 60069. Printed in the USA. CFE Media, LLC does not assume and hereby disclaims any liability to any person for any loss or damage caused by errors or omissions in the material contained herein, regardless of whether such errors result from negligence, accident or any other cause whatsoever.

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PLANT ENGINEERING

April 2020

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input #4 at www.plantengineering.com/information

PlantEngineering.com 3010 Highland Parkway Suite 325 Downers Grove, IL 60515 Ph. 630-571-4070, Fax 630-214-4504

CONTENT SPECIALISTS/EDITORIAL KEVIN PARKER, Editor KParker@CFEMedia.com JACK SMITH, Managing Editor JSmith@CFEMedia.com AMANDA PELLICCIONE, Director of Research 860-432-4767, APelliccione@CFEMedia.com KATIE SPAIN NAREL, Art Director KSpain@CFEMedia.com SUSIE BAK, Production Coordinator SBak@CFEMedia.com

EDITORIAL ADVISORY BOARD H. LANDIS “LANNY” FLOYD, IEEE Life Fellow H.Landis.Floyd@gmail.com JOHN GLENSKI, President, Automation Plus jglenski@processplus.com SHON ISENHOUR, Partner, Eruditio LLC sisenhour@EruditioLLC.com DR. SHI-WAN LIN, CEO and co-founder, Thingswise, LLC Industrial Internet Consortium (IIC) board member shiwanlin@thingswise.com JOHN MALINOWSKI, Senior manager of industry affairs (retired), Baldor Electric Company DAVID SKELTON, Vice president and general manager Phoenix Contact Development and Manufacturing dskelton@phoenixcontact.com BILLY RAY TAYLOR, Director of commercial and off-highway manufacturing The Goodyear Tire & Rubber Billytaylor@goodyear.com LARRY TURNER, President and CEO, Hannover Fairs USA lturner@hfusa.com MARK WATSON, Senior director, manufacturing technology, IHS Markit Mark.watson@ihsmarkit.com

CFE MEDIA CONTRIBUTOR GUIDELINES OVERVIEW

Content For Engineers. That’s what CFE Media stands for, and what CFE Media is all about—engineers sharing with their peers. We welcome content submissions for all interested parties in engineering. We will use those materials online, on our Website, in print and in newsletters to keep engineers informed about the products, solutions, and industry trends. * www.plantengineering.com/contribute explains how to submit press releases, products, images and graphics, bylined feature articles, case studies, white papers, and other media. * Content should focus on helping engineers solve problems. Articles that are commercial in nature or that are critical of other products or organizations will be rejected. (Technology discussions and comparative tables may be accepted if non-promotional and if contributor corroborates information with sources cited.) * If the content meets criteria noted in guidelines, expect to see it first on our websites. Content for our enewsletters comes from content already available on our Websites. All content for print also will be online. All content that appears in our print magazines will appear as space permits, and we will indicate in print if more content from that article is available online. * Deadlines for feature articles intended for the print magazines are at least two months in advance of the publication date. Again, it is best to discuss all feature articles with the content manager prior to submission.

Learn more at: www.plantengineering.com/contribute

INSIGHTS

By Kevin Parker, Editor

A profound impact on manufacturing Though so many of us have been told to stay right where we are, events are moving fast and it’s not easy to see where we’ll be by the end of April. Each of us has worked hard our entire adult life. It’s no wonder we’re of two minds. Our self-interest instructs us to take necessary cautions and we encourage all others to do the same. We also want to get back to a fully functioning economy. Yet it’s getting to look like a long haul. “Sovereign [oil producers] will continue to pump as much as they can to support their economies while higher cost producers, especially in the U.S., may need to shut down at some point in the near future. Any emergency from the supply side (OPEC+Russia) looks unlikely and would probably fail anyways due to weak demand expectations in the near term,” wrote Mayak Joshi of Chatham Financial in a recent note. While recognizing the necessity of economic measures, self-interest also instructs us to fear the long-term consequences of trillion-dollar stimulus packages — piled on top of an already indebted economy — including the kind of inflation that destroys investments and the security of those on fixed incomes. It is magnificent that so many people today continue working from home, but goods-making is a physical process, meaning that to keep working, production personnel must remain in the line of fire.

Critical functions

The U.S. Department of Homeland Security’s Cybersecurity and Infrastructure Security Agency has released guidelines identifying workers and industries essential to continuity of functions critical to public health and safety, as well as economic and national security. Manufacturing is one of 14 employment categories so identified. The guidelines are not mandatory but constitute an advisory. The critical manufacturing category www.plantengineering.com

includes workers needed for making materials and products for medical supply chains, transportation, energy, communications, food and agriculture, chemical manufacturing, nuclear facilities, water and wastewater treatment and the defense industrial base. O n e m a nu f a c t u r i n g company that is keeping on trucking is Sealing Equipment Products Co. (SEPCO) of Alabaster, AL. The company and its authorized distributors continue to operate on their regular schedule because the components it produces support utilities, power grids, medical facilities, government offices, food services, data centers and other vital information technology infrastructure. In addition, SEPCO products support exempted industries and sectors, such as aerospace, logistics and transportation, personal product equipment (PPE) manufacturing, chemical processing and refining, mining, water and wastewater treatment and military applications. As it continues to operate, the company says, its team also is executing appropriate CDC recommended safety precautions, including social distancing.

On war footing

An Aurora, IL, metal manufacturer is transforming its factory to make emergency beds in response to the COVID-19 crisis. “We were very involved in aiding the efforts of our military in World War II, and this is no different,” Richards-Wilcox President Bob McMurtry said. “We have the ability and desire to help fill the need for temporary beds, so it was a simple decision.” Richards-Wilcox is transforming its 365,000-square-foot metal fabricating factory into an emergency bed critical response manufacturer to fabricate temporary beds for medical, overflow and quarantine facilities. Beds will be ready for shipment early in April. Manufacturing needs to be brought back to the U.S. so we can remain master of our own house. PE PLANT ENGINEERING

April 2020

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2 2415 1286 (0)1227 374710 170 8 187 613 (0)7 61 36 56 12 930 020 509 (0)7 3879 4180 6778 9225 81 1103 2400 (0)41 453 1871

input #5 at www.plantengineering.com/information

HH-0542

CHILE UK GERMANY FRANCE SPAIN AUSTRALIA SINGAPORE INDONESIA SOUTH AFRICA

INSIGHTS COVID-19

By CFE Media editorial staff

Survey results: increased recognition of COVID-19’s adverse impact Digital work from home is fine, but manufacturing takes place in the physical world

early three of four respondents to a Coronavirus (COVID-19) impact survey conducted by CFE Media & Technology from March 20 to 25 said their businesses were negatively affected, up from half the week before. Of the 74% negatively impacted, the percentage of those feeling a “great deal” of impact increased from 13% for the time period of March 10 to 19 to 35% during the time period of March 20 to 25. Those experiencing severe supply chain impacts also nearly doubled in a week from 9% to 17%. Leading company actions to date focus on limiting travel (80%); encouraging work from home (56%); working on contingency plans now with changes expected Figure 1: Those soon (57%); and eliminating travel (45%). feeling severe Respondents were drawn from visitors to the Control supply chain Engineering, Plant Engineering, Oil & Gas Engineering, impacts as a and Consulting-Specifying Engineer websites. result of the Coronavirus (COVID-19) doubled from the previous survey period. Courtesy: CFE Media and Technology COVID-19 engineering impact survey, March 20-25

Actions taken in response

The survey asked what, among 24 possible actions, the respondents’ companies were taking because of coronavirus. The top 10 responses were: 1. Limiting travel 2. Working on contingency plans now; expect to see changes soon 3. Encouraging work from home 4. Eliminating travel, with the percentage rising to 46% from 35%, previously. 5. Delaying or eliminating hiring 6. Mandating work from home (for those that can) 7. Delaying or eliminating investments 8. Adding supply chain contingencies such as secondary sources 9. Adding new manufacturing capabilities to make up for breaks in supply chain

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10. Increasing production of relevant product categories to meet increased demand.

Not everyone at home

Fewer people said remote working wasn’t an option in the second sample, while 47% said they can complete critical parts job functions at home; only 24% said they could not, and 29% said they were unsure/ or for only some parts. Among respondents, 53% say their companies are having supply chain problems. Those with severe problems nearly doubled from the previous survey time period, increasing from 9% to 17%. Respondents were asked, what strategies should the U.S. government review to help address this type of situation in the future? The three ranked responses were • Incentivize re-shoring of key manufacturing segments back to the U.S. • Invest in medical research and development to speed vaccine development and virus testing capabilities • Do even more to promote manufacturing automation where production can be completed with minimum operator involvement.

Advice from respondents

The survey also asked several open-ended questions. Asked what operational initiatives their company had taken to prevent the spread of coronavirus in the facility, responses included issuance of a daily email reminding employees about company health policy and CDC recommendations and mandating work from home (for those that can). Anyone who comes into the facility is required to follow the prescribed sanitation processes. If someone does travel, they should work from home for 14 days. Manufacturing is a physical process that can’t be completed in a virtual or digital world. Asked what critical functions in their organization are most difficult to perform from a remote location, one respondent said, “all of the actual manufacturing,” while another pointed in greater detail to “test set-up and data collection, field service, installation, shipping and receiving, inventory work orders and quality control.” Asked what strategies the U.S. government should review, many respondents pointed to the need to bring manufacturing back to the U.S. to limit reliance on global supply chains. PE PLANT ENGINEERING

April 2020

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SOLUTIONS REALITY MODELS

By Anne-Marie Walters

Digital twins drive innovation in the energy sector Representations also serve as interfaces to further information

D Figure 1: A digital twin is a representation of a physical asset, process or system that includes engineering information relevant to its operation. All graphics courtesy: Bentley Systems

igital twins are taking center stage — advancing beyond building information modeling to enable asset-centric organizations to converge their engineering, operational, and information technologies for immersive visualization and analytics visibility. As is well known, a digital twin is a digital representation of a physical asset, process or system that includes the engineering information that allows us to understand and model its performance. Typically, a digital twin can be continuously updated from multiple sources, including sensors and continuous surveying, to represent its near real-time status, working condition or position. A digital twin enables users to visualize the asset, check status, perform analysis and generate insights to predict and optimize asset performance. In the energy sector, digital twins are used to optimize the operation and maintenance of physical assets, systems and production processes. Many organizations using digital twins on projects are proving their value. An excellent example is Shell Chemical’s use of a digital twin on a very large construction project in Pennsylvania. Shell is surveying its plant with drones on a twice weekly basis as the plant is being constructed. The reality model is combined with other asset data to update the project’s digital twin. The digital twin is used to track construction and identify issues by visualizing change over time. This capability enables the

www.plantengineering.com

team to immediately respond to onsite changes. Shell is also capturing the asset’s digital record as it is being constructed for use in operations and plant maintenance, such as the precise location of underground utilities. The digital twin enables the organization to make better sense of its data, both now and in the future.

Embracing digital twins

The energy sector is well placed to take advantage of digital technologies. Whether it is simply adding a vibration sensor to a piece of rotating machinery or creating a full digital twin of an entire plant, digital twin technologies can reduce costs and streamline maintenance and operations processes. Digital twins are a hot topic, and many organizations are keen to work out how they can best benefit from their use. Most companies are looking for advice on where to get started. Our advice is to start with the good asset data that you already have, get it in a position to be shared, and grow from there. Quite often, the good data is buried in systems that are inaccessible to the people who need it. One of the biggest benefits of digital twin technology is that it makes trusted, upto-date information more widely available. Bentley provides an open, connected data environment, which is a set of cloud-provisioned or onpremises services that support digital context, digital components and digital workflows. By enabling an open, connected data environment, energy firms can better manage and access consistent, trusted and accurate information. Owner-operators and project delivery firms also can share the benefits of an open, integrated and connected framework. The energy sector has always embraced innovation, and there are several examples where digital technologies are already delivering significant business advantages. For example, Oman Gas developed a reliability and integrity program based on a digitalized, automated framework provided by Bentley’s AssetWise Reliability solution. The applications are reducing human intervention and improving resource effectiveness. Another example is Vedanta Ltd. — Cairn Oil & Gas in India. This organization is using asset performance PLANT ENGINEERING

April 2020

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SOLUTIONS REALITY MODELS

Figure 2: Having a single source of truth allows for quick maintenance and operations decisions while also ensuring they are based on the most accurate data available.

software to optimize production across its over 800 offshore wells. The company implemented smart well integrity and a flow assurance management system to manage integrity risks and manage its stocks. Bentley’s AssetWise provides a connected data environment that interacts with the company’s existing systems and integrates data from many sources. In Russia, Volgogradnefteproekt is playing a pivotal role in going digital with Lukoil for the development of the Filanovsky field in the Caspian Sea. Volgogradnefteproekt has overall project management responsibility for all Lukoil projects in the Caspian Sea and has introduced an integrated BIM approach consolidating input from the various contractors. The organization implemented this approach to deliver and maintain a consistent 3D model using a connected data environment. Used across design, engineering and construction, the connected data environment has already delivered benefits, including reducing overall design time by 70% and construction costs by 20%. The organization also uses the 3D digital engineering model from design through construction and commissioning to operations and maintenance, which is expected to reduce annual operations costs for the field by 30%.

Saving time, organizing information

Digital twins, and other digital technologies, can help the energy sector save significant costs over time. A sound approach leverages the investments that companies have made in technologies, offering seamless upgrades to new platforms and using existing systems, sensors, and other data sources as much as possible. In many cases, using reality modeling to capture as-is conditions is less expensive than traditional survey techniques. The next step for many organizations is to gather the data accumulated from sensors into a single view, leveraging reality modeling for users to easily make timely decisions based on current data. Digital twins can help users organize their information. Having a single view of the truth allows for quick maintenance and operation decisions while also assuring that decisions are based on the most accurate data available.

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Digital twins help users decide the viability a business option, as well as follow up on that decision. Another benefit that digital twins provide is streamlined updating processes. Using traditional updating processes, it can take as much as six months to record a change made in the field by maintenance. If someone looks at the records during this six-month gap, the records are outdated, leading to accidents and major compliance issues. The work processes associated with digital twins can ensure that all information is immediately updated, and data is always in compliance. Digital twins’ interoperability with other applications is another major benefit. Digital twins are opening new opportunities for all types of new services. Because of the rapid growth in the adoption of reality modeling, new companies are replacing traditional inspection and surveying organizations, providing digital models of assets rather than reports. An example of a new service offering is the recent announcement by Siemens Power and Bentley Systems to provide asset performance management services for power plants. This new cloud-based service empowers power plant owners to take full advantage of digitalization, which helps improve maintenance operations and planning.

Open environment, improving safety

Cloud technology is crucial for digital twins, helping enable collaboration, improve decision making, and deliver better project outcomes and better-performing assets. To have open and live access to information within digital engineering models, organizations need to implement a connected data environment. This type of environment allows engineering technologies (ET) to be brought together with information technologies (IT) and operational technologies (OT) to improve the throughput, safety, and reliability of their production assets. Microsoft’s Azure cloud platform can be used to ensure the safety and security of information. Microsoft Azure has many layers of security and is regarded by many people in the industry as the platform most secure from malicious attack. In fact, many energy organizations have found that keeping their data in the cloud is safer than keeping data in their own data centers. In addition, leveraging applications that also work in a connected data environment — such as project collaboration solutions and asset performance management solutions — ensures both user and component level access to data and information. Both type solutions ensure that the right people are viewing the right information at the right time, making their digital twins a safe place to store their data. www.plantengineering.com

Accelerating your digitalization Digital twins have the potential to offer huge benefits to the energy sector. The challenges, however, are where to start, what are the next steps, and how you can accelerate your digitalization. Most companies in the energy sector have good document management systems supporting their regulatory processes, as well as often having good enterprise asset management systems supporting maintenance. Much of this data, however, is inaccessible to those people who need it and often not as timely as it should be. Sharing this information using a federated approach — including use of mobile platforms — will bring initial benefits, including better ways of finding information. If you have existing plants, use reality modeling as a starter to allow digital twins to capture as-is conditions. Link those models to sensor information to enable operations and maintenance to have a better understanding of context. Finally, adding simple workflows to the digital twins to record changes in the field will keep

information evergreen and up to date, providing a sound basis for next steps. These steps might be leveraging artificial intelligence and machine learning to improve maintenance and operations processes, enabling digital twins to truly drive your business. PE Anne-Marie Walters is industry marketing director, oil & gas and manufacturing, Bentley Systems.

Figure 3: Whether it is simply adding a vibration sensor to a piece of rotating machinery or creating a full digital twin of an entire plant, digitalization technologies can reduce costs and streamline maintenance and operations processes.

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SOLUTIONS REMOTE OPERATIONS

By Ryan Williams

Deploy IIoT sensors and networks in remote locations IIoT adds value within a plant, but also is a natural fit for field data gathering

mart sensor and device installations are flourishing everywhere, forming the basic building blocks of any Internet of Things (IoT) initiative. Applying IoT capabilities can be a useful way to monitor and even initiate control for consumer applications like home temperature, lighting and sprinkler controls. When smart devices are made tougher and connected securely over the Internet, they can function as key components for industrial IoT (IIoT). Manufacturing and processing companies are rapidly implementing IIoT projects because of expected benefits as proven by other firms in the same sector. Wireless IIoT-capable instruments are far easier to install than conventional wired devices and convenient to monitor machine conditions and process equipment and measure Figure 1: conditions almost anywhere to identify issues before Traditional they become more significant problems. methods for IIoT is ready to help digitalize and gather data from monitoring a factory, or even more distributed applications such surface water as pumping stations or general environmental condirequire travel tions. A prime example is using the IIoT to constantly to challenging and easily measure water quality. This is applicable to sites, which any organization working with water systems such as is expensive cooling ponds or cooling tower reservoirs. The examples and leads to identified in this article relate to surface water quality incomplete in even more remote locations such as rivers and lakes, data. All images as well as aquaculture. These IIoT concepts extend to courtesy: any remote monitoring situation. Endress+Hauser Let’s look at how today’s digital ecosystems have progressed to enable a complete solution of sensors, communications, software, analytics and visualization — empowering users to readily monitor and be alerted about measured conditions.

Water matters

Monitoring surface water condition is a relatable and worthy endeavor. We all need

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and use water every day and are aware of the many ways water resources have been polluted. For instance, a tiny amount of oil can contaminate great quantities of water, and there are many other pollutants such as plastics, chemicals and bacteria that are harmful to natural water conditions. Some water pollution can be traced to point sources, such as factories with improperly treated discharges. Other types of pollution are much harder to trace and diffuse, originating from airborne fumes and gasses and returned to surface water during rainfall. The consequences of polluted water are many. Dissolved oxygen must exist at a certain minimum level to support healthy marine life, while too much oxygen can impair good bacteria that would otherwise decompose wastes. Obviously, chemicals or other materials present in polluted water can be toxic and cause health problems for humans or wildlife that drink or even just come into contact with the water. Some chemicals are nutrients that may promote algae growth, in the worst case leading to harmful algal blooms (HABs), which can rapidly deplete oxygen in the water and in turn cause sudden fish kills. Good monitoring practices can identify these and other problems early so they can be addressed quickly before more serious conditions develop.

What can be done?

A first step in solving any problem is gathering data. Measuring water conditions is the only way to understand not only the instantaneous status, but also the historical and trending conditions. Recording, viewing and analyzing this data also is the only way to determine if corrective action is having the desired effect. The remote and outdoor nature of surface water locations introduces many measurement challenges (see Figure 1). In years past, researchers would periodically travel to these bodies of water and take samples for later analysis, a time-consuming and expensive method that can introduce errors and lead to gaps in the data. Today, IIoT is enabling many types of intelligent measuring technology to be easily deployed. This is particularly the case for water analytical situations, where the key parameters of interest are: • Conductivity • Dissolved oxygen (DO) www.plantengineering.com

• pH • Temperature. High conductivity can signal pollution by chemicals or metals. The critical role of DO has already been discussed. Measurement of the water pH indicates if the water is too acidic, another condition that can threaten marine life. Finally, high water temperature is not a pollutant, but it can be dangerous to the health of marine life, and in conjunction with other conditions can lead to increased chances for an algal bloom. Combined, these four measurements provide a comprehensive water health profile. Therefore, installing an effective measuring system for these parameters is fundamental to efforts for protecting the environment.

Measurement methods

Many of the sensor technologies used to measure water quality are well-established, although they must be configured for the outdoor environment (see Figure 2). Conductivity sensors measure how easily the water conducts electrical current, with higher conductivity indicating a high number of ions due to dissolved salts or inorganic materials. Water pollution can be a reason for unexpectedly high conductivity. Both optical and amperometric dissolved oxygen sensors are available today for accurate and reliable oxygen measurement with minimal maintenance. Natural bodies of water usually have a pH value between 6.5 and 8.5. Most pH sensors use a glass electrode and can measure over a wider range than this. An additional feature of many pH and conductivity sensors is incorporation of a Pt1000 resistance temperature detector (RTD) sensor to provide a temperature reading. A Pt1000 RTD sensor is a platinum RTD with a nominal resistance at 0°C of 1,000 ohms. For surface water monitoring, it is important to select sensors that resist extremes of corrosion, moisture, soiling and fouling. They must be easily installed, serviced and calibrated. The most advanced sensors, such as Endress+Hauser’s analytical sensors with Memosens technology, maintain their factory calibration information on-board and communicate it to the transmitter when connected, simplifying maintenance. These sensors use digital technology that allows them to easily connect to a universal digital transmitter. A digital transmitter makes data easily available to remote monitoring systems.

Bringing it all together

Instead of buying sensors and devices from various vendors and trying to make them work together, a better approach is to obtain all sensors and the associated multichannel transmitter as a coordinated package from a single source. Packaging a suite of traditional sensors with modern instrumentation is the key to quickly creating an IIoT-capable system in a www.plantengineering.com

cost-effective manner (see Figure 3). The most capable instrumentation kits will use sensors with intelligent connectivity to the transmitter, simplifying installation, operation and maintenance because they supply both calibration information and measured values. Power must be connected to the transmitter, but it is usually impractical to run any type of wired phone or network connection to a water measurement system. Therefore, it is important for these systems to incorporate a cellular device. This enables the system to act as an IIoT device with connectivity to the Cloud, making the transmitter an information gateway supplying sensor data. Transmitting raw data is just the beginning. A comprehensive system like the Endress+Hauser Netilion Smart System for surface water includes not only the necessary hardware, but connectivity to an associated IIoT Cloud. The most basic functionality lets users visualize all data values using a compatible mobile app. Other advanced features useful for surface water monitoring include: • Geographical-oriented overviews, location indications and device information • Data history of measured values with graphical views • Notification of limit and alarm events and acknowledgements, with overview • Display of NAMUR NE 107 status messages.

Figure 2: Water sensor technologies and transmitters for conductivity, dissolved oxygen and pH make it possible for continuous measurement even in difficult locations.

It is possible for users to assemble and configure the sensor, transmitter, communication, Cloud and monitoring elements. However, using a preconfigured system tailored for surface water monitoring is likely the most cost effective, convenient and reliable way for end users to monitor the measuring points from anywhere and at any time.

IIoT improves seafood industry

Aquaculture, or fish farming, is an important industry worldwide. Obviously, water quality is an important factor for this activity at all stages of raising fish from fingerlings up to harvesting size. Water quality concerns for aquaculture are like those for surface water monitoring, with DO measurement in particular a prime concern. While general water monitoring applications measure conductivity, aquaculture end users need to know the amount of ammonium in the water. In addition to pH, these aquaculture facilities also are concerned with the level of nitrates in the water. Fish will thrive best when the DO level is proper for their health. Many aquaculture operations incorporate PLANT ENGINEERING

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SOLUTIONS REMOTE OPERATIONS

Figure 3: Systems for surface water monitoring include sensors, transmitter and accessories needed to deploy and connect to the Cloud.

active aeration. Not only are DO measurements monitored, aeration levels can be optimized. Ammonium concentrations vary based on fish feeding and excreting, and on water treatment cleaning performance. Continuous measurement is important to ensure ammonium is kept at safe levels, and to enable a proactive response if it is trending the wrong way. Nitrate concentrations can negatively impact the health of farmed fish, but another consequence is that high nitrate concentration in the farming plant discharge can have a negative environmental impact. This is because nitrates promote t he g rowt h of algae, which as discussed earlier can lead to anaerobic zones and other problems. Installing IIoT systems using water measurement technologies, linked to the

Cloud and mobile devices, is a positive step to actively managing and optimizing aquaculture. End users can understand the health of their operations, make changes to improve performance and be alerted with remote alarm notifications before potential issues develop into major problems.

Final words

Surface water resources are vulnerable to many types of physical, chemical and biological pollution that can harm people, animals and plants. Manual data gathering in isolated locations is a good start to improving water quality, but unlikely to provide a broader, realtime solution. Improved and automated data gathering and analysis are key to understanding water quality and identifying the most impactful pollution sources. Fortunately, IIoT instruments and methods are available to establish a comprehensive measurement and monitoring program. This is a necessary first step in efforts to protect water resources. PE Ryan Williams is the national product manager for Solutions and Service at Endress+Hauser USA.

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SOLUTIONS AUTOMATION & PROCESS CONTROL By Josh Eastburn

An overview of industrial IoT, from edge to cloud Next generation distributed I/O brings users one step closer to seamless connectivity

y now, most anyone working in a role involving industrial automation has heard about digital transformation, the internet of things (IoT), and industrial IoT (IIoT). These initiatives involve ever smarter devices installed progressively closer to the “edge,” perhaps connected to an internet “cloud,” or even connected through something called the “fog.” Even if we consolidate these terms under the umbrella of IIoT, for most folks a simple question remains: what is the goal of the IIoT? Simply put, end users would like the IIoT to create a cohesive system of devices and applications able to share data seamlessly across machines, sites, and the enterprise to help them optimize production and Figure 1: discover new cost-saving opportunities. Traditional This has always been a goal of industrial automamethods of tion, but traditional operational technology (OT) acquiring data architectures are poor at scaling, priced prohibitively involve the and demand complex configuration and support. So complexity of what is changing? configuring and Much as consumer hardware and software technolomaintaining gies have shifted to improve ease-of-use and connecmany layers tivity, industrial products and methods are following in a hierarchy the same trend by adopting information technology of hardware (IT) capabilities. This article discusses how a more and software. distributed global architecture is enabling connectivity All figures from the field to the cloud for sensors and actuators, courtesy: Opto and for the input/output (I/O) systems and controllers 22 linked to them.

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Up and down the architecture

Classical industrial automation architectures generally address data processing from a hierarchical standpoint. One good feature of this hierarchy is the clarity it provides with regards to where data can originate, be stored, undergo processing, and be delivered. However, the task of transporting data and processing it in context is often quite difficult because so many layers of equipment are required to connect devices and applications. The lowest level of an automation architecture is generally considered to be the physical devices residing on process and machinery equipment: sensors, valve actuators, motor starters and so on. These are connected to the I/O points of control system programmable logic controllers (PLCs) and human-machine interfaces (HMIs). Both PLCs and HMIs are well suited for local control and visualization, but less useful for advanced calculations and processing. Fortunately, using industrial communications protocols, they can send data to upstream supervisory control and data acquisition (SCADA) systems where it might be historized and made available to corporate level analytical software. Sharing data within multi-vendor systems, however, often requires additional middleware such as an OPC server. More advanced site manufacturing execution system (MES) and overall enterprise resource planning (ERP) software also reside at higher levels of the

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architecture, hosted on PCs or servers on site, or in the cloud, where the cloud is defined as providing large-scale, internet-based, shared computing and storage. Raw information generally flows up to higher levels to be analyzed and used to optimize operations. Developments over the past decade are significantly altering this traditional hierarchy, flattening and simplifying it to a great extent.

Spanning edge, fog, and cloud

Computing capability and networking bandwidth used to be much less available. Each step up the hierarchy from a basic hardwired sensor to cloud computing systems was required to access greater computing resources and networking capabilities (Figure 1). Today, the relationship has changed because sensors and other edge devices are far more capable, with some of them including processing and communications abilities similar to a PC. Each device can perform more as a peer, instead of acting in a passive listen-andrespond role. Therefore, the architecture is evolving to become flatter and more distributed (Figure 2). The edge is still a critical source of data, and the cloud is still a valuable resource for heavyweight computing. However, the resources in between, especially at the site level, are becoming a blend of data-generating devices and data-processing infrastructure. This fuzzy middle ground earns the name “fog” because it is akin to a widespread, pervasive, and middleweight “cloud.” Many other factors besides advancing technology are driving this shift to a flatter architecture. The most straightforward motivation is to balance computing and networking demand between the edge and higher-level systems. Edge computing offloads central processing, preserves data fidelity, improves local responsiveness and increases data transfer efficiency to the cloud. Ultimately, however, this new edge-to-cloud architecture depends on having new options at the edge for acquiring and processing field data.

Distributed I/O evolves

Field data can be raw I/O points connected at the edge or derived calculation values. Either way, the problem with traditional architectures is the amount of work it takes to design, physically connect, configure, digitally map, communicate, and then maintain these www.plantengineering.com

data points. Adding even one point at a later date may require revisiting all these steps. To create more scalable, distributed systems, some vendors are making it possible to bypass these layers between the real world and intermediate or top-level analytics systems. Classic I/O hardware, for example, is not very intelligent and must be mastered by some supervisory controller or system. But with enough computing power, all the necessary software for enabling communications can be embedded directly in an I/O device. Instead of requiring a control engine to configure and communicate I/O data to higher levels, I/O devices can transmit information on their own. This kind of edge data processing is becoming possible also due to a proliferation of IIoT tools in recent years, for example: • MQTT with Sparkplug B: a secure, lightweight publish/subscribe communications protocol designed for machine-to-machine communications with a data payload designed for missioncritical industrial applications • OPC UA: a platform-independent OPC specification, useful for machine-to-machine communication with legacy devices • Node-RED: a low-code, open-source IoT programming language for managing data transfer across many protocols and web APIs.

Figure 2: Modern edge devices, such as the Opto 22 groov RIO, flatten and simplify the architecture required to connect field I/O signals to business and control applications.

Combined with standard IT protocols like VPN and DHCP for secure remote connection and automatic addressing, these technologies give today’s I/O hardware the ability to act as first-class participants in a distributed system, rather than requiring layers of supporting middleware (Figure 3). Another obstacle to scalability for IIoT systems based on classic I/O hardware is the work required to provide power, network connections, and the right I/O module types. To address these issues, vendors are taking advantage of new technologies to make distributed remote I/O more feasible. One example is power over Ethernet (PoE) capability, which uses a network cable to simultaneously supply low-voltage power and network connectivity. When PoE is embedded into a remote I/O device, it can even supply I/O loop power, simplifying electrical panel design and saving money on additional components and labor. PLANT ENGINEERING

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SOLUTIONS AUTOMATION & PROCESS CONTROL

To make it easier for designers to specify the right I/O interface types, some new I/O devices also include more flexible configuration options, like mixed-signal I/O channels. These provide extensive options to mix and match I/O signal types as needed on one device, reducing front-end engineering work and spares management. The combination of these features within distributed I/O devices makes it possible for implementers to easily add I/O points anywhere they are needed, starting with a few points and scaling Figure 3: up as much as necessary at any time. Wiring needs Modern devices are minimized, so long as networking infrastructure leverage edge is accessible. computing to For more comprehensive control and calculation, make direct of course, any number of edge controllers can also I/O-to-cloud be integrated. The combination of edge I/O and edge integration control leads to a new distributed data architecture. possible.

Architecture options

So what new architectural possibilities are available to industrial automation designers using modern distributed I/O and edge computing? The logical hierarchy is flattened even as the geographical distribution is expanded, with edge devices making local data directly available to computing resources at the edge or at higher organizational levels (Figure 4). Figure 4: Edge controllers and edge I/O enable new information architectures in which devices can share data locally and across the organization, through edge, fog, and cloud: 1) private shared infrastructure with edge data processing 2) legacy PLC integration with edge controller as IoT gateway 3) direct-to-cloud I/O network 4) regional many-to-many MQTT infrastructure.

Here are some examples of new information architectures that are becoming possible for use in places like commercial facilities, campuses, laboratories and industrial plants: Shared Multi-Site Infrastructure: Where field signals are distributed over large geographic areas or multiple sites, edge devices can facilitate data transmission to networked applications and databases, improving the efficiency and security of local infrastructure or replacing high-maintenance middleware such as Windows PCs. Brownfield Site Integration: Edge I/O can form a basic data processing fabric for existing equipment I/O in brownfield sites and work in combination with more powerful edge controllers and gateways using OPC UA to integrate data from legacy RTUs, PLCs, and PACs. This approach improves security and connectivity without interfering with existing control systems. Direct Field-to-Cloud Integration: Engineers can design simple, flat, data processing networks using only edge I/O devices (without controllers or gateways), expanding as needed to monitor additional field signals. A distributed I/O system like this can process and report data directly to cloud-based supervisory systems, predictive maintenance databases, or MQTT servers. Many-to-Many Data Distribution: Edge devices with embedded MQTT clients can publish field data directly to a shared MQTT server or redundant MQTT server group located anywhere the network reaches: on premises, in the cloud, or as part of regional fog computing resources. The server can then share that data with any number of interested network clients across the organization, including control systems, web services, and other edge devices.

Seamless connectivity

Seamless connectivity is now a reality thanks to technologies that make ubiquitous data exchange possible. New hardware and software products enable interconnectivity among physical locations in the field, at the local control room, in the front office, across geographic regions and up to global data centers. Distributed edge I/O, edge computing, and associated networking technologies support data transfer through the edge, fog, and cloud portions of an industrial architecture. End users can erase the former boundaries between IT and OT domains and get the data they need to optimize operations. PE Josh Eastburn is Opto 22 director of technical marketing. After 12 years as an automation engineer working in the semiconductor, petrochemical, food and beverage, and life sciences industries, Eastburn works with the engineers at Opto 22 to understand the needs of tomorrow's customers.

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SOLUTIONS CONDITION MONITORING

By Westin Siemsglusz

Improve plant uptime with advanced sensing systems What every plant manager must know about today’s sensing systems

any manufacturing companies struggle to keep pace with market demands due to production inefficiencies, unplanned shutdowns and delays. Machine performance often is the difference between delays and ontime delivery. Many — if not most — plant performance issues can be addressed by adopting predictive maintenance strategies that identify problems before they result in broken equipment, flawed products, reduced output and costly delays. While preventive maintenance was widely adopted and embraced over the past decade, relatively few manufacturing operations have implemented predictive strategies and tactics. Advanced sensing systems that monitor plant machinery condition are the key to modern predictive maintenance strategies. Manufacturers who have the requisite conditioning-monitoring equipment and systems in place can develop predictive maintenance strategies and put them to work to realize uptime and productivity gains.

Performance controlled

Technology is the servant of today’s manufacturing plant operators. Advances are being made in the development of sensing systems, not only in capabilities

to measure and gauge, but also how information is delivered to those needing it. The stakes are too great to not consider installing condition-monitoring systems. Many variables come into play when things go wrong, potentially crippling a manufacturing line. Irregularities in temperature, humidity and mechanical pressure can lead to breakdowns, costly to repair and impacting uptime. Operating without advanced condition monitoring increases production headaches and negatively impacts bottom lines. However, productivity is improved when operations management is aware of possible machine failures before they fail. Conditioning monitoring is gaining wider usage as plant managers come to understand and appreciate the benefits sensing equipment delivers. Modern condition monitoring requires a digital platform and is made possible by the Industrial Internet of Things (IIoT). Factory connectivity is possible thanks to intelligent networked equipment that transmits data from the machines. This information is stored in the cloud, securely, and is manipulated in whatever format required by managers and technicians. Information is accessible for those who need to keep plants running smoothly, producing efficiently and delivering on-time.

Safety and security

One way to reduce safety risks is to keep maintenance technicians measuring performance or conducting diagnostics away from running machinery. Managers and operators can mitigate risk by measuring machine performance remotely. Thanks to conditioningmonitoring equipment, tests and diagnostics is done by sensors that record data and send it to the cloud, where it can be conveniently retrieved and analyzed. People no longer need to go into harm’s way to analyze machine performance. Data security must also be considered. It is important to understand the benefits associated with

Figure 1: Advances are being made in the development of sensing systems, both in their capabilities to measure and gauge physical properties and how they deliver vital information to people who need it. All images courtesy: Parker Hannifin

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The annual survey, sponsored by Advanced Technology Services (ATS), conducted among maintenance professionals in process, discrete and hybrid industries identified top struggles to improving maintenance to be lack of resources or staff (41%), outdated technology (33%) and lack of understanding of options/ technologies (31%). Also, according to the study, aging equipment (34%) and mechanical failure (20%) are the leading causes of unscheduled downtime. In an effort to reduce downtime, 46% of facilities plan to introduce or change their maintenance strategy and another 46% plan to upgrade equipment.

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SOLUTIONS CONDITION MONITORING

cloud-housed conditioning monitoring systems. Cloud access is password protected and available 24/7 via any device with an Internet connection. The cloud enables secure storage of proprietary information transmitted directly from sensor-enabled machines, without requirements for human gathering, recording and transcribing. Cloud-based condition monitoring can deliver information automatically. A clear advantage exists in receiving exception-based alerts.

Look ahead

Figure 2: Information is transmitted from the machines on which sensors are installed with no requirement for personnel to gather, record or transcribe the data.

Continuous condition monitoring equipment can be easy to install and operate. Systems are affordable for virtually any manufacturer whose managers and operators have access to Internet-connected laptops, desktops, smartphones and tablets. IIoT-based condition monitoring systems provide a continuous flow of information that indicates the condition of production lines and specific pieces of equipment, and help manufacturers realize improvements in operational efficiencies. Parker Hannafin’s sensors and software are at work in a variety of manufacturing plants. Experience demonstrates that they support manufacturers seeking to operate machinery efficiently and keep their plant production on schedule and on time. Success stories include a recent example provided by a manufacturer of washing machines and dryers. Its operations included a plastic injection-molding machine paired with a stamping press, both operated by the same hydraulic power unit (HPU). At one point in the recent past, the manufacturing setup began producing defective parts. Safety also was a concern, as it was typical for two technicians to be

stationed, working as a team, around the machines. One used a manual diagnostic tool at a high-pressure unit while the other was on the floor to cycle the machine and observe its operation. All the tasks involved required considerable setup time, creating safety risks by requiring the technicians to be close to hot machines with moving parts running at speed. Today, after the installation of sensors at five points on the injection molding machine, a single technician runs the machine and uses custom software to track pressure measurements and watch machine functions from a safe area. Troubleshooting is simplified, downtime is minimized and costs are reduced. A wide variety of manufacturing companies that have installed advanced condition monitoring systems realize similar productivity and plant uptime gains. Parker Hannafin’s cloud-based condition monitoring system supports accurate and reliable predictive maintenance data gathering. Benefits include reductions in: • Maintenance costs. Many have seen 50% reductions in costs for labor, overhead and materials. • Mean time to repair. Operators can better plan and make decisions about when and where to repair. • Spare parts costs. Reduce costs by up to 30%. Instead of ordering and stocking spare parts, conditioning monitoring provides enough lead time so parts can be ordered only as needed. • Downtime. Reduced up to 40% due to maintenance performed only as needed. This results in fewer planned shutdowns and assets remaining in service longer. • Machine failures. Expect 55% reduction in the two-year period after implementing a predictive maintenance program with conditioning monitoring sensors. Other gains include: • A 30% extended asset life. Based on five years of operating with predictive maintenance, condition monitoring helps prevent damage to machinery and systems and extends their service life. • A 30% increased asset availability. Realized by monitoring equipment and systems in real time. • A 25% increase in production. Thanks to reliable condition monitoring, plant operators avoid unplanned downtime.

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• April 2020

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ANSI/EASA AR100-2015: Recommended Practice for the Repair of Rotating Electrical Apparatus is the standard for maintaining (or sometimes even EDITATI O CR improving) AC electric motor effiC ciency and reliability.

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SOLUTIONS CONDITION MONITORING

and application of the analytics so as to establish a predictive maintenance schedule. A continuous condition-monitoring system should measure a variety of performance metrics that affect a machine’s output and reliability. These include temperature, humidity, vibration, pressure, strain and current. Each continuous condition monitoring system is engineered to work with a customer company’s proprietary software. Vibration is a critical area. Your condition monitoring system should include ways to measure your machines’ vibrations, as this often is an important early indicator of problems. Sensors also should monitor pressure critical to quality control and process efficiencies. Temperature is an obvious area of concern for manufacturing operations. Continuous conditioning monitoring systems detect irregularities that can result in costly downtime and reduced revenues. Humidity problems also can result from increased operating temperatures. Maintaining optimum temperature and humidity conditions helps ensure machines perform at a high level, improving their length of service. Your condition-monitoring sensors also should be able to For use in layouts where the logo will be placed on a dark color field such as technical measure stress and displacement while enduring the rigors services gray. SILVER = C0.M0.Y0.K30 of millions of cycles. As manufacturing machinery’s elecLIGHT BLUE = PMS285 or C91.M53.Y0.K0 trical components wear, they often require more power to drive operations. Your equipment sensors should be capable of monitoring amperage so that maintenance work can be done before problems develop. Your condition monitoring systems will work hard for you and deliver numerous advantages.

Final words

Features and benefits of a condition monitoring solution should include easy setup and operation, convenient webbased interface and no software to install or update. Formulating alert notifications should be possible, whether these arrive via email, text or in-system, and they should be customizable. Data can be reviewed anytime, anywhere. Safety is improved becausePATENTED measurements TECHNOLOGYcan be taken without interrupting production. Time savings can be significant, as maintenance departments can do more with less. Identifying problematic machines can be the focus. Plant managers are moving beyond preventive maintenance practices and embracing predictive maintenance strategies built around continuous condition monitoring systems powered by advanced sensors. Their return on investment is significant as they experience fewer breakdowns and headaches, and thereby deliver major gains in plant uptime and productivity. PE Westin Siemsglusz is the IoT market sales manager for Parker Hannifin’s Quick Couplings Division. She started her career with Parker's Filtration Group in 2014 working with customers on improving their filtration and integrating condition monitoring solutions into their systems. She also is a member of the company’s IoT Solutions Team investigating innovative applications for IoT products for the plant floor.

• April 2020

PLANT ENGINEERING

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SOLUTIONS MOTORS AND DRIVES

Your questions answered:

Troubleshooting techniques for ac induction motors Webcast presenters answer questions on troubleshooting techniques for ac induction motors

n March 3, 2020, CFE Media & Technology hosted a webcast on troubleshooting and maintaining ac induction motors. The webcast invoked numerous questions from the audience. Here are some of the most interesting, which were answered by Michael Lyda, a motor and drive engineer at Advanced Energy Corporation. Ronnie Alford, motor lab coordinator at Advanced Energy Corp. also presented as part of the webcast. Much thanks to them both.

1. You state, “Every 10o C cuts insulation life by half.” Does that mean for every Every 10o C above ambient temperature rating? No. Think of it as every 10° C rise above normal winding temperature at full rated load.

2. These days, technology can provide electronic protections for over/under voltage and heat rise. Why is it not implemented?"

These things are available, just with added cost to the initial purchase. Temperature relays are standard these days for certain types of motors.

For the voltage unbalance, does the ground help in any way? The ground helps for safety. The relationship between the ground and voltage unbalance is this: When voltage unbalance is present in a 3-phase system, you will likely see current running through the ground. This is due to the sum of all currents not being zero in an unbalanced system, and the ground is the only place for the excess current to go. This also is referred to as the zero-sequence current.

Some utilities' standards allow a 3% voltage unbalance and state that the user

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should just de-rate their motors if utilitysupplied voltage is unbalanced at their location. Is derating enough or does it cause other problems? This really depends on the application. I would look at each on a case-by-case basis. For example, if you already have an oversized motor on the application, then de-rating it due to the unbalance will still likely keep you running below or at the rated full load operating temperature on even the line with the highest current. But if your motor is already designed near the rated load with balanced voltage, the increased current due to the voltage unbalance could lead to early failure (excess heat). Looking at the impact on motor efficiency, voltage unbalance is detrimental to efficiency in almost every case. Looking at voltage unbalance at the input to a variable frequency drive (VFD), the VFD may trip off if the unbalance is too high.

5. Do you feel 500 V is a proper level of voltage when testing motors used on VFDs? The 500 volts level is specified for infrared (IR) testing for motors rated under 1,000 V.

6. How would you remedy connecting a 230 V motor to a 208 V service? Provide a motor rated for 208 V.

7. Is there a way to measure negative

sequence current which is normally produced during current balance? You can always check the current flowing through to ground (if there is any), which gives you a good idea. There are fancy meters that you can buy to do this. PLANT ENGINEERING

April 2020

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SOLUTIONS MOTORS AND DRIVES

Michael Lyda, a motor and drive engineer at Advanced Energy Corp.

8. I often see extremely distorted sine

waves (voltage and current) because of harmonic distortion on the ac line. How much distortion of the sine wave is allowed? Tough question. IEEE 519 is a resource you could take a look at. Power utilities don’t like harmonics because they can’t charge you for harmonic current or reactive power. They can only charge you for real power. They also don’t like the negative impacts that increased harmonics have on the grid and other customers. I don’t know of any regulation around this topic, but the IEEE 519 standard will get you headed in the right direction.

9. How does harmonic mitigation on the input of a VFD affect its output?

Adding a line reactor to the input of the VFD adds inductance to the circuit thus lowering the harmonic impact of the capacitance on the output. This is good news for the motor. Motor performance and reliability are improved when it sees less current harmonics.

10. I have not seen many VFD-driven

motors with bearing ground protection. Noting that the bearing is the lead cause of failure, how much can this protection impact those statistics?

• April 2020

11. If the service factor (SF) is 1.25, what

percentage of increase in overload current should be applied if the SF is to be used in design? I’m thinking that air compressors seem to use all of the available SF.

Most motors will have an SFA column with the service factor amperage listed. If your motor does not, then just multiply the full-load amps (FLA) by the SF to get the SFA. For the air compressors generalization, I’m not completely sure, but maybe the compressor manufacturer is using a smaller motor to cut the overall cost of the unit. This may give them a competitive advantage while staying capable of delivering the required output (some of the time).

12. What temperature of a motor surface

with insulation class C is considered permissible? The insulation class temperatures refer to winding temperature only. I am not aware of any ratings around surface temperatures. But if I could point you to a resource it would be UL 1004. I may be wrong, but I believe surface temperature would be more of a safety concern.

13.

You can run a 50 Hz motor at 60hz. It’s called field weakening area. Output power should be kept constant, which means torque should be reduced. Good point, yes you can. You can also drive 60 mph in a 50-mph zone, but one day it may backfire. If this is a critical application, I would be leery of mismatching the frequency of the supply. For an application where you may be typically running at 50% to 75% load of the motor anyway, you will likely not see much of a difference. On the flip side, if your motor is more closely matched to the rated load (at 50 Hz), then you will see overheating when running at 60 Hz — and we all know what that leads to. PE

Ronnie Alford, motor lab coordinator at Advanced Energy Corp.

The bearing ground protection on VFD-driven motors is to mitigate shaft bearing currents originating from the pulse width modulation (PWM) signal from the VFD. Voltages will be hitting the motor winding at much higher voltage than nameplate rating and the PWM switching frequency will be many orders above the driven frequency of the motor. The high frequency switching can lead to current if there are any temporary shorts (like shaft to bearing through the ball bearings). One reason you may not see many of the grounding rings is cost. They aren’t cheap.

PLANT ENGINEERING

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SOLUTIONS OVERALL EQUIPMENT EFFECTIVENESS

By Emrah Ercan

Conduct asset performance management with a softwarebased approach Unite separate parts of the organization, allowing teams to work collectively

anufacturers embrace digital transformation to boost operational efficiency, minimize risk and improve productivity. Many accomplish these goals through better understanding of asset performance. The most common metric for measuring manufacturing productivity is overall equipment effectiveness (OEE), which identifies the percentage of truly productive production time. In other words, productive time is where good parts are made at optimum efficiency, without downtime. First popularized in the 1960s by Seiichi Nakajima, founder of the total productive maintenance system, OEE is a function of a unit’s availability, performance compared to designed capacity and product quality. OEE is commonly thought of as a manufacturing key performance indicator (KPI) in that it provides a thorough evaluation of asset productivity, whether it be for a manufacturing line or entire plant. Quantification, i.e., data, gives production managers greater visibility into where and how effectiveness is lacking. Addressing these shortfalls in effectiveness is one of the best ways to improve plant productivity. For OEE, equipment productivity loss is categorized as the “Six Big Losses” as follows: Availability: • Equipment failure • Setups and adjustments. Performance: • Idling and minor stops • Reduced speeds. Quality: • Process defects • Reduced yield. The Six Big Losses provide detail into the factors that undermine manufacturing productivity and guidance as to what specific areas are best targeted

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for making improvements. In this sense, OEE offers a framework for uncovering the core issues limiting efficiency. Since the inception of OEE, digital technologies have enhanced measurement accuracy and efficient application of improvements. And, with the ability to unlock insights from thousands of data points, advanced analytical tools like asset performance management (APM) software give operators the ability to make incremental OEE improvements, and thereby, productivity enhancements. Today, APM software offers solutions to optimize OEE even further. The next evolution in APM software allows manufacturing facilities to collect and integrate historical data to build a dynamic model — a digital twin — that ingests new data to predict the remaining useful life of critical plant assets. As a virtual representation of a plant’s assets, a digital twin is modeled from past performance data, real-time present data, and “future” data supplied by machine learning algorithms and guidance from engineers. A digital twin is valuable for its ability to detect bottlenecks, facilitate predictive maintenance programs and identify benchmarking opportunities for informing OEE efforts. On a business level, APM software also can offer greater understanding of real cost-of-production and return on investment, which will help businesses optimize end-pricing to customers, making them more competitive.

Predict remaining useful life

A digital twin built from APM software allows mimicking of asset lifecycles, simulating their remaining useful life. In manufacturing environments, this approach allows understanding the current state of critical assets and predicting how they will fare in the future. By simulating forward — using historic data trends and current operational dynamics as a guide — a digital twin delivers a view into the future. PLANT ENGINEERING

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SOLUTIONS OVERALL EQUIPMENT EFFECTIVENESS

With performance, availability and quality measurements, manufacturers can generate OEE benchmarks of their assets and production lines to understand which areas of their operations are the most productive and where improvements need to be made. Image courtesy: CFE Media

By modeling outcomes that would result from changing key parameters, digital twin technology provides important insights for optimizing OEE and driving continuous improvement. In addition, virtual representation models can be designed for the component level, the system level, i.e., for an entire production line or the process level (the entire manufacturing process). If a model estimates the period remaining before the asset is likely to break down or reach the end of its useful life, engineers can stress-test input changes or take preemptive action to prevent failure before it happens. As adjustments or repairs are made, this data can be fed back into the digital twin to determine whether the future state of the component, asset, system or process thereby changes.

Detect bottlenecks

Bottlenecks impede material flow — and hence, productivity — in manufacturing facilities and constitute the weak points in any supply chain operation. The throughput at a bottleneck determines the pace on a manufacturing line and is the limiting factor for efficiency in a facility. The root issues of bottlenecks generally include process and machine limitations, such as outdated,

• April 2020

PLANT ENGINEERING

inefficient or faulty equipment requiring continuous repairs and resulting in slower production and downtime. However, bottlenecks are not always apparent. The outcomes of a bottleneck — for example, production shortfalls — might be painfully obvious, but where and why it is occurring might not be. In these cases, a virtual twin assembled from historical data is a tool for uncovering bottleneck sources. By examining trends across the data record, such as equipment performance or production data corresponding to each manufacturing line, facility managers can discover those factors that impact plant efficiency. For example, chronic underperformers can be identified or historical data can indicate how often a line has run out of a certain raw material or packing supply. What makes bottlenecks difficult to document is that root causes may not be readily apparent. But with a clearer view of the facility, managers can better discover their underlying cause. Take the example of a brewery. If historical data reveals that a pasteurizer can produce a greater volume of beer compared to what can be handled by the packaging line (the next step in the production process), the bottleneck’s root cause will be evident. But if that packaging line is being pushed to operate at maximum capacity and absorb everything coming from the pasteurizer to meet a target output, the brewery might be more likely to see the bottleneck as arising from equipment failure on the packaging line. This scenario might also result in shortened asset lifecycles. With access to this insight, a facility manager might realize the best course of action is to invest in enlarging the packaging line rather than running equipment at its design limits.

Predictive maintenance

Creating a virtual asset representation from historical data and simulating performance forward under varying scenarios allows operators to anticipate exposure, wear on components, risk factors and where failures are most likely to occur. Simulations developed from historical knowledge also can include contextual data about an asset’s maintenance schedule — corrective www.plantengineering.com

maintenance performed, repairs and replaced parts. This can be merged with further information regarding performance records, operating environment and newly available IIoT data collected from the physical asset. By combining all this data, predictive models can advise as to maintenance actions for minimizing unplanned downtime and potentially eliminating the need for fixed maintenance schedules.

Benchmark for OEE

Digital simulations also are used to conduct benchmarking between sites and assets for optimizing OEE efforts. By benchmarking real-time production and performance metrics, regional managers can make accurate comparisons at the asset, system and process levels. Benchmarking data can be used to compare chemical treatment programs in different regions or the performance of cooling towers, boilers or specific water treatment technologies across multiple sites. In a packaging scenario, benchmarking data provides plant managers with greater visibility into output, cost and investment performance of each packaging line within a facility. With performance, availability and quality measurements, manufacturers can generate OEE benchmarks of their assets and production lines to understand which areas of their operations are the most productive and where improvements need to be made. These evaluations also can be extended to the entire facility, allowing OEE benchmark comparisons at a larger scale.

not follow from simply adopting APM software and targeting OEE enhancements alone. Companies must first focus on enacting mature APM software programs based on connecting systems and technology across the enterprise. As the “glue” to bring previously siloed areas together, such as enterprise resource planning, digital supply networks and enterprise asset management systems, the value of APM software lies in its capacity to unite separate parts of the organization, allowing different teams to work collectively as one unit. Applied in this way, field-level results drive enhanced performance, which translates into financial results through topline growth, cost reduction, safety, quality and capital efficiency. PE Emrah Ercan serves as global director of digital solutions at SUEZ Water Technologies and Solutions and is a member of the company’s innovation and digital board of directors. He is responsible for strategic direction, commercialization and development of the company’s digital solutions. Previously, he served as vice president of strategic initiatives at GE Oil & Gas and GE Digital, where he established an internal incubator to fund early-stage digital oilfield ideas.

Improve financial performance

OEE also offers tremendous value as a business KPI. Applied as a business metric, OEE enables companies to view their operations in financial terms, helping them understand where to deploy resources for improving cost performance. Here, APM software provides benefit by delivering deeper insights into how improvements can reduce manufacturing costs, increase profit margins and enhance ROI. Armed with more detailed cost awareness in terms of their business operations, companies can better optimize product end-pricing to advantage. However, recognize that achieving efficiency gain in core operations and improved financial performance does

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SPECIAL REPORT

EDGE COMPUTING A transformative, optimized architecture

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EDGE COMPUTING

4-STEP pathway to digital transformation On the edge: Putting computing power close to the process reduces control system latency, creates a distributed architecture, and can integrate machine learning (ML) and artificial intelligence (AI). See four steps toward edge computing.

dge computing architectures have been advanced by cloud services, which have long helped companies simplify and secure data aggregation and processing functions. As time progressed, technological advancements such as mobility and differentiation in user interface and user experience (UI/ UX) approaches resulted in more connected and distributed processes, devices and machines. Companies realized there was a need for more immediate intelligence from data closer to the source. This increased demand for edge computing.

Edge computing: Four-step progression

Four steps toward greater adoption of edge-computing follow (see graphic). 1. Cloud computing revolutionizes business. 2. Edge computing architectures resolve emerging challenges. 3. Concerns arise over costs of digital transformation. 4. Optimization and asset utilization benefits make edge computing more feasible.

Edge computing can be crucial for some industries and manufacturing industry applications to resolve a range of challenges. This includes equipment breakdown and unplanned downtime. Intelligent temperature monitoring sensors, for example, can be automated to record temperature changes in the immediate surroundings. In case of an emergency, these devices can activate sprinklers, alert the fire department and shutdown all power systems in a factory. This scenario will require machine-to-machine (M2M) edge computing to decrease network latency and deliver real-time control and moni-

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April 2020

toring. Earlier, devices at the edge were only programmed to locally collect data and transmit it to a remote server (cloud). With the assistance of AI, edge devices can now be embedded with machine learning (ML) capabilities to self-learn and execute actions without waiting for a response from a central computer. Programmable logic controllers (PLCs) can be taught to detect issues, analyze the issue, and execute counteractive procedures, according to some PLC manufacturers. PLCs can act as edge nodes with ML capabilities to activate prescriptive and predictive maintenance without interventions from information technology systems or humans. Every manufacturing plant wants what this cutting-edge innovation can deliver. The problem: at what cost?

Edge computing justification

Organizations balk at large investments in new technology without getting a tangible sense of the return on investment (ROI). Technologies are evolving rapidly. Just as we embraced cloud computing and are now rethinking this strategy for high availability and instant compute abilities, we could perhaps pose the same question for edge computing. The immediate benefits may outweigh the costs, but the evolving technologies pose a risk in terms of investment. Intelligent sensors with ML and AI capabilities are far from being cost effective. If an organization has already implemented a cloud strategy, does it make sense to move them to an edge computing strategy immediately? This depends on the requirement. The additional cost for sensors, local processing power and other features will add to the overall overhead and increased costs. As a strategy, this defeats the purpose it was meant to mitigate.

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www.beckhoff.us/C6015 With the ultra-compact C6015 Industrial PC, Beckhoff has again expanded the application possibilities of PC-based control. Wherever space or cost limitations previously prevented the use of a PC-based control solution, this new IPC generation offers an excellent price-to-performance ratio in an extremely compact housing. With up to 4 CPU cores, low weight and unprecedented installation flexibility, the C6015 is universally applicable in automation, visualization and communication tasks. It is also ideal for use as an IoT gateway. Processor: Intel® Atom™, 1, 2 or 4 cores Interfaces: 2 Ethernet, 1 DisplayPort, 2 USB Main memory: up to 4 GB DDR3L RAM Housing: Die-cast aluminum-zinc alloy Dimensions (W x H x D): 82 x 82 x 40 mm input #17 at www.plantengineering.com/information

2018 Flexible installation via rear or side panel mounting, or on DIN rail.

HONORABLE MENTION

SPECIAL REPORT

EDGE COMPUTING The evolving landscape around edge computing brings new opportunities and challenges. Edge computing offers undeniable benefits over legacy network architecture systems and raises questions that require extensive research before investment. Courtesy: L&T Technology Services

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Consider economies of scale. How close to the edge is close? Should it be

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completely on equipment or premise?

self-protecting edge-computing platform specifically designed for industrial control system environments, as previously reported. The platform comes embedded with zero-touch computing properties and is expected to simplify a range of remote management activities such as cloud-based health monitoring, automated site and data recovery. Such platforms can offer a middle path to optimize costs by considering capital expenditures (capex) and operational expenditures (opex). Such sceKEYWORDS: Edge computing, narios should consider the economies cloud services of scale. The question to ask is: How Edge computing distributes control close to the edge is close? Should it be architectures and reduces latency. completely on equipment or can it be Machine learning and artificial on premise? Processing data on the intelligence can be integrated into devices instead of using co-location edge computers and PLCs. data centers and existing cloud infraEdge computing can bring cloud services to distributed architectures. structure requires research and time. Depending on this answer, infrastrucCONSIDER THIS ture and cost optimization and utilizaHow could an edge-computing tion indicators could go up or down. distributed architecture help your

M More ANSWERS

processes?

Cloud and edge computing

ONLINE Click on the headline, if reading from the digital edition, to access more resources. www.controleng.com/magazine www.controleng.com/webcasts www.controleng.com/webcasts/past

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Technology trends can be ambiguous with interminable discussions on the pros and cons of each trend. Most organizations tend to err on the side of caution and deliberate before taking a conscious decision to either adopt or

let pass an upcoming technology. Based on empirical evidence it is clear that enterprises who have failed to adopt new technologies lagged behind those who have. In 2008, many industry champions dismissed cloud computing trend as passing and yet, almost a decade later, cloud computing is moving to the edge. Cloud computing saw rapid adoption because it provided organizations with easy accessibility to vast storage with near zero application usage latency and pay-as-you-go models sweetening the deal. Organizations had every reason to go for this. However, after a decade, as applications are distributed across geographies and major challenges remain with cloud providers, latency, experiential consistency and security, organizations are rethinking cloud strategies.

Having an edge in 2020, beyond

Gartner estimates 91% of today’s data is created and processed in centralized data centers. By 2022 about 75% of all data will need analysis and action at the edge. Edge computing will become the principal method by which enterprises implement digital transformation. Edge computing offers many benefits over legacy network architecture systems. As it continues to evolve and make more inroads for organizations, it also will raise questions that will require extensive research before investment. Organizations need to look at transformational opportunities with a thoughtful, deliberate approach to validate this investment. ce

Dr. Keshab Panda is CEO and managing director, L&T Technology Services, a Control Engineering content partner. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com. SPECIAL REPORT: CONTROL ENGINEERING

MOVE SECURELY INTO THE CLOUD S

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RI U C E

-IN T L I BU

SPECIAL REPORT

EDGE COMPUTING

Edge computing terms, skills Ask six edge computing questions on data collection, networks, control systems.

hether we realize it or not, most people use edge computing daily. A prime example is when we use the speech recognition features of our mobile phones to ask for Siri or Cortana. Since language processing takes a lot of computational power the phone first does some initial processing, lightening the load for the server and streamlining the data going to it. If all processing was performed on the phone, it would tax the phone’s resources. Processing data in the cloud frees up the user’s phone to perform other tasks and allows companies like Google and Apple to update and improve the software. If a phone did no pre-processing before sending data to the cloud, our networks and servers could become bogged down with data. A similar model makes sense in industrial applications. Edge devices operate at the edge of a local network and provide the interface between control system(s) on the plant floor and the outside network. They act as a bridge between the control system and cloud servers or remote computers, processing data between the control system and servers. Performing data computations on the edge device reduces the traffic and the processing power required by both the control system and remote servers. Having an edge device also allows users to update functions on the edge device without disrupting the control system. Edge devices also can provide a “firewall” or “air gap,” isolating controls equipment from the public network, for better security. Edge devices also can buffer data if there is network latency or even a network outage. If this happens, the edge device stores the data until the network connection can be restored.

Six edge computing questions to ask

Ask these questions to clarify if an edge device is right for an application: 1. Do I need to collect historical data from the control system? 2. If I collect data, are there benefits to storing this data in a central location? Could this data be used for reporting, down time analysis, predictive maintenance or inventory tracking? 3. Does the control system need to interface with the outside network, such as the plant network, business systems or the internet?

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4. Does the control system receive information from the outside network, such as inventory, recipe and batching systems? 5. Is there a benefit to adding mobile devices or features such as alarm notification? 6. Can non-essential functions be offloaded from the “mission critical” control system? For example, could functions such as image processing and recipe management be moved to a non-production computer? If the answer was yes to one or more question, then an edge device may be a good fit for the application.

Edge device benefits

The benefits of using an edge device can be grouped into the following categories. Sharing data • The edge device interface allows the control system to share data with external systems. –The edge device can act as a bridge or protocol converter, allowing legacy equipment to interface with other devices and networks. –Ethernet IP devices can interface with the external network without having to modify the existing network or change IP addresses. Improving security • Edge device provides a security layer between the control system and external network. –The edge device can provide a fire wall and air gap to help protect the control system. –The edge device can provide security monitoring and access control. Processing and network improvements • Moving non-critical functions to an edge device allows the control system to “focus” on the most important tasks. –It frees up more memory and processing power for mission critical functions. –Non-critical functions, running on the edge device, can be updated and modified without the disrupting production. • Reduce network traffic and mitigate the impact of network disruptions. –Basic data processing on the edge device can help reduce network traffic. –Buffering data on the edge device can reduce the impact of network issues. SPECIAL REPORT: CONTROL ENGINEERING

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Edge devices can do a lot more. They can take help a basic application become future-

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ready. Edge devices operate at the edge of a local network and bridge the control system and cloud servers or remote computers, processing data between the control system and servers. Images courtesy: MartinCSI

–Edge device can convert data to “lighter weight” messaging protocols such as MQTT, reducing bandwidth and improving efficiency.

Next steps after evaluation

After the evaluation, users need to ask how to select the best device for the applications. What features and functions are needed? These three edge device core considerations should be front of mind. • Functionality: The control system should operate with or without the edge device. When looking at functions to put in an edge device, ask: “If the edge device is turned off, would the process still run reliably?” The answer should be yes. • Security: An edge device should restrict direct access to the control system from the outside network. The edge device can provide a means to isolate the control system while still allowing data to flow in both directions. • Performance: With performance, users need to ask the following questions: –Is the control system processing large amounts of incoming or outgoing data? If so, consider having the edge device process this data. –What data processing is being performed in the cloud or a remote server? If moved to an edge device the amount of data sent across the network will be reduced. An edge device can be anything from a relatively simple, low-cost device to something as robust as an industrial PC. What makes an edge device is more a matter of where and how it is used than the actual hardware. Edge devices can do more than these core features. They can take help a basic application become future-ready. Enhanced features include:

SPECIAL REPORT: CONTROL ENGINEERING

Users talking to an AI like Siri or Cortana are actually engaging in edge computing without realizing it.

• Performing logic and math calculations. • Acting as an HMI and host screens. • Acting as an Ethernet switch and incorporate features found in managed switches and routers. Network address translation (NAT). • Edge devices facilitate Industrial Internet of Things (IIoT)/Industry 4.0 functionality and allow users to perform –Protocol conversion. For example, network traffic conversion from Modbus TCP/IP, CIP and Profinet protocols to MQTT. –Run apps and APIs that directly interface with software running on remote servers or the cloud. –Run an operating system such as Linux or Microsoft Windows, allowing users to install off-the-shelf software. –Provide added firewall and network security features and diagnostics. –Run a structured query language (SQL) database.

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While the core functionality can be found in most edge devices, the enhanced features will provide room for the application to grow into the future. Selecting an edge device and determining how it is used will depend on the specific application and the customer’s needs. When an edge device is properly selected and configured, the result will be a control system with improved performance, higher security and greater maintainability. Most importantly, it provides meaningful information available to those who benefit from it the most. ce Nate Kay, project manager, MartinCSI. Edited by Chris Vavra, associate editor, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

KEYWORDS: edge computing,

smart devices Edge devices act as a bridge between the control system and cloud servers. Edge devices are useful for applications where data from an outside network needs to be gathered and evaluated. What makes an edge device is more a matter of where and how it is used than the actual hardware itself

ONLINE View other articles in the Edge Computing Special Report for the Control Engineering April 2020 issue.

CONSIDER THIS What applications do you think would benefit most from edge computing and why?

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