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PLCs starting at only $69.00 Whether the job is very simple or extremely complex, we have the affordable PLC solution you need. Our three PLC families provide a variety of control options and can handle a wide range of applications from simple counter/timer logic to coordinated motion. So don’t break the bank with those other guys, keep your project on time and under-budget with AutomationDirect!
CLICK starting at
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The CLICK PLC family offers extreme value for everyday applications. The compact size and easy programming make CLICK great for small applications and beginner projects.
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The Do-more PLC family features one of the most advanced instruction sets in the market as well as many other features that allow it to stand strong against any challenge.
starting at
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The Productivity Series PLCs are scalable, high-performance tag name based controllers with expansive built-in communication options and other features you’ll love at an awesome price.
With our PLCs you’ll never get hit with extra fees since our software, manuals, tech support, and access to online resources are all completely FREE! You can learn all about our PLCs by visiting:
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HMIs starting at $98.00 Our C-more HMIs are designed to provide complete system visibility and utmost cost savings for your interface needs. From basic systems to advanced, C-more HMIs have the animations, logic, math, alarming, remote accessibility (web server/mobile app) and communication needed for modern systems.
www.automationdirect.com/ operator-interface
AC VFDs starting at $108.00 Dynamic braking, PID, V/Hz control, sensorless vector control and a variety of communication options including BACnet are just a few of the features available with our AC drives. With horsepower ratings up to 300 hp and the ability to control eight motors with one GS4 drive, you’re guaranteed to find the AC motor control and the savings you’re searching for.
www.automationdirect.com/VFD
Sensors starting at $12.50 You need sensors? Well, we’ve got tons, actually over 3,000 sensors and accessories! We currently offer rotary encoders for detecting position and speed, sensors for detecting proximity, pressure, temperature, level, flow, current and voltage, and limit switches for detecting presence or end-of-travel limits. With discrete or analog outputs, these sensors can provide critical data when automating any machine or process.
www.automationdirect.com/sensors
g n
oday!
g, GA USA. All rights reserved.
Over 25,000 low-cost quality industrial control products are available on our webstore (www.automationdirect.com) 24/7/365 and each one comes with the customer service and support you deserve. So for your next project, check us out and remember when it comes to automation, no one gives you more than AutomationDirect! input #2 at www.controleng.com/information
1-800-633-0405
the #1 value in automation
Nobody does FREE better than AutomationDirect... NO PURCHASE NECESSARY!
linePLCTr n O
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FREE ONLINE PLC TRAINING Over the years, we have seen the demand for PLC training grow exponentially not just with our customers but with those new to PLCs in general. To support this demand, we have expanded our online PLC training offerings, allowing easy and free access to anyone interested in learning about industrial controllers. This completely free online PLC training course is available 24/7 so you can learn at your pace and at your convenience. To access the training or learn more about what is provided, follow the link below.
www.automationdirect.com/plc-training
FREE PLC SOFTWARE
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Our CLICK, Productivity and Do-more series PLC software packages are available to download as many times as you’d like, free of charge. Our Do-more Designer software even includes a project simulator, so no hardware is required to test your logic. To try out ladder logic or test drive our PLCs, visit: www.automationdirect.com/ADCPLC
Free technical support is available via phone ((800) 633-0405), email or chat, M-F 9am to 6pm EST. Our technical support specialists are continually trained on our vast selection of products and can provide assistance with selecting the right products, troubleshooting technical issues, and/or finding the proper solution for any application.
With the pace of business today, waiting around for components to be delivered is unacceptable. We understand this, and with our automated warehouses and huge inventory we are able to ship products the same day (if ordered before 6pm) and get them to you fast with 2-day delivery free on orders over $49 (visit our store for further details/ restrictions).
...and our prices are unbeatable too! input #1 at www.controleng.com/information
Order Today, Ships Today! * See our Web site for details and restrictions. Š Copyright 2019 AutomationDirect, Cumming, GA USA. All rights reserved.
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Don’t get burned by high prices. Stay cool with quality, affordable temperature sensors from AutomationDirect. ProSense® Digital Temperature Sensors Starting at $149.00
• A precision RTD sensing element combined with measuring electronics in a stainless steel transmitter probe • Two solid-state switch outputs • Scalable 4-20 mA analog output option on select models • Built-in digital display, with LED status indicators • Standard probe lengths and integral NPT process fittings • Simple pushbutton setup, or use the FREE XT-SOFT software
ProSense® Type K, Type J & Type T Thermocouples Starting at $18.50
• Measure from -328 to 2100 °F • Probes with connection heads, hex nipples, attached plugs, or lead wire transitions • Adjustable immersion sensors • Bolt-on ring sensors • Ambient air room temperature sensors
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• Measure from -58 to 572 °F with PT100 platinum three-wire elements • Probes with connection heads, hex nipples, attached plugs, lead wire transitions, integral M12 connectors, or sanitary connections for clean-in-place • Adjustable immersion sensors • Bolt-on ring sensors • Ambient air room temperature sensors
ProSense® Temperature Transmitters with Integral Sensors Starting at $122.00
• A precision RTD sensing element combined with transmitter electronics in a compact, strong stainless steel housing • With three preconfigured measuring ranges these probes are ready to use right out-of-the-box • Use the FREE ProSense software to program custom ranges and change other parameters • Choose from four standard probe insertion lengths and two NPT thread sizes for direct or thermowell mounting - no mounting adapters or fittings required
Also Available Thermometers/ Temperature Gauges
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Order Today, Ships Today! * See our Web site for details and restrictions. © Copyright 2019 AutomationDirect, Cumming, GA USA. All rights reserved.
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the #1 value in automation
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Vol. 66 Number 3
ÂŽ
MaRCh 2019
ANSWERS 21 | Hardware capabilities impact edge computing success Consider processing, form factors, and certifications
23 | New edge computing opportunities can help manufacturers Faster data and new analytical possibilities
21
Cover images on edge Computing: Inductive Automation (top, p. 23) shows a simpler infrastructure maps once at the edge and delivers data more efficiently, with messaging queuing telemetry transport (MQTT); the Opto 22 groov EPIC combines I/O, control, communications and HMI (lower left, p. 26); and Beckhoff Automation offers ultra-compact Industrial PCs (IPCs) to serve as add-on gateway devices, perform machine control, and edge computing (lower right, p. 21).
INSIGHTS 5 | Research: HMIs for processes TEChNOlOgy UPDaTES
6 | Factory of the future resolves problems today 10 | Digitalization 14 | Cybersecurity 16 | Optimization NEWS
18 | Data is the currency of the future; Manufacturer hosts STEM career day; Automation group names president; Online headlines 20 | Think Again: More open process automation?
24 | Edge computing for efficiency, quality
Streamline operations, enhance efficiencies, quality
26 | Gaining the edge in automation Architecture, flexibility, easier programming
27 | 10 best practices for edge computing
Choose, install, and use edge computing devices for a manufacturing or process facility application.
28 | Standards: CANopen IoT benefits 30 | Big Data analysis or data acquisition? Data architectures adapt to new opportunities in data collection, analytics.
32 | Connecting quality data to process data 33 | Resolve five Big Data, data acquisition challenges 34 | Solids level measurement
Accurately measuring the quantity of solids in a tank or silo is crucial to product management, custody control.
INSIDE PROCESS
P1 | Verifying primary and secondary flow measurement performance: Part 2 P7 | Temperature sensor calibration
CONTROL ENGINEERING (ISSN 0010-8049, Vol. 66, No. 3, GST #123397457) is published 12x per year, Monthly 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. CONTROL ENGINEERING copyright 2019 by CFE Media, LLC. All rights reserved. CONTROL ENGINEERING is a registered trademark of CFE Media, LLC used under license. Perio dicals postage paid at Downers Grove, IL 60515 and additional mailing offices. Circulation records are maintained at 3010 Highland Parkway, Suite #325 Downers Grove, IL 60515. Telephone: 630/571-4070. E-mail: customerservice@cfemedia.com. Postmaster: send address changes to CONTROL ENGINEERING, 3010 Highland Parkway, Suite #325 Downers Grove, IL 60515. Publications Mail Agreement No. 40685520. Return undeliverable Canadian addresses to: 3010 Highland Parkway, Suite #325 Downers Grove, IL 60515. Email: customerservice@cfemedia.com. Rates for nonqualified subscriptions, including all issues: USA, $165/yr; Canada/Mexico, $200/yr (includes 7% GST, GST#123397457); International air delivery $350/yr. Except for special issues where price changes are indicated, single copies are available for $30 US and $35 foreign. Please address all subscription mail to CONTROL ENGINEERING, 3010 Highland Parkway, Suite #325 Downers Grove, IL 60515. 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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control engineering
March 2019
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No. of controllers expected to be purchased More than 50
INSIGHTS
RESEARCH
1 to 5
21 to 50
12% 27%
11% 19%
31% 11 to 20
6 to 10
On average, end users expect to buy 21 controllers over the next 12 months. Source: Control Engineering 2018 Programmable Controllers Study
90%
of end users specify variable-speed drives for new applications; 76% for retrofit and 73% for replacement. Source: Control Engineering 2017 Motor Drives Study
2 in 5
end users expect the number of employees in their department to change in the next 12 months. Source: Control Engineering 2018 Career & Salary Study
35%
of end users buy or specify their HMI software and HMI hardware as integrated components. Source: Control Engineering 2018 HMI Software & Hardware Study
More research Control Engineering covers several research topics each year. All reports are available at www.controleng.com/research.
www.controleng.com
2018 HMI SOFTWARE & HARDWARE STUDY
HMIs in process manufacturing
T
hirty-one percent of respondents to the Control Engineering 2018 HMI Software & Hardware survey work at a facility primarily involved in process manufacturing, such as chemicals and pharmaceutical manufacturing. Below are five key findings as they relate to use of human-machine interface (HMI) software and hardware in these industries: 1. Integrated software, hardware: Thirty-six percent process manufacturing facilities usually buy or specify HMI software that is integrated with HMI hardware, while 32% purchase them separately. 2. Annual spend: Process manufacturing facilities spent an average of $165,000 on HMI software and hardware in the past 12 months. Eighty-three percent of end users in these industries expect to buy HMI software or hardware again in the next 12 months; the average estimated spend is $156,000. HMI software and hardware are most often purchased from local distributors or directly from a vendor.
3. Integration features: Capability with prior versions (76%), ease of integrating data from other systems (67%), and HMI software integrated with HMI hardware (60%) are the most desired/ valuable integration features in HMI software for process manufacturing facilities. 4. Cybersecurity: Seventy-five percent of process manufacturing facilities restrict access to their HMIs for cybersecurity reasons; 59% have increased HMI password protection procedures. 5. Mobility: Half of surveyed facilities prefer to use mobile industrial HMI hardware, 47% use industrial tablets or handheld devices, and 26% want an enclosure around a mounted commercial tablet. ce
M More RESEARCH
View additional findings at www.controleng. com/2018-hmi-software-and-hardwarestudy. Amanda Pelliccione is the research director at CFE Media, apelliccione@cfemedia.com.
Justifications for new HMI software and/or hardware in process manufacturing facilities 62%
Automation upgrade
43%
New installation
39%
Operations/engineering upgrade
26%
Operator: ease of use or efficiency
18%
Enhance information or systems integration Enterprise upgrade
14%
Increase production
14%
Cybersecurity risk is less
12%
Industrial Internet of Things (IIoT)
10%
Overall equipment effectiveness (OEE)
10%
Process manufacturing facilities most commonly acquire new HMI software and/or hardware as a result of an automation upgrade (62%), new installation (43%), or operations/engineering upgrade (39%). Source: Control Engineering control engineering
March 2019
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INSIGHTS
Technology UpdaTe Alex West, IHS Markit
A factory of the future resolves today’s problems Improve productivity, be more flexible to customer needs, and provide better working conditions by using technologies from factories of the future, as needed by industry and company type, with faster return on investment (RoI).
A
nyone considering the “Factory of the Future” should start by thinking of challenges manufacturers face today. It’s an interesting time for manufacturing with technologies such as the cloud, artificial intelligence (AI), robotics, augmented and virtual reality (AR/VR), additive manufacturing, digital twins, and others promising a revolution in products manufacturing. Success or failure of these technologies depends on their abilities to address pain points manufacturers face today. Common industry challenges include:
M More INSIGHTS
• Skills and people retention • Improving productivity and downtime • Worker safety • Flexibility and speed to market.
KEYWORDS: Advanced
technologies, manufacturing productivity Technology investments are needed for factory of the future capabilities. Advanced technologies can augment productivity, flexibility, and better working conditions. Easier customization seems likely.
CONSIDER THIS Are you accelerating toward the factory of tomorrow or stalled in a factory of yesterday?
ONLINE If reading from the digital edition, click on the headline for more on this topic, including graphics, AR/VR, customization, training, safety and robotics, and speed to market.
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Will companies find use cases for these new technologies, or are we looking at the next technology looking for a problem to solve? In IHS Markit’s research of 500 industrial companies for its “Industrial IoT Intelligence Service” report, respondent identified Internet of Things applications that would benefit most from their organization’s use of the cloud. Leading responses were predictive maintenance, asset tracking, condition monitoring, plant/factory control, resource planning, and maintenance planning.
Productivity, downtime
While there are many new technologies that could be introduced, cost remains king. A company’s ability to impact its bottom line will be central to any purchasing decision. These decisions are often based on a short payback window of less than a year, rather than total cost of ownership (TCO). Machine and equipment failures can cost tens of thousands of dollars per minute because of unplanned downtime. There is
control engineering
also the cost of repairing the failed part, the damage caused to associated pieces of equipment, and the cost of getting emergency replacement parts, which all contribute to the final cost. Traditional preventive maintenance planning is limited and resources are inefficient in identifying potential equipment failure. Technologies able to reduce unplanned downtime can show a quick and tangible payback.
Less downtime
How can the factory of the future reduce unplanned downtime? By increasing access to data collected from machines and equipment, companies can monitor the characteristics of a machine’s performance based on the measurement of different parameters including vibration and temperature. Applying analytics to asset health monitoring applications is one of the low-hanging fruits of the Industrial Internet of Things (IIoT) with the ability to see a quick payback on investment. IHS Markit research also identified respondents’ primary objectives for using cloud-based analytics as to improve productivity (throughput), reduce downtime/production failure, and efficient maintenance/scheduling.
Faster ROI
Whether improving productivity, being more flexible to customer needs, or providing better working conditions, the technologies found in the factory of the future will succeed on their ability to meet specific challenges that will vary by industry and company type. With questions around how to monetize new solutions such as the IIoT, identifying those that show not just a clear business benefit, but also the ability to provide a quick return on investment (ROI), will be central in driving the move to the factory of the future. ce
Alex West is an analyst with IHS Markit. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media, mhoske@cfemedia.com. www.controleng.com
POWER We stock enough power to brew a 12 oz. cup of coffee for the entire population of New Orleans. Put that in your mug and drink it. input #6 at www.controleng.com/information
Š Allied Electronics & Automation, 2019
Get your A&C fill at
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input #7 at www.controleng.com/information
MARCH 2019
®
INNOVATIONS NEW PRODUCTS fOR ENgiNEERS NEERS
43 | Collaborative robot, proximity sensor, ball screw
44 | Power conversion, power distribution, drives
BACK TO BASiCS
48 | Digital transformation with cybersecurity
Newsletter: Information Control • Automation programming advances enhance communication, programming • Industrial controller selection: Look beyond the basics • Hot topics in Control Engineering for 2018 • Industrial network communications • Cloud-based software for industrial applications. Get the latest industry trends, case studies, and news and more at www.controleng.com/newsletters
Industrial Internet of things (IIot) 2019 webcast series Control Engineering’s webcast series on the IIoT continues in 2019. Learn more about the upcoming webcast in the series: www.controleng.com/webcasts.
CFe edu: Catapult your career forward Earn learning units and discover exclusive content through videos, presentations and access to experts at CFE Edu, an ondemand education platform by CFE Media. See the courses: cfeedu.cfemedia.com/catalog. Courses include: • Introduction to IIoT and Industrie 4.0 • Introduction to PLCs • The Electrical Bundle • Safety First: Arc Flash 101 • Electrical Systems: Designing Electrical Rooms • Critical Power: Generators and System Design.
Oil & Gas Engineering helps maximize uptime and increase productivity through the use of industry best practices and new innovations, increase efficiency from the wellhead to the refinery by implementing automation and monitoring strategies, and maintain and improve safety for workers and the work environment. Read the digital edition at www.oilandgaseng.com.
controleng.com provides new, relevant automation, controls, and instrumentation content daily, access to databases for new products and system integrators, and online training. www.controleng.com
control engineering
March 2019
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INSIGHTS
Technology UpdaTe Mark T. Hoske, Control Engineering
Facility digitalization digitalization adds profitability and flexibility to manufacturing and process facilities, as noted at aRc Forum 2019.
M
anufacturing and process facilities are taking advantage of trends in digitalization to make applications more efficient, effective, secure, with lower risk, greater profitability, and more flexibility. Highlights from 2019 ARC Industry Forum media meetings reflect trends driving new product announcements.
Greg Bentley is CEO of Bentley Systems. Courtesy: Mark T. Hoske, Control Engineering, CFE Media
Digital twins
Greg Bentley, CEO of Bentley Systems, discussed the benefits of a digital twin cloud service developed jointly with Siemens. The service is designed to enable up-to-date, as-operated digital twins that synchronize the real plant and its engineering representations to make process plant operations more efficient. During one construction project, Bentley said, drones were flown weekly to create 3-D project models, preserving information for future use (such as where buried utilities are located), creating more than 3 million tags, connecting databases with schematics and piping and instrumentation diagrams (P&IDs) to reduce time for the project and reducing risk, Bentley said. Engineering design tools for plant infrastructures and building information modeling KEYWORDS: Digitalization, can create an immersive experience in virtual automation reality for training or better locate hidden utilARC Forum 2019 included ities for smarter, more effective maintenance manufacturing and process or upgrades in the future. Services software trends. brings together physical and virtual so the as Digitalization is among designed, as built and as operated versions the key trends impacting manufacturing. reflect current reality. An up-to-date model of the Cloud services digitally connects compofacility provides opportunities nents and workflows. An implementation can:
M More INSIGHTS
for savings.
CONSIDER THIS Are you integrating new designs and technologies quickly enough to accelerate faster than your competitors?
ONLINE See related New Products for Engineers by category at www.controleng.com/NP4E See related articles on: Manufacturing and process facility trends: Optimization Manufacturing and process facility trends: Cybersecurity
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1. Use 3-D reality mesh to find 2-D images of components to be identified. 2. Train the software by creating bounding boxes around components and add classifications. 3. Run a detector on 3-D reality mesh to locate and classify changes to components and systems. 4. Use a browser application to highlight classified components in a reality mesh. Each iteration applies knowledge and
control engineering
Siemens has 20 MindSphere application centers and more than 300 partners in the ecosystem. The system, using an open API driver, works on Amazon AWS and Microsoft Azure systems and will be available in China on Alibaba cloud (August release expected), as explained at ARC Forum 2019. Courtesy: Mark T. Hoske, Control Engineering, CFE Media
advances the model integrating a cost, schedule, and safety index. Rules can be created and applied as needed, Bentley said. (For instance, were the same grade of materials used?)
Cloud applications, digitalization tools
Bill Boswell, Siemens vice president of marketing for cloud application solutions – MindSphere, said infrastructure can leverage the Industrial Internet of Things (IIoT) with a cloud-based, open IoT operating system. Technologies such as smart meters have shown how digital technologies save time and add value and functionality in utility applications. Getting started with digitalization, Boswell said, is often easier with a digital maturity model and horizontal industry technologies for specific customer needs. The ability to connect and monitor, analyze and predict, digitalize and transform integrates IoT data and other information into the plant and product lifecycle. The concept of creating a digital twin can be applied to products, productions, and performance. In a collaboration platform, applications, an open platform as a service (PaaS), and connectivity with edge products—computing power, distributed control, analysis, and communications distributed close to the process. Software development tools, application program interfaces (APIs), and libraries can speed development, simplify programming, device linking with IoT extensions, and integration with other systems, including enterprise-level software, Boswell said. API versioning allows backward compatibility, and software can access and work with multiple cloud-based systems, he said. Siemens’ acquisition of Mendix low-code software helps reduce programming time by 10 times by using model-driven development for visual modeling. ce
Mark T. Hoske is content manager, Control Engineering, CFE Media, mhoske@cfemedia.com. www.controleng.com
The power of space If you could use a product in your control panel that required up to 69% less space than traditional solutions, while providing up to 200 kA SCCR, would you?
input #8 at www.controleng.com/information
Go big, by going small The next evolution has arrived. The BussmannTM series Low-PeakTM CUBEFuseTM and ULÂŽ 98 Listed Compact Circuit Protector disconnect switch are now available up to 400 amps.
input #9 at www.controleng.com/information
The Compact Circuit Protector for Class CF CUBEFuse is now available in higher amp ratings, and it still delivers the smallest footprint compared to any Class J fused disconnect solution — requiring up to 69% less space. Freeing up space is powerful, and we’ve done just that, while packing up to a 200 kA short-circuit current rating.
What will you do with all that space? CUBEFuse.com
INSIGHTS
Technology UpdaTe Mark T. Hoske, Control Engineering
Manufacturing cybersecurity cybersecurity in manufacturing and process facilities: aRc Industry Forum
M
anufacturing and process facilities are taking advantage of cybersecurity trends to make applications more secure, as discussed at the 2019 ARC Industry Forum.
Sam Wilson is global product marketing manager, Honeywell industrial cybersecurity. Courtesy: Mark T. Hoske, Control Engineering
Cybersecurity threats via USB
Sam Wilson, global product marketing manager, Honeywell Industrial Cybersecurity, discussed big risks of small, removable devices. Cyber threats and customer experiences help shape Honeywell Process Solutions’ developments for industrial cybersecurity. Wilson said USB devices can act like a keyboard or mini-computer and launch attacks. Cybersecurity attributes to have include an inability to bypass safeguards, enterprise visibility and reporting, establish and follow good USB basic practices, enforce technical controls, monitor and manage network traffic, regular and rapid anti-virus updates, patch and harden end nodes, consider restricting personal USB devices, and use and test backup and recovery. Using Honeywell cybersecurity technology, 44% of
a customer’s 50 oil and gas sites detected and blocked at least one suspicious file; and 11% would not have been detected by traditional anti-virus software.
Smarter safety with cybersecurity
Dr. Alexander Horch, vice president of R&D and product development for Hima, explained the importance of integrating scalable safety with cybersecurity with hardware and software, including firmware and communications. Such integration reduces complexity so operators can buy and use only what’s needed. This helps lower one application’s costs with more than 60% savings in engineering and testing. Changes can be achieved while leaving cabling and input/output level unchanged, with less engineering. Stronger communication encryption between controllers is under consideration in IEC 61784-3 (functional safety fieldbuses), edition 4, Horch said. ce
Mark T. Hoske is content manager, Control Engineering, CFE Media, mhoske@cfemedia.com.
Finally, an I/O solution we can milk for all it’s worth. Sealevel is an American-owned designer and manufacturer of critical communication products, I/O and industrial computers. With more than 30 years of experience and over 250 standard products, our forte is using in-house engineering to create custom adaptations for our partners, precisely matching their application requirements. Industrial automation. It’s where Sealevel got its start. Let’s start something together.
The SeaLINK® 2402 USB serial I/O adapter provides USB connectivity to legacy or non-USB compliant devices.
input #10 at www.controleng.com/information SEALEVEL.COM
Honey, I’m home! Tired of being gone nights and weekends troubleshooting projects? It’s time to contact an automation specialist at SEW-EURODRIVE to help solve your design challenges. We provide a complete package including project planning, software, components, commissioning, and service from start to finish. We know exactly how our products work together because we designed them. Relax … we got this!
seweurodrive.com | 864-439-7537 input #11 at www.controleng.com/information
INSIGHTS
Technology UpdaTe Mark T. Hoske, Control Engineering
Optimization optimization is among the trends for manufacturing and process facilities at aRc Forum 2019.
M
anufacturing and process facilities are taking advantage of optimization trends to make their applications more efficient, with lower risk, greater profitability, and more flexibility, as explained in highlights below from 2019 ARC Industrial Forum new product announcements.
Engineering intelligence
Samir Bagga, chief marketing officer and Akshay Chandra, senior manager, strategic marketing initiatives at L&T Technology Services, discussed the need for smarter factories with wireless material tracking, machine vision-based quality inspection, digital twins, energy optimization, collaborative robotics, integrated 3-D modeling, and virtual reality. Chandra, an electrical engineer, offered some application metrics. Wireless material tracking with radio frequency identification (RFID) tags on one manufacturing line increased productivity 30%, parts availability 40%, and annual savings by $100,000. Machine vision for quality inspection increased productivity 8% and lowered reject rates 20% for $150,000 annual savings on one line. Digital twin implementation improved overall equipment efficiency (OEE) by 13%, decreased inventory by 40%, and saved $1 million per year. Paperless factory implementation increased productivity 15%, decreased rework 10%, and decreased material waste by 4%.
M More INSIGHTS
KEYWORDS: Optimization, automation ARC Industry Forum 2019 included manufacturing and process trends. Optimization of production is among the key trends impacting manufacturing and automation. CONSIDER THIS Are you integrating new designs and technologies quickly enough to accelerate faster than your competitors?
ONLINE See more from Aveva on cloud architecture, Schneider Electric on profits and safety and Bently Nevada on wireless monitoring, with more photos.
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March 2019
Energy optimization
Satoru Kurosu, Yokogawa director, executive vice president, premium solutions and service business headquarters, and Oscar Santollani, senior vice president, visual MESA software business at KBC (a Yokogawa company), discussed how to address energy-related carbon emission reduction goals with endto-end energy optimization software. Such software uses analytics to help reduce costly uncertainty in energy planning, scheduling, and trading over multiple time periods. Kurosu sees opportunities in helping with more efficient use of energy to reduce carbon-based emissions with a call to action for approximately $32 trillion in existing assets. Power generation and industry account for about 60% of energy related CO2 emissions, he
control engineering
Inductive Automation’s Ignition Perspective module helps users apply automation where they are in an expected way, as explained at ARC Forum 2019. Courtesy: Mark T. Hoske, Control Engineering, CFE Media
said, noting Yokogawa can help industry achieve energy optimization to decrease consumption, support the transition to renewables for attention to the supply and demand sides of the equation. Existing tools and techniques can help customers realize more than 10% savings in energy optimization. Santollani said better forecasting creates better decisions. Software that improves through behavior modeling and variable prediction creates more optimal operating conditions.
Automation platform
Don Pearson, chief strategy officer, and Carl Gould, co-director of software development for Inductive Automation, said an industrial automation platform should integrate web technologies, enterprise-empowering features, and a next-generation visualization system. Doing so can create appealing, mobile-responsive industrial applications that run natively on any mobile device and web browser. Pearson said automation software priced to allow unlimited tags creates more opportunities to expand architectures across the enterprise, with security, and mobility for automation, which are three most-important areas of customer concern. Gould said features such as collaborative concurrent development and no designer lockouts allow big projects to vanish faster with less contention. Using GitHub open-source software allows providers easier opportunities. Inheritance concepts, fast tag system management, and security with single sign-on (SSO), federated identity infrastructure, and two-factor authentication helps. With mobile visualization tools, helpful features include drag-and-drop setup, pre-built templates, HTML5, and the ability to use smartphone and tablet functions such as position sensors, GPS, and Bluetooth. Software can make automation easier in seven ways, Pearson said. Get those tips with this article online. ce
Mark T. Hoske is content manager, Control Engineering, CFE Media, mhoske@cfemedia.com. www.controleng.com
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INSIGHTS
NEWS
‘Data is the currency of the future’ Manufacturing’s digital revolution arrives with a fundamental change in what manufacturers deliver. That was the message from ThyseenKrupp senior vice president Nihar Satapathy in his opening remarks at the 2019 ARC Industry Forum Group on Feb. 5 in Orlando. Satapathy told the 900 attendees at the annual forum that performance data available from any manufactured product will be just as valuable as the product itself.
Take a fresh perspective
“Data is going to be the currency of the future,” Satapathy said. “Data is what’s driving most of the value. The data already exists; we just have to figure out how to use it in a different way. The customers of tomorrow will not expect you just to build something for them. They will want you to help them anticipate changes.” Embracing those changes are important
for customers. Satapathy added it is also a business imperative. “The reason you need to digitally transform is that you are at the risk of being out-competed in the market,” he said. “We find ourselves having to compete every day.” For ThyssenKrupp, that meant taking a fresh look at product offerings like elevators. It also meant transforming the elevator into a device that constantly communicated its machine health and availability. This allows companies to intelligently deploy maintenance teams and efficiently use equipment. “With data, companies are interested in understanding the flow of people within a building,” Satapathy said. “So, what exactly is the product we’re selling?” Satapathy said ThyssenKrupp learned lessons that apply to manufacturers: • Digitalization is inevitable, like it or not. Embrace it sooner, not later.
Manufacturer hosts STEM career day for local students
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enze Americas welcomed students from local middle schools to its North American headquarters in Uxbridge, Mass. The event was co-sponsored by the Blackstone Valley Education Foundation (BVEF) and enabled students to explore possible science, technology, engineering, and mathematics (STEM) career paths in manufacturing. “We enjoyed opening our doors to the young people in our community to provide a glimpse of what a career in manufacturing and engineering looks like today. It was a pleasure hosting the local students and educating them on the important role our industry plays in our economic future. Some members of this group will be our future engineers, so we were happy to have them participate in exciting learning activities, talk with current staff engineers, and tour our manufacturing facility,” said Floyd Spencer, sales and technical training manager, Lenze Americas, who said all feedback was positive from teachers and students. Lenze looks forward to hosting future educational events. Engineering professionals discussed potential career paths and shared what attracted them to engineering Lenze gave middle school students and manufacturing. a tour of their Massachusetts head– Edited from a Lenze press release quarters for a STEM career day. Courtesy: Lenze Americas by CFE Media.
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• Technology is available today. Manufacturers need to find a relevant business case to create customer value. • Partnerships are important, so leverage relationships and be open to new ways of engagement. “We realized early on we did not have resources to do it ourselves,” Satapathy said. • Stay the course—it will be worth it, and it will also be game changing. • It’s a journey, so prepare for the long haul with time, effort, and resources. Part of that journey is to remain aggressive about moving forward because technology continues to accelerate. “We, as all of you have, went through the process trying to stay one step ahead,” he said. “We focused on customer value-add. If you can do that, you can find a way to monetize it.” Bob Vavra, content manager, CFE Media, bvavra@cfemedia.com.
Headlines online Top 5 Control Engineering articles Feb. 11-17 Articles on plant cybersecurity management, the product awards, control systems, future plant design, and largest system Integrators were the most-viewed, Feb. 11-17. DMDII receives Defense Dept. funding to strengthen research Human aspect of cyber-physical systems Using artificial intelligence to engineer materials’ properties Automation company has new president Kevin Barker was appointed president of Beckhoff Automation LLC to manage Beckhoff’s U.S. business operations.
CORRECTION In a Control Engineering February 2019 p. 25 article, “Network, control system upgrade” under Phase 1 subhead, it should have said “Under Phase 1 operations....” In the longer, online version, corrections and additions have been made. See “Profinet network, control system upgrade helps reduce energy costs.”
ClARIFICATIONs The online version of the February Control Engineering article, “Selecting a scope for a variable frequency drive,” pages M8-M10, now includes extra information and six images.
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Less means more!
Focused on the essentials: the new i500 Slim design, scalable functionality, and extremely user-friendly. The groundbreaking i500 is size-optimized and allows for zeroclearance mounting, saving valuable cabinet space. And thanks to the innovative interface options, it’s easy to commission in minimal time. The best thing of all is that the modular structure adapts to different production configurations in no time at all. Less does mean more! Learn more at www.lenze.com
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Process automation systems need lower lifecycle costs, easier integration with third-party components, better scaling, intrinsic security, flatter architecture, and interoperability without conflicting standards.
Mark T. Hoske, Content Manager 630-571-4070, x2227, MHoske@CFEMedia.com
he deadline for open, interoperable process automation systems is 2021. Those involved in multiple efforts remain confident in the promise of greater efficiency, higher safety, greater ease of use at a lower cost, and without conflicting standards. Experts outlined the vision and progress of Open Process Automation (OPA) standards efforts in the U.S. and Europe at the 2019 ARC Industry Forum conference by ARC Advisory Group in February.
Amanda Pelliccione, Director of Research 978-302-3463, APelliccione@CFEMedia.com
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erence Model (layers 0 through 4, physical layer through business systems). It should be more than a device from one vendor, reduce scope of failure, and keep operations running. The distributed control network (DCN) should include a real-time (RT) communications network and operations platform with RT services (abnormal event detection, procedural automation, advanced control, and process optimization). Proof of concept was in April 2018 in the London Open Process Automation OPA vision, objectives forum meeting with ExxonMobil David DeBari, process conand Lockheed Martin, about 50 trol engineer, ExxonMobil devices, and 10 vendors, DeBari Research and Engineering and said. The effort demonstrated OPA program prototype lead interoperability, configuration engineer, joined the effort seven portability, network throughput, years ago after seeing inefficieninterchangeability, application cies in the migration process for portability, and control appliprocess automation systems— cation capabilities. After a proMark T. Hoske, also called a process control Content Manager totype on a pilot unit, a test bed system (PCS) and distributed to support field trials, and field control system (DCS). trials with seven companies in “About seven years ago, I said this is 2020. A full standard for commercial use crazy, but I’m in. I did not like the migra- is expected in 2021. More 80 participants tion process,” DeBari said, for DCS and including users, vendors, suppliers, and programmable logic controller-based sys- academics are involved. tems—not including safety systems. The industry put in different kinds More interoperability efforts Separately, but with similar goals, Euroof computers 30 and 40 years ago, which replaced pneumatic process control sys- pean standards body NAMUR is working tems. The need to lower lifecycle costs, on its module type package (MTP) proget more benefits, lower the expense to gram and technology. NAMUR and The integrate third-party components, add Open Process Automation Forum (OPAF) best-in-class devices from other manufac- agreed to collaborate to converge initiatives turers, and economically scale and update into a consistent overall architecture. Other industry organizations also agreed to help. as needed, with intrinsic security. Also at the ARC Industry Forum, Ted The vision is to have a control system architecture flatter than the Purdue Ref- Masters, president and CEO, FieldComm Group (HART, Foundation fieldbus, and FDI Group), said it’s strengthening support of process automation standards and compliance with OPC Foundation, NAMUR, See more standards efforts on p. 28 and Profibus/Profinet International and OPAF. more trends and technologies from ARC Many are trying to think again about Industry Forum, pp.10, 14, 16, and 18. In end users’ requests for interoperability. the digital edition, click the headline to see
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Jack Smith, Content Manager 630-571-4070, x2230, JSmith@CFEMedia.com Kevin Parker, Senior Contributing Editor, IIoT, OGE 630-571-4070, x2228, KParker@CFEMedia.com Emily Guenther, Director of Interactive Media 630-571-4070, x2229, eguenther@CFEMedia.com
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Contributing Content Specialists Suzanne Gill, Control Engineering Europe suzanne.gill@imlgroup.co.uk Ekaterina Kosareva, Control Engineering Russia ekaterina.kosareva@fsmedia.ru Seweryn Scibior, Control Engineering Poland seweryn.scibior@trademedia.us Lukáš Smelík, Control Engineering Czech Republic lukas.smelik@trademedia.us Aileen Jin, Control Engineering China aileenjin@cechina.cn
Editorial Advisory Board
www.controleng.com/EAB Doug Bell, president, InterConnecting Automation, www.interconnectingautomation.com David Bishop, president and a founder Matrix Technologies, www.matrixti.com Daniel E. Capano, president, Diversified Technical Services Inc. of Stamford, CT, www.linkedin.com/in/daniel-capano-7b886bb0 Frank Lamb, founder and owner Automation Consulting LLC, www.automationllc.com Joe Martin, president and founder Martin Control Systems, www.martincsi.com Rick Pierro, president and co-founder Superior Controls, www.superiorcontrols.com Mark Voigtmann, partner, automation practice lead Faegre Baker Daniels, www.FaegreBD.com
CFE Media Contributor Guidelines Overview Content For Engineers. That’s what CFE Media stands for, and what CFE Media is all about – engineers sharing with their peers. We welcome content submissions for all interested parties in engineering. We will use those materials online, on our website, in print and in newsletters to keep engineers informed about the products, solutions and industry trends. www.controleng.com/contribute explains how to submit press releases, products, images and graphics, bylined feature articles, case studies, white papers, and other media. * Content should focus on helping engineers solve problems. Articles that are commercial or are critical of other products or organizations will be rejected. (Technology discussions and comparative tables may be accepted if non-promotional and if contributor corroborates information with sources cited.) * If the content meets criteria noted in guidelines, expect to see it first on our Websites. Content for our e-newsletters 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 appropriate content manager prior to submission. Learn more at: www.controleng.com/contribute
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ANSWERS
Cover story: eDGe CoMPUtING Eric Reiner, Beckhoff Automation
Hardware capabilities impact edge computing success Industrial PCs offer a range of processing capabilities, form factors, and certifications engineers must consider when implementing edge computing strategies in new applications or legacy systems.
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dge computing in cloud-connected plants has many advantages. By gathering and analyzing process data on local controllers before sending it to the cloud, engineers can visualize production data on humanmachine interfaces (HMIs), monitor machine health, and schedule predictive maintenance as well as minimize data upload costs. Edge computing also heavily relies on networks, software, algorithms and communication protocols, such as message queuing telemetry transport (MQTT), advanced message queuing protocol (AMQP) or OPC Unified Architecture (UA). Controller hardware is an often-overlooked aspect of edge computing. While many factors affect the success of edge computing applications, the hardware determines if the applications are even possible. It is important to install a high-quality PC-based controller that can handle the advanced data acquisition, processing, and cloud communication tasks that are crucial when designing and commissioning new Internet of Things (IoT)-ready machines. Open PC-based hardware is even more crucial when retrofitting legacy equipment with edge computing capabilities, which requires additional steps to obtain plant data. As a result, key considerations when selecting an appropriate edge computing device include: • A device’s ability to fit into cramped control cabinets • The quality of housing materials • Processing power • The ability to divide tasks among CPU cores.
The right hardware can vary by application as well. Understanding the available options is the first step to ensure a successful edge computing project.
Processing power, customization
Controllers used for edge computing must handle large amounts of data while completing other automation tasks. Today’s industrial PCs (IPCs) provide
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Figure 1: Ultracompact Industrial PCs (IPCs) can serve simply as add-on gateway devices or also perform machine control in addition to edge computing requirements. All images courtesy: Beckhoff Automation
many levels of processing power and memory, ensuring appropriately sized hardware for each application and price point. IPCs should offer flexibility for customization in how they use available processor cores. Edge computing devices can feature a variety of processors from a single-core to a quad-core processor, in speeds from 400 MHz to 1.6 GHz. Manycore IPCs and embedded PCs feature more advanced options, with four to 40 cores and speeds of 2.2 GHz. When examining these specifications, it is also important to look for automation software that allows users to dedicate tasks to individual cores and make the CPU run at peak effectiveness. This will also ensure the IPC can multitask and accommodate more functions on one device. For example, with a quadcore CPU, isolating the programmable logic controller (PLC) on core 0, motion control on core 1, and HMI on core 3 allows an engineer to dedicate the final core to edge computing activities. Local data storage and RAM capabilities also fall on a wide spectrum. Some IPCs offer from 512 MB MicroSD cards to 960 GB solid-state drives with the option to add a second storage device for additional space if needed and from 1 GB up to 64 GB of DDR4 RAM. On the other end are even more capable IPCs that provide up to 1 TB DDR4-RAM EEC and 4 TB or more on 3 1/2-in. hard disk drives. As with processing power, the specific application determines the control engineeering
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KEYWORDS: Edge
computing, controllers, industrial PC Factors that impact edge computing success What to consider when selecting an edge computing device
COnSiDER thiS What capabilities does your IPC need for successful operations?
OnLinE Read more about edge computing online at www.controleng.com.
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EDGE COMPUTING
Figure 2: IPCs offer a range of processing power and form factors, with cabinet installation and DIN rail-mountable options, for various edge computing applications.
Figure 3: Embedded PCs connect directly to the input/output (I/O) modules, creating an excellent edge computing option to control machines and systems as well as analyze and send data from the edge to the cloud.
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amount of storage required. For example, cutting-edge installations with advanced vision systems will require more memory and processing power, while less complex projects will not. In greenfield edge-computing applications, IPCs will likely control machines or lines and analyze and make corrections based on real-time process data. Implementing this level of control in a brownfield setting would require a retrofit, which may not be worth it to engineers hoping to gather and leverage more process data. Without a rip-and-replace strategy, an IPC can easily gather data from the legacy fieldbus and/or PLCs, filter and analyze it with advanced algorithms, and send the required information to the cloud.
Form factor, material choices
The edge device must be well suited to the factory and enclosure. Production environments, depending on what is being manufactured, run the gamut from very hot to very cold, and existing control cabinets often cannot accommodate much additional heat. IPCs and embedded PCs in compact form factors can withstand temperature extremes and support many application types. IPCs with rugged metal housings can, for example, integrate into a variety of spaces with the option for cabinet installation or DIN-rail mounting. The durable metal construction ensures they are ready for use in many plant environments, and when outfitted with a heat sink or fan, it also minimizes the risk of overheating the enclosure. In addition, selecting a certain processor series can minimize the risks involved with high temperatures. A broad selection of connector ports, such as gigabit Ethernet, USB 2.0 and 3.0, DisplayPort (a Video Electronics Standards control engineering
Association connector standard), along with scalable memory and RAM make these IPCs excellent edge devices for new applications that demand the highest performance levels and for existing systems that require edge capabilities. When implementing a new control system, embedded PCs offer additional benefits. These DIN rail-mountable controllers connect directly to input/output (I/O) modules in the control cabinet, further minimizing hardware footprint and cabling requirements. Embedded PCs equipped with either industrial-grade plastic or metal housings can operate with minimal heat dissipation and in a range of temperatures, often spanning as high as 50°C and as low as -25°C. For engineers looking to upgrade or implement new PC-based control systems, it will be worthwhile to invest in the minimal effort required to retrofit the cabinet. However, for those who want increased data acquisition and analysis on the edge, without fundamental changes to the system architecture, IPCs offer a solution with many options to choose from to meet the application’s needs, in an almost plug-and-play way.
Certifications, software assistance
Examining these hardware, software, and networking factors will lead engineers in the right direction, but they may encounter similar options. In these instances, examining product certifications and software capabilities can break a tie. Depending on the cloud service in use, Microsoft Azure Certified IPCs or controllers approved by Amazon Web Services (AWS) can provide a better option and peace of mind. Controllers with multiple certifications are designed to reassure engineers hardware changes will not be necessary if the cloud services change. Regardless, PC-based controllers are well suited to accommodate public and private cloud systems. In addition, PC-based controllers offer the best operating system and processing power for edge computing applications. Engineers should ensure any edge device supports Microsoft Windows 10 IoT and has the capability to handle future upgrades. The goal of edge computing is to make continuous improvements far into the future. With the proper software and hardware selection, a successful edge computing implementation will boost machine performance, reduce downtime, increase throughput, and help ensure factories remain as efficient and competitive as possible. Carefully considering the many PCbased controller options will give controls engineers an advantage. ce
Eric Reiner, IPC product specialist, Beckhoff Automation. Edited by Emily Guenther, associate content manager, Control Engineering, CFE Media, eguenther@cfemedia.com. www.controleng.com
ANSWERS
COVER STORY: EDGE COMPUTING Travis Cox, Inductive Automation
Edge computing opportunities Edge computing = faster data + new analytical possibilities.
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lacing devices near the edge of networks, close to machines, can bring in more data. That data can be analyzed at the edge, which can be faster than doing it at a centralized location. Collecting and analyzing data close to its source can allow users to know their production systems better. Many industrial facilities have legacy equipment and slower-than-desired polling protocols. Edge computing can modernize and simplify things while obtaining more data with less latency. It also can allow more divisions within a company to be data consumers. Additionally, it can make the edge data the one source of truth, which improves data reliability. Edge computing also is ideal for enhancing the Industrial Internet of Things (IIoT).
Transfer data from legacy equipment
Nearly every company has legacy equipment. Getting data from there into supervisory control and data acquisition (SCADA) and other systems can be laborintensive, especially when everyone has to connect. Companies have to poll that information, create mappings, and know exactly what each device is. There’s a lot of work involved. Edge computing can simplify that infrastructure by doing mapping once—at the edge—and delivering data in a much more efficient way, using the publish/ subscribe protocol message queuing telemetry transport (MQTT). MQTT devices report by exception. If data is only sent when the values change, this means there’s less traffic on the network. That means users can get more data, and they can get it faster. For example, if an application nees a 50-ms rate, chances are that a polling strategy from a central system wouldn’t do. When devices are next to the controller and publishing that data up, you can achieve faster rates and get access to more information.
Edge computing benefits
Edge computing offers simplicity with plug-andplay devices that require less maintenance. And once the data is published to a broker, SCADA can access it, as well as other systems, such as enterprise resource
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planning (ERP), information technology (IT), or business intelligence. With MQTT and the Sparkplug payload specification, numerous systems can autodiscover new data or information, without needing to know what the end device is. The edge computer can send raw data, a data subset, pre-processed information, already-acted upon information, or some combination, depending on the architecture and application. As data collection goes more smoothly, so does control. Users are still writing back to the programmable logic controller (PLC), but it’s happening in a more efficient manner. Edge computing also can enable advanced process control (APC). Software platforms can do just APC; it’s often expensive and specialized. Edge computing is making that world more accessible. It’s easier to build models because there are more algorithms that can be leveraged. It’s becoming easier to do real-time tuning of processes. That’s an exciting area of edge computing. The closer to the controller, the faster the whole thing will be.
Edge computing simplifies an infrastructure by mapping once at the edge and delivering data in a more efficient way, with message queuing telemetry transport (MQTT). Courtesy: Inductive Automation
Benefits: less scrap, downtime
Numerous real-world examples show how edge computing can make a big difference. Consider a semiconductor factory with many tools that put silicon on discs. The equipment is very finely tuned, and there are low tolerances for error. While it’s running, edge computing with these very complex models can be determining if the project is going off course or will be deviating from the course. The edge computer could contribute to making an adjustment (or make the adjustment, depending on the architecture) before there are real problems. Lost material could mean thousands of dollars in scrap. Compared to traditional computing, the faster response time of edge computing offers significant savings for many applications. Another example is prediction of equipment failure. Equipment can be extremely expensive, millions of dollars, or hundreds of thousands. It’s not advantageous to organizations to have the backup equipment (Continued on p. 25.) control engineeering
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Keywords: Edge computing, Industrial Internet of Things (IIoT) Edge computing allows faster data analysis for faster understanding of production systems. Machine learning and advanced analytics enhance edge computing. oNLINe Read this online for more on remote monitoring and additional stories about edge computing.
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COVER STORY: EDGE COMPUTING Nate Kay, P.E., MartinCSI
Edge computing for efficiency, quality Edge devices streamline operations and offer many benefits including enhanced efficiencies and quality of service for industrial manufacturers.
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users to existing systems cloud.
dge computing refers to the edge of network computing, but what network? In industrial manufacturing, many control systems are set up on local Ethernet networks. These networks may consist of a local business network, industrial computers, programmable logic controllers (PLCs), and industrial touch screens often called humanmachine interfaces (HMIs). Many benefits derive from connecting local networks to larger public networks or server computers. For simplicity’s sake, publicly-accessible networks will be referred to as the cloud. The edge is the boundary between edge these local networks and the cloud. Edge devices provide the interface between the allow cloud and the local networks. An airport is similar to how edge connect devices and the cloud interact. The hub is the central airport, often located control in larger cities, where flights are routed through. The spokes are the routes to the planes take in and out of the hub airport. Smaller cities have connecting flights to hub airports. If, for example, someone is traveling from Columbus, Ohio, in the United States to the United Kingdom, they may first fly from Columbus to an airline hub in Chicago, then to a hub in London, and finally to their destination city. Think of the cloud as the hubs and the edge devices as the smaller local airports.
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Benefits of edge devices The first benefit cited in the airport analogy was a reduction in traffic over a point-to-point model. Likewise, when it comes to the Internet of Things (IoT), instead of having individual devices connect point-to-point to the cloud or each other, these devices connect to an edge device, which then connects to the cloud. Edge devices can reduce the overall volume of data that must be transmitted and act as a buffer, which helps improve efficiency and quality of service (QoS).
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Many existing networks are not setup to connect directly to the cloud. The network architecture, including information technology (IT) standards such as domains, domain name system (DNS), dynamic host configuration protocol (DHCP), firewalls, etc., isn’t there. Redesigning the local network from the ground up can often be time-consuming and cost prohibitive. However, adding an edge device can allow existing networks to connect to the cloud without overhauling the network. Edge devices incorporate IT practices such as firewalls, transport layer security (TLS)/secure sockets layer (SSL) security protocols, and network address translation (NAT). This allows existing devices (including PLCs and HMIs) to exchange data with the cloud through the edge device while the edge device provides isolation and security between the cloud and the existing network.
Computing resources Another advantage of edge computing is some computational resources can be handled by the edge device instead of in the cloud or by the local control system. For example, consider an industrial controls application where data collection and analysis is needed. The existing control system may not have devices with the capability to collect and analyze large amounts of data. Even if it did, its main function is not data collection and analytics, but to keep manufacturing processes running. The cloud-based system has plenty to do, including serving up the data, providing reports, and handling the requests of dozens of other control systems and end users. By having the edge devices handle some of the data collection, buffering, and analytics we can reduce the burden on the cloudbased system, and the control system can perform its critical tasks. Several edge devices allow users to connect existing control systems to the cloud. Some of them allow the user to connect the existing control system to cloud-based systems with little-to-no modwww.controleng.com
An airport is similar to how edge devices and the cloud interact. An airline hub at a central airport connects to other locations. Think of the cloud as the hubs and the edge devices as the smaller local airports. Courtesy: Lindsey Kielmeyer, MartinCSI
ification of the existing devices and network. This is possible by selecting edge devices that incorporate technology such as NAT, virtual private networks (VPNs), firewalls, Layer 2 switching, and Layer 3 routing. Edge devices can provide an efficient and easy way to move today’s technology into the future with a well-established hub and spoke model. ce Nate Kay is a project manager at MartinCSI. Edited by Emily Guenther, associate content manager, Control Engineering, CFE Media, eguenther@cfemedia.com.
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KEYWORDS: Edge computing The benefits of edge computing How edge devices optimize operations COnSiDER thiS How can edge devices help optimize your facility’s operations?
OnLinE Read more about edge computing at www.controleng.com.
Edge... (Continued from page 23.) sitting on a shelf, having to spend that capital for unused assets. If equipment breaks, and it takes a day or two to get a replacement, that could be millions of dollars in lost revenue. Do users take that risk? If the company has edge devices collecting data and comparing it against these models, patterns can be detected that humans can’t see. Lead time for equipment failure will help the company. And it works better on the edge, because it’s focused just on that equipment. Machine learning and analytics offer more options and new techniques. What edge-computing platform do I get? Avoid smoke and mirrors. Seek practical solutions available now. Understand what’s out there and what is open and interoperable. Legacy equipment wasn’t built to be replaced easily. With many edge computing options, customers can select best-in-class interoperable hardware and software without being locked into one vendor. ce Travis Cox is co-director of sales engineering at Inductive Automation. Edited by Chris Vavra, production editor, Control Engineering, CFE Media, cvavra@cfemedia.com.
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CovEr story: EDGE CoMPUtING Cov Benson Hougland, Opto 22
Gaining the edge in automation Edge computing advances give users more options for architecting automation systems, flexible communications and programming choices.
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raditional automation architectures are built around centralized programmable controllers connected to remote field devices and instruments. This concept is shifting as computing power is progressively embedded near the edge of automation systems using new types of intelligent components. Edge computing designs offer some advantages compared to traditional and more centralized strategies.
Combine and conquer
Edge computing benefits designers and manufacturers by consolidating components and configurations. An edge programmable industrial controller combines input/output (I/O), control, data processing, communications, and human-machine interface (HMI) functionality that can be located near or on machines, process trains or smart equipment. An on-board touchscreen display, with options for a larger local monitor, is useful for machine manufacturers since control and visualization are effectively merged. KEYWORDS: Edge computing, automation This makes commissioning, operating and Edge computing provides troubleshooting easier since a separate PC engineers many options for a is not required. Local operator functions, variety of applications. such as pushbuttons and indicators, can be Benefits include programming handled on the HMI more effectively than flexibility and allowing users to traditional pilot devices. Edge computing plug into familiar products. makes it easier for users to incrementally Edge computing is ideally suited for gathering field data and roll out system improvements. Instead of securely processing it for higheraffecting large in-service installations, an level data architectures. edge computing system can be installed cONSIDER THIS and tested locally and merged into the largHow can you apply edge er system via a quick hot cutover. computing automation? Shifting communications and data proONlINE cessing to the edge makes sense for many More on edge computing reasons. Control decisions are made in real time where they are needed. Data is obtained, pre-proAn edge programcessed, and analyzed near the source. This reduces the
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mable industrial controller, like Opto 22’s groov EPIC, can combine I/O, control, networking and HMI functions to flatten architecture. Courtesy: Opto 22
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required network bandwidth, data storage, and processing power upstream of the edge component. Programming for these edge components can take many forms. Traditional programmable logic controller (PLC) users usually will look for ladder logic or other IEC 61131-3 programming languages. Flowchart-based programming language is often better suited for the application. Python or C/C++ might be preferred for more advanced calculations and data processing. Some edge computers can accommodate these programming languages and others. Communications flexibility is another hallmark of edge computing. An edge programmable industrial controller has various communication ports and supports a wide range of protocols so it can connect with numerous local intelligent systems, such as PLCs. Edge computing components support operations technology (OT) protocols such EtherNet/IP, Modbus, BACnet, those from OPC Foundation, and others. It also supports information technology (IT) protocols and development tools such as TCP/IP, simple network management protocol (SNMP), message queuing telemetry transport (MQTT), and Node-RED. This suite of interfaces effectively “flattens” and simplifies the system architecture and system integration. Edge computing is suited for gathering the right data in the field, processing it into useful information, and securely communicating it to higher-level data architectures. Edge computing can interact with other supervisory on-site automation platforms, enterprise databases, or even exchange data with cloud services.
Picking the right control system
When designing a control system, users select the best set of features. That has meant relying on more centralized platforms, which are functional, but also impose constraints. The expanding abilities of edge computing give designers and engineers new options. Edge computing can combine as much or as little I/O connections, control, communication, data processing and HMI visualization functionality as needed. Edge computing is often an ideal solution for users needing granular, modular, and scalable architectures that can fulfill many requirements. ce
Benson Hougland is vice president of marketing, Opto 22. Edited by Chris Vavra, production editor, Control Engineering, CFE Media, cvavra@cfemedia.com. control engineering
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ANSWERS
Cover story: eDGe CoMPUtING Mark T. Hoske, Control Engineering
10 best practices for edge computing When choosing, installing, and using an edge computing device for a manufacturing or process facility application, these 10 best practices can help.
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dge computing devices, so called for their use at the edge of a discrete manufacturing or process control application, need to be properly selected, installed, and used, according to John Fryer, Stratus’ senior director of industry solutions, at the 2019 ARC Industry Forum in February.
Digital tranformation architecture
Edge computers are industrially hardened computers used for monitoring, communications, and/or control deployed close to applications (as opposed to a central location away from the process). In a digital transformation architecture, edge computers may be deployed as part of evolving Industrial Internet of Things (IIoT) strategies and can include features that make it easier to connect to, communicate with, or use cloud-based applications. Computing power near the process can help ensure the application can continue if cloud connections fail. Other names for edge computing devices may include industrial computers (IPCs), programmable logic controllers (PLCs), programmable automation controllers (PACs), or just industrial controllers.
Edge computing best practices
Fryer provided 10 best practices for edge computing.
1. Agreement: Before starting a digital transformation project, get buy-in from operational technology and information technology staff. Doing so increases likelihood of success. Consider starting with a scalable project in an area of great distress, rather than with a seven-figure project. 2. Ownership: Don’t let information technology (IT) staff take over digital transformation or plant-related edge computing implementations. IT staff may not understand how patches and software upgrades affect high-availability, realtime needs on the factory floor. 3. Reliability and resiliency: Think through the reliability and resiliency requirements for edge computing and digital transformation. www.controleng.com
These include maintenance and cybersecurity considerations. 4. Training: Ensure plant-floor personnel have training required to understand and implement the system. 5. Retention: Limit turnover of valued operations technology (OT) staff by valuing tribal knowledge. Complex, IT-based technologies may include a higher degree of risk because of training requirements. 6. Support: Ensure appropriate support for installed technologies. IT staff may not be willing to provided what’s needed at 2 a.m. 7. Hardware support: Select hardware that minimizes the need for long-term support. 8. Software simplicity: Avoid duplicative software with high license and support costs. 9. Lifecycle considerations: Take a total cost of ownership (TCO) view to lower associated risk and costs. 10. Application needs: Understand implementation needs; especially in remote or rugged locations of the facility or plant.
Faster implementations
Technologies that are easier to own, deploy, and manage include a higher probability of meeting application requirements over the life of the implementation. Less time spent on architecture and configuration allows for faster deployment, which decreases time to produce when more of what’s required is included in the box, suggested Brian Beitler, controls engineer at Kline Process Systems. Fryer said hot-swap functionality can ensure the project remains operating without interruption if hardware needs switching. ce
Mark T. Hoske is content manager, Control Engineering, CFE Media, mhoske@cfemedia.com.
John Fryer, senior director of industry solutions at Stratus Technologies, discussed edge computing strategies as part of digital transformation, at the 2019 ARC Industry Forum in February. Courtesy: Stratus Technologies
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KEYWORDS: Edge computing best practices Edge computing can put control, monitoring, and communications close to the process. Various devices can serve edge computing functions. CONSIDER THIS Ease of implementation and use can speed startup, use, and lifecycle productivity of an edge computing application.
ONLINE From the digital edition, click on the headline for more resources. Also go to www.controleng.com/webcasts for more about edge computing.
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STANDARDS
Oskar Kaplun, CAN in Automation
The benefits of CANopen IoT CANopen Internet of Things (IoT) is intended for networks without embedded internet protocol support, allowing access to local and remote CANopen networks using web protocols and communication services.
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n many applications, specifically-designed cell phone or tablet applications enable users to perform remote control and maintenance of air conditioning and heating regardless of the location. Those apps also allow condition monitoring of automated systems’ components for preventive maintenance. There is demand to provide access from the web-based monitoring or control unit to the embedded sensor with fieldbus interface and viceversa. This is fulfilled for the networks supporting internet protocols. This access may invoke cloud connection or using the cloud for remote data processing or distribution. The CAN in Automation (CiA) Special Interest Group (SIG) CANopen IoT designed specification CiA 309.5. It allows CANopen embedded network users to access their local and remote CANopen networks using web protocols and communication services such as Restful HTTP, Websocket, and MQTT.
Figure 1: An example of CANopen IoT cloud connection path. All graphics courtesy: CAN in Automation
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What is CANopen IoT?
One of the challenging issues is the end user has typically no detailed information on the fieldbus interface. Usually, the fieldbus system is transparent for the end user. Nevertheless, fieldbus systems often require geographical addresses such as device identifier, or device parameter addresses, to allow access to a specific network participant or a dedicated function. A pool of harmonized functions is accessible from anywhere in and outside the embedded fieldbus network. The end user can rely on and control the harmonized functionality independently from the hardware platform and communication technique without having knowledge of fieldbus details. CiA suggested using logical addressing as system-wide and technologyindependent identifiers for CANopen elements. This addressing method allows users to request functions such as data monitoring and process control without knowing CANopen. The system itself still has to be pre-configured by a technician who knows CANopen. CiA members also intend to offer more confortable diagnostics by providing an enhanced, harmonized, visualization. The embedded devices provide diagnostic data in a certain manner. Providing the visualization on the embedded device may solve this requirement. Therefore, any industrial terminal, tablet, cell phone, remote desktop, etc., might serve as a humanmachine interface (HMI) for diagnostic services. Bypassing the limiting central host controller opens possibilities for remote diagnostics and maintenance. However, providing visualization typically demands a lot of memory. Small sensors, which do not have the required memory resources, can provide visualization using an HTTP and Websocket with a broadband internet connection. CiA members are working on this challenge. The SIG CANopen IoT harmonizes the previously mentioned challenges. On an application level, CiA offers function-oriented services. Using these new services, the application-specific, harmonized functions can be initiated, monitored, and controlled. The functions are CANopen communication services and parameters mapped with logical addressing into Restful HTTP or Websocket. The functions www.controleng.com
are requested/collected either straight or through the cloud using an existing internet infrastructure. The requester/collector is the web-based application while data provided is the application server located in the CANopen IoT gateway.
Figure 2: CANopen IoT gateway communication.
Web or cloud
For example, the CANopen IoT gateway may either tunnel HTTP requests/ responses to the web app or through the cloud. Through the cloud, the communication path has to comprise the edge gateway having all tunneled data prepared for cloud-conform processing. The example of the local communication includes a CANopen IoT gateway, which contains the IoT and CANopen functional parts and manages the interaction between them. The CANopen functional part communicates with the CANopen embedded network while the gateway provides the data obtained there to the other gateway functional parts. The IoT functional part prepares the embedded CANopen data in JSON format and maps it into the Restful HTTP request/response to transmit to the CANopen network/web-based application. Since CANopen process data or diagnostic information may occur upon an event with data dynamically updated to submit to the web, using a Websocket protocol may optimize bidirectional communication. A Websocket session is established by the web app. Once CANopen data occurs in the CANopen functional part, it is processed in the IoT part and submitted to the web app. In this case, the web app does not need to poll HTTP requests for this data to the gateway. ce
Oskar Kaplun is an engineer at CAN in Automation, a CFE Media content partner. Edited by Emily Guenther, associate content manager, Control Engineering, eguenther@cfemedia.com.
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KEYWORDS: CANopen, Internet of Things (IoT) CiA’s CANopen IoT challenges CANopen’s functions and benefits
COnSiDER thiS How can CANopen IoT optimize a facility’s data?
OnLinE Read more online about CANopen at www.controleng.com.
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input #15 at www.controleng.com/information
ANSWERS
BIG DATA
Michael Risse, Seeq
Big Data analysis or acquisition? Data architectures adapt to new opportunities in data collection, analytics.
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he starting point of a discussion with data and advanced analytics needs to begin with Moore’s Law. In 1965, Gordon Moore, a co-founder at Intel, noticed the number of transistors on a chip doubled every year while the price was cut in half. He predicted this trend would continue. And while the number of transistors per chip has slowed recently, researchers find the basic point is still true. Data storage prices have plummeted, and computers are a fraction of the size they used to be. What can be computed on the same-sized and priced chip has increased many times over. Results of this market transition are a data explosion; pervasive sensing and connectivity; the Internet of Things (IoT) with 50 billion endpoints; and how today’s smartphones are more capable in computing, storage and input/output (I/O) than early mainframes and even Deep Blue (1997/IBM). This applies to companies such as ExxonMobil, which made a $2 billion investment in Lockheed Martin to drive open systems architecture for process automation. For some, Moore’s Law price advantages have been too long in coming to manufacturing’s front lines. The result of this ubiquitous and inexpensive computing is process manufacturers have an opportunity to re-imagine their data analytics strategies by implementing options that used to be too expensive to consider. Data used to be centralized for analytics because it was expensive to collect, store, and analyze. Keywords: Big Data, asset Ubiquitous and less expensive commanagement, cybersecurity puting will continue. What the initiative Even with the advent of Smart is called (Industrie 4.0, smart manufacturManufacturing and Industrie 4.0, ing, digital transformation), the question is process manufacturers need to know what to do with the data what to do with the data being collected.
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they’re collecting. Process manufacturers need to plan for ubiquity and ensure their data is preserved and secure. Computing innovations need to be balanced with improved performance.
online Read this article online at www.controleng.com for a longer article, more images, and links to other relevant articles.
Consider this What manufacturing changes will happen in the next five years thanks to Big Data?
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New words for new models
New economics and ubiquitous computing mean the Purdue-model centralized approach (Figure 1) is being adapted to new opportunities. The centralized model is the most common architecture in process plants worldwide and is familiar to users. Purdue model updates take advantage of new technologies such as: • Wireless systems integrating new sensors into existing control and monitoring deployments, either within a plant or at distance, to expand operational visibility.
control engineering
• Edge computing, which is a broad term that includes local data storage, analytics, and actions. • Cloud computing, which is simply renting computing, storage, and analytics from a vendor. This enables two key scenarios: First, a “direct to cloud” approach for data collection, storage, and analytics for sensor telemetry. This typically is referred to as an Industrial Internet of Things (IIoT) use case where data goes directly from end points to cloud storage. Second, for data already collected to be further aggregated for comparison across plants, by using an enterprise historian, or combined with other manufacturing and business data sets to enable broader analytics, often referred to as a data lake. These approaches are not exclusive, and most companies will use more than one, if not all. For example, a plant could bring in data from newly deployed wireless sensors to augment existing plant analytics. This could be combined with data from suppliers, data from raw materials transportation such as temperature and humidity, and data from quality instruments for richer analytics and insights. New products will expand options. Into what category should one put the Amazon AWS and Microsoft Azure on-premise products, Amazon Outposts (Figure 2) and Azure Stack, which put their cloud software platforms on server hardware intended for local hosting in an end user’s IT department? Perhaps it’s public cloud, private cloud, and local cloud? With a local cloud IoT scenario, data could be routed from new sensors directly into a company’s IT department server room to ensure strict data governance and to address security issues. Some options will sound familiar to industry insiders. Vendors focused on edge computing will be hard pressed to explain how edge computing components differ from real-time units (RTUs). Cloud vendors pushing data lakes may be hard pressed to explain why their approach is substantially different than an enterprise historian that rolls up individual plant data. It may be hard to separate the vendor self-interest at play. It’s not a coincidence a fully decentralized and networked architecture of computing endpoints is being championed by the vendors that sell the required networking, CPUs, and operating systems. Technology offerings clearly are evolving faster than the language used to explain them. Entire plants www.controleng.com
sometimes are considered the new edge. The other issue is the mismatch of innovation and time to implement. Products and marketing can be invented overnight. This is far faster than proof points and best practices from successful deployments. Flexibility is being driven by lower costs and improved connectivity for where and how to deploy sensors, data collection, storage, and analytics. A comprehensive view of possible architectures and tradeoffs would be well beyond the scope of description because of the rapid development of new innovations and buzzwords. Below are four considerations about ubiquitous computing’s impact on plant architectures for data creation, collection, storage, and analytics.
1. What’s the starting point?
For new sensor deployments, the collected data resides in the cloud even if the cloud is hardware in a local data center. This is more appropriate for monitoring/visibility as the architecture will have to support communications disruptions in addition to meeting a host of data security requirements. Microsoft, Amazon, Google, and 100+ startups, including industrial-specific wireless companies, offer a full stack of “edge to insight” software. This approach offers rapid deployment and new cloud services revenue. The alternative is brownfield plants where the center of gravity is, and will continue to be, on premise. Low latency, guaranteed networking, and local access to data are all key to this model, and these solutions are in place and working. A more likely scenario for brownfield plants is expansion of their data collection, either through local wireless solutions or through an adjacent cloud-based system where data is integrated with their plant systems. Where the data lands is flexible with this model, either on premise or in the cloud.
2. Do assets have neighbors?
In the edge computing model, the premise is any asset may be analyzed individually and diagnosed for predictive failure, optimized run time performance, etc. If the asset is operating independently, that makes sense. This creates a smarter RTU model for high value assets. However, if the asset has neighbors with a process unit or a line of machinery, which is often the case, it’s not so obvious where the data collection and analytics should occur. What can happen is adjacent assets end up fighting for optimization status. What’s needed is optimization of an entire process unit or manufacturing line. The answer is aggregating the data from multiple assets at the line, unless it’s part of a larger unit. Careful planning for where data is collected, stored, and analyzed for optimization will be required except for in a stand-alone asset scenario. Even then—given pricing, energy, and other inputs unavailable on the plant floor—the best results may be with a central data collection and analytics model.
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Figure 1: An explosion of new architectures for data collection, storage, and analysis is modifying the Purdue Model. Courtesy: Seeq
3. Who owns the data?
With new computing architectures, the questions are where data should be stored and by whom. Asset vendors increasingly are offering remote monitoring services for the assets they sell. Resulting questions about data governance include: • Who owns the generated data? • Does the data get copied twice (to the monitoring vendor and to the plant owner)? • How and to where does the asset data move (security, wireless, cloud), etc.? • How are the insights brought back and integrated into the customer’s systems for operational improvements?
Figure 2: AWS Outposts and similar services put a vendor’s cloud software platform on server hardware running locally in a customer’s IT department, creating a local cloud. Courtesy: Seeq
4. Who has the expertise?
Data inputs beyond the ones needed for real-time control and monitoring often are required to optimize asset, line, or plant performance. Overtime costs for staff, rush order costs for spare parts, and customer commitments are part of production optimization, and are why plant engineers and experts have such encouraging employment prospects. This will require advanced analytics offerings to access, visualize, and contextualize data to create insights. ce
Michael Risse, chief marketing officer (CMO) and vice president, Seeq Corp. Edited by Chris Vavra, production editor, Control Engineering, CFE Media, cvavra@cfemedia.com. control engineeering
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DATA ACQUISITION, ANALYSIS Edwin van Dijk, TrendMiner
Connect quality, process data Using advanced analytics can help product quality, operational efficiencies.
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KeyWORDs: Big Data, data analytics, quality assurance (QA) Advanced analytics to improve quality assurance Use advanced analytics to improve the overall production process. COnsiDeR this How can a facility benefit with advanced analytics?
OnLine With this article online: See a case study on residence time assessment to reduce quality deviation in a chemical batch process.
roduct quality will remain a constant focus and challenge for process manufacturing companies. A changing landscape brings new ways for the industry to strive for, and achieve, operational excellence by using Big Data. Big Data and the Industrial Internet of Things (IIoT) have opened new ways to improve product quality. Self-service advanced analytics allows subject matter experts (SMEs) to contribute to operational excellence and meet corporate quality and profitability objectives. A modern definition of quality is “fitness for intended use,” which implies meeting or exceeding customer expectations. Another way of defining quality is what impacts the product quality before the customer uses it in these three ways (see Figure): 1. Raw material: Raw materials entering the production process are often natural materials that typically have varying consistencies, which requires process adjustments to maintain an unvarying quality level of the finished product. 2. Production line: A production line’s design and configuration impact the process and asset performance, which, in turn, impact each other. Materials impacting asset performance, or overall equipment effectiveness (OEE), would be when a substance fouls heat exchangers as it runs through the tubes. An asset’s performance can impact product-processing circumstances, such as a pressure-drop due to a malfunctioning pump. A process control system usually can achieve a consistent a production level while remaining safety-compliant and cost-effective. The intermediate product quality can be tested and monitored during production, but to know if the
product meets the requirements, lab tests are done according to control system procedures. 3. Product storage and shipment conditions: Packaging, handling and environment may impact how long the product remains in specification. For the customer, the product received might be considered as raw material for another production process. When using products within a production process, the customer gathers quality data and provides feedback to the supplier to improve future deliveries of the ordered goods. This feedback closes the top loop in the figure.
Quality control or quality assurance?
Quality control (QC) and quality assurance (QA) ensures product quality. QC and QA are closely related, but different concepts. QC detects errors in the product while QA prevents quality problems. Typically, QC is done after the fact, while QA includes activities to prevent quality problems and requires systematic measurement, comparison with a standard, process monitoring, and an associated feedback loop. The key to QA is within sensor-generated, timeseries production data collected in data acquisition applications. A historian with a trend viewer and analytics capabilities can capture data. Programming skills may be needed to analyze operational performance. With computing power increasing, visualizing the time-series process and asset data of many instruments is possible. Process experts can use visualization and pattern recognition capabilities from self-service analytics tools to assess production processes and correlations. The software is used to see what has happened, how often, why it has happened, and even suggest potential root causes upstream in the process. By empowering process engineers with advanced analytics tools, more production issues can be assessed by interpreting the data. Process data gives good options to assure product quality through self-service analytics. See the the online use case. ce
Figure: Product quality is impacted and controlled in various stages before the customer uses it. Courtesy: TrendMiner
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Edwin van Dijk is the vice president of marketing at TrendMiner. Edited by Emily Guenther, associate content manager, Control Engineering, CFE Media, eguenther@cfemedia.com. www.controleng.com
ANSWERS
BIG DATA ACQUISITION Qasim Maqbool and Ahmed Habib, Intech Process Automation
5 Big Data challenges
Demystify the need for Big Data; see five data aquisition challenges.
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he term Big Data has been widely used, and everyone seems to be insistent on employing Big Data tools and techniques, which includes industrial applications. Find greater success by demystifying Big Data and five related challenges.
factors can sometimes mean the difference between investing a million dollars and saving millions. When upgrading a distributed control system (DCS), integrating a Big Data system for wider view is beyond the one plant team’s budget and scope.
1. Data types, structure
If the desired data needs to be locally stored (for security or privacy considerations) the existing data is already stored structurally and only needs to be analyzed and contextualized with other data such as through an OPC server. Using remote analysis and visualization with dashboards and data connectors is more effective financially, especially while delivering similar decision support as with Big Data implementation. Many industries have connected disparate data sources; analyses and insights deliver multifold productivity and efficiency boosts. Early Big Data adopters will gain a competitive edge over those relying on integrated traditional data analyses. Most industries need traditional data analyses as much as Big Data.
Most people in the manufacturing industry have heard of “Big Data.” What constitutes Big Data is less clear. At a glance, Big Data is the all-encompassing term for traditional data and data generated beyond traditional data sources. In a plant’s context, this traditional data can be split into two streams: Operational technology (OT) data and information technology (IT) data. OT data for a plant consists of alarms and events data, data historian collections, etc. IT data for the plant is enterprise resource planning (ERP) data, which primarily covers production, procurement, and access logs. Traditional IT and OT data are stored in unique systems and structures. Big Data is “multistructured,” meaning it has the necessary knowledge management tools to access different data from different origins and contextualize it for analyses and reports.
2. Data scalability, context
Beyond data storage and acquisition, Big Data systems need to be able to quickly address and analyze data on demand without being affected by the scale and pace of data acquisition and querying. This is called Big Data scalability, and it is one of the first concerns for Big Data systems. Other concerns include system reliability (performance) and decision support for real-time analyses. Analyses include machine learning (ML) and artificial intelligence (AI), which can help in finding data anomalies, predicting future behavior for production, equipment, and forecasts, and providing detailed scenarios for decision support.
3. Data integration efficiency
After establishing Big Data context, determining need becomes simpler. When and how Big Data is needed is a more nuanced matter. Big Data system integration requires extensive effort and commitment from an organization, not just an IT team. At the granular level, information pockets can be invisible in an organization or sometimes intentionally kept secret to avoid a “Hawthorne effect” (when observation can change behavior). Ignoring these
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4. Data storage
5. Big Data upgrades
Some of the Big Data biggest challenges are in planning a Big Data upgrade. An extensive solution can be continuously scaled to integrate newer data sources and designed for upgrades without affecting functionality and performance. For most organizations, this means switching services to the cloud, upgrading systems for better data monitoring and logging, and almost always increasing the human capital with skills to implement Big Data solutions across departments and functions. Those that employ onpremise security concerns need to consider the higher costs of maintaining in-house data servers with a dedicated system support team. System scalability may not be as effective as cloud-based deployments. Companies working with Industrial Internet of Things (IIoT) and Big Data have a vested interest in pushing Big Data solutions. While it is more beneficial to have Big Data in the long term, existing systems with gaps can be filled with a better-organized approach to traditional data management and analyses. Traditional data acquisition, trending, and monitoring can have much greater cost-benefits. Thoroughly planned traditional data analysis technologies need to be precede a Big Data implementation. Only then can an organization see what Big Data systems could achieve. ce control engineeering
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KeyWORDs: Big Data, data acquisition Challenges exist with Big Data and data acquisition. Data structure and scalability need to be addressed. Data integration, storage, and upgrades are important. CONsIDeR THIs Breaking down challenges related to Big Data can make implementations less daunting.
ONLINe More information on each point are available by clicking on the headline of the digital edition. www.controleng.com/ magazine See New Products for Engineers categories at www.controleng.com/NP4E.
Qasim Maqbool is principal platform engineer industrial intelligence solutions, and Ahmed Habib is marketing manager, for Intech Process Automation. Intech Process Automation is a Control Engineering Content Partner. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media, mhoske@cfemedia.com. March 2019
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PROCESS SENSORS Daniel E. Capano, Gannett Fleming Engineers and Architects P.C.
Solids level measurement
Accurately measuring the quantity of solids in a tank or silo is crucial to product management, custody control and transfer.
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ranular solids are a collection of macroscopic particles such as snow, sand, rice or coal. Although the form of granular solids is easy to explain, their behavior is complex and differ from liquids and gases. Accurately measuring the quantity of solids in a tank or silo is crucial to product management and custody control and transfer.
Sensor types
As with liquid level measurement, devices fall into two broad categories: noncontact and contact. Within those categories, devices are broken down further into point-level and continuous-level monitoring. This article describes the principles behind those devices and some applications. Solids level measurement is not as cut and dry as liquid level measurement. Liquids have a characteristic weight that can be translated into level using static pressure devices; solids can vary widely within batches. Liquids also find their own level and present a uniform surface to a measuring device in the absence of mixing or other disturbances. This is one of the challenges of solids measurement. Solids tend to present an uneven surface to the measuring device, and load or settle unevenly in the container in which they are stored. Finding a level surface to bounce a signal from is challenging. Noncontact devices used for solids measurement are identical to those used in liquid level measurement with ultrasonic, radar and lasers being the most common devices. UltrasonKeyWORDs: process sensors, ic devices have the advantage of being inexsolid level monitoring pensive, and their behavior is understood. Unfortunately, this leads to misapplication, Key cOncepts which can leads to inconsistent results. The As with liquid level measurement, devices same holds true for radar devices. Solids tend measuring solids fall into two to resist settling into a uniform and level surbroad categories: noncontact face. More often, solids are delivered to a tank and contact. or silo by a conveyor that dumps the solids The application, use, placement into one spot, causing it to form a cone deterand method of monitoring and mined by that solids’ “angle of repose.” When controlling solids levels rely on a understanding of the solids. that angle is exceeded, there is a mass settling or sloughing. If a noncontact device is monicOnsIDeR tHIs toring the top of the cone, this sloughing will Solids characteristics may result in a sudden change in level. Howevinclude combustible dusts that could present a life safety hazard. er, as is usually the case, the device is placed adjacent to the delivery area, a true level will GO OnlIne never be realized, and the sloughing will Link to more info, online again cause a sudden change in level. resources, process sensors.
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Measurement issues
The issue is the problem of reflection from an angled surface. Ultrasonic, guided-wave radar (GWR) and laser devices rely on the reflection of a signal from the surface of the material being measured. The surface of a liquid is uniform and presents a good reflecting surface for the signal “bounce.” Solids vary in consistency, granular size and of course, angle of repose. The angle of repose is the angle a solid will naturally settle if it is delivered as a consistent stream. Every solid has a characteristic angle of repose. This can be used in a point-level application. A noncontact measuring device transducer can be mounted at the angle of repose to determine when a solids cone reaches a control point such as a high-level alarm. Continuous level measurement is not as easy. Lack of a uniform surface prevents a coherent reflection from returning to the transducer, and the varying granular size creates a scattering effect—both conditions result in an unreliable signal. Lasers are more reliable point-level devices and are more accurate in determining the presence of a solid at a control point. A laser can be mounted in an “over the shoulder” arrangement where the mounting of a device over the container is impractical. A recent application is the filling of a truck with sludge cake. It was impractical to mount a level monitoring device over the truck because of material handling and delivery equipment. Dust in the container, bulking of solids, and uneven loading can affect noncontact devices. Remember that dust can combust. Coal dust and grain silo explosions were very common until safety procedures were implemented. This characteristic must be considered when designing a system. Aside from fuel, oxygen, and ignition required for gas combustion, dust requires dispersion and confinement to become combustible. Dispersion can interfere with noncontact types of level-device operation. Proper equipment enclosures should be designed into the system for proper protection. Bulking of solids occurs when the solid “cakes” and becomes a separate mass from the rest of the silo contents, as in the solids piling up on one side of the silo. This can result in no contact with or by the level device. A common remedy is vibration or “fluidizing” the solids with air to assure even distribution. Uneven loading can happen for many reasons. System design and operator experience, along with mechanical agitation in some cases, can help mitigate this problem. www.controleng.com
| PI11-01USA |
SAL 18 Series RF Admittance Point Level Switch from Aplus Finetek Sensor Inc. is said to be an advanced radio-frequency (RF) level switch to fit many varied applications detecting presence/absence of liquids, solids and slurry materials, including asphalt mix, bitumin, dry powders, granular materials, etc., for highand low-level material detection. Automatic build-up immunity is provided. Courtesy: Aplus Finetek Sensor Inc. and CFE Technology’s New Products for Engineers database.
MultiRanger 200 from Siemens is a shortto medium-range ultrasonic single and multi-vessel level monitor/controller. It can be used on materials including municipal waste, woodchips, and materials with high angles of repose. It offers alarms, on/off and alternating pump control and can be used in diverse applications such as wet wells, hoppers, dry solids storage and other areas. Courtesy: Siemens and CFE Technology’s New Products for Engineers database.
Industrial automation and process technology in one system with EtherCAT and PC Control
Measurement devices
Contact measurement devices for this application are unique to solids measurement. These devices rely on either direct contact with the materials or by weight. Solids differ in size, density, moisture content, and weight. These characteristics are used to detect or to infer a level. A common point-level detection device is the vibrating reed or “tuning fork” type of sensor. Another common measurement method is a weight and cable system, commonly called a “yo-yo.” This device is mechanical, though it contains a slide wire transducer that follows the mechanism as it travels down to the surface. Strain gauges are used to retrofit existing containers or silos to allow indication of solids loading within the container. ce
Daniel E. Capano is senior project manager, Gannett Fleming Engineers and Architects, P.C. and a Control Engineering Editorial Advisory Board member. Edited by Jack Smith, content manager, Control Engineering, CFE Media, jsmith@cfemedia.com control engineering
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www.beckhoff.us/process With a comprehensive range of components for explosion protection and common process industry interfaces in TwinCAT automation software, Beckhoff offers the possibility to integrate automation and process technology in a system without barriers into Zone 0/20. The range extends from the compact, intrinsically safe EtherCAT Terminals from the ELX series and the TwinCAT software which offer important process technology interfaces, such as HART, NAMUR and FDT Technology. Robust Control Panels and Panel PCs are also available for process applications in the CPX series. These are classified for Zone 2/22 installation and round out the offerings for hazardous applications. All together, these solutions allow users to directly connect intrinsically safe field devices and realize integrated control architectures with barrier-free process technology.
input #16 at www.controleng.com/information
ANSWERS
INSIDE ProcESS: PArT 2 Joseph Amalraj and Babar Shehzad; Syncrude Canada Ltd.
Verifying primary and secondary flow measurement This part 2 article continues to discusses a method to analyze performance of primary and secondary flow measurements by separating repeatability and accuracy (bias shift) without assuming the PM is always accurate and repeatable. The method also identifies whether the issue is with the PM or with the SM.
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n the January 2019 issue of Control Engineering, the first part of the article, “Verifying primary and secondary flow measurement performance,” discussed using a secondary flow measurement (verification meter) to verify the performance of a primary flow measurement (custody transfer meter) when the primary flow measurement is used to bill a transacted product. This article continues the discussion by introducing the novel method.
Verify PM and SM in a novel way
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For argument’s sake, assume the secondary flow measurement (SM) exactly duplicates the primary flow measurement. That is:
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KeyWORDs: flow
measurement, flowmeter For the primary flow measurement, industries use highly accurate and repeatable flowmeters, typically compensated by pressure, temperature, and density/gas chromatograph. For the secondary flow measurement, industries use less accurate but repeatable flowmeters. Instrument accuracy depends on the measurement principle, design, installation, and maintenance of the instrument, whereas, repeatability of an instrument is an inherent feature of the measurement technology used.
CONsIDeR THIs How are flow measurements in your plant verified?
GO ONlINe See the full version of this article at www.controleng.com.
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• The secondary flow measurement uses the same type/make of primary flow measurement.
For absolute constant flow, the average of the primary flow measurement and the secondary flow measurement will be the flow itself, and the standard deviation of the primary flow measurement and the secondary flow measurement will be equal to zero. However, for a varying flow during the billing cycle the average (µ) of the primary flow measurement will be equal to the average of the secondary flow measurement, and the standard deviation (σ) of the primary flow measurement will be equal to the standard deviation of the secondary flow measurement. That is, σPM = σSM (Equation 1) and µPM = µSM (Equation 2) Combining equation 1 and equation 2 we get, (σPM / µPM)% = (σSM / µSM)% (Equation 3) i.e., (σPM / µPM)% - (σSM / µSM)% = 0 (Equation 4).
• The secondary flow measurement has all the instruments the primary flow measurement uses to compensate/correct the flow measurement.
In real process plant scenarios, the secondary flow measurement is not duplicating the primary flow measurement. Hence, it is safe to modify Equation 4, as:
• The secondary flow measurement uses the same type/make meter prover of primary flow measurement.
(σPM / µPM)% - (σSM / µSM)% < X, (Equation 5: novel method equation) Where X could be = +1% or +2% (depending on measured fluid is liquid or gas).
• The secondary flow measurement has the same proving frequency of proving the primary flow measurement. In this ideal situation, one can derive that for a given billing cycle, the average of the primary flow measurement will be equal to the average of the secondary flow measurement, and the standard deviation of the primary flow measurement will be equal to the standard deviation of the secondary flow measurement.
control engineering
The primary flow measurements have very high repeatability mostly 0.1 to 0.2%. Hence, having a +1% or +2% (depending on whether the measured fluid is liquid or gas) in equation 5 should be acceptable for industries. The result of equation 5 is known as the “novel method difference.” This difference helps to better analyze the performance of the primary and secondary flow measurements. The current methodology takes the difference of the time-stamped primary flow measurement and www.controleng.com
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ANSWERS
INSIDE ProcESS: PArT 2 secondary flow measurement values and then computes the standard deviation and the average based on the differences. The novel method calculates the standard deviation and the average separately for the primary flow measurement and the secondary flow measurement. The novel method difference is calculated to analyze the performance of the primary flow measurement and the secondary flow measurement for the billing cycle. Red = primary flow measurement GReen = secondary flow measurement
Figure 4: The process trend indicates a primary flow measurement failure. All graphics courtesy: Syncrude Canada Ltd.
Red = primary flow measurement GReen = secondary flow measurement
Figure 5: The process trend indicates a primary flow measurement signal loss. (See Figures 1-3, online.)
Figure 6: Software implementation framework.
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novel method advantages
The novel method compares the separately calculated values of the primary and secondary flow measurements. Advantages of this method are: • Full data sample available for the whole billing period is used. • No bias in the assumption that the primary flow measurement is absolutely accurate and repeatable. • Testing is performed whether the primary flow measurement is close to the secondary flow measurement within the accepted tolerance (+1% or +2% depending on whether the measured fluid is liquid or gas). • Engineering units for flow measurement for primary and secondary flow measurements need not be the same.
Proof of concept
1. The measurement verification using the novel method difference (equation 5) for the same period shown in Figure 3 is shown in Table 7. The novel method difference is -0.21%. Since the flow has significant variation, the PM and SM are coping to capture the true value of the process. This methodology eliminates the bias that the PM is accurate and repeatable. Based on this methodology, there is no need to maintain the secondary flow measurement. This example illustrates how by using the novel method difference for the entire billing cycle, it was concluded there is no need to maintain the secondary flow measurement while the current industry methodologies concluded to maintain the secondary flow measurement. 2. Another example was chosen where the current selected constant flow samples methodology had a secondary flow measurement repeatability of 13.05%. The novel method difference is 8.24%, which is very much greater than the accepted +2%. The novel method result is shown in Table 8A. The very high %SD/Avg (typically greater than 35%) for the PM and SM indicated there is a problem with either the primary or secondary flow measurement. Upon reviewing the process trend (Figure 4) it was noted that the primary flow measurement signal was lost for some periods. Investigation with the primary flow measurement company indicated issues with an instrument used to compensate flow measurement. It was decided to recalculate the results using the novel method difference after eliminating the duration where the primary flow measurement data was not good. After eliminating the bad data, the novel method difference indicated the difference between the primary and secondary flow measurements is -0.25%, www.controleng.com
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ANSWERS
INSIDE ProcESS: PArT 2 BlAck = Novel Method Difference Red = Primary flow measurement GReen = Secondary flow measurement
Figure 7: The graph shows primary and secondary flow measurements with novel method difference <+2%. BlAck = Novel method difference Red = Primary flow measurement GReen = Secondary flow measurement
Figure 8: The graph shows primary and secondary flow measurements with novel method difference >+2%. BlAck = Novel method difference Red = Primary flow measurement GReen = Secondary flow measurement
3. Another billing cycle period was chosen where the current selected constant flow samples methodology had a secondary flow measurement repeatability of 4.94%. It should be noted this facility had a history of very good repeatability (< +2%) as the flow in this facility is fairly constant. The novel method difference is 33.99%, which is much greater than the current selected constant flow samples method repeatability of 4.94%. The novel method result is shown in Table 9A (online). The large novel method difference indicated a problem with either the primary or secondary flow measurement. On reviewing the process trend, it was noted the primary flow measurement showed zero flow for a considerable duration and the primary flow measurement had significant oscillations for some days within the billing cycle period (see Figure 5). It was decided to recalculate the results using the novel method after eliminating the durations where the primary flow measurement was reading zero flow and where the primary flow measurement had oscillations. Table 9B (online) shows novel method difference results. Eliminating the durations wherein the primary flow measurement reading was zero and eliminating the durations wherein the primary flow measurement had significant oscillations, the novel method indicated that the difference between the primary and secondary flow measurements is 0.79%, which is much less than the accepted +2%. Based on this methodology, there is no need to maintain the secondary flow measurement. The novel method revealed the issue is either with the PM or the SM. Review of the trend showed the issue is with the PM, not with the SM.
Applying novel method difference
Figure 9: The graph shows primary and secondary flow measurements with novel method difference >+2%.
which is much less than the accepted +2%. The novel method result is shown in Table 8B (online). Based on the novel methodology, there is no need to maintain the secondary flow measurement. In addition, the novel method revealed the issue is either with the PM and or with the SM and further analysis is required to determine which measurement is deviating from the true valve. Review of the trend concluded the issue is with the PM and not with the SM.
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Based on the manual calculations done on the historical monthâ&#x20AC;&#x2122;s data, it was decided to build an application to include the novel method difference between the primary flow measurement and the secondary flow measurement computations for checking the individual performance of the measurements. A rolling period of 3 days for the novel method difference was chosen instead of the whole billing cycle period of a month for corrective actions, such as verifying the calibration/configuration parameters of the secondary flow measurement and checking with the primary flow measurement in charge to verify the performance of all the instruments used to compensate the flow. A software application was developed for the primary and secondary flow measurement calculations. The real-time flowmeter data is captured and stored in a real-time data historian. The scheduling component of the software runs the calculation every 5 minutes to update the flow measurement values. The logic to calculate the aggregates is exactly the same. One piece of code was written for all locations, which runs one process on multiple contexts www.controleng.com
‘
Based on this methodology, there is no need to maintain the secondary flow measurement.
’
as separate threads with input and output tags. Figure 6 shows the calculation framework, which runs after a specific period defined as part of the properties of the framework. The calculation outputs are written to output tags with aggregate values such as averages, standard deviation, percent standard deviation, and difference of percent standard deviation for each location and are stored in a data historian. The 3-day rolling period for the novel method difference was giving false alarms when the flow variation was significant within the 3-day rolling period. The flow variation was further analyzed, and a 7-day rolling period was introduced in lieu of a 3-day rolling period, which eliminated false alarms. With this article online, see three examples of industry usage. ce Joseph Amalraj is a senior technical specialist, and Babar Shehzad is a systems advisor. Both work for Syncrude Canada Ltd. Edited by Jack Smith, content manager, Control Engineering, CFE Media, jsmith@cfemedia.com.
Novel method difference results PM
SM
2,552
99
Standard deviation
392
15
Standard deviation divided by average
15.36%
15.57%
Average
Repeatability Novel method difference
-0.21%
Table 7: Novel method difference - significant flow variation.
Novel method difference results Average Standard deviation Standard deviation divided by average
Repeatability Novel method difference
PM
SM
1,657
50
733
18
44.24%
36.00% 8.24%
Table 8A: Novel method difference > + 2% - PM measurement bad data. See three more results tables and the article in full online.
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ANSWERS
INSIDE PRocESS Keith Riley, Endress+Hauser Inc.
Temperature sensor calibration Risk of sensor failure is less if the temperature sensor can be calibrated in situ.
T
he most common calibration standard operating procedure [SOP] for temperature sensors in hygienic process industries is a two- or three-point calibration. Calibration can be performed in the facilities lab or near the insertion point. This reflects the state-of-the-art method to obtain the clearest possible temperature curve for the sensor and detect deviation. This practice is in line with expectations from auditors and regulatory authorities. With the process temperatures in the hygienic industries, a standard resistance temperature detector (RTD) will last for years. Even so, the biggest risk for a thermometer in a hygienic system is the calibration process. Opening the device, removing the insert, connecting and disconnecting power cables, introducing the thermometer into the oil bath or block calibrator, or transporting the thermometer to the laboratory increases the likelihood of mechanical damage. Removing the sensor from the process or thermowell is the biggest reason for RTD failure. A related question is: “What is the best way to return the sensor to the exact same measuring position in the process after removing it for calibration?” Risks are significantly less if the temperature sensor can be calibrated in situ.
Temperature calibration timing
A major limitation with the traditional 3-point calibration is the calibration cycle times. What is the performance of the RTD between calibration cycles? Most faciliKeyWORDs:Hygienic ties establish the cycle times based upon temperature sensor, sensor an analysis of risk management and cost. calibration More calibrations (shorter cycles) reduce Sensor elements can fail when the risk, but increase the expense. removed for calibration. Fewer calibrations [longer cycles] do In-situ calibration reduces risk the opposite. A sensor with self-calibraof sensor failure. tion or self-verification capability proProduct quality is ensured when vides continuous health monitoring of in-place calibration is performed with sterilization cycles. the RTD. Each time sterilization in place (SIP) happens, a sensor performs a caliCONsIDeR THIs bration without: Would in-place calibration
M More ANSWERS
save time and resources in your processes?
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• The need to halt the production process • Removing the RTD from the process • Any effort needed from the maintenance or metrology staff.
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Endress+Hauser’s iTherm TrustSens Hygienic RTD Sensor won a 2019 Engineers’ Choice Award in the Process control - Process sensors category. The self-calibration or self-verification capability of TrustSens provides continuous health monitoring of the RTD. Minimum temperature threshold necessary to initiate TrustSens’ self-calibration feature is 118°C. Courtesy: Endress+Hauser
At this point, calibration will immediately identify or eliminate the risk of non-conformities with the RTD before the calibration cycle is up, thus, ensuring the highest product quality. The minimum temperature threshold necessary to initiate self-calibration is 118°C, according to one sensor’s design specifications. This most commonly occurs during an SIP cycle. However, since not all hygienic applications employ sterilization in place, there are other ways to take advantage of self-calibration. One is to remove the sensor from the process and place it in ceramic dry block heat source to achieve a temperature of 118°C. Once this occurs, the dry block can be turned off and allowed to cool with the sensor remaining in the dry block heater. As the temperature falls below 118°C, self-calibration will take place and ensure the RTD remains within tolerance, which will significantly reduce process downtime. ce Keith Riley is national product manager for pressure/ temperature, Endress+Hauser Inc. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media, mhoske@cfemedia.com. www.controleng.com
INNOVATIONS
NEW PRODUCTS FOR ENGINEERS
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PE
Collaborative robot series has manual teaching function for programming Omron Automation’s TM series collaborative robot is designed to seamlessly work with humans to enhance productivity and ensure safety. The TM series robot complies with safety requirements for human-robot collaboration specified in ISO 10218-1 and ISO/TS 15066. It can be easily trained to perform almost any repetitive task in any location thanks to a manual teaching function that allows operators to teach the robot with hand-guidance without the need for software. The robot reduces installation, and no prior robot programming experience is necessary. The robot also comes with built-in vision and integrated lighting for capturing products with a wide viewing angle. Omron Automation www.omron.com
Input #200 at www.controleng.com/information
Inductive proximity sensors
AutomationDirect’s Contrinex DW inductive proximity sensors added more harsh duty sensors and new standard duty sensors with quadruple sensing ranges. They fit harsh duty applications, come in 4 mm smooth and 5 mm models and can have stainless steel housings. The 8 mm and 12 mm diameter DW series sensor models are available with quadruple sensing ranges. The 8 mm M8 sensor has a 4 mm (shielded) sensing distance; 12 mm M12 sensor has an 8 mm (shielded) sensing distance.
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High-load ball screws
Thomson Industries Inc. has introduced a ball screw with more than twice the load capacity of a standard ball screw. The redesigned ball screws handle more than double the load capacity and provide 10 times the service life compared to standard ball screws at equivalent performance points. Highload ball screws are ideal for demanding motion control applications such as injection molding, pressing and large fabrication equipment. Thomson high-load ball screws minimize replacement and maintenance costs significantly for the application. This provides an ideal opportunity to replace roller screws or hydraulic systems.
ÖLFLEX® SERVO FD 7TCE meets UL TC-ER trayrating and continuous flex cabling requirements, eliminating the need for two different types of cable in a single run — lowering risk of vibration-related connectivity loss, and reducing installation time. High flexibility from ultra-fine copper wiring and high strand count — delivers tight bend radii and longevity up to several million bending cycles. Low capacitance insulation and super EMI shielding, tri-laminate foil tape, and high-coverage tinned copper braid — yields lower insulation degradation and reduces potential current leakage to ground over long distances. ÖLFLEX® SERVO FD 7TCE provides wide operating temperature range, oil resistance, and meets FT4 flame test standards.
Thomson Industries Inc. www.thomsonlinear.com
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INNOVATIONS
NEW PRODUCTS FOR ENGINEERS
See more New Products for Engineers. www.controleng.com/NP4E
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DC/DC converter series
Traco Power’s THN 15N series of 15 W DC/DC converters is designed to meet EMI Level A standards without external components and reduced no-load power consumption of 96-336 mW and efficiencies up to 91%. They are ideal for addressing power conversion requirements in mobile equipment, instrumentation, distributed power architectures and industrial electronics applications. The THN 15N features a wide 2:1 input range of 9-18 / 18-36 / 36-75 Vin with single and dual outputs ranging from 3.3 to 24 VDC. It has an temperature range of -40 to 70°C (up to 105°C with derating) and provides input to output isolation of 1,600 VDC. It features remote on/off control and a voltage trim function inside a 6-sided shielded metal case with an insulated base plate. Traco Power, www.tracopower.com Input #203 at www.controleng.com/information
Power distribution unit
Eaton’s High Density power distribution unit (PDU) platform is designed for environments in which high power density is essential, such as data centers and large enterprise facilities. Eaton’s High Density rack PDU offers improved outlet counts and the addition of 11 color options for easy identification of A/B power feeds. Providing 11 outlet module options, the High Density rack PDU allows configuration for up to 54 outlets per PDU and unlocks over 20,000 configurable options for users. Alternative phase outlets simplify load balancing and improve airflow by putting outlets where they are needed, reducing the potential for tripped breakers. Eaton Corp., www.eaton.com
Input #205 at www.controleng.com/information
Rugged ac drive
FactoryMation’s FMX TD400 Tough Drive is a rugged ac drive for demanding motor control applications. The TD400 series is designed to operate at the limits of typical line voltages found in the U.S. market and is rated for operation at 50°C. The drives also feature volts per hertz, sensorless vector, and permanent magnet control modes. FactoryMation, www.factorymation.com Input #204 at www.controleng.com/information
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INNOVATIONS
Back to Basics Gregory Hale, ISSSource
Digital transformation cybersecurity companies looking at digital transformation need cybersecurity. Everyone–not just it–needs to take responsibility to make it work. see seven areas that need attention.
A
digital transformation cannot occur without a solid cybersecurity plan. Unfortunately, there are plenty of manufacturers that are just beginning this transformation process. Assessing cybersecurity readiness for a single site can be daunting, but there is hope. A user has to start with a basic assessment of what exists and what it’s connected to. When that is done, the user can conduct upfront planning and create a course of action. “Some users do not feel they are in an unsafe place,” said Rick Gorskie, a global manager for cybersecurity at Emerson Automation Solutions during a presentation entitled, “Assessing Cybersecurity Readiness: From a Single Site to an Entire Enterprise,” at the Emerson Global Users Exchange in San Antonio. “There are working models of people thinking information technology (IT) infrastructure would provide protection. Many people think it is IT’s job to handle security. I am here to say that is not the case.” While Emerson always talked about cybersecurity at previous user group conferences, this year’s effort was impressive in the breadth of coverage they gave the subject.
Best practices for users
M More
INNOVAtIONs INNOVAt
Keywords: Cybersecurity,
information technology, IT Many manufacturers are beginning the process of making a shift toward digital transformation. Many companies believe their cybersecurity posture is strong, but oftentimes it isn’t. Cybersecurity starts with an assessment of where the company can improve.
online Read additional stories about cybersecurity at www.controleng.com.
Consider this What positive changes can your company make with a cybersecurity assessment?
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Gorskie said many of his customers feel their security posture is better than average. But the reality is that that may be more of a pipe dream than anything else. That is why he feels manufacturers should start off with a basic assessment of their site. There are seven key categories/ vectors a user should look at: 1. Network security 2. Workstation hardening 3. User account management 4. Patch and security management 5. Physical and perimeter security 6. Security monitoring 7. Data management.
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Once that assessment comes out there should be a report looking at what issues should be addressed first; that is the beginning of the journey toward a more secure environment. “Most users will be ready to start immediately after doing an assessment,” Gorskie said. Users need to understand one of the biggest issues facing them is patching. Patching has been an ongoing issue for years, and with continuous processes, like a refinery, running for years on end, users don’t feel they have time to implement patches. With ransomware incidents like WannaCry and NotPetya that worked off a patched Microsoft vulnerability, manufacturers felt the crush of not patching a patched vulnerability. It cost some companies hundreds of millions of dollars. “Patching the most important thing to do, and we don’t do it,” he said. Once the user is ready to start their cybersecurity journey, they need to move to create policies and procedures, Gorskie said. “It is not rocket science; it is something we do every day.” Gorskie related examples from creating security procedures to safety procedures. “If you don’t follow safety procedures, you will eventually be let go,” he said. “Security should be the same way. It is about doing the right thing and making sure you follow it.” While he said OT security is different than IT security, there needs to be a mindset change on the plant floor. There are plenty of tasks IT people do on a daily basis, Gorskie said, but there are some things OT does daily. “Cybersecurity is not a set it and forget it,” Gorskie said. “We use some of the IT techniques and apply it to the OT space.” When it comes to security, manufacturers can’t just have security for security’s sake, rather they need to incorporate security into desired business results. In the end, according to Gorskie: “It all starts with a basic cybersecurity assessment. Do the assessment. Start the journey.” ce Gregory Hale is the editor and founder of Industrial Safety and Security Source (ISSSource.com), a news and information website covering safety and security issues in the manufacturing automation sector. ISSSource is a CFE Media content partner. Edited by Chris Vavra, production editor, CFE Media, cvavra@cfemedia.com. www.controleng.com
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