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System integrators at their best
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Jack Smith Editor
he cover story in this issue of AppliedAutomation is a case study about how a system integrator (SI), Optimation Technology, upgraded a complex batch system for Grober Nutrition, a family-owned, Canadian-based company that expanded to the U.S. market. To support the plant’s new build, the SI provided engineering, controls programming and design, and skilled trade’s installation services, which included mechanical, electrical and construction management support, as well as control panel, pipe supports and frame fabrication, and much more, according to the author. However, two years later, Grober Nutrition needed upgrades. The SI added graphics and controls for a doser, powder knockers and frack tank. It also reconfigured the recipe screen to allow for more information and identified the need for machine guarding in various areas of the plant.
The other story in this issue, also from an SI, focuses on data acquisition (DAQ) best practices. The author explains that in today’s industrial automation environment, the amount of data available is increasing so fast, businesses are hard-pressed to keep up with it. He writes, “Businesses run the risk of missing valuable data that is critical to success or, worse, storing mounds of data with little to no impact on the business. With new advances in smart manufacturing and Industrial Internet of Things (IIoT)-enabled technologies on the market, businesses can capture, collect and store data from incoming raw materials to the final product to consumers. They also can discover which real-time data adds value to improve operational efficiencies and increase their competitive edge in the marketplace. The first step is understanding data acquisition systems and consider the eight essential best practices for data acquisition success.”
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Contents A6 System integrator upgrades
complex batch system Canadian food & beverage company, Grober Nutrition, expanded to the U.S. with the help of Optimation Technology Inc., and keeps growing
A10 Eight data acquisition
best practices To discover which real-time data adds value to improve operational efficiencies and increase competitive edge in the marketplace, first understand data acquisition systems and consider the eight essential best practices for data acquisition success
A6
ON THE COVER: Optimation provided engineering, controls programming and design, and skilled trade’s installation services, which included mechanical, electrical and construction management support, as well as control panel, pipe supports and frame fabrication. Courtesy: Optimation Technology Inc.
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C A S E S T U D Y: B AT C H
System integrator upgrades complex batch system Canadian food & beverage company, Grober Nutrition, expanded to the U.S. with the help of Optimation Technology Inc., and keeps growing The beginning
Jennifer Palumbo O p t i m a t i o n Te c h n o l o g y I n c .
T
hey say hindsight is 20/20. You can look back on most things in life and see what you did well and what you would do differently. Often, the wisdom that comes with years allows you to see these distinctions better. For capital projects, it’s one thing to look back on how you executed the project. What about after you’ve been operating for a few years after completion? If you knew then what you know now, what would you change? Two years after the completion of a milk replacer production facility for Grober Nutrition, plant personnel reflect on how the new plant has met expectations and prompted for new goals for the not-so-distant future.
Grober Nutrition is a family-owned, Canadian-based company that provides consistent, nutritional and safe products to optimize the growth and health of young animals such as calves, lambs, kids, pets and zoo animals. Looking to expand into the U.S. market, Grober Nutrition USA was formed, along with plans for a new, state-of-theart milk replacer production facility. Grober’s product is a powdered formula used to replace milk for young animals. Surplus whey from a skim milk manufacturer is available as a supply component for the formula. The process includes evaporating permeate to a specific concentration, which is used as an ingredient in a slurry, which is then fed to a large dryer. The permeate and other proprietary ingredients (whey, oil/fat, dairy) are blended to produce the final product. To sell this high-end product throughout the U.S., the company needed a turnkey supplier for electrical, process piping, controls and instrumentation support of a $12 million, 60,000-squarefoot facility in Auburn, New York. Enter Optimation Technology, an engineering, design and skilled trades services company that provides turnkey solutions for industrial clients. Through a formal bidding process, Grober chose Optimation to support the new plant’s build. Optimation provided engineering, controls programming and design, and skilled trade’s installation services, which included mechanical, electrical and construction management support, as well as control panel, pipe supports and frame fabrication (see Figure 1). Integral to the production process were a liquefier, mix tanks, surge tank, homogenizer and process filtering equipment, which Optimation installed as well as all process piping and electrical between the process equipment. Around 10,000 feet of stainless-steel piping, some large Figure 1: Optimation provided engineering, controls programming and design, and skilled trade’s installation services, which included mechanical, electrical and construction management support, as well as control panel, pipe supports and frame fabrication. All images courtesy: Optimation Technology Inc.
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Applied Automation
diameter, was installed by Optimation as a part of the project (see Figure 2). Grober specified a large Filtermat dryer from The Netherlands. Although Grober is headquartered in Canada, the company has Dutch roots, and chose this dryer because of the process engineer’s knowledge of the equipment. This choice would prove to be beneficial and challenging to Grober’s operations down the line. Another challenge for Grober and Optimation was acquiring some used equipment and installing it without detailed installation drawings. Teams ranging in size from 10 to 20 people had to complete the work using only preliminary engineering drawings. All the equipment and necessary utilities were installed according to Grober’s specification, which had to meet FDA requirements and sanitary codes. Grober required an X-Ray inspection of 10% of welds. Optimation also provided software and controls engineering for the plant’s control system. To provide the best solution possible, Optimation conducted interviews with plant employees to better understand what processes Grober wanted to control. The evaporator was the most important because it was integral for concentrating the product and it had to achieve a requirement of 40% and 50% solids. The batching system made the same product over and over during a production run and the system was set up to automatically restart recipes. The recipe system was configured using Rockwell’s SequenceManager. This overall system had three unique subsystems that each ran recipes. Each system feeds the next in line. After the mix is complete, it is homogenized and fed to the Filtermat. A challenge presented itself in designing the controls for the dryer: This was one of only a few dozen Filtermat dryers in the U.S. Optimation wrote custom code to allow different recipes to be run, all of which were editable by the end user. The hardware consisted of Allen-Bradley Rockwell programmable logic controllers (PLCs), View SE distributed human-machine interfaces (HMIs), and a Stratus hardware redundant server, which was used to run the system software. Rockwell’s PlantPAx was used on the View SE application. This allowed a consistent look and feel of the HMI using objects available from Rockwell, with standard faceplates. This also allowed the PLC code to be modular, reducing development time by using these PlantPax objects. Because of the complexity of the process, the software was broken down into three different ControlLogix PLCs. There was an evaporator/tank farm PLC, a batching/mixing/CIP PLC and a homogenization/dryer PLC. These breakdowns were chosen because of the input/output (I/O) required for each. It also helped make each program more manageable.
Fast forward two years Plant manager Charles Balko and production manager Brian Crannell didn’t start working at Grober until after
Figure 2: Around 10,000 feet of stainless-steel piping, some large diameter, was installed at Grober by Optimation as a part of the project
the project was completed in 2017. They weren’t a part of the specification development. They have the benefit of working in the plant for the past two years and the fresh perspective that comes from not being involved in the project from the beginning. Crannell worked with Optimation during the final programming steps on the evaporator and Filtermat dryer process. He taught himself Rockwell’s Sequence Manager system using the training documents created by Optimation. Now, he’s in charge of teaching all new operators how to run the system. “As far as the system goes, it’s user friendly,” Crannell said. “As far as a graphics standpoint, and the overall operations and programming standpoint, it is a well thought out system. The book goes into detail on how to run the sequence manager, how to skip process steps, how to manually run the process and how to pause/hold the recipe steps. This system is complex, but overall it’s a well thought-out program.” The complexity of the system is due to the rarity of the Filtermat dryer, Balko said. “There’s a few dozen Filtermat dryers in the United States and most are drying WPC or NFDM not PEF, so this system was very much a one-off,” he said. “Hard to say that anyone could write the specs for this project, because they hadn’t done it before,” Balko said. “Because of the rarity of the equipment. The recipe screens have good specs because it’s pretty cut and dry. The controls of the drying system were more of a theory. It’s kind of hard to write a good set of specs on how we wanted it to work, because we didn’t know. The drying screen is really confusing, because there’s a lot going on there. But could they have done it differently? Yeah, but would it have been better? No, probably not. There’s just so much information there, so when you’re trying to learn, it just overwhelms people.”
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C A S E S T U D Y: B AT C H Security and training
a service Optimation provides for clients and has seen a high demand As new operators are trained on for recently. Often, however, a the complex drying screen, Balko request for guarding comes through and Crannell see one thing they because an employee has been would have pushed for had they hurt. In Grober’s case, the company been involved in the project early is looking to safeguard employees on: different levels of security for before an incident occurs. Crannell operators, based on levels of experisaid these safety observations often ence. This was discussed early on are made while performing day-toby Optimation and Grober. However, day operations in the plant. Balko and Crannell’s predecessors “Honestly, the process is so compassed on multiple levels of security. plex, to know every little aspect of Two years into using and training safety, it’s one of those things that new operators on the system have you learn as you go,” Crannell said. shown how important it can be. “Knowing what we know now, if you “If you have a new operator who were to build now, there would be is overzealous and likes to change quite a few things that we would do things that he shouldn’t be changing, differently from a safety standpoint.” the current systems allow the opera(All of these safety issues have been tor to do that, where in some cases corrected as they come up; Grober we wouldn’t want that,” Crannell has a robust safety committee). said. “Let’s say the operator makes a setpoint adjustment on a dryer/evapFigure 3: Grober USA already needs to Expansion orator parameter, and they type in an expand and is looking to add more tanks as incorrect setpoint number. The sysGrober USA has seen great it builds out. tem will take it. The direct result from success in its first two years. this can cause major issues with Production goals were projected to product quality and damage to the process equipment.” be 2,800 pounds per hour. After Grober made modificaAnother possibility for the future is adding remote viewtions to its dryer chamber, it has been able to smash that ing of the system’s screens, allowing a supervisor and/or goal, producing 3,500 pounds per hour on average to a process engineer to view and make adjustments off site. max of 4,200 pounds per hour. “Originally, this plant was “There are times when I receive calls in the middle of the built here to make enough product for us and to send night, and I don’t have access to the process screens,” to Canada,” Balko said. “Turns out, we can make more. Crannell said. “I’ve had to either do it through Team Viewer We’re now selling the additional product to non-competior through my general knowledge of the process. This sys- tors on the west coast.” tem is so complex, so to try and walk an operator through With success comes another challenge, Balko said. an issue when you’re not right there, it’s difficult.” Grober USA needs to expand already. “The place is too In addition to adding security, Grober also is looking at small. We don’t have enough tanks now. We’re already getting the most of the system’s historian. This will aid the realizing that we need to grow, adding two more tanks company in audits and with providing clients with specific and extending the building out,” he said (see Figure 3). information. This will require many little changes to the overall sys“Some auditors will come in and want to know when tem going forward, such as making changes to the liquethings were last cleaned in place and the increments of fier screens. cleaning, so if you can provide them access to that via the Grober has started to penetrate the American market historian, that would be phenomenal,” Crannell said. and has goals to continue to ramp up more sales in the U.S., as well as looking to export to other countries. To Safety meet these goals, Balko and Crannell’s plans for continuous improvement and expansion of the plant’s operations Balko and Crannell agreed safety is priority number will be key. Grober has engaged Optimation to aid in the one at the plant. Grober has made a few programming expansion efforts, which Balko said needs to happen as changes to make the system more efficient and safer for the operators. It added graphics and controls for a K-Tron soon as possible. doser, powder knockers and frack tank. They’ve also Jennifer Palumbo is director of marketing at Optimation reconfigured the recipe screen to allow for more informaTechnology Inc., a certified member of the Control System tion. Integrators Association (CSIA). For more, visit the comThey’ve also identified the need for machine guardpany profile on the Industrial Automation Exchange. ing in various areas of the plant. Machine guarding is
A8 • December 2019
Applied Automation
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Eight data acquisition best practices To discover which real-time data adds value to improve operational efficiencies and increase competitive edge in the marketplace, first understand data acquisition systems and consider the eight essential best practices for data acquisition success By Brian Bolton
I
n today’s industrial automation environment, the amount of data available is increasing so fast businesses are hard-pressed to keep up with it. Data comes from multiple sources now more than ever. In addition, the cost of storage space has decreased, making the increase in Big Data affordable. Under these circumstances, businesses run the risk of missing valuable data that is critical to success or, worse, storing mounds of data with little to no impact on the business. In the past, engineers and instrumentation/electrical technicians tended to be the only ones to access and use the data, but now the entire organization uses data. So, how can businesses ensure the quality, type and quantity of stored historized data remains relevant year after year and the right people can access and use it? With new advances in smart manufacturing and Industrial Internet of Things (IIoT)-enabled technologies on the market, businesses can capture, collect and store data from incoming raw materials to the final product to consumers. They also can discover which real-time data adds value to improve operational efficiencies and increase their competitive edge in the marketplace. The first step is understanding data acquisition systems and consider the eight essential best practices for data acquisition success.
Breaking data down bit by bit In its simplest form, a data acquisition system (DAQ or DAS) samples signals that measure real-world physical conditions and converts the resulting samples into digital numeric values that a computer can manipulate. These systems convert analog waveforms into digital values for processing. Data acquisition components include: • Sensors to convert physical parameters to electrical signals • Signal-conditioning circuitry to convert sensor signals into a form that can be converted to digital values • Analog-to-digital (A/D) converters to convert conditioned sensor signals to digital values.
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Applied Automation
Many companies have used all forms of programming languages to develop data acquisition software programs to help capture mission critical data. At the same time, numerous vendors have developed their own versions of data historians (e.g., OSIsoft PI, AspenTech IP21 and Rockwell Automation’s FactoryTalk Historian), which are used to acquire and store selected data from instrumentation and control system sources. For the first data acquisition best practice, it is essential businesses understand automation and control system sources to know which ones are right for your data acquisition needs. 1. Understand automation and control sources. Field instruments use a variety of sensors to convert physical properties, such as valve position, temperature, pressure, level, density, viscosity and more, to electrical signals interpreted via control systems. The control systems are the heart and brain of the automation process, so understanding how they fit in with data acquisition system requirements is key. The type of control system used depends on the complexity of the process being automated. The three most common control systems are: • Supervisory control and data acquisition (SCADA): A SCADA software tool is used to view, monitor and control process variable data, while providing a graphical representation of the process via human-machine interface (HMI) displays. • Programable logic controllers (PLCs): A PLC is an effective solution for handling data up to about 3,000 input/output (I/O) points. • Distributed control systems (DCSs): A DCS becomes the most effective solution for handling data when the I/O point count is greater than 3,000. Other common system platforms to consider when planning for a data acquisition system include: • Manufacturing execution systems (MESs)/manufacturing operations management (MOM) • Enterprise resource planning (ERP) systems
Figure 1: Data acquisition network connections. All images courtesy: Maverick Technologies
• Enterprise asset management (EAM)/Computerized management maintenance systems (CMMSs). These platforms can collect, generate, organize and manage data that will be valuable to the business through data-analytic tools. Figure 1 is an example of how data acquisition systems and tools are networked. 2. Understand connectivity and interfaces. Getting process automation data from the control system sources and written to the data historians requires connectivity via interfaces. Understanding the different types of interfaces needed for collecting and storing the required data is the second data acquisition best practice. The interfaces often reside on a separate server and are commonly referred to as “interface nodes.” Some of the most used interface types include:
OPC is an interoperable software interface standard that allows Windows programs to communicate with industrial hardware
data from a process data historian, relational database or a remote terminal unit (RTU). • UFL: Universal file and stream loading, known as PI UFL, was developed by OSIsoft for reading ASCII data sources and writing the data to the PI data historian.
3. Properly set up buffering. “Buffering” is an interface node’s abil• OLE for Process Control (OPC): devices. ity to access and temporarily store the OPC is an interoperable software collected interface data and forward it interface standard that allows to the appropriate historian. Properly setting up buffering is Windows programs to communicate with industrial the third data acquisition best practice. hardware devices. OPC servers are implemented in To effectively perform data acquisition, it is recoma client/server architecture. A control system uses a hardware communication protocol the OPC server soft- mended that buffering is enabled on the interface nodes. Otherwise, if the interface node stops communicating with ware program converts into an OPC protocol. a historian, the collected data is lost. Buffering application programming interfaces (APIs) (e.g., API Buffer Server • OLE for Process Control-Data Access (OPC-DA): [Bufserv] and PI Buffer Subsystem [PIBufss]) can read the OPC-DA, developed by the OPC Foundation, was data in shared memory. If a connection from a data source designed to eliminate the need for custom drivers/ to the historian server exists, the buffering application also connectors to communicate with various sources. The can send the data to the historian server. If there is no OPC-DA standard has had multiple revisions to keep connection to the historian server, it continues to store the up with the changes in data sources. data in shared memory (if shared storage memory is available) or writes the data to disk (if shared memory storage • OLE for Process Control Historical Data Access (OPCis full). When the buffering application re-establishes conHDA): OPC-HDA is used to retrieve and analyze historical process data for multiple purposes, optimization, nection to the historian server, it writes to the historian server the interface data contained in both the shared inventory control and regulatory compliance to name a memory storage and the disk. few. OPC-HDA servers typically are used for retrieving
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D ATA A C Q U I S I T I O N 4. Effectively plan backup and archiving. Establishing efficient and effective backup and archiving plans is the fourth data acquisition best practice. It is also important to understand the difference between backing up data versus data archiving. Data backups are used to restore data in case it is lost, corrupted or destroyed. Data archives protect older/historical information that is not needed for everyday business operations but is sometimes needed for various business decisions. =Backup strategies are key for protecting current/immediate data. Most IT professionals already have established best practices for backing up all the networked systems. This applies to systems inside and outside of firewalls. Protocol documentation is critical to backing up and restoring data when things do not go as planned. =Data archiving is the practice of moving data that is
no longer being used to a separate storage device. Data archives are indexed and have search capabilities to aid in locating and retrieving files. Several data backup software vendors (e.g., AWS Cloud Services, Rubrik and SolarWinds MSP) are addressing archiving in their current and future software releases. Several studies (e.g., SolarWinds MSP) are available online concerning backups versus archiving. 5. Properly set up scan classes. Understanding how to set up scan classes is the fifth data acquisition best practice. Historian interfaces use a code called a “scan class” to scan tags at different time intervals and schedule data collection. Scan classes determine a period of time in hours, minutes and seconds that tells the historian how often to collect the data. An interval and an offset define the scan class. The offset can be used to adjust specific time intervals. The offset helps avoid having two scan classes with the same frequency scanning at the same time. The commands used for scan classes include: • /f=SS (The frequency equals time in seconds) • /f=SS;SS (The frequency equals time in seconds with an optional offset time) • /f=HH:MM:SS (The frequency equals time in hours, minutes and seconds) • /f=HH:MM:SS,hh:mm:ss (The frequency equals time in hours, minutes and seconds with an offset time) • /f=00:01:00,00:00:15 /f=00:01:00,00:00:45 (Two scan classes with the same frequency but using offsets to avoid scanning at the same time). Knowing the data to be collected is essential to setting up the scan class. For example, data for temperature, level, pressure and flow will need a faster scan rate. Data for starting a pump or opening a valve may only need to be written when the state changes. Properly setting up the scan classes will ensure your system runs as efficiently as possible.
Figure 2: Dog treat manufacturer’s element/asset hierarchy.
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Applied Automation
6. Organizing data. A little over five years ago, the organization of collected data at the historian level was limited. As the amount of data being collected continued to grow, it became more difficult to find and group data in ways that made sense to the people consuming the data. Organizing data is the sixth data acquisition best practice. Various software programs make it easier to organize data. The most commonly used PI Server and its asset framework (AF) component make the organization and sharing of data much easier. The AF component can integrate, contextualize, refine, reference and further analyze
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D ATA A C Q U I S I T I O N data from multiple sources and even external relational tant to approach the use of metadata as an extension of the databases. Users can create a hierarchy of elements/ live attributes being collected. assets and all their attributes including metadata. For example, a major dog treat manufacturer has four 8. Obtain data from the edge. Understanding the facilities that manufacture chicken-, beef- and pork-flaadvantage of obtaining data from the edge and knowing vored dog treats. All four facilities also have the same type how to obtain it is the eighth data acquisition best practice. of equipment, raw material storage, blenders, presses, Collecting data from the edge is not a new concept, but it ovens and packaging. Figure 2 gives a high-level view is more affordable than ever. Edge computing is a way to of the dog treat manufacturer’s element/asset hierarchy. streamline the flow of traffic from IIoT devices and provide Setting up an AF structure and perreal-time local data analysis. forming the task properly requires Edge devices provide an entry Edge computing is a individuals who have a high-level point into an enterprise core netunderstanding of the elements/ work. Some of the latest edge way to streamline the flow assets within the organization. devices have the historian databasAttributes for the assets should be es embedded for collecting data for of traffic from IIoT devices added at the asset detail level. For synchronization via multiple ways of raw material storage tank CRM01, connecting. New small form-factor and provide real-time you may have the following: devices can be purchased for as little as $299. Data from sensors in local data analysis. • Level the field is written to edge devices • High level alarm and then written to the edge • Temperature infrastructure. From the edge infrastructure, the data is • Cooling on/off replicated to the centralized data center (typically in the • Tank capacity cloud) at a low roundtrip speed of 5-10 ms. Data from the • Inlet valve open/closed edge brings information from the most remote areas of • Discharge valve open/closed the business to the heart of the data collection system at • Product name. near real-time speed. Having as much real-time quality data available as possible for decision making will keep Metadata from other sources can be set up as well: businesses competitive.
Valuable data leads to success
• LOT number • Date received. 7. Metadata use. Understanding the effects and use of metadata is the seventh data acquisition best practice. “Metadata” is defined as “a set of data that describes and gives information about other data.” Using software-coded connectors, access to data from all types of data sources is possible. Having the ability to link metadata to assets provides some unique ways to collect, analyze, visualize and report on process conditions. Linking data from MES, ERPs, or even maintenance planning sources will make the available information even more relevant to users. Generating templatized displays will allow a user to visualize similar assets with just a single mouse-click. These content-rich displays have process-related assets and attributes, as well as various metadata details. Now the displays can show not only what is being monitored, but also other tasks, such as “time until next maintenance due” and “name, model, date of installation and runtime hours.” Having such a high level of detail makes for better informed, data-driven business decisions. Businesses that think through their processes and identify every piece of data that can contribute to their success, and work toward acquiring that data, will be the most successful. It is impor-
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To ensure historized data remains relevant year after year and the right people can access it, consider these eight best practices as the most practical means to help determine data acquisition objectives and strategies. Also, consider consulting a third-party automation solutions provider to help implement a quality, high availability data acquisition system. They can provide a holistic view of data acquisition systems and software, while helping review the various vendor options on the market, including historians and data-analytic tools. Today’s data acquisition technologies provide the opportunity to improve asset utilization and realize the benefits of Big Data and enhanced production processes. Achieve business gains and stay ahead of the competition with the most dependable data acquisition system and software in place. Brian E. Bolton is a consultant for MAVERICK Technologies. He has more than 35 years of experience in chemical manufacturing, including more than 20 years involved with the OSIsoft PI Suite of applications, quality assurance, continuous improvement and data analysis. Maverick Technologies is a member of the Control System Integrators Association (CSIA).
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LIFE
If you have a smart automatic water, gas, electricity, or heat meter in your home. If you have an electronic toll collection transponder, tire inflation sensor, or emergency E-CALL system in your car. If you have a GPS tracking device on your trailer, container, or cargo. If you have wireless sensors, controls, or monitors in your factories and plants. If you use electronics with real-time clock or memory back-up in your office.
If you have never heard of Tadiran Batteries, it is only because you have never had a problem with our products powering your products. Take no chances. Take Tadiran batteries that last a lifetime.
* Tadiran LiSOCL2 batteries feature the lowest annual self-discharge rate of any competitive battery, less than 1% per year, enabling these batteries to operate over 40 years depending on device operating usage. However, this is not an expressed or implied warranty, as each application differs in terms of annual energy consumption and/or operating environment.
Tadiran Batteries 2001 Marcus Ave. Suite 125E Lake Success, NY 11042 1-800-537-1368 516-621-4980 www.tadiranbat.com
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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. Visit us at MODEX 2020 – Booth #4419 | March 9-12 | Atlanta, GA
As easy as that.