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Contents A4 Getting stronger process readings Getting an accurate process variable measurement depends on many factors, but it must begin with the right instrumentation.
A10 Three phases of industrial digital transformation Manufacturing, packaging, and logistics companies are unlocking new potential through digital transformation with the power of the Internet of Things (IoT) and advanced analytics.
A4
C OMMENT Enhancing automation systems
E
Jack Smith Editor
ven though they are about different topics, both articles in this issue are about enhancing automation systems. Regardless of the medium being controlled—flow, pressure, temperature, level— every control scenario begins with the sensor. There is no way to close the loop without it. The cover story in this issue is about how to get stronger readings from process instrumentation. Although its focus is primarily on measuring pressure, the concepts apply across much of the range of process instrumentation. The author explains in detail how pressure sensors develop signals and the issues that can impede that process. In addition, she also explains the role and operation of the transmitter. “The transmitter takes the raw analog signal from the sensor and cleans it up. Depending on the type of sensor, it might generate a resistance, voltage, capacitance, or some other type of signal in response to the process variable. The transmitter must
measure the signal and compare it against the desired range according to how the device is configured.” The author also discusses what to do with instrumentation measurements from the transmitter. “It may be something as basic as a remote display with simple alarming functions, or a more elaborate platform such as a programmable logic controller (PLC) or a distributed control system (DCS).” The other article in this issue focuses on how manufacturing, packaging, and logistics companies are unlocking new potential through digital transformation with the power of the Internet of Things (IoT) and advanced analytics. The author proposes three phases to unlocking full digital transformation: visualizing through factory connectivity and data integration; forecasting using predictive production modeling and responsive machine design; and self-regulating data-driven manufacturing and ongoing transformation.
ON THE COVER Rosemount wireless pressure gauges use a sophisticated sensor with transmitter electronics to provide the capabilities of a full
electronic transmitter, but in an analog gauge form factor with a traditional needle display. Courtesy: Emerson Automation Solutions
Applied Automation December 2018
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P R O C E S S I N S T R U M E N TAT I O N
Getting stronger process readings Getting an accurate process variable measurement depends on many factors, but it must begin with the right instrumentation. By Megan Wiens Emerson Automation Solutions
C
onsider this typical situation: a process unit in a chemical plant needs a pressure reading from a reactor. The unit’s automation system uses the reading to help determine reaction rate, and the operators in the control room want to see it on their human-machine interface (HMI) screen. If the reading is lost, the process must be shut down. How should the plant’s instrumentation engineer make sure the reading is correct and always available to the operators and the automation system? For the purposes of this article, the focus is on measuring pressure, but the concepts apply across much of the range of process instrumentation. Think for a moment about what must happen to get the reading from one end of the chain to the other:
• The process fluid must have a path to reach the sensor. • The pressure sensor must be deflected in a measurable way in proportion to the fluid pressure against atmosphere. • An electrical element must convert the deflection into an analog signal. • The transmitter must clean up the raw signal, scale it, and transmit it using a prescribed format, either analog or digital. • Wires, or perhaps radio, must carry the signal to the input/output (I/O) card of the automation system. • The automation system must convert the signal into appropriate engineering units for display and use the data in whatever equations it is performing for the larger control effort. All of those elements must work correctly to capture the right value in real time to support control and monitoring. Let’s pull on the chain a little and look for potential weak links.
Through to the sensor
Figure 1: The sensor diaphragm is the only moving part of the measurement chain. It must deflect in a repeatable and reliable way in response to changing pressures. All images courtesy: Emerson Automation Solutions
A4 • December 2018
Applied Automation
The sensor itself is the one moving part of the entire picture. It must flex in response to the pressure in a predictable and consistent manner. Usually, it involves a metallic isolator diaphragm with a strain gauge, or the movement is measured through capacitance (see Figure 1). For a strain gauge, movement must be linear enough to deflect the same amount for the same degree of pressure change, and return to its original form when the pressure is relieved. It must be sensitive, but at the same time able to withstand pressures far higher than its reading range. For the sensor to be displaced, there must be a mechanism to allow the process fluid
to press against it, which means there must be a process connection. The process fluid must have a path to the sensor, or the pressure gets transmitted via an uncompressible intermediate fluid, in which case there will be two isolator diaphragms with a fill fluid trapped in between. There also may be an impulse line so the sensor can be mounted some distance from the actual process equipment. The path to the sensor or isolator diaphragm must be clear and unimpeded. Any blockage can slow response or decrease accuracy. Some transmitters have the ability to determine when an impulse line is plugging and can alert operators of the problem forming. Slugs of gas in a liquid line, or viceversa, can cause reading inaccuracy. Impulse lines should be clear and bled, although it can be beneficial to have some condensate in a steam pressure line. The physical and mechanical elements of the reading chain are pretty well understood and established. Sensor technology has not changed much over recent years, but there have been more dramatic advances in the next stages.
The transmitter might even have a local display to show the primary variable in appropriate engineering units, and perhaps secondary variables such as temperature. Ultimately, the final output is the result of calculations and/ or look-up tables to scale the reading according to the transmitter’s configuration. The development of more sophisticated electronics has made this much easier, often without users recognizing the improvements. This in itself is impressive, but only part of the picture. Today’s transmitters have additional capabilities such as self-diagnostics. While the main signal processing functions are going on, there also are internal functions evaluating the quality of power coming into the transmitter, the condition of the internal electronic components, sensor functionality, and other items, including plugged impulse lines as just mentioned. If a problem is present or developing, the diagnostics can send a warning via a digital wired or wireless protocol.
The busy transmitter
Getting to the I/O point
The transmitter of a process instrument has a lot to do, so much that we tend to refer to a complete instrument as a transmitter. Technically though, the transmitter is a specific part of the larger unit, with the sensor being the other main part. The transmitter takes the raw analog signal from the sensor and cleans it up. Depending on the type of sensor, it might generate a resistance, voltage, capacitance, or some other type of signal in response to the process variable. The transmitter must measure the signal and compare it against the desired range according to how the device is configured. This can be an involved process (see Figure 2). For example, the transmitter often needs an internal temperature sensor because the output of the pressure sensor is affected by temperature in addition to pressure. Additional corrections must be made for any nonlinearity of the sensor. All of these elements, and more, must enter into the signal processing.
Somewhere the processed electronic signal must be turned into something a human being can understand. If the reactor pressure is 110 psi, it must be converted and displayed as that value or 7.59 bar or whatever the operators need. The local display on the transmitter is handy for assisting with configuration and troubleshooting, but there are few applica-
Figure 2: Today’s transmitter is a small computer capable of highly sophisticated calculations, able to run without interruption for many years.
Figure 3: Many transmitters have an on-board display to show the current variable value and for configuration.
Applied Automation
December 2018
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P R O C E S S I N S T R U M E N TAT I O N
Figure 4: A WirelessHART network can form a sustainable mesh with fewer than 10 instruments.
Retro design with today’s sophistication
M
any users like the functionality of a traditional pressure gauge, but not its fragile Bourdon tube, finicky mechanism, and instability. Some wireless pressure gauges use a sophisticated sensor with transmitter electronics to provide the capabilities of a full electronic transmitter, but in an analog gauge form factor with a traditional needle display (see Figure 5). A small stepper motor moves the needle in real time. Add basic diagnostic functions and WirelessHART communication, and it checks the most-wanted feature boxes without the problems of traditional pressure gauges.
A6 • December 2018
Applied Automation
tions where a human will be close enough to the transmitter to see it on a regular basis and react as required (see Figure 3). Some sort of automation system invariably enters into the picture. It may be something as basic as a remote display with simple alarming functions, or a more elaborate platform such as a programmable logic controller (PLC) or a distributed control system (DCS). Traditionally, this involves wiring to transmit a 4-20 mA analog plus HART signal or digital fieldbus data, but WirelessHART now is being used quite frequently. For traditional users with the wired analog approach, there are different ways in which the automation system can process what it’s getting from the transmitter. Some can read HART natively, but if the I/O only has the ability to read the analog signal alone, all the other diagnostic information will be stranded in the transmitter. It can warn of problems, but the system won’t be able to hear it. One way to address this issue is by adding a WirelessHART converter to the transmitter. This allows
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P R O C E S S I N S T R U M E N TAT I O N the 4-20 mA signal with HART imposed to still Figure 5: Rosemount wireless pressure gauges be transmitted to the automation system, use a sophisticated sensor with transmitter with an additional WirelessHART signal electronics to provide the capabilities of transmitted elsewhere, such as an asset a full electronic transmitter, but in an management system, with all diagnostic analog gauge form factor with a tradiinformation intact. tional needle display. Some of the most sophisticated diagnostic capabilities extend beyond the device itself and examine the larger control loop. Where smart I/O is available, the diagnostics can detect and report conditions capable of distorting the reading and creating a false value. This warns operators of situations that appear to be correct but are wrong. As straightforward as wiring is, it often emerges as the weakest link. In a traditional wired environment, the path from the actual transmitter to the I/O card of the DCS easily can include multiple marshalling cabinets, hundreds of feet of cable and perhaps 20 terminations. If the wiring is 15 to 25 years old, which is certainly not uncommon in Some of the most today’s facilities, the insulation is probably getting brittle and terminal sophisticated diagnostic strips are quietly oxidizing. If left undisturbed, these connections can capabilities extend beyond the work for a long time, but if cable bundles are moved around to solve a device itself and examine problem or if marshalling cabinets are opened for troubleshooting, problems cluster of wireless transmitters the larger control loop. can develop. For example, shorts and can establish a sustainable signal drop-outs can occur, disrupting network and support a variety the control room and automation system. of instruments that do not depend on legacy wiring, or Fortunately, new wiring and I/O systems can drastieven need to interface with the DCS using conventional cally reduce the number of terminations while adding I/O cards (see Figure 4). native HART connectivity. Moreover, using WirelessHART Strengthening the links can reduce the terminations to perhaps two or even zero. Particularly when working in legacy environments, It’s important to know the weak links of a system, but WirelessHART can have a higher reliability rating than building strong links is just as important. In many respects, wired networks. having the best possible transmitter is the most important element. If the source of data is not reliable and accurate, Sum of the parts the best infrastructure in the world won’t make it any better. The instrumentation available today from a variety of As can be seen, all the elements must work together for suppliers is sophisticated, stable, accurate, and reliable. If effective measurements. Any part performing badly can used in an environment capable of interacting with it fully, impede communication or cause it to break down altoit can provide secondary variables and diagnostic informagether. Some companies try to solve the situation by treattion in addition to its primary variable. ing the symptoms rather than root cause. If a critical value As companies rely more on automation in a growing can’t get through to the DCS, the solution may be adding variety of ways, reliable instrumentation is foundational. a redundant instrument on the same faulty infrastructure. It might improve the chances of data getting through, but it Megan Wiens is a global pressure product engineer is like a bandage. for Emerson Automation Solutions in Shakopee, Minn., This is not always the best approach, but sometimes it where she is responsible for advanced diagnostic capais a practical one. However, adding a redundant path via bilities across the Rosemount pressure portfolio. In this WirelessHART is a much better option. If it isn’t possible role, she works to implement product solutions that to upgrade existing infrastructure, simply adding another improve plant safety, increase process efficiency, and path subject to the same problems is not the best option. Even if there is no existing WirelessHART network, a small enhance process insight.
A8 • December 2018
Applied Automation
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D i g i ta l t r a n s f o r m at i o n
Three phases of industrial digital transformation manufacturing, packaging, and logistics companies are unlocking new potential through digital transformation with the power of the internet of things (iot) and advanced analytics. By Daniel Repp Lenze Americas
T
he digital transformation of the manufacturing industry is well underway but what that means for plant engineers, specifically, is still a little unknown. For many companies it is unclear how to best implement the new digital technologies and how to determine which implementation partners will be the most reliable and experienced. However, two things are clear: digitalization is critical if companies want to stay competitive in the future, and automation plays a key role.
The goal is no longer about just automating the movement of physical product, but fully automating the data as well. This requires moving from manual, humangenerated information workflows to a more real-time process. Digital transformation is about digitalization, networking, process analysis, and deep information automation. Transformation is the right term. While it won’t be easy, digital transformation has the potential to unlock formerly unattainable benefits for all aspects of manufacturing from a machine builder to factory floor to end customers. There are three areas of potential to unlock full digital transformation, many of which are already well within reach.
Figure 1: Using intelligent, networked parts allows data to come directly out of the machine, eliminating human error and enabling a much faster flow of information and business intelligence. All images courtesy: Lenze Americas
A10 • December 2018
Applied Automation
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ith the rapid increase in both plant floor computers and sophisticated electronics, harmonics are getting a lot of attention. Chris Jaszczolt of Yaskawa’s Matrix drives management team looks at the IEEE 519 standards as well as the practical challenges of harmonics:
Q: Harmonics have always been an issue for manufacturers, but it seems to be a more critical issue in today’s plants. Why? JASZCZOLT: Electric motors make up
over 45% of the world’s electrical energy usage. In the past, only a small portion of a pant used drives to control their motors. More and more of these motors are being controlled by drives for their energy savings and process control benefits. Having more drives on a system means they will have a bigger harmonic impact to the overall system. Harmonic currents lead to conductor heating, transformer heating and sizing issues, power factor reductions, and lower efficiency. Also, high harmonic currents leads to the distortion of the input voltage, which is what the recommended practices outlined in IEEE 519 is trying to mitigate. More recently, utility companies are starting to fine their customers for high harmonic currents, citing non-compliance with IEEE 519.
Q: Is there such a thing as an IEEE 519 compliant device? JASZCZOLT: Non-linear loads like drives are neither compliant nor non-compliant with IEEE 519. IEEE 519 is a “recommended practice to be used for guidance in the design of power systems with non-linear loads.” In other words, the entire system dictates whether or not a system is compliant. However, it can be stated that a drive facilitates IEEE 519 compliance.
This means that the current harmonics at the input of the drive is very low, usually less than 5% iTHD (total harmonic current distortion) at rated power. If these drives are replacing an existing drive system, they will reduce total harmonic current draw for the system. For new installations, using drives that facilitate IEEE 519 compliance virtually guarantees that the new device will not be the cause to a system non-compliance. In other words, they will add much more good load than bad (harmonic) load to the system, which will reduce the percent harmonic content of the overall system. However, adding these devices does not guarantee system compliance because they do not correct harmonic content of the pre-existing system. To obtain system compliance, the entire system should be analyzed to determine what devices will need harmonic mitigation to bring the entire system into compliance.
Q: Where should plant managers begin to look for solutions to address harmonic concerns?
JASZCZOLT: All drives should be looked at to see if they can benefit from harmonic mitigation. The focus should be on the higher horsepower drive loads since they will have the biggest impact on total harmonic distortion for the system. Smaller horsepower drives may not need high level mitigation, since they have little impact to the overall system distortion levels. Typically smaller horsepower drives can benefit from a simple, low cost addition of an input AC line reactor or DC reactor. Adding a reactor can improve harmonic content from over 80% iTHD to less than 40% iTHD at the input of the drive. Most large horsepower drives already have reactors built into the drive, which means higher level harmonic mitigation solutions would be needed to reduce the total system harmonic distortion levels. Finally, be aware that drives are not the only non-linear load on a system. Electric ballasts (lighting), arc furnaces, and all other switch mode power supplies (servers, computers, etc) also draw non-linear current and will affect total system harmonic distortion levels.
Q: What tools are available to assist plant managers in identifying and managing their harmonics issues? JASZCZOLT: Many drive manufacturers understand the need for harmonic mitigation. Many submittals require a harmonic report on the drive before being quoted. Therefore, these drive manufactures offer harmonic estimation software to provide estimated harmonic content of a specific device or an entire system. Since the true harmonic content is affected by more than just the load (wire type, wire size, wire routing practices, grounding practices, etc.), these tools can only offer an estimate.
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D i g i ta l t r a n s f o r m at i o n
1.
Visualizing: factory connectivity and data integration Today, the information flow at many plants is still manual or semi-manual. Machine operators or engineers collect data on paper or mobile devices—about things such as how long it takes to prepare a machine for production, to change from status A to status B, or to transfer part X to part Z. That information is then loaded into a computer program that can assess the data. This process is light years ahead of where we were just two decades ago, but still takes significant time and effort, and there is the undeniable risk of human error in the process—both accidental and intentional. How do we get from the analog, linear model of the past and reach the digital, platform-based model of the future? The Internet of Things (IoT) and full-factory connectivity are tools that will help enable the digital transformation. Using intelligent, networked parts means data can come directly out of the machine, eliminating human error entirely and enabling a much faster flow of information and business intelligence (see Figure 1). It also relieves operators and engineers from having to collect data manually and enter it into the existing process software themselves. Instead, they can focus on their core work. With a more connected and integrated data stream, information can be pulled together from different process steps or from different parts such as a motor or gearbox or from entire production lines, which may contain components and machines from various manufacturers. The data can then be used to create a complete representation of the existing production process—spanning machines, plants, and even production sites.
Figure 2: Capturing and understanding the existing behavior of a machine, machine line, or a site is the foundation on which more advanced analytics are built. This provides visibility into part, machine, and system trends.
2. Forecasting: predictive production
modeling and responsive machine design
Capturing and understanding the existing behavior of a machine, machine line, or a site is only a small sliver of what is possible. However, it is the foundation on which more advanced analytics are built that provide visibility into part, machine, and system trends. These trends include predictive models to reduce or eliminate unexpected downtime or unforeseen problems (see Figure 2). Instead of simply capturing linear values to assist in visualizing what is happening at any moment, the system captures complex, nonlinear developments or trends that forecast problems. Warning systems can then be set up to enable intervention in the production process before critical values such as impermissible quality factor of overloading of a machine occurs. Advanced analytics often combine factory-level data with other data streams such as business administration information or weather data to account for external factors that can impact production. Factors such as ambient temperature, humidity, differences in raw materials, or shift management can easily be added into the digital process. The full potential of the IoT only can be realized if there is a new level of coordination within a company, including changes to the work environment and the creation of a collaborative workforce. It also requires OEMs, suppliers, data scientists, and engineers to work collaboratively, a development which has resulted in additional benefits.
Applied Automation
December 2018
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D i g i ta l t r a n s f o r m at i o n
3. Self-regulating: data-driven manufacturing and ongoing transformation
One step beyond predictive lies total automation, in which systems adjust themselves based on forecasting models without manual interventions. Such systems rely on innovative and ultra-efficient methodologies such as statistical process control to optimize production on the fly by tweaking various aspects that, to date, have been onerous, manual adjustments. For example, changing the setpoint values or even the whole process sequence of a machine could be done without any human involvement. Additionally, the ability to gain an abundance of critical information quickly through Cloud computing will
One step beyond predictive lies total automation, in which systems adjust themselves based on forecasting models without manual interventions.
change how everyone within the industry functions, from suppliers to end users. The more machines and systems that are analyzed, the more collective data that can be used to identify which changes to a system or a machine, or even a particular industry, might have the most impact. In the foreseeable future, we could see computergenerated trends and predictions flowing directly to the OEM so machines can be improved in real time, resulting in a stable, high-speed production process based on the optimal use of the machine. Data-driven manufacturing is the future. Companies can only reach full digital transformation and realize all the benefits if they’re willing to automate their information data flow just as well as they automate their production, printing, or packaging lines. Daniel Repp is a business development manager for automation solutions at Lenze Americas. In 2000 he began working in the controls technology department for the company’s German headquarters, and in 2011 relocated to China as a business developer for automation solutions. Repp moved to the U.S. in 2015 to begin working for Lenze Americas.
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