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INSIGHTS
Remote monitoring and data visualization
T
Jack Smith Editor
he cover story in this issue of AppliedAutomation examines the progression of remote monitoring and describes previously unobtainable benefits. The author writes, “The Industrial Internet of Things (IIoT) is one way smarter field devices are changing how users can be informed about remote conditions. As the cost of hardware has come down, more computing power can be deployed closer to the field, which means simple data monitoring can be enhanced with advanced analytics and displayed anywhere.” The author tracks the progress of remote access from programmable logic controllers (PLCs) and human-machine interfaces (HMIs) through Ethernet, wi-fi, internet access and mobile data, then virtual private networks (VPNs), cloud connectivity and finally to edge processing. The author provides three applications as examples of how edge processing can enhance remote monitoring.
The other story in this issue explores ways organizations can create, store, move and retrieve data as well as ways to see, perceive and interpret it — in other words, data visualization. According to the author, three data visualization trends are increased cloud connectivity, integrated predictive maintenance and connected field service, and diversified user interfaces (UI). The author writes, “For data visualization specifically, cloud connectivity can provide the costeffective ‘heavy lifting’ of processor-intensive analytics, compared to onsite alternatives, so users are able to visualize larger amounts of data from multiple sources to help expedite decision making.” The author also provides examples of data visualization tools for predictive maintenance and different ways users interact with the data. The author writes, “Advances in technology have resulted in multiple different ways data can be accessed, viewed and even acted upon.”
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Contents A6 Take remote monitoring to the edge Advanced edge controllers enable remote monitoring techniques to supplement standard industrial automation practices
A12 Data visualization applications and trends
A6
There are as many ways organizations can create, store, move and retrieve data as there are ways to see, perceive and interpret it
ON THE COVER Edge controllers and the IIoT support remote monitoring by deploying more computing power and communications abilities in the field. Courtesy: Emerson
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Applied Automation April 2020
•
A5
REMOTE MONITORING
Take remote monitoring to the edge Advanced edge controllers enable remote monitoring techniques to supplement standard industrial automation practices By Kyle Hable
• Wider visibility enables new insights • Improved collaboration with original equipment manufacturers (OEMs).
Emerson
I
The most fundamental result of remote monitoring is it ndividual consumers have embraced all sorts of remote extends the visibility of users beyond their physical locamonitoring video and mobile applications as they have tion, which in turn means people can see more. For operbecome available over the last decade. Improved techating companies with many sites, some widely dispersed nologies applied to cameras, wireless networking and drones have enabled many types of personal use. Now, geographically, remote monitoring gives a small maintenance department additional reach, and makes it more many of these technologies have made their way into convenient for experts to be engaged as needed. From a the industrial automation space and are enabling a host of practical standpoint, reduced personnel travel saves time remote monitoring advances. and money, and makes it easier to The result is a new class of advanced edge controllers that The most fundamental result attract and retain highly skilled labor. Also, any technology that minimizes can provide any application with worker exposure to any form of hazinnovative remote monitoring capaof remote monitoring is it ard is welcome. bilities. This article examines the extends the visibility of users Many manufacturing and process progression of remote monitoring operations can be characterized to a and describes some previously beyond their physical locadegree by KPIs. Remote monitoring unobtainable benefits. is an ideal solution for collecting the tion, which in turn means Remote monitoring data required to create KPI calculafor any industry tions, and then transmitting this data people can see more. or the resulting KPI calculations to a The Industrial Internet of Things supervisory level so users can take (IIoT) is one way smarter field action. Some local responses will be quick, such as adjustdevices are changing how users can be informed about ing a setpoint for more efficient operation or dispatching remote conditions. As the cost of hardware has come maintenance personnel to solve a problem. down, more computing power can be deployed closer Other times, the information supplied by remote monitorto the field, which means simple data monitoring can be ing will undergo more extensive processing (either preenhanced with advanced analytics and displayed anyprocessing at the edge or computations in a supervisory where (see Figure 1). system) and analysis to determine longer term trends. For example, progressively increasing power consumption can There are many remote monitoring benefits for industrial signal equipment wear due to increased friction in rotating users including: equipment caused by impending bearing failure. While new automation systems should be designed with • See where you cannot be remote monitoring in mind, much of the existing equipment • Personnel can monitor more in service can benefit when remote monitoring is added. • Reduced personnel travel An important result of remote monitoring initiatives is when • Reduced need for personnel to enter hazardous areas the wider visibility, such as across many sites or types of • Better operation through key performance indicator equipment, empowers new insights never before possible (KPI) presentation when these targets were observed on a one-by-one basis. • Quicker reaction time This occurs when many assets of a similar type, such • Enhance simple monitoring with advanced preprocessas hundreds of machines deployed worldwide, can be ing, computation and analysis observed and compared to yield best practices for opera• Monitoring can be added onto existing systems or built tion and maintenance. into new systems
A6 • April 2020
Applied Automation
Figure 1: Edge controllers and the IIoT support remote monitoring by deploying more computing power and communications abilities in the field. All images courtesy: Emerson
Another key opportunity involves using edge controllers and remote monitoring technologies to provide advanced collaboration between end users and OEM machine builders, enabling an improved customer service model and new business models not possible before. Possibilities include: • • • •
Online updates and upgrades Digital site service agreements Prescriptive field service deployments Timely consumables replenishment.
Individual machines operating as part of a complete factory can take advantage of this service delivery model. OEMs can update software configurations and enable optional features in coordination with the end user, and without travelling to site. Digital site service agreements may include attractive features such as an extended warranty if the OEM is able to monitor equipment performance. This holistic approach to manufacturing can include the ability to deploy field service personnel when trouble is detected and quickly enough to avoid downtime, as opposed to classic calendar-based maintenance. Consumables can be delivered automatically on an as-needed basis, so they are always on hand for customers performing their own maintenance.
OEMs can update software configurations and enable optional features in coordination with the end user, and without travelling to site. Service organizations can even use this approach to accommodate third-party machines.
Industrial remote access progress Until programmable logic controller (PLC) and humanmachine interface (HMI) digitalization efforts became commonplace decades ago, industrial monitoring efforts were local and mostly manual. Experienced operators would look, listen and feel to interpret how machinery was working, and if failure was imminent. Once PLCs and HMIs were employed, it became possible to add improved monitoring and diagnostic capabilities. However, these informative features remained relatively local, and any kind of remote access connectivity was slow, difficult to manage, insecure and expensive — or all of these. For many years, modems or dial-out annunciators working over the “plain old” telephone systems were a
Applied Automation April 2020
•
A7
REMOTE MONITORING Edge processing advantage Edge controllers basic means of remote monitoring. Eventually, networking technoloEdge controllers combine classic gies such as Ethernet, wi-fi, internet control with cutting-edge analytcombine classic access and mobile data improved ics and other capabilities. They to a sufficient level for enabling include a real-time operating sys control with cuttingimproved connections. tem with a general-purpose operFirst, users gained the ability ating system, all housed in one edge analytics to use their laptops and vendor package industrialized for installasoftware to connect over a site tion in the field right next to operand other capabilities. network to PLCs and HMIs to visuating equipment (see Figure 2). alize operation, and even change The real-time operating system programs. Incorporating virtual private networks (VPNs), provides deterministic control much like conventional already commonly in use with most company information PLCs, while the general-purpose operating system uses technology (IT) departments, made it possible for these Linux to add many types of advanced computing and same connections to be made from remote locations via communications capabilities, like a standalone PC. The the Internet. Advances in mobile electronics and modern real-time and general-purpose operating systems funcweb technology brought remote visualization to handheld tion in an independent manner, but also can securely devices. Cloud connectivity and mobile apps reduced the communicate for cooperative applications. complexity of implementing remote connections. For existing sites, an edge controller can be added as The latest industrial technology advances have circled a supervisory data concentrator for many other automaback to the factory floor. Instead of incrementally upgradtion platforms. As an industrial product, it is able to coming PLCs and HMIs, a new category of edge controllers is municate with these systems using standard protocols, available to supersede control, visualization and connectiv- and even hardwired input/output (I/O) signals. The modity features of traditional automation — and improve upon ern PC-like aspects of an edge controller enable it to take it with new edge-based processing and analytical options. things a step further because it can be used for advanced calculations and analysis on low-latency data, right at the industrial edge where the data is sourced. Processing data at the edge allows analytics to be performed on full fidelity data with no compression. Results are produced quickly, allowing immediate action, and cybersecurity concerns are allayed because the data remains in the edge controller. For further analytics, an edge controller can communicate data up to higher level systems. It also can host web pages to play a key role as part of an HMI system, and perform many other tasks, concurrently without affecting real-time control, which remains separate. This separation extends to external communications, as the real-time controller and the Linux platform each have their own Ethernet port. New and retrofit installations can move beyond data processing, using the edge controller as a complete control, computing and communications platform. In addition to the capabilities described above, edge controller automation can act on computational results and play a more interactive remote monitoring role. Edge controllers thus unlock many new remote monitoring possibilities, as shown in the following applications. Drone deployment. For widely dispersed operations, such as well head sites or pumping stations, several edge controller features come into play for advanced remote monitoring. At remote sites, an edge controller Figure 2: Combining the real-time deterministic control of a can used to evaluate and monitor trouble signals, and it PLC with the advanced computing and communications of a PC, can be integrated with onsite video cameras for handling Emerson’s Edge Controllers provide a comprehensive platform for motion triggered events. Notifications can be relayed industrial remote monitoring. to supervisory systems via an appropriate lightweight A8 • April 2020
Applied Automation
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REMOTE MONITORING
Edge controllers can be used to directly control many types of field equipment, or they can be installed in parallel with existing systems.
Figure 3: Edge controllers and remote monitoring enable wideranging visibility, performance tracking and diagnostics spanning a fleet of equipment at one or more sites.
network transport protocol, such as messaging queuing telemetry transport (MQTT). Edge controllers also can preprocess these trouble and event signals to introduce a level of protection against false trips. As an example of an advanced application, an edge controller could automatically deploy a drone when trouble is detected, using it to investigate the trouble location. Any detailed information gathered can be relayed to operators so they can better identify the problem, and then respond quickly and effectively. Multisite food and beverage producer. Industrial processing and manufacturing companies with multiple similar sites are common. Many food and beverage producers have automated continuous processing systems and OEM packaging equipment at many different regional locations (see Figure 3). Each site has local operations and maintenance personnel. Some manual methods of problem tracking are possible, but this creates a lot of overhead. Because the sites operate in an independent manner, they may all be expending effort to solve similar problems. One such company was experiencing problems with pallet handling equipment at many locations. Each site was individually investigating problems such as out-ofspecification pallet styles, failures of certain equipment or component brands or even procedural issues such as operators stacking the pallets too high.
A10 • April 2020
Applied Automation
This company installed an edge controller at each site to provide centralized remote monitoring of the key trouble indicators. This enabled them to determine commonalities among sites and pinpoint root causes, with results communicated to each site for improved operations. Power generation trash shredders. A power generation facility operates heavy trash shredding equipment, which tends to show initial signs of needing service in the form of increasing electrical current draws and vibration. Edge controllers can be used to directly control many types of field equipment, or they can be installed in parallel with existing systems. The key is an edge controller’s exceptional ability to act as an information gathering and remote monitoring platform. In this case, the end user was not directly using the information. Instead, the equipment OEM incorporated edge controllers for fleet monitoring to gather real-time data and track faults, initiate SMS and email alerts for dispatching service personnel. This enabled conditionbased maintenance, and even informing their design groups in support of product improvement. Other OEMs can offer remote monitoring as a valueadded service for end users to reduce downtime and improve efficiency. Some OEMs are now providing machines as a service, charging users based on a machine’s output, instead of selling machines. In these cases, remote monitoring is essential to maintain a high level of throughput, and to closely monitor production levels.
Final words Edge controllers are already available to perform any type of traditional industrial automation, while adding contemporary computing features. These industrial edge controllers are uniquely positioned to provide advanced remote monitoring capabilities, helping end users solve problems while saving time and money. Kyle Hable is a product manager responsible for integrating and advancing IIoT and edge technology across Emerson’s machine automation solutions product portfolio. He has spent his entire career connecting data and embedded things to Ethernet networks, working hands on with both IT and OT customers implementing custom and standard solutions across a variety of technologies and industries.
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D ATA V I S U A L I Z AT I O N
Data visualization applications and trends There are as many ways organizations can create, store, move and retrieve data as there are ways to see, perceive and interpret it By Melissa Topp ICONICS
A
s we progress into 2020, a milestone year for prognosticators of years past and present-day futurists, the state of data visualization continues to evolve, as expected. In 2020, there are as many ways organizations can create, store, move and retrieve data as there are ways to see, perceive and interpret it. Currently, there are three growing trends in data visualization, including: • Increased cloud connectivity • Integrated predictive maintenance and connected field service • Diversified user interfaces (UI).
Seeing further through the cloud Many organizations already have realized the value of adopting a cloud-based data platform. Among these benefits are increased scalability (due to growing cloud platforms such as Microsoft Azure), reduced onsite hardware obsolescence and expanded connectivity due to the ability to use open standards such as OPC UA, BACnet, SNMP,
Modbus, web services and/or classic OPC tunneling, as well the ability to ensure secure communications via a combination of AMQP, MQTT, REST, WebSockets and TLS encryption with x.509 certificates. For data visualization specifically, cloud connectivity can provide the cost-effective “heavy lifting” of processor-intensive analytics, compared to onsite alternatives, so users are able to visualize larger amounts of data from multiple sources to help expedite decision making (see Figure 1). Additional integrated tools, such as those geared toward business intelligence (BI), help provide a cohesive view of an organization’s entire data system, since such systems can be diverse, comprised of multiple components and may use their own data storage and interfaces for access to stored data (e.g., web services, databases, historians, etc.). Analytics/BI tools help to correlate multiple datasets while allowing for queries via a common set of filters and/ or parameters. Through these tools, the collected data can then be visualized in a normalized way, providing logical “shaping” and better grounds for comparison for end users. There are many applications and associated industries for cloud-connected data visualization (see Figure 2). One scenario is the global manufacturing enterprise, where multiple geographically dispersed facilities can provide their data to a centralized visualization tool via the Industrial Internet of Things (IIoT). Another scenario is for a company visualizing its energy management efforts, which could include the costs, consumption rates and carbon emissions for a single building up to an entire campus. Any organization gathering large amounts of data from multiple sources in multiple locations can benefit from the latest cloud-based visualization tools.
Maintaining control/controlling maintenance
Figure 1: ICONICS GENESIS64 running on a laptop. All images courtesy: ICONICS
A12 • April 2020
Applied Automation
Predictive maintenance is a growing application for data visualization, where organizations wish to switch over from the legacy break-fix model to one that is more efficient, proactive and cost-effective. Some related software solutions use fault detection and diagnostics (FDD) technology — a form of analytics particularly valuable to operations and maintenance teams (see Figure 3). FDD technology incorporates a standard library of fault rules that can be customized to predict equipment failures and advise personnel of preventive actions. This type of info
Figure 3: Predictive maintenance software displayed on an HMI screen. Figure 2: Data visualization is increasingly integrated with cloudbased applications.
(symptoms, causes and recommended actions) may have only previously existed for some organizations in the memory of senior personnel or, in some instances, in print or noninteractive electronic archives. FDD tools use an advanced fault rules engine that calculates fault probability as well as associated costs. It saves users configuration time by making integration easier, faster and more intuitive. The tools integrate easily with an organization’s multiple data systems, including popular building automation system (BAS), supervisory control and data acquisition (SCADA), programmable logic controllers (PLCs) and others used to monitor equipment conditions. Through FDD tools, associated alerts can be visualized in creative and intuitive ways to assist maintenance personnel in their daily tasks. Users also can create reports and charts to help visualize operations and address equipment performance inefficiencies. An additional tool that can be integrated with visualization and predictive maintenance tools involves an organization’s connected field service (CFS) operations. This contains advanced abilities that help streamline efficiency of field service organizations through intelligent scheduling and reliable notifications (see Figure 4). The dedicated software can be tied to the same alarms and faults recognized by the FDD system. It also provides a prebuilt operator or dispatcher dashboard, offering an overview of all the current alerts and who is responding to them. The CFS uses intelligent algorithms and customizable weighted scoring to determine which field worker is best for a specific maintenance task, then sends a notification to that worker’s mobile device for immediate action. The fully customizable workflow can use factors such as workers’ schedules and current GPS location to determine the best technician for the task. Alerts can be delivered via email, SMS or through an integrated mobile human-machine interface (HMI) app via
Figure 4: Field service notification via a smartphone.
push notification. When the technician receives the alert, he or she can reply to the message or use the mobile app to either accept responsibility, reject the alert or report as “busy,” (which passes the alert on to the next selected qualified worker). Another useful aspect of CFS software is its integration with popular enterprise resource planning (ERP), customer relationship management (CRM), computerized maintenance management system (CMMS) and directory services such as Microsoft Dynamics 365. This allows for retrieval of information such as worker contact info and scheduled availability from those connected systems.
Diversified UI Another major trend in data visualization is how organizations are taking a closer look at the relationship between the types of data they generate and how they are best presented to their employees/users/customers. Advances in technology have resulted in multiple different ways data can be accessed, viewed and even acted upon. Of course, desktop and laptop PCs are still predominantly used, both in interface development and final displays. However, PC-based visualization also has evolved, where traditional 2D graphics have been joined by more immersive, interactive 3D and mixed reality (MR) options. More mobile options, including tablets and smartphones, also have been adopted by organizations worldwide. Today’s modern HMI authoring tools allow for “design once, deploy everywhere” functionality. Such responsive design allows for displays to be rolled out to multiple device types, with multiple different screen sizes and resolutions, helping to ensure a more cohesive, standardized look and feel.
Applied Automation April 2020
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A13
D ATA V I S U A L I Z AT I O N When connected, important data Also, as the number of mobile metrics can be viewed in an device types increased, so did coninstant straight from a user’s prenectivity options and speeds, so ferred wearable device. that users in the field could experiAlthough not considered tradience the same rich, rapid visualizational visualization, voice assistion, monitoring and control. tants such as those developed The evolution of data visualizaby companies like Microsoft tion has resulted in more interest(Cortana), Google (Google ing forms. Some organizations Assistant) and Amazon (Alexa) realized the need for presenting can provide results to spoken data to an operator where he or inquiries and even trigger actions she might not have both hands for connected devices (e.g., turnfree to use a laptop, tablet or ing lights on and off, locking and smartphone. Microsoft, known for unlocking doors, etc.). the operating systems and producThe same concept applies for tivity software it pioneered for more Figure 5: Using a holographic machine interface. using voice-commanded assistraditional devices, created the tants within industrial or building HoloLens self-contained holographautomation. Automation software vendors have created ic computing device to meet this need (see Figure 5). voice machine interfaces, where the types of queries are Now updated to HoloLens 2, this MR device provides like what would be made graphically via traditional HMIs an augmented view where data can be visualized within on digital displays. an operator’s field of vision. Recognizing the need for For plant/operations managers, one could ask Cortana, a hands-free, rugged wearable device, RealWear, of for example, “Hey Cortana. What is the OEE [overall Vancouver, Wash., developed the HMT-1. The company’s equipment effectiveness] for line one, and how does aim is to allow workers “to maintain full situational awareit compare to last shift?” and be met with the voice ness and maximum productivity.” response of “The OEE for line one is 78%, which is up Just as when they recognized and adapted to tablets 2% from yesterday.” and smartphones joining their customers’ desktops and For facility maintenance personnel, one could ask Alexa, laptops, automation software vendors found a developfor example, “Alexa. What is the current voltage of this ment opportunity in wearable computing devices. The chiller compressor?” and the reply could be “The current concept of a “holographic machine interface” emerged, voltage of this compressor is 200 V at 50 Hz.” where a user would be able to quickly view information For organizational management, one could query the on the piece of equipment they were currently looking at. Google Assistant with, “Okay Google. What is our total oil For example, a technician could walk up to a machine in production year-to-date, and how does it compare to last a factory and be able to see a 3D schematic of its internal year?” and the response could be, “You have produced components. Through a voice request, the same techni5,640,000 barrels of oil year-to-date. That is up 4% from cian also could see related product documentation and last year.” specifications, or a video on how to replace a specific component, or real-time operational values. The combinaLooking into the future of visualization tion of certain devices and software can provide a “remote expert mode,” where the onsite technician can provide a This article covers a few of the growing data visualizalive view of what he or she is looking at to another technition trends, including increased IIoT integration, closing cian, who may be located elsewhere, who has more expethe loop in predictive maintenance and field service notirience with the task at hand and can remotely lend his or fications and increasing an organization’s user interface her expertise. options. Speaking of the task at hand, data visualization has also What will the future of data visualization look like? It reached smartwatches. Apple released its Apple Watch may involve new, more sophisticated connectivity methods line, while multiple other manufacturers created smartto complement the IIoT, or integrating artificial intelligence watches that use a variant of the Android OS called Wear (AI) or collaborative robots into predictive maintenance OS. All are minicomputers meant for the wrist, boasting and field service. It will involve the expansion of user interconsiderable processing abilities and are prime for data faces, as the form and utility of connected devices, as well visualization capabilities. Automation software vendors as the underlying software, is guaranteed to evolve. have found the perfect combination of “at a glance” quick info delivery of role based key performance indicators Melissa Topp is senior director of global marketing at (KPIs), especially for those smartwatches paired with mulICONICS, developer of the GENESIS64 HMI/SCADA autotiple means of connectivity (cellular, wi-fi, etc.). mation suite.
A14 • April 2020
Applied Automation
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