B. Overton, Emerson, Knoxville, Tennessee
Today’s hydrocarbon process manufacturing operations are almost unrecognizable from those of just 10 yr ago. Manufacturers are producing new products to meet new goals and supply an ever-increasing customer base that seemingly cannot consume products quickly enough. To meet these expanding needs, plants are relying on maintenance and reliability teams more than ever before, and those teams are feeling the strain.
On one hand, maintenance and reliability teams have dramatically improved their abilities and tools over the last few decades. Plant personnel are more effective than ever with their reliability programs, successfully detecting issues and performing repairs when aberrations appear. However, most teams would like to perform those tasks more efficiently than they are. Today’s process manufacturing organizations—operating in a tight labor market and under tight cost constraints—have very limited resources. As a result, teams have been asked to do more with less, which ultimately requires more efficient operations.
One solution to this conundrum is built-for-purpose edge analytics devices. Edge analytics devices use targeted technology to collect vibration and process data from balance-of plant-assets. The system—at the location of the equipment being monitored—then applies automated, embedded analytics to alert personnel to common faults for a wide range of assets, such as fans, motors, gearboxes, pumps and other rotating machinery.
As today’s forward-thinking maintenance and reliability teams implement edge analytics, they are seeing dramatic performance improvements. Personnel are more productive, asset life is extended, and teams can perform more in-depth, accurate root cause analysis (RCA) to eliminate failures before they occur.
Improve personnel efficiency. Historically, plant management could count on a deep bench of experienced technicians to keep their assets running at peak performance. As these experienced personnel walked the plant, they used a combination of portable monitoring devices and their own intuition—based on years or decades of experience—to locate, isolate and identify problems with rotating machinery.
In the wake of the COVID pandemic, however, many organizations are finding themselves very short on experienced applicants for available positions. As a result, many plants are operating with skeleton crews—some organizations are using smaller groups of centralized experts to support multiple plants across a wide geographic area. Under these conditions, teams can no longer spend 80% of their time walking around the plant looking for problems, especially when most of that time is spent examining assets that may not require attention.
Today’s teams must instead focus their efforts so they are spending less time collecting data and more time working on assets that might present an anomaly. Edge analytics devices can greatly reduce the amount of time teams spend in the field by continuously monitoring assets and generating analytics results and diagnostics right at the source.
Once that data has been collected and analytics have been generated, the edge device sends actionable information directly to reliability and maintenance personnel at their workstations or via a mobile device. Received alerts identify the issue, the severity and steps for remediation. With everything they need instantly available, less-experienced personnel can more easily fix problems as they occur, and highly experienced personnel can spend less time evaluating problems and more time solving them.
Analytics in action. For one large process manufacturer, its maintenance and reliability team must monitor more than 2,000 pumps across multiple business units at its sites. Each site has its own analyst who is responsible for collecting and analyzing data for applicable assets (FIG. 1).
In recent years, the organization discovered it could not sufficiently staff the analyst role to stay ahead of mechanical failures occurring in balance-of-plant assets, so management set a goal to reduce the amount of time analysts spent in the field.
Edge analytics devices will be critical to accomplishing that goal. Edge devices can collect data from every unit across the site and automatically notify analysts of any anomalies. Key personnel will immediately know what assets require attention and what steps to take, without ever having to go into the field to collect data. This improved visibility helps the organization operate successfully with a smaller staff, and will free that staff to focus on other tasks during times when assets do not need immediate attention.
Extend asset life. Much of the work in maintaining balance-of-plant equipment is focused around bearings (FIG. 2). Bearings are subject to many faults—poor lubrication, misalignment, looseness and more—that are difficult to diagnose before they cause failure. These difficult-to-diagnose issues are often quick to fix. If teams could take the isolation, identification and analysis time out of the equation, they could solve many issues before they evolve into more serious problems.
Consider an under-lubricated bearing. To fix the problem, the technician first must identify it, which means traveling out to the asset and analyzing it, either with a portable analyzer, visual inspection, or (more likely) both. If the asset is far in the field, or even at another site across the country or across the globe, the time to problem identification is further extended. Under-lubrication can be difficult to detect, so the time spent at the asset collecting data may be significant.
Once the technician identifies the problem, they must travel back to the shop and analyze the collected data. Assuming they can correctly identify the problem, they must then create a work order to have someone go out and lubricate the asset. The time to repair in this instance is exceedingly long, and it all presumes the team had enough experienced personnel to perform the regular rounds in the first place.
Imagine the same situation, but in this case, the vibration identifying under-lubrication starts 2 d after the technician performs regularly scheduled rounds on the asset. It could be days, weeks or months before the asset is examined again, and all the while wear and tear will be breaking down the bearing. Due to difficult circumstances like this, many bearings installed in the field fail to reach their full functional life.
Edge analytics devices deliver a fast return on investment precisely because they quickly identify critical problems, empowering maintenance and reliability teams to act before those issues become failures. An edge analytics device eliminates the time spent examining assets, the inconsistency of inspection by different personnel, and the time spent analyzing the collected data.
In addition, the high performance of the embedded analytics systems enables the devices to detect and identify issues well before personnel can, giving teams far more time to intervene before issues become failures. As a result, teams using edge analytics devices typically find that the realized functional life of their bearings has been extended.
Improve RCA. One of the primary benefits of edge analytics devices is that they make it easier for maintenance and reliability teams to correlate operational data with asset health data to delve deeper into problems and better identify root causes of recurring issues. Modern edge analytics devices can bring in different types of signals: temperature, pressure, analog signals, etc. Armed with this valuable data as well as traditional vibration data, teams can more easily determine how external factors may be contributing to the alerts they receive.
Moreover, the most advanced edge analytics devices can send data to control systems or receive process data from those systems via Modbus and OPC UA communication to further identify how process changes impact the health of balance-of-plant assets. If issues occur due to external factors, this extra layer of analysis makes it far easier to isolate and remedy any problem.
Edge analytics devices can also be integrated with an organization’s machinery health software to allow deeper analysis and trending of asset health data. Even if a plant has analysts working with these systems, the team saves significant time not just by avoiding sending people to the field to collect data, but also in providing analysts immediate solutions for the plant’s most common problems, freeing them to focus their skills on more complex issues.
Analysis in action. At one process manufacturer that was producing a critical product during the pandemic, the maintenance and reliability team was delivering data from its edge analytics devices to its historian to correlate it with operational data. After detecting high vibration on a fan, but finding no bearing problems, the team examined the operational data alongside the data from the edge analytics device. The team determined that the vibration issue occurred because intake filters on the fan were icing up. The high vibration had nothing to do with a bearing—the source was external. Once the team removed the ice, operations returned to normal.
Stay ahead of the maintenance curve. Skilled personnel are central to the operation of a successful maintenance and reliability team. However, these personnel are often pushed to their limits simply trying to keep up with maintaining the plant’s assets; analysis and repairs are often delayed, resulting in high costs, or, in the worst case, production outages.
Edge analytics devices are designed to not only dramatically reduce the low-value task of walking around the plant collecting data, but also to help teams develop a routine centered on predictive maintenance. This functionality empowers them to stay ahead of critical tasks and focus on driving more efficient operation across a facility, fleet or enterprise. HP
NOTES
a Emerson’s AMS Asset Monitor
BRIAN OVERTON is the Sales Enablement Manager and subject matter expert for machinery health products at Emerson. With more than 31 yr with the organization, Overton’s experience is extensive, covering all aspects of reliability maintenance. Prior to his tenure with Emerson, he proudly served in the U.S. Navy as a nuclear-trained electrician, where his foundational knowledge of reliability maintenance was established. Overton relies on these years of experience when it comes to product and program development, both internally and with customers.