Efficient facilities embrace control system predictive maintenance
Hydrocarbon facilities are operating differently and managing more pressures than they did just 5 yr–10 yr ago.
Hydrocarbon facilities are operating differently and managing more pressures than they did just 5 yr–10 yr ago. Today, plants are being redesigned to achieve more sustainable operations and to drive improved performance to ease strained supply chains. In many cases, this means doing more with less, particularly when it comes to staffing. As post-pandemic hiring shortages and increased retirements continue, it becomes harder to improve efficiency through traditional methods.
As a result, hydrocarbon plant operators are struggling to squeeze every bit of efficiency out of aging systems, and even greenfield builds must make the most of every resource to meet ever-tighter sustainability standards. Without a deep bench of experienced staff, teams face a difficult choice: stay on top of routine maintenance while losing the time needed to improve performance, or focus on performance improvements while risking unexpected trips and outages.
One overlooked area for maintaining efficiency is the health of the control system. If controllers and I/O are not performing properly, the plant may be at risk of a trip that could potentially lead to a shutdown. Failures in the control system often receive less attention than other causes of outages, such as faults in rotating equipment, because they are less common and harder to diagnose. However, such incidents, at best, cause revenue loss from downtime, and, at worst, create environmental or safety incidents.
Technologies for monitoring control systems have traditionally been complex and cumbersome. So, rather than relying on automation, many teams focus their time on routine maintenance strategies of varying effectiveness to ensure that operations continue, albeit at a plateau.
There is a better way to handle maintenance tasks. Today, teams can adopt new technologies and implement modern predictive maintenance software to relieve much of the burden of time-consuming routine maintenance operations. With much less time and complexity than previously imagined, teams can now implement a predictive maintenance solution that will provide the peace of mind of reliable automation operation, along with the flexibility, freedom and visibility necessary to improve plant performance.
Beyond routine maintenance
Routine maintenance has changed over the years, as paper notebooks have given way to computerized maintenance management systems that help teams ensure that maintenance is carried out on time and performed to manufacturers’ specifications.
However, a few common problems remain with a routine maintenance approach. First and foremost, its effectiveness is dependent on the expertise and number of maintenance personnel available in any facility. Maintenance activities for the control system are typically complex—especially when they require diagnosis—and these tasks require expertise that takes years to develop. They also require numerous types of personnel and a great deal of time. If a facility has many controllers and thousands of I/O points, both diagnoses and remediation steps will take significant time. For plants with only a single experienced person, the associated prioritization of work means that important tasks can go unperformed for extended periods.
Moreover, if a problem begins right after routine maintenance, then it will likely be some time before that problem is noticed, thus creating the potential for a trip. Operating exclusively under a routine maintenance strategy means that such problems can be missed until the system is checked again.
Pivot to predictive maintenance
Incorporating modern predictive maintenance software into a facility’s automation maintenance strategy takes much of the guesswork and human error out of driving peak reliability and performance. Predictive maintenance software collects health information directly from the control system in real time and updates maintenance personnel on the health of their systems, no matter where they may be.
For years, many maintenance teams have been hesitant to invest in control system predictive maintenance out of concern that it is too complex to install and maintain. This concern has only intensified as teams have lost expert personnel to retirements, creating the appearance that there would be no expert to use the system. However, new predictive maintenance solutions are changing that paradigm.
Today’s predictive maintenance software solutions are easy to install, use and maintain, and they provide a fast return on investment, regardless of the expertise of users. By keeping the following four strategies in mind (selecting a software solution, requiring real-time alerts, choosing software that provides decision support, and adopting a streamlined user experience), maintenance teams of any size or ability level can easily select a predictive maintenance solution to meet their needs.
Select a software solution
Many legacy predictive maintenance solutions were difficult to install and maintain. They required specific appliances, specialized hardware and complex software to configure and operate. However, today’s most advanced predictive maintenance solutions are entirely software-based and designed to reduce maintenance and overhead.
Predictive maintenance software is easy to set up and configure, and once installed, will always monitor the control system with little effort. The best solutions can be installed in less than 1 hr by the plant’s own personnel. These systems can run on a standalone computer or installed on a control system workstation for reduced footprint and easy accessibility (FIG. 1).
FIG. 1. Software solutions are easy to set up and configure, providing flexibility and constant monitoring.
Require real-time alerts
While today’s control system specialists and engineers would prefer not to spend excessive amounts of time in the control room, traditional routine maintenance strategies typically force them to do just that. A technician on a small team at a hydrocarbon facility may easily be responsible for three or four systems. If that person must frequently go to the control room, log into the predictive maintenance system, run a diagnostic that takes 30 min–40 min, then log out and do the same with each other system, half of the day’s productivity disappears just performing routine maintenance.
Under these circumstances, critical work is typically delayed—sometimes for days—or the maintenance team extends time between control room visits so they can complete repairs, creating the potential to miss critical failures.
The best modern software-based predictive maintenance solutions automatically send real-time alerts to ensure that control system specialists and engineers, no matter where they are located, will be immediately aware of potential issues and their severity, so they can take steps to intervene. With these systems in place, as users travel between sites, they no longer need to worry that their departure might mean they will lose visibility of plant health. Additionally, traditional technicians become highly capable mobile workers who can quickly respond to changes in automation health as they occur.
For example, predictive maintenance software can send instant alerts when controllers are running low on free memory. It also runs regular checks on overall I/O integrity and can alert personnel when I/O components experience faults.
Real-time alerts also increase the likelihood that essential work will be performed on schedule. In a routine maintenance setting, visibility of plant issues is typically limited to the person who ran the diagnostic. However, with predictive maintenance, multiple staff—including maintenance managers—can receive alerts. Scheduling and expediting become much easier, and problems that might not trip the plant, but still impact productivity, are less likely to be ignored.
Choose software that provides decision support
Today’s plant personnel have a wide variety of experience, and not every plant can have a 30-yr veteran who knows the ins and outs of every element of the control system. Even plants that do have such an expert cannot expect that person to be on site every day.
The best predictive maintenance software solutions can remedy this problem, providing decision support to take the guesswork out of maintenance and to upskill newer personnel. Automated alerts not only bring instant awareness to problems, but they also identify root causes and offer suggestions to quickly remedy identified issues (FIG. 2).
FIG. 2. Predictive maintenance provides decision support that enables users of any experience level to quickly identify and troubleshoot problems.
For example, one critical asset that can require decision support for less-experienced personnel is the controller. For a new technician, an alert reading “Standby secondary communication is bad” might not immediately indicate that an ethernet cable is disconnected or defective, or that the hub is unpowered or not communicating. However, modern predictive maintenance software delivers that same alert with actionable suggestions, such as checking the primary network cable and switch connected to the standby controller; ensuring that the switch is powered up and not locked; using a different port on the switch; or replacing the cable, switch or both. This active guidance not only helps newer personnel troubleshoot problems faster, but it also upskills workers more quickly, giving them the expertise they need to be more confident in future decisions.
Adopt a streamlined user experience
Predictive maintenance software should be designed to make the user experience as simple and efficient as possible. As mentioned, this starts with not requiring technicians to spend hours of their day logging into multiple systems.
Technicians using a predictive maintenance system with real-time alerts can immediately skip the step of running diagnostics to uncover issues, and feel safe in the assurance that the software will notify them of any automation system failure immediately—with plenty of time to react and intervene.
To make the system even more user friendly, it should include features to let users customize their alerts. Consider a distillation column that is down for maintenance. Having the equipment down could generate a distracting flood of control system failure alerts. However, shutting alerts down altogether runs the risk that they do not get turned back on when the process area is operational again.
The best predictive maintenance software offers timed “snooze” features, allowing teams to disable alerts for a set amount of time, after which they will automatically come back online; this is perfect for situations such as planned outage windows.
Additionally, today’s technicians rely on more software tools than ever. To streamline the use of these many disparate packages, plants and facilities are opting into comprehensive maintenance portals where they can see all their tools from a single screen.
Choosing a predictive maintenance software that interfaces with the support portal from the facility’s automation vendor helps teams maintain better visibility from a single interface. Management gains a clearer picture of overall automation health, while individual technicians save time by not having to learn and navigate multiple systems.
Predictive maintenance is the intuitive solution
Modern predictive maintenance software is not the cumbersome, complex system that many maintenance teams believe it to be, often based on their past negative experiences with older solutions. Today’s best predictive maintenance solutions are lightweight, intuitive software packages designed to be installed and run by plant personnel on the automation systems they already have in their facilities.
As today’s high-efficiency and more sustainable solutions change the way hydrocarbon processing facilities operate and expand, predictive maintenance solutions must integrate seamlessly to monitor many disparate control elements through a single intuitive interface. Using this type of solution, technicians and engineers can make better decisions faster and with more support, helping them to reduce downtime while keeping the plant running at peak performance. HP
The Author
Golder, N. - Emerson, Austin, Texas
Nina Golder is the Global Vice President of Lifecycle Services for Emerson, where she is responsible for software and service offerings for post-project support, maintenance and reliability for automation and control systems. Golder has been in the industry for 20 yr, serving in many commercial leadership roles within Emerson. She earned an engineering degree from the University of Texas at Austin and an MBA degree from Drexel University’s LeBow College of Business.
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