Valve maintenance on its way to the cloud
Constanze Schmitz - 29 June 2017
For decades, process plants have been designed to be heavily automated to provide safe and stable operation. In general, plant operators have a good understanding of how a process plant operates but the feedback ARC has been receiving highlights the fact that it’s impossible for end users to be experts in everything.
Edited by Constanze Schmitz, Analyst ARC Advisory Group Europe
While operators and maintenance technicians have good basic knowledge and training in the control valves’ mechanical systems, their knowledge often does not extend to the intelligent electronics included in today’s digital positioners. Modern control valve positioners have morphed into digital controllers capable of recording a multitude of parameters affecting control valve operation, e.g. air supply, electrical supply, travel stroke.
Instrument or electrical teams rarely receive adequate training in these increasingly sophisticated and complex devices and are not typically experts in valve diagnostics. Modern digital positioners provide more raw valve health data than ever before but end users are struggling with the sheer volume of data available, making it challenging to obtain full value from the increased diagnostic capabilities provided by their intelligent valve positioners. They also struggle to get a handle on the new work processes needed to get the full value from intelligent valve positioners.
Leading automation suppliers have developed control valve management systems to address this complexity and overcome the site expertise gap. Yet many studies show current practice by most industrial manufacturers is to ignore this feature and simply perform scheduled maintenance or fix the control valve when a failure occurs. Thus, they apply reactive maintenance practices for control valves, with lost production as result; or on inefficient schedule-based maintenance practices.
True predictive maintenance would require a more substantial look across differing data sets that complement the asset management reports. As more end users begin to recognize the downsides of reactive and/or schedule-based maintenance methods, they are increasingly turning to control valve suppliers for valve maintenance services. These services leverage the supplier’s valve expertise supplemented with remote monitoring to fill existing gaps in valve maintenance practices and provide more actionable information.
By combining data from the control valve asset management solutions with process historian data, industrial process analytics vendors can now provide the needed expertise and efficiency by automating the data aggregation. The goal for maintenance has always been to have the most knowledgeable expert(s) perform the service at the right time (and the right price). Owner-operators today realize the value associated with purchasing control valves from a supplier that can provide remote, IIoT-enabled asset management and predictive services at relatively low cost.
For suppliers, being able to securely access and diagnose data from their installed control valves can help them build a better, more reliable valve and ensure optimum performance. Based on the high cost of unnecessary maintenance and unplanned downtime, combined with the growing skills gap across the industry, ARC expects the use of “Expertise as a Service (EaaS), remote monitoring and diagnostics and other IIoT-enabled services to grow. EaaS paves the way for new workers to join global competency centers or other centers of excellence, thus avoiding the 4 Ds – dull, dirty, dangerous and distant work.
Fisher is leveraging a collaborative environment connecting customers with local Fisher services experts and global valve experts. This environment enables data from multiple sources to be visualized and aggregated and allows people located around the world to look and work on the same data in a collaborative manner. It also allows company analysts to view valve health data in time series and look at valve health trends over several years to determine trends over time and predict impending valve health deterioration so remediation can be scheduled and performed well before an operator alarm is triggered.
ARC observes that other leading companies also appear to be heading down a similar path; leveraging IIoTenabled technologies to deliver new and more effective predictive or prescriptive maintenance services for critical assets.