Since an asset optimization program was initiated more than two years ago at the Monsanto herbicides plant in Muscatine, Iowa, it's prevented several potentially expensive process interruptions, saving the company tens of thousands of dollars.
For example, a pre-warn alarm of travel deviation in a distillate-receiver-level control valve led to discovery of leaking packing that was easily replaced without incident. Had this problem with a "Type A" or most critical control valve escalated without our knowledge, it could have caused an unplanned process shutdown costing as much as $100,000 per hour.
The pre-warn status alert was issued by our asset management software, which was acquired in 2005 for the Glyphosate Technicals (GT) Unit. The software was configured to issue an alert when output of a control valve and actual valve position (AVP) values differed by more than 5% for just five seconds, which we consider a sign of impending trouble requiring maintenance attention. In this case, electrical and instrumentation (E/I) technicians removed the valve assembly at the next scheduled production shutdown, replaced the packing, reinstalled the assembly and calibrated the valve. In addition, we performed diagnostic scans and tests to create a benchmark signature for archiving in an instrumentation database for future comparison.
Fostering Predictive Maintenance
The asset management application makes predictive maintenance possible by providing access to a multitude of diagnostic data generated by smart field devices in our plant in addition to supplying alerts that enable us to avoid unwanted process interruptions that might lead to potentially extended downtime. The diagnostics indicate a device's operating condition as well as various performance characteristics, including control valve travel deviation, which helped us avoid a reactive maintenance scenario with the distillate-receiver-level control valve.
By tapping into device diagnostic information, we can predict with reasonable accuracy how long an instrument or valve will continue to perform satisfactorily before repairs or replacement will be necessary. In some cases, we must take immediate action to keep the process running. However, often we can plan the job for the next scheduled maintenance shutdown — enabling us to ensure all necessary repair parts are staged (kitted) and technicians are equipped with the right tools and knowledge to safely, efficiently and correctly make the repair.
Of course, all equipment and instrumentation degrade with age; in a plant with hundreds or thousands of input/output (I/O) points, it's impossible to respond to every performance issue. We approach that challenge in two ways. One is through asset prioritization based on criticality assessments to identify those measurement devices and control valves that are essential in providing maximum production availability. The other method is by filtering device status alerts, so we can perform further analysis on conditions with potential to negatively impact production.
By prioritizing all our facility's assets we've been able to achieve a high level of process reliability. But first we needed to determine which components would cause all or part of a process to shut down if they were to become compromised or fail. By identifying critically important devices and valves we now know just where to focus our predictive maintenance (PdM) efforts. Those components deemed less critical receive lower priority preventive maintenance (PM) or are allowed to run to failure, if this won't result in harm to other equipment, unsafe conditions or compliance issues.