Focus on Critical Assets Pays Off

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.

Plugged Sensor Tube

Figure 1. Software showed a flow meter problem that wasn't apparent otherwise and that could have led to costly downtime.

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.

Asset prioritization enables us to focus our attention on Type A critical devices, especially when they trigger an alert. Just as a football team must protect its star quarterback to keep him in the game, we must provide special protection for our key assets to keep them productive and prevent costly process downtime.

With hundreds or thousands of devices in a unit continually reporting on their own health via numerous diagnostic status conditions, process operators can be overwhelmed by warnings and alarms. Which ones are most important and need to be investigated? In plants without a method of prioritizing this information, maintenance personnel are called upon to make a lot of fruitless trips to the field. We try to avoid wasting valuable technician time by filtering the status alerts to identify those coming from the most critical devices, leaving less significant issues to be investigated on a lower priority by our maintenance technicians.

We previously used an alert messenger application with Emerson's AMS Suite: Intelligent Device Manager predictive maintenance software for that purpose. But we are now examining use of AMS Alert Track Snap-On customizable software that filters status alerts and routes predefined critical items directly to a customizable list of recipients such as maintenance planners and schedulers. This tool efficiently removes the task of electrical personnel examining the list of numerous alerts and notifies appropriate decision makers immediately via e-mail and mobile devices.

Getting Started
The GT Unit acquired its AMS Device Manager application from another Monsanto facility. One of the initial challenges was getting the E/I technicians to buy into the new system. I, too, was skeptical at first and had to prove to myself that the AMS Device Manager application could save money and maintenance time by preventing unexpected downtime. Many process engineers viewed it as another "toy" — until it revealed some critical control valve travel deviation issues and identified one severely bent valve stem. These are conditions that operators can't determine by simply looking at or listening to a control valve but that can lead to big trouble. That started to open some eyes.