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Forget preventive maintenance. Today's uptime requirements call for an entirely different approach
Preventive maintenance isn't completely dead, of course. Rosenbaum, who bought into RCM 15 years ago, still believes in PM. "It heads off trouble before it starts, and the return is well worth the money invested."
Certain equipment does have a wear-out zone, and prudence dictates that it should be maintained before it breaks.
"We count valve operation cycles automatically, using our data historian, an OSI PI system," says Don Erb, manager of production planning and information, Ciba Specialty Chemical, McIntosh, Ala. "When the cycle count reaches a certain trigger value, the valve is scheduled for maintenance during the next opportunity."
Ciba's valve performance is evaluated based on historical data. "After we have one fail at a number of cycles, we check valves in similar service next time before they reach the same number, with the objective of service before failure occurs," explains Erb. "One major objective of our plant is reliability improvement. Our reliability has been improving over the past year, and although this is certainly not the only program in place, it is contributing."
Many process plants have developed similar PM programs for valves, only to find that 30% of the valves that are taken apart for preventive maintenance have absolutely nothing wrong with them (Chemical Processing, November 2001). As Honeywell's Desborough points out, this is probably because these programs drive maintenance actions based on device usage, not on control loop performance degradation.
Therefore, what we need is a better way to determine when assets actually require maintenance. This requires a three-pronged attack:
1. Sensors, tracking systems, or on-board diagnostics on each asset that help identify the presence of a problem.
2. A data acquisition system to collect asset information.
3. Software to analyze the data, determine that a problem exists, and suggest maintenance procedures to correct the situation.
All of the above pieces are readily available on the open market. Plants with fieldbus-based hardware, a frameworks-based control hierarchy, and asset management software already have the infrastructure in place to do RCM. Those with legacy systems can buy the necessary hardware and software and install it on their process. As with all things in this industry, you can get the RCM capability you need by spending anywhere from a few thousand to a few million dollars.
In olden days, supervisors would dispatch technicians to the field to check on problems. But not anymore. "The days of having instrument technicians run to the field every time there is a problem are long gone," says Rami Mitri, director of asset optimization, New England Controls, Mansfield, Mass. Downsizing and reduced budgets have taken a toll on maintenance operations in many plants, he says. As staff and budgets decrease, equipment problems increase. "Many customers neglect to link downsizing to reduced maintenance on critical equipment that can either shut down or delay production."
To overcome problems caused by downsizing and budget cuts, Mitri says end users have to adopt new, enabling technologies for maintenance. In many cases, this means being able to identify problems before they occur, so maintenance dollars go further.
Several ways exist to determine if a device or system is having problems:
* Manual observation (leaking, making noise, boiling over, etc.).
* Condition sensing (running hot, vibrating, losing pressure, etc.).
* Internal diagnostics (the device itself detects problems).
* Performance analysis (valve sticking, slow control response, hunting, etc.).
PG&E, the giant utility in California, uses manual techniques to check its gas distribution operations, says Brian Steacy, general manager of DST Controls, Benicia, Calif. DST supplied PG&E with a PDA-based data acquisition system.
"PG&E opted out of fully automating its data acquisition because it would have been cost-prohibitive and, more importantly, not entirely safe," says Steacy. "Much of PG&E's compressor station instrumentation is too far flung to be hardwired, and many of the thousands of gauges that must be read daily are old, mechanical, or otherwise too costly to match up with transducers or hang on a network."
Figure 3: Space-Age Failure Patterns
Today, complex devices are understood to fail according to one of these six patterns.
Using a handheld system provides regular human presence and keeps an eye on things to help avoid disasters, such as leaking compressor lubricant, unusual conditions, and graphic evidence that a cat had strayed into a compressor cooling fan. "The fan kept running, so the alarm wasn't triggered, but visual inspection revealed the necessity to shut the fan down for cleaning, repair, and balancing," says Steacy.
Wandering cats aside, manual observations are becoming the solution of last resort these days. Therefore, users must seek out ways to detect problems remotely, or predict them based on operating conditions.
One of the best ways is via condition monitoring, as explained in "Prevent Failure" [CONTROL"November '02]. That article explains how vibration analyzers and sophisticated data analysis can predict equipment problems in advance.
Condition monitoring, of course, often requires sensors to be installed on equipment to detect the conditions. Fortunately, this is getting much easier for end users. Many devices now come with HART or fieldbus interfaces, both of which can transmit diagnostic information.
Manufacturers also are building diagnostics into various devices, such as power supplies. The S8VS power supply from Omron Electronics, for example, can monitor percent usage and available life remaining.
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