Pick the right RCM metrics for the right process

Choosing the right metrics isn’t always a cut and dried matter. As we look at RCM metrics, I am going to add another dimension to the metrics decision—that of process.
By Dan Miklovic, LNS Research October 20, 2014
Reliability-centered maintenance (RCM) has been defined in numerous ways over its evolution, from a statistics-based approach, to analyzing equipment failures, to the philosophical or stylistic, broader definition more commonly accepted today that espouses a spectrum of styles from reactive maintenance to proactive maintenance with both calendar and condition-based preventative maintenance within those bounds.
Choosing the right metrics isn’t always a cut and dried matter. As we look at RCM metrics, I am going to add another dimension to the metrics decision—that of process. 
Not all manufacturing plants are alike
Manufacturing processes are different—while automobiles and gasoline both are produced in manufacturing processes and both generally considered highly dependent on the other for their usefulness, the way you make them could not be more different. 
In addition to the vast differences in the equipment used in manufacturing in both plants, robots versus huge distillation columns, the typical refinery operates 24 hours a day every day of the year, while an automobile plant typically runs one or two shifts a day and five days a week. In this case, both the physical process variations as well as the production process variations lead to very different maintenance needs.
Process vs. Discrete approaches
In a continuous process like refining, uptime is a holy grail. If you go down for any reason, production comes to a halt and that time is non-recoverable. In situations like this, the emphasis on asset performance is centered on detecting imminent failure and preventing it. 
In failure modes and effects analysis (FMEA), you analyze how equipment might fail, what effect that failure might have, and then what steps you can take to prevent that failure from occurring. In this type of production environment, your RCM focus needs to be aligned to the uptime goal and the elements which the various FMEA activities identify as the most critical to achieving that objective. 
In a discrete manufacturing process like in an automotive or aerospace plant, there may be significant periods of time available for maintenance activity. By extending operational capacity for a few hours or days, activities might differ considerably. 
In many discrete manufacturing operations there are parallel work centers, such as a robot painting operations, where downtime in a single cell only slows but does not stop operation. In this case, there are numerous opportunities to recover the lost production through overtime or process reconfiguration. In this environment, KPIs or metrics that measure flexibility and contribute to machine center OEE and maintenance cost-effectiveness might be more relevant than in the continuous-process plant example.

Edited by Bob Vavra, Content Manager, Plant Engineering, bvavra@cfemedia.com