Predictive maintenance is a term coined years ago as the means to use technology to identify a component defect in its earliest stage of degradation. Today some also call this same process condition-based maintenance (CBM). Either way it is detecting defects early. The premise behind this activity is when a defect is detected early; the repair can be performed during a scheduled outage. The lead time prevents secondary costs that would be incurred by an unscheduled outage due to the lack of defect knowledge. We break defects down into two categories; the first is the primary state of failure and the other is secondary state of failure.
A primary failure is the first detectable signal that a defect exists. For example, if you are dealing with equipment the first detectable signal a component is failing could be a vibration signature that exposes a bearing fault frequency.
If the same bearing as above fails catastrophically all the additional damage incurred is considered secondary failure. When the bearing that was identified in the primary state fails catastrophically the shaft will drop from lack of support causing shaft and housing damage. The shaft and housing damage did not have to occur, but did. Therefore it is considered secondary failure.
Secondary failure is most often a result of not taking action on items exposed from the predictive maintenance technologies exception reports. When the primary bearing defect is exposed, the fate of the component can only be imminent failure.
Whether secondary damage occurs, is up to the management since they control when the repairs take place. Unfortunately, the first usual response to a high priority defect is “will it make it to the next shutdown?” Then the premise of condition based maintenance has been at best diluted or at worst ignored.
Taking the predictive maintenance job to the next step:
No one cares more about making a correct defect call than the Reliability technician. Whether it is a defect discovered using vibration, ultrasonic, infrared, or any other of the numerous predictive maintenance technologies available, the Reliability technician wants to confirm it was a valid diagnosis.
What normally happens is the Reliability technician will wait for the components of the diagnosed defect’s to be removed and retrieve it for examination. When confirmed as a valid call, the component is normally saved as a trophy of sorts. This is understandable as the technician is proud of the fact the call produced a defect that could be corrected before secondary damage could occur.
It should only make sense they would have the most interest in finding the solution. With some additional basic knowledge they could determine how the defect materialized. With basic fracture pattern knowledge, technician’s would be able to identify the failure mechanism by reading a fractured component’s surface. To determine if a part failed due to fatigue or overload is a great step toward knowledge and/or solution because the two failure mechanisms only can occur under conditions specific to each mechanism.
As an example, let’s say a shaft failed and the technician can determine it is due to fatigue. Let’s further say he or she can also determine the fatigue was due to misalignment. The technician can show proof both by reading the vibration signature and by reading the failed shaft’s surface.
What is there to gain from this?
Taking predictive maintenance to the next level is a natural progression of a company’s overall Reliability approach.
About the Author:
Mark Latino is President of Reliability Center, Inc. (RCI). Mark came to RCI after 19 years in corporate America. During those years a wealth of reliability, maintenance, and manufacturing experience was acquired. He worked for Weyerhaeuser Corporation in a production role during the early stages of his career. He was an active part of Allied Chemical Corporations (Now Honeywell) Reliability Strive for Excellence initiative that was started in the 70’s to define, understand, document, and live the Reliability Culture until he left in 1986. Mark spent 10 years with Philip Morris primarily in a production capacity that later ended in a reliability engineering role. Mark is a graduate of Old Dominion University and holds a BS Degree in Business Management that focused on Production & Operations.
This article was previously published in the Reliable Plant 2014 Conference Proceedings.
By Mark Latino, Reliability Center Inc.