A more proactive approach is when analysis of in-service lubricants is used is to perform predictive maintenance (PdM) of industrial equipment. The advantage that predictive maintenance has over scheduled maintenance is that maintenance is determined by what is actually occurring at any given time with the health of the equipment. If it is known through oil analysis that perhaps a bearing or gear is starting to fail, repairs can be scheduled before unexpected downtime occurs and work activity is interrupted. With predictive maintenance through analysis of in-service lubricants maintenance can be scheduled well enough in advance so that down time does not greatly affect work schedules. Predictive maintenance using oil analysis will allow corrective action to be performed well before equipment performance deteriorates and indications develop that equipment is going to fail. Under these circumstances not only would a failed bearing require unexpected replacement but many times additional components suffer damage. In order optimize equipment maintenance based on equipment condition detected through analysis of in-service lubricants sampling schedules should occur at regular intervals, including between oil drains.
Many facilities currently use a process called Reliability Centered Maintenance (RCM). Reliability Centered Maintenance is a process which is intended to establish acceptable minimum levels of maintenance in order to optimize equipment reliability. The use of oil analysis of in-service lubricants through predictive maintenance techniques in addition to traditional preventive measures can be a key component in Reliability Centered Maintenance. Predictive maintenance through oil analysis can be used to improve scheduled maintenance by either bringing to light additional issues that scheduled maintenance needs to address or to optimize the timing of scheduled of maintenance.
When taking oil analysis to the next level for optimizing equipment reliability root cause analysis focuses on the source equipment failure and maintenance issues. While with predictive maintenance there’s a general tendency to treat the symptom rather than the underlying fundamental problem, root cause analysis targets and measure the real cause of the problem. Generally root cause detection through oil analysis focuses on contaminants or operating conditions that lead to real problems. Contaminants can be detected such as dirt, water, coolant, or incorrect fluid. Adverse operating conditions can be detected by looking for signs of oil degradation due to excess heat, or inadequate fluid film due to improper viscosity. The cost of eliminating the root cause that leads to symptoms of degraded equipment reliability is much less expensive than fixing the symptoms after they occur. Eliminate the cause, prevent the problem from recurring.
The return on investment (ROI) by using oil analysis to compliment maintenance practices can be greatly increased in industrial applications when the data is used as proactively as possible. By using oil analysis to optimize predictive maintenance or reliability-base maintenance there can easily be a ten-fold return on investment over just using oil analysis in during scheduled preventative maintenance practices. If root cause analysis to keep contaminants below a threshold level that affects equipment reliability or detrimental operating conditions are caught before there’s a chance for negative impact, investment can be returned an additional ten-fold.
David Doyle, CLS, OMA I, OMA II
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