5. PROCESS AND OPERATING DATA BASED METHOD TO PREDICT REMAINING USEFUL LIFE OF EQUIPMENTPages 98-107
Abstract
Reliability of components in equipment is critical to ensure overall equipment and system availability, safe operation and cost effectiveness. Reliability depends upon many factors such as design, material, operating conditions and maintenance strategies. To predict the condition of components, such as bearings, this paper presents how process data can be used to drive reliability. An algorithm based on statistical functions is developed to predict the expected bearing lifetime. Some of the critical operating parameters are considered, including: temperature, vibration, and lubrication. This prediction model also serves to develop actions such as adjustment to maintenance schedules to reduce the number of failures, and enhance overall plant reliability and availability by avoiding a component failure. To validate the model, three bearing case studies for gas compressors are used, and their results show that the proposed method is capable of predicting failures with good accuracy. The results have shown excellent correlation between model prediction and the real plant experience. Additionally, this approach is particularly useful for failure investigations and suggested inspection intervals. The suggested technique can be used for other components, such as mechanical seals.
Keywords:
Bearing,
Reliability,
Equipment,
Operating Parameters,
Remaining Useful Life.
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Khalid A. Al-Jabr, 
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