Optimum Threshold Level of Degrading Systems Based on Sensor Observation

Abstract

Degradation models are normally used to predict the system’s failure under condition-based predictive maintenance policies. Repairs or replacements of the system are performed once the degradation level reaches a predetermined threshold level. This results in a significant time and cost savings compared to the situation when the system is repaired upon failure. In the former case, the maintenance is planned and the necessary spare parts and manpower requirements are readily available, while in the latter case it is difficult to predict the failure time and plan the necessary resources to perform the maintenance action immediately upon failure. Recent developments in sensors, chemical and physical nondestructive testing, and sophisticated measurement techniques have facilitated the continuous monitoring of the system condition. A condition parameter could be any critical characteristic such as crack growth, vibration, corrosion, wear and lubricant condition. With the measured data, the predictive maintenance policy determines the optimum threshold level at which maintenance action is performed to bring the system to a “better” condition, if not as good as new, in order to maximize system availability or minimize the average maintenance cost.