Corrected RUL-Based Maintenance Policy for Degrading Systems Under Random Failure

Abstract

This paper develops a corrected remaining useful life (RUL) based maintenance policy for continuous monotonically degenerate systems under random failure. The maintenance policy proposes a correction factor that follows a general distribution to comprehensively consider the potential errors in RUL prognostics. A Weibull proportional hazards model (PHM) is applied to jointly model the degradation state data and service age to directly describe the failure rate of the system. The degradation state of the system is regarded as a time-varying covariate and characterized by a Gamma process. According to the established PHM, the closed-form expressions for the probability density function and cumulative distribution function of RUL are derived. A corrected RUL can be obtained by considering a stochastic correction factor in the prognostics. This work considers a corrected RUL-based maintenance policy, which makes decisions according to an optimal control limit. The optimization problem is established and solved in a semi-Markov decision process (SMDP) framework with the goal of minimizing the long-run expected average cost per unit time. The effectiveness of the proposed method is illustrated by a numerical example.