A POMDP framework to find optimal policy in sustainable maintenance

Abstract

The increasing importance of maintenance and a cleaner environment besides the relations between them has encouraged the current authors to investigate a mathematical Markovian model for the condition-based maintenance problem while considering environmental effects. In this paper, the problem of proposing a maintenance optimal policy for a partially observable, stochastically deteriorating system is studied in order to maximize the average profit of the system with sustainability aspects. The modeling of this Condition-Based Sustainable Maintenance (CBSM) problem is done by mathematical methods such as Partially Observable Markov Decision Process (POMDP) and Bayesian theory. A new exact method, called accelerated vector pruning method, and other popular estimating and exact methods are applied and compared for solving the presented CBSM model, and several managerial conclusions are obtained.