A POMDP framework to find Optimal Policy in Sustainable Maintenance

Document Type: Article


1 Department of engineering, Faculty of industrial engineering, Yazd university, Yazd, Iran

2 Industrial Engineering Department, University of Yazd, PO Box 89195-741, Yazd, Iran


The increasing importance of these two subjects, maintenance and cleaner environment, beside the relations between them, encourages us to investigate a mathematical Markovian model for Condition Based Maintenance problem while considering environmental effects. In this paper, the problem of proposing maintenance optimal policy for a partially observable, stochastically deteriorating system is studied, in order to maximize the average profit of the system with consideration of sustainability aspects. The modeling of this Condition Based Sustainable Maintenance (CBSM) problem is done using mathematical methods such as Partially Observable Markov Decision Process (POMDP) and Bayesian theory. A new exact method named Accelerated Vector Pruning method and other popular estimating and exact methods are applied and compared in solving the presented CBSM model and several managerial conclusions were obtained.


Main Subjects