A near optimal preventive maintenance policy with the effect of age reduction factor

There are many repair/replacement problems which have been investigated during the past decades. A repairable system is usually subject to stochastic failure when it deteriorates with age. The objective of this research is to investigate the optimal maintenance policy by modeling the deteriorating process of a system as a Markov decision process. The optimal repair/replacement policy is proposed by incorporating the costs of operating system, general repair, failure replacement and preventive replacement under the discounted cost criterion. The alternative maintenance actions depend on the status of the repairable system. The specific options for a failed system are either to replace the system or to perform a general repair. A working system's maintenance options are whether performing a preventive replacement or keeping the system with the operating cost. The major modifications of the standard replacement model in this research are the addition of the general repair with age reduction effect and the maximum number of general repairs permitted. Finally, the optimal parameters of the maintenance policy can be obtained by solving the n-stage problem using the backward recursive scheme over a set of finite horizons to approximate the optimal policy for the infinite planning horizons Significance: Maintenance activities are increasingly important with the challenge for improved efficiency of manufacturing system. This research investigates the optimal maintenance policy without the limit of using the general repair once as in the literature. Furthermore, the proposed model considering the general repair with age reduction effect is more suitable for industrial applications and thus is closer to the real world situations.