A Markov chain model to determine optimal maintenance policy for production process in automotive company

Abstract

This paper considers an operating machine with deteriorating performance over time. Initially, functioning at 100% of its nominal capacity, the machine fails after a stochastic period, reducing its capacity to a proportion of the nominal level. In this degraded capacity state, three maintenance and repair policy options are available for evaluation. By modelling the system as a discrete-time Markov chain and analyzing the probability transition matrix between the system states, the costs associated with the loss of production, part replacement, and ongoing operation in each state can be quantified. The objective function representing the average cost per unit time of production is calculated to determine the optimal maintenance policy. Different policies are modelled by the Markov chain and the average cost of each policy is obtained. The results demonstrate the applicability of the proposed methodology to evaluating different policies.