Demand-driven condition-based maintenance planning under Markovian deterioration of machine condition

In this paper, single product single machine systems under Markovian deterioration of machine condition throughout a specified finite planning horizon are studied. It is assumed that the machine is subject to random failures and that any maintenance activities carried out in a period, reduces the system’s potential production capacity during that period. Furthermore, it is assumed that the machine is minimally repaired at failure, and PM is carried out, after inspection, to restore the machine to an ‘as-good-as-new’ status. The objective of the study is to find the optimal intervals for inspection and preventive maintenance (PM) activities in condition-based maintenance (CBM) planning with a discrete monitoring framework subject to minimize the sum of inspection, PM, minimal repair, and backlog costs. To achieve the goal, a stochastic dynamic programming model that enumerates demand is presented calling the demand-driven CBM model. The numerical results show that this model decreases the total cost significantly that depends on the demand and the unit backlog cost, which is an increasing and a concave function in the unit backlog cost regardless of the initial machine state.