A myopic policy for optimal inspection scheduling for condition based maintenance

In this paper, we propose a decision policy for condition-based maintenance that schedules inspections according to the current health of the system, optimized myopically over the next inspection interval. In traditional condition-based maintenance practices, regular inspections are considered a given requirement. Most measurements, however, confirm that the machine in question is in good working order and that no maintenance is necessary. We consider the possibility that there are savings to be had in the number of inspections that are undertaken. As such, we use a proportional hazards model for risk of failure and a Markovian process to model the system covariates. The cost and time of inspections are incorporated into our model, and an optimal decision for one interval is made. This process can be repeated for each decision point, resulting in a decision policy that produces an inspect-or-replace result and an optimal time for the next inspection. Applied over the life of an asset, this policy can be used as a complete condition monitoring program supporting evidence based asset management.