Maintenance policies for systems with condition monitoring and obvious failures

We investigate a maintenance optimization problem with condition monitoring, which allows the decision maker to observe some wear-related variable throughout a system's lifetime to more accurately determine its degree of deterioration. Specifically, we examine the problem of adaptively scheduling observations (both perfect and imperfect) and preventive maintenance actions for a multistate, Markovian deterioration system with obvious failures, such that the long-run average-cost per unit time is minimized. We establish structural properties of the perfect observation-information problem and adjust them for heuristic use in the imperfect observation-information problem. We model both cases as partially observed Markov decision processes and provide numerical examples of optimal and heuristic solutions for both cases.

Acknowledgments

Contributed by the Reliability Engineering Department