Determining economical maintenance intervals

Abstract Several models have been proposed for scheduling the preventive maintenance (PM) of complex repairable systems in industry. These are often application-specific and some make unrealistic assumptions about stationarity of the process and quality of repairs. We investigate two principal types of general model, which have wider applicability. The first considers fixed PM intervals and is based on the delayed alternating renewal process. The second is adaptable, allowing variable PM intervals, and is based on proportional hazards or intensities. We describe how Bayesian methods of analysis can improve the decision making process for these models and discuss simulation algorithms for fitting the models to observed data. Finally, we identify some issues that need more research.

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