Modelling Uncertainty in Preventive Maintenance Scheduling

In this article we consider the practical implementation of Bayesian methodology in determining the optimal preventive maintenance (PM) interval for a complex repairable system. The behaviour of this system is described using a probabilistic model based on the failure intensity pattern. This model includes a number of unknown parameters and a Bayesian approach is established to provide information about the joint posterior distribution of these parameters. This posterior information is then incorporated into previously established PM interval scheduling methodology to determine optimal PM intervals within a decision-theoretic framework.

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