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Abstract:
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Models for degradation and maintenance of items based on first passage times of stochastic processes have proven useful in diverse applications such as production machines or pipelines. In the present work we consider items that are inspected and maintained at sequentially determined random times, with degradation modeled by increasing stochastic processes. The inverse Gaussian process is considered as a concrete example. Two threshold levels will be considered for the deterioration process, a lower one corresponding to a degraded state, for which a preventive maintenance action may be performed, and a higher one corresponding to the failure state, at which the item is replaced. A simulation based algorithm is developed to calculate long-run expected costs with an aim to arrive at optimal inspection and maintenance procedures. An interesting part of the algorithm involves bridge sampling from the degradation process.
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