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Develops practical models for preventive maintenance policies using Bayesian methods of statistical inference. Considers the analysis of a delayed renewal process and a delayed alternating renewal process with exponential times to failure. This approach has the advantage of generating predictive distributions for numbers of failures and downtimes rather than relying on estimated renewal functions. Demonstrates the superiority of this approach in analysing situations with non‐linear cost functions, which arise in reality, by means of an example.

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