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Modelling Uncertainty in Preventive Maintenance Scheduling
Author(s) -
Bell Stuart A.,
Percy David F.
Publication year - 2012
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1409
Subject(s) - preventive maintenance , scheduling (production processes) , bayesian probability , computer science , posterior probability , probabilistic logic , interval (graph theory) , reliability engineering , operations research , joint probability distribution , data mining , mathematical optimization , engineering , artificial intelligence , statistics , mathematics , combinatorics
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. Copyright © 2012 John Wiley & Sons, Ltd.