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Abstract
This paper discusses a framework for determining appropriate condition based maintenance policy for an industrial system. The framework can be considered as providing practitioners with guidelines for condition based maintenance (CBM) management or as the first step in the development of an expert system for CBM management. The framework proposes that components of the system of interest be classified using multi-dimensional Pareto analysis, with this classification then indicating appropriate maintenance actions. For a particular component, condition based maintenance may then be an appropriate action. In this case, it is proposed that a binary decision tree is used to suggest an appropriate condition based maintenance decision model for the component. Such decision models are briefly reviewed. The ideas in the paper are illustrated throughout using examples from condition based maintenance and maintenance modelling in general.
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Notes on contributors
P. A. Scarf
Philip Scarf Lecturer in Statistics and Operational Research at the Univeristy of Salford, UK. His interests are in the areas of maintenance modelling and capital replacement. Within these broad fields, he has particular interests in model fitting and decision making under uncertainty. He has chaired two international conferences on Mathematical Modelling in Maintenance and Reliability. He is a Fellow of the Royal Statistical Society and The Institute of Mathematics and Its Applications. Dr. Scarf is co-editor of the IMA Journal of Management Mathematics.
