A Control-Limit Policy And Software For Condition-Based Maintenance Optimization

AbstractThe focus of the paper is the optimization of condition-based maintenance decisions within the contexts of physical asset management. In particular, the analysis of a preventive replacement policy of the control-limit type for a deteriorating system subject to inspections at discrete points of time is presented. Cox's PHM with a Weibull baseline hazard function and time dependent stochastic covariates is used to describe the failure rate of the system. The methods of estimating model parameters and the calculation of the optimal policy are given. The structure of the decision-making software EXAKT is presented. Experience with collecting, preprocessing and using real oil and vibration data is reported.RésuméDans ce rapport il s'agit de l'optimisation du processus décisionnel par rapport à un programme de l'entretien par surveillance de la condition des machines. Plus spécifiquement on décrit l'analyse d'une politique de maintenance préventive appliqué à un système qui se détériore mais qui est sujet aux inspections aux moments précis. Le modèle par Cox qui si traite aux risques proportionnelles (PHM) comprennant une ligne de base Wiebull ainsi que des co-variants stochastiques est employé dans le bût de décrire le taux de défaults du système. Des méthodes pour effectuer l'estimation des paramètres du modèle ainsi que le calcul de la politque optimale sont présentés. L'architecture du logiciel décisionnel, EXAKT, est décrit. On inclut, également, dans ce rapport, de l'experience sur le collecte, le traitement, et l'usage des données provenant d'un programme d'analyse d'huile et de la vibration.Key words:: condition-based maintenanceproportional-hazards modelMarkov processcost minimizationdecision softwareMots-clés:: programme de l'entretien par surveillance de la condition des machinesmodelisation des risques proportionnelles (PHM)processus Marcovminimisation des coûtslogiciel décisionnel Additional informationNotes on contributorsD. BanjevicDragan Banjevic is a Research Associate in the Department of Mechanical and Industrial Engineering and Visiting Professor in the Department of Statistics, University of Toronto. His research interests are in theoretical and applied probability, especially in reliability. His papers have appeared in Statistics and Probability Letters, Journal of Applied Probability, Theory of Probability and its Applications and other journals.A.K.S. JardineAndrew Jardine is a Professor in the Department of Mechanical and Industrial Engineering at the University of Toronto. His teaching and research interests lie in the general area of Engineering Management with a special interest in maintenance. He has had practical experience in devising maintenance and replacement procedures for a number of national and international organizations. He is author of Maintenance, Replacement and Reliability and co-editor of Maintenance Excellence: Optimizing Life Cycle Deicisions.V. MakisViliam Makis is a Professor in the Department of Mechanical and Industrial Engineering, University of Toronto. His teaching and research areas include quality and reliability engineering with special interest in modeling and optimization of stochastic systems. His articles have appeared in Mathematics of Operations Research, Technometrics, IIE Transactions, IEEE Transactions on Reliability, Journal of Applied Probability, Naval Research Logistics, EJOR, INFOR, Journal of the OR Society, International Journal of Production Economics, IMA Journal, Kybernetika, etc. He is a Senior Member of the Institute of Industrial Engineers and of the American Society for Quality.M. EnnisMarguerite Ennis obtained her B.Sc. in Statistics at the University of Stellenbosch in South Africa and her M.Sc. and Ph.D. degrees at the University of Toronto. She is interested in the application of statistics in both the medical and industrial fields and works as a freelance consultant. in data analysis and statistical graphics.