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Linear and Nonlinear Preventive Maintenance Models

Wu, Shaomin, Zuo, M.J. (2010) Linear and Nonlinear Preventive Maintenance Models. IEEE Transactions on Reliability, 59 (1). pp. 242-249. ISSN 0018-9529. (doi:10.1109/TR.2010.2041972) (KAR id:31008)


Preventive maintenance (PM) is a maintenance program with activities initiated at predetermined intervals, or according to prescribed criteria, and intended to reduce the probability of failure, or the degradation of the functioning of an item. In the literature, a number of PM models have been introduced to depict the effectiveness of PM. Based on these models, approaches to scheduling PM policies have been considerably studied. This paper attempts to review existing PM models, and investigate their inter-relationships. We then categorize these models into three classes: linear, nonlinear, and a hybrid of both. These three PM model classes depict the relationships of the hazard functions before, and after a PM. Possible extensions to these three PM models are discussed. The statistical properties for models are derived, and approaches to optimizing the PM policy are given.

Item Type: Article
DOI/Identification number: 10.1109/TR.2010.2041972
Additional information: Unmapped bibliographic data: PY - 2010/// [EPrints field already has value set] AD - School of Applied Sciences, Cranfield University, Bedfordshire MK43 0AL, United Kingdom [Field not mapped to EPrints] AD - Department of Mechanical Engineering, University of Alberta, Edmonton, AB T6G 2G8, Canada [Field not mapped to EPrints] JA - IEEE Trans Reliab [Field not mapped to EPrints]
Uncontrolled keywords: Corrective maintenance, Hazard function, Linear preventive maintenance, Maintenance effectiveness, Nonlinear preventive maintenance, Preventive maintenance, Corrective maintenance, Hazard function, Inter-relationships, Linear preventive maintenance, Maintenance programs, P-M model, Probability of failure, Statistical properties, Maintainability, Probability density function, Preventive maintenance
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 01 Oct 2012 16:25 UTC
Last Modified: 16 Nov 2021 10:08 UTC
Resource URI: (The current URI for this page, for reference purposes)

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