Abstract
The effect of ageing on the deterioration rate of most repairable systems cannot be ignored. Preventive maintenance (PM) is performed in the hope of restoring fully the performance of these systems. However, in most practical cases, PM activities will be only able to restore part of the performance. Bridging the gap between theory and practice in this area requires realistic modelling of the effect of PM activities on the failure characteristics of maintainable systems. Several sequential PM models have been developed for predetermined PM interval policies but much less effort has been devoted to age-based ones. The purpose of this paper is to develop an age-based model for imperfect PM. The proposed model incorporates adjustment factor in the effective age of the system. The system undergoes PM either at failure or after a predetermined time interval whichever of them occurs first. After a certain number of such PMs, the system is replaced. The problem is to determine both the optimal number of PMs and the optimal PM's schedule that minimize the total long-term expected cost rate. Model analysis relating to the existence and uniqueness of the optimal solutions is provided. Numerical examples are presented to study the sensitivity of the model to different cost function's factors and to illustrate the use of the algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 1644-1651 |
| Number of pages | 8 |
| Journal | Journal of the Operational Research Society |
| Volume | 59 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2008 |
Bibliographical note
Funding Information:Acknowledgements—The authors are grateful to an anonymous referee for constructive comments that lead to substantial improvements in the presentation of the paper. We would like also to acknowledge the support of King Fahd University of Petroleum & Minerals under Project # FT-02/04.
Keywords
- Age-based preventive maintenance policy
- Imperfect maintenance
- Long-run expected cost rate
ASJC Scopus subject areas
- Management Information Systems
- Strategy and Management
- Management Science and Operations Research
- Marketing