Selective Maintenance under Uncertainty

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Published Jul 14, 2017
Yu Liu Tao Jiang

Abstract

In this paper, a new multi-objective robust selective maintenance model is formulated by considering the uncertainties produced by imperfect inspections. The resulting optimization problem aims at maximizing the expectation of the probability of a repaired system completing a mission and simultaneously minimizing its variance. A multi-objective particle swarm optimization algorithm in introduced to identify the Pareto front, which offer a set of non-dominated selective maintenance strategies. An illustrative example shows that the selective maintenance strategy with the maximum expectation of the probability of a repaired system completing a mission may not be desirable as it usually possesses a huge variance. Several comparative studies are also conducted to examine the effect of observation accuracy and maintenance budget on the results. It concludes that the proposed approach can effectively improve the robustness of the probability of a repaired system completing a mission.

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Keywords

PHM

References
Rice W. F., Cassady C. R., Nachlas J. A. (1998). Optimal maintenance plans under limited maintenance time. Proceedings of The Seventh Industrial Engineering Research Conference, 1-3.
Cassady C. R., Pohl E. A., Jr W. P. M. (2001). Selective maintenance modeling for industrial system. Journal of Quality in Maintenance Engineering, 7(2): 104-117.
Pandey M., Zuo M. J., Moghaddass R., Tiwari M. K. (2013). Selective maintenance for binary systems under imperfect repair. Reliability Engineering and System Safety, 113: 42-51.
Coit D. W. (1997). System-reliability confidence-intervals for complex-systems with estimated componentreliability. IEEE Transactions on Reliability, 46(4): 487-493.
Section
Invited Papers