Title
Optimal Selective Maintenance Strategy for Multi-State Systems Under Imperfect Maintenance
Abstract
Many systems are required to perform a series of missions with finite breaks between any two consecutive missions. In such a case, one of the most widely used maintenance policies is a selective maintenance in which a subset of feasible maintenance actions is chosen to be performed with the aim at achieving the subsequent mission success under limited maintenance resources. Traditional selective maintenance optimization reported in the literature only focuses on binary state systems. Most systems in industrial applications, however, have more than two states in the deterioration process. In this work, a selective maintenance policy for multi-state systems (MSS) consisting of binary state elements is investigated. Taking the imperfect maintenance quality into consideration, the Kijima model is reviewed, and a cost-maintenance quality relationship which considers the age reduction factor as a function in terms of maintenance cost is established. Moreover, with the assistance of the universal generating function (UGF) method, the probability of the repaired MSS successfully completing the subsequent mission is formulated. In place of enumerative methods, a genetic algorithm (GA) is employed to solve the complicated optimization problem where both multi-state systems, and imperfect maintenance models are taken into account. The effectiveness of the proposed method is demonstrated via a case study of a power station coal transportation system. Finally, a comparative analysis between the strategies with and without considering imperfect maintenance is conducted, and it is concluded that incorporating imperfect maintenance quality into selective maintenance achieves better outcomes.
Year
DOI
Venue
2010
10.1109/TR.2010.2046798
IEEE Transactions on Reliability
Keywords
Field
DocType
universal generating function method,imperfect maintenance,multi-state systems,multistate systems,maintenance cost allocation,genetic algorithm,selective maintenance,genetic algorithms,optimal selective maintenance strategy,maintenance quality,universal generating function,maintenance engineering,enumerative methods,cost function,comparative analysis,industrial relations,random variables,generating function,optimization problem,industrial electronics,system performance,preventive maintenance,weibull distribution
Random variable,Imperfect,Predictive maintenance,Optimization problem,Maintenance engineering,Preventive maintenance,Mathematics,Reliability engineering,Genetic algorithm,Maintenance actions
Journal
Volume
Issue
ISSN
59
2
0018-9529
Citations 
PageRank 
References 
36
1.65
12
Authors
2
Name
Order
Citations
PageRank
Yu Liu119019.09
Hong-Zhong Huang258358.24