Multi-mission selective maintenance and repairpersons assignment problem with stochastic durations. (March 2022)

• Record Type: Journal Article
• Authors: Liu, Lujie; Yang, Jun; Kong, Xuefeng; Xiao, Yiyong
• Is Part Of: Reliability engineering & system safety. Volume 219(2022)
• Publication Date: 2022-03
• Subjects: Multi-mission selective maintenance -- Repairpersons assignment -- Stochastic durations -- Genetic algorithm -- Uniform design; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2021.108209
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: A multi-mission selective maintenance model with stochastic durations is proposed. The stochasticity of mission, maintenance action and break duration is considered. An integrated model of selective maintenance and repairperson assignment is given. It is solved by a new tailored genetic algorithm with the aid of uniform design. The grand total cost and its stochasticity can be reduced by decreasing the duration stochasticity. Abstract: Systems are often required to execute a sequence of missions separated by scheduled breaks. To improve the success rate of the next mission, multi-mission selective maintenance is applied in the limited break. In general, the durations of missions, maintenance actions, and breaks are stochastic due to the influence of repairpersons, the environment, and so on. However, the existing researches rarely consider the stochasticity of these three kinds of durations in the multi-mission selective maintenance problem, which leads to the underestimation of the grand total cost and the neglect of its stochasticity. Besides, the real system reliability may be lower than the minimum requirement if the stochasticity of durations is ignored in the maintenance decision-making. To overcome the above problems, a new multi-mission selective maintenance and repairpersons assignment model with stochastic durations is developed. The proposed model is transformed into an optimization problem constrained by the limited maintenance resources, and the objective is to minimize the expected grand total cost with a given reliability threshold. Then, a tailored genetic algorithm with the initial population generated by the uniform design is proposed to solve the optimization problem. Finally, numerical examples are carried out to demonstrate the effectiveness of the proposed method.