Title: Selective maintenance for maximising system availability: a simulation approach

Authors: Wenbin Cao; Xisheng Jia; Qiwei Hu; Wenyuan Song; Hongyu Ge

Addresses: Department of Management Engineering, Mechanical Engineering College, No. 97 Heping West Road, Shijiazhuang, Hebei 050003, China ' Department of Management Engineering, Mechanical Engineering College, No. 97 Heping West Road, Shijiazhuang, Hebei 050003, China ' Department of Management Engineering, Mechanical Engineering College, No. 97 Heping West Road, Shijiazhuang, Hebei 050003, China ' Department of Management Engineering, Mechanical Engineering College, No. 97 Heping West Road, Shijiazhuang, Hebei 050003, China ' Department of Management Engineering, Mechanical Engineering College, No. 97 Heping West Road, Shijiazhuang, Hebei 050003, China

Abstract: Selective maintenance is a process of identifying the sets of components to be repaired and corresponding maintenance activities to be performed when given sets of limited maintenance resources, such as time, budget, repairman, spares, etc. Examples of selective maintenance abound in applications such as manufacturing systems, military systems, power generation systems, etc. In this paper, a simulation method is proposed to optimally select the maintenance schemes, including the selected components to be repaired and maintenance tasks allocation with the objective of maximising system availability. Genetic algorithm (GA) is adopted to optimally allocate maintenance tasks to the limited repairman. An illustrative example is presented to demonstrate the applicability. Furthermore, the effects of repairman and mission duration on system availability are discussed in the end.

Keywords: selective maintenance; system availability; Monte Carlo simulation; genetic algorithms.

DOI: 10.1504/IJICA.2017.082493

International Journal of Innovative Computing and Applications, 2017 Vol.8 No.1, pp.12 - 20

Received: 16 Jan 2016
Accepted: 15 Mar 2016
Published online: 27 Feb 2017 *

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