Integrated imperfect multimission selective maintenance and repairpersons assignment problem

被引:57
作者
Chaabane, K. [1 ]
Khatab, A. [1 ]
Diallo, C. [2 ]
Aghezzaf, E. -H. [3 ,4 ]
Venkatadri, U. [2 ]
机构
[1] Lorraine Univ, Lab Comp Engn Prod & Maintenance, Metz, France
[2] Dalhousie Univ, Dept Ind Engn, Halifax, NS, Canada
[3] Univ Ghent, Dept Ind Syst Engn & Prod Design, Fac Engn & Architecture, Ghent, Belgium
[4] Flanders Make, Ind Syst Engn ISyE, Lommel, Belgium
关键词
Multimission selective maintenance; Reliability; Preventive maintenance; Repairpersons assignment; Optimization; MULTISTATE SYSTEMS; OPTIMIZATION; STRATEGY; MODELS; BREAKS;
D O I
10.1016/j.ress.2020.106895
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents a new variant of the selective maintenance problem (SMP) to jointly optimize the maintenance planning and resource allocation problems for multiple missions. The classical SMP deals with components and maintenance level selection with the aim of maximizing the system reliability given limited budget and break duration. Of the few papers dealing with the multimission SMP, none addresses the repairperson assignment problem. This work develops an SMP model for jointly optimizing maintenance and assignment decisions in a system running multiple missions. The resulting SMP addresses five joint decisions: selection of components to maintain, selection of maintenance levels performed on the selected components, identification of breaks where maintenance tasks are performed, repairpersons selection, and maintenance tasks assignment to selected repairpersons. The objective is to minimize the total maintenance and labour costs for a maintenance plan that guarantees a given reliability threshold. The fundamental constructs and the relevant parameters of this SMP are developed and discussed. Given its combinatorial complexity, a heuristic method based on the genetic algorithm is developed and implemented as a solution technique. Results from numerical experiments carried out demonstrate the validity and the benefits of the proposed approach, and show the robustness and efficiency of the developed heuristic.
引用
收藏
页数:13
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