Title
Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams
Abstract
The paper deals with a maintenance grouping approach for multi-component systems whose components are connected in series. The considered systems are required to serve a sequence of missions with limited breaks/stoppage durations while maintenance teams (repairmen) are limited and may vary over time. The optimization of the maintenance grouping decision for such multi-component systems leads to a NP-complete problem. The aim of the paper is to propose and to optimize a dynamic maintenance decision rule on a rolling horizon. The heuristic optimization scheme for the maintenance decision is developed by implementing two optimization algorithms (genetic algorithm and MULTIFIT) to find an optimal maintenance planning under both availability and limited repairmen constraints. Thanks to the proposed maintenance approach, impacts of availability constraints or/and limited maintenance teams on the maintenance planning and grouping are highlighted. In addition, the proposed grouping approach allows also updating online the maintenance planning in dynamic contexts such as the change of required availability level and/or the change of repairmen over time. A numerical example of a 20-component system is introduced to illustrate the use and the advantages of the proposed approach in the maintenance optimization framework.
Year
DOI
Venue
2015
10.1016/j.ress.2015.04.022
Reliability Engineering & System Safety
Keywords
Field
DocType
Multi-component systems,Maintenance grouping,Availability,Repairmen,Genetic algorithm,MULTIFIT algorithm
Decision rule,Rolling horizon,Heuristic,Maintenance planning,Optimization algorithm,Engineering,Optimal maintenance,Dynamic maintenance,Reliability engineering,Genetic algorithm
Journal
Volume
ISSN
Citations 
142
0951-8320
9
PageRank 
References 
Authors
0.52
17
4
Name
Order
Citations
PageRank
Phuc Do Van11025.63
Hai Canh Vu2413.25
Anne Barros324318.42
Christophe Bérenguer426219.23