Maintenance planning and dynamic grouping for multi-component systems with positive and negative economic dependencies

Vu, Hai Canh; Van, Phuc Do; Barros, Anne; Bérenguer, Christophe

doi:10.1093/imaman/dpu007

Cited by 33 publications

(25 citation statements)

References 29 publications

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“…One may notice that, in recent years, many authors have devoted considerable effort on developing novel methods to model repair processes, (see, e.g. Jain & Gupta, 2013;Liang & Parlikad, 2015;Sheu et al, 2015;Vu et al, 2015;Wu & Scarf, 2015, 2017Zhao et al, 2015;Wu, 2017). We consider the current paper and the process we describe as a further important contribution to the literature on the modelling the failure process of a repairable system.…”

Section: Contribution and Importance Of This Workmentioning

confidence: 99%

The semi-geometric process and some properties

Wang

2017

IMA Journal of Management Mathematics

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The geometric process has been widely applied in reliability engineering and other areas since its introduction. One of its assumptions is that the times between occurrences of events are independent. This assumption is rather restrictive and can limit its application in the real world. This paper extends the geometric process to a new process, which we call the semi-geometric process, by relaxing this assumption. Some probabilistic properties of the process are derived and parameter estimation is described. A numerical example, based on a real-world data set, is used to illustrate the model and validate the estimation methodology.

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Section: Contribution and Importance Of This Workmentioning

confidence: 99%

The semi-geometric process and some properties

Wang

2017

IMA Journal of Management Mathematics

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“…These kind of situations, which are referred to, in this paper, as "dynamic contexts", may have significant influence on the maintenance planning and cost and should be taken into account in the maintenance optimization process. It should be noticed that other kinds of dynamic contexts such as maintenance opportunities, changes in production planning, changes in the system structure have been investigated in maintenance optimization, see [7,29].…”

Section: Maintenance Constraints and Dynamic Contextsmentioning

confidence: 99%

“…This approach is however limited to a class of problems with two significant assumptions: (i) maintenance durations are neglected; (ii) each component is preventively maintained one time in horizon interval. To overcome these limitations, several extensions of the rolling horizon approach have been recently developed in [7,29]. Nevertheless in such papers, maintenance constraints have not yet been considered.…”

Section: Introductionmentioning

confidence: 99%

Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams

Van

Barros

et al. 2015

Reliability Engineering & System Safety

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International audienceThe 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

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“…[12,13] to solve the maintenance optimisation problem. The genetic algorithm was also employed by Vu et al [14] in their study of maintenance planning and dynamic grouping problem of complex systems with either positive or negative economic Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/ress dependence. Doostparast et al [15] used the simulated annealing algorithm to identify the optimal maintenance plan to minimise the total maintenance cost with respect to a desired level of system reliability.…”

Section: Introductionmentioning

confidence: 99%