2014
DOI: 10.1016/j.ress.2013.07.009
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Integrating noncyclical preventive maintenance scheduling and production planning for multi-state systems

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Cited by 107 publications
(32 citation statements)
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“…Note that M indicates the PM activity can fully restore the product to its status immediately after the previous PM activity, where the repair work is allowed to be minimal. Similar assumption of minimal repair can be seen in the existing PM literature [46,43,11]. Furthermore, the PM activities are considered to be imperfect, and an AGAN condition cannot be thus available.…”
Section: The Warranty Policy With Preventive Maintenancementioning
confidence: 78%
“…Note that M indicates the PM activity can fully restore the product to its status immediately after the previous PM activity, where the repair work is allowed to be minimal. Similar assumption of minimal repair can be seen in the existing PM literature [46,43,11]. Furthermore, the PM activities are considered to be imperfect, and an AGAN condition cannot be thus available.…”
Section: The Warranty Policy With Preventive Maintenancementioning
confidence: 78%
“…Zhao et al [27] assume order-dependent-failure (ODF) and proposed an iterative method to solve the problem on a single-machine system. Fitouhi and Nourelfath [28] extended the model [23] to multi-state systems. Recently, Yalaoui et al [29] proposed some very interesting exact and heuristic algorithms to efficiently solve moderate to larger instances of the model proposed in [24].…”
Section: A Brief Review Of the Literaturementioning
confidence: 99%
“…Fitouhi and Nourelfath [8] developed an integrated model for planning production and non-cyclical PM for a single machine. The backorder cost is considered and an enumeration method is used to get all of the PM solutions in the model, which was later extended in [9] to multi-state systems. Nourelfath et al [15] also developed an integrated model for production and PM planning in multi-stage systems, where the preventive maintenance selection task in the integrated planning model is solved using a genetic algorithm.…”
Section: Assumptionsmentioning
confidence: 99%