Improved joint preventive maintenance and hedging point policy
We investigate the preventive maintenance and inventory control problem of a one-machine, one-product manufacturing system subject to random breakdowns. Both preventive and corrective interventions have random and non-negligible durations during which an excess of final products inventory is necessa...
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| Published in | International journal of production economics Vol. 127; no. 1; pp. 60 - 72 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
01.09.2010
Elsevier Elsevier Sequoia S.A |
| Series | International Journal of Production Economics |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-5273 1873-7579 1873-7579 |
| DOI | 10.1016/j.ijpe.2010.04.030 |
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| Abstract | We investigate the preventive maintenance and inventory control problem of a one-machine, one-product manufacturing system subject to random breakdowns. Both preventive and corrective interventions have random and non-negligible durations during which an excess of final products inventory is necessary to fulfill demand. The objective of this study is to find the production rate and the preventive maintenance schedule that minimize the total cost of maintenance and inventory/backlog in the case of periodic preventive maintenance. A near-optimal policy characterization with a simple structure is carried out using a numerical approach. Such a policy is a combination of a hedging point policy and a modified periodic preventive maintenance strategy, under which preventive maintenance actions are performed only if the inventory level exceeds a sufficient level. A simulation-based experimental approach is adopted to achieve a close approximation of the optimal control parameters. It is concluded from a sensitivity analysis and a comparative analysis that the near-optimal control policy leads to a significant cost reduction as compared to the combination of a hedging point policy and a classical periodic preventive maintenance policy. |
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| AbstractList | We investigate the preventive maintenance and inventory control problem of a one-machine, one-product manufacturing system subject to random breakdowns. Both preventive and corrective interventions have random and non-negligible durations during which an excess of final products inventory is necessary to fulfill demand. The objective of this study is to find the production rate and the preventive maintenance schedule that minimize the total cost of maintenance and inventory/backlog in the case of periodic preventive maintenance. A near-optimal policy characterization with a simple structure is carried out using a numerical approach. Such a policy is a combination of a hedging point policy and a modified periodic preventive maintenance strategy, under which preventive maintenance actions are performed only if the inventory level exceeds a sufficient level. A simulation-based experimental approach is adopted to achieve a close approximation of the optimal control parameters. It is concluded from a sensitivity analysis and a comparative analysis that the near-optimal control policy leads to a significant cost reduction as compared to the combination of a hedging point policy and a classical periodic preventive maintenance policy. We investigate the preventive maintenance and inventory control problem of a one-machine, one-product manufacturing system subject to random breakdowns. Both preventive and corrective interventions have random and non-negligible durations during which an excess of final products inventory is necessary to fulfill demand. The objective of this study is to find the production rate and the preventive maintenance schedule that minimize the total cost of maintenance and inventory/backlog in the case of periodic preventive maintenance. A near-optimal policy characterization with a simple structure is carried out using a numerical approach. Such a policy is a combination of a hedging point policy and a modified periodic preventive maintenance strategy, under which preventive maintenance actions are performed only if the inventory level exceeds a sufficient level. A simulation-based experimental approach is adopted to achieve a close approximation of the optimal control parameters. It is concluded from a sensitivity analysis and a comparative analysis that the near-optimal control policy leads to a significant cost reduction as compared to the combination of a hedging point policy and a classical periodic preventive maintenance policy. [PUBLICATION ABSTRACT] |
| Author | Gharbi, A. Berthaut, F. Kenné, J.-P. Boulet, J.-F. |
| Author_xml | – sequence: 1 givenname: F. surname: Berthaut fullname: Berthaut, F. email: francois.berthaut@polymtl.ca organization: Automated Production Engineering Department, École de technologie supérieure, Production System Design and Control Laboratory, University of Québec, 1100 Notre Dame Street West, Montreal, Que., Canada H3C 1K3 – sequence: 2 givenname: A. surname: Gharbi fullname: Gharbi, A. email: ali.gharbi@etsmtl.ca organization: Automated Production Engineering Department, École de technologie supérieure, Production System Design and Control Laboratory, University of Québec, 1100 Notre Dame Street West, Montreal, Que., Canada H3C 1K3 – sequence: 3 givenname: J.-P. surname: Kenné fullname: Kenné, J.-P. email: jean-pierre.kenne@etsmtl.ca organization: Mechanical Engineering Department, École de technologie supérieure, Integrated Production Technologies Laboratory, University of Québec, 1100 Notre Dame Street West, Montreal, Que., Canada H3C 1K3 – sequence: 4 givenname: J.-F. surname: Boulet fullname: Boulet, J.-F. email: JFBoulet@Trellisys.com organization: TRELLISYS TECHNOLOGIES, INC. 755, boul. Saint-Jean, bureau 400 Pointe-Claire, Que., Canada H9R 5M9 |
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| SubjectTerms | Computer simulation Cost reduction Demand Dynamische Optimierung Economics Instandhaltung Inventories Inventory control Lagerhaltungsmodell Maintenance costs Optimization Policies Preventive maintenance Preventive maintenance Stochastic dynamic programming Simulation Response surface methodology Produktionssystem Response surface methodology Sensitivity analysis Simulation Stochastic dynamic programming Stockpiling Studies |
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| Title | Improved joint preventive maintenance and hedging point policy |
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