Determining of an Optimal Maintenance Policy for Three State Machine Replacement Problem Using Dynamic Programming
| Autor: | Mohammad Saber Fallahnezhad, Morteza Pourgharibshahi |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | International Journal of Supply and Operations Management, Vol 4, Iss 2, Pp 180-192 (2017) |
| Druh dokumentu: | article |
| ISSN: | 2383-1359 2383-2525 |
| DOI: | 10.22034/2017.2.07 |
| Popis: | In this article, we present a sequential sampling plan for a three-state machine replacement problem using dynamic programming model. We consider an application of the Bayesian Inferences in a machine replacement problem. The machine was studied at different states of good, medium and bad. Discount dynamic programming (DDP) was applied to solve the three-state machine replacement problem, mainly to provide a policy for maintenance by considering item quality and to determine an optimal threshold policy for maintenance in the finite time horizon. A decision tree based on the sequential sampling which included the decisions of renew, repair and do-nothing was implemented in order to achieve a threshold for making an optimized decision minimizing expected final cost. According to condition-based maintenance, where the point of defective item is placed in continuing sampling area, we decided to repair the machine or to continue sampling. A sensitivity analysis technique shows that the optimal policy can be very sensitive. |
| Databáze: | Directory of Open Access Journals |
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