TY - JOUR ID - 2730 TI - Determining of an Optimal Maintenance Policy for Three State Machine Replacement Problem Using Dynamic Programming JO - International Journal of Supply and Operations Management JA - IJSOM LA - en SN - 23831359 AU - Fallahnezhad, Mohammad Saber AU - Pourgharibshahi, Morteza AD - Department of Industrial Engineering, Yazd University, Yazd, Iran Y1 - 2017 PY - 2017 VL - 4 IS - 2 SP - 180 EP - 192 KW - Machine replacement KW - Dynamic programming KW - Sequential sampling plan KW - Maintenance DO - 10.22034/2017.2.07 N2 - 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.  UR - http://www.ijsom.com/article_2730.html L1 - http://www.ijsom.com/article_2730_0472c06ac5a83a39fbb39a71d569304d.pdf ER -