An optimal maintenance policy for machine replacement problem using dynamic programming

• Main Authors: Mohsen Sadegh Amalnik, Morteza Pourgharibshahi
• Format: Article
• Language: English
• Published: Growing Science 2017-06-01
• Series: Management Science Letters
• Subjects: Machine replacement; Dynamic programming; Sequential sampling plan; Maintenance
• Online Access: http://www.growingscience.com/msl/Vol7/msl_2017_9.pdf

In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling including renew, repair and do nothing and wish to achieve an optimal threshold for making decisions including renew, repair and continue the production in order to minimize the expected cost. Results show that the optimal policy is sensitive to the data, for the probability of defective machines and parameters defined in the model. This can be clearly demonstrated by a sensitivity analysis technique.