Abstract
This study investigates the decisions with the integration of order selection and maintenance decision problem for make-to-order (MTO) manufacturers with single deteriorating machine. In MTO manufacturing environments, future orders with varying ready dates, due dates, normal processing times, and revenues arrive randomly from a non-homogeneous Poisson process. Moreover, for a deteriorating machine, the more jobs processed before a maintenance activity, the longer the processing time of an order due to machine wear. A maintenance activity restores the deteriorating status of the machine and hence increases its production rate. During a maintenance activity, the machine is shut down, which results in production delay. However, the processing times of future accepted orders will be reduced. With the objective of maximizing overall long-term profit, proper decisions of both maintenance and order acceptance are necessary to better utilizing the limited capacity. Two types of maintenance environments, full maintenance and partial maintenance, are considered in this study. For full maintenance environment, a static maintenance and order selection (SMAOS) decision method is proposed to solve the decision problems. In addition, a dynamic decision method called simulated expected revenue decision procedure (SER) proposed by Yeh (2012) is adopted and modified in this study. Simulation experiments for full maintenance environment are conducted to compare the performance of SER and SMAOS with a simple FCFS with maximum deteriorating rate (FMDR) policy. According to the experiment results, both SMAOS and SER outperform FMDR by an average profit of 63%. However, due to long computation times for the partial maintenance environment, the experiments or the improvements in decision algorithms are left as future research directions.