A PRODUCTION PLANNING APPROACH BASED ON ITERATIONS OF LINEAR PROGRAMMING OPTIMIZATION AND FLOW TIME PREDICTION

ABSTRACT In long flow time manufacturing environments like those found in the semiconductor industry, a production planning system needs accurate future flow time parameters to generate an effective plans. However, the future flow time parameters used in a planning system depend on future product demand mix. Formerly, an iterative computational approach proposed by Hung and Leachman was used to converge the differences in flow time parameters between a production planning model and a simulation model. The simulation model is used to predict the future flow times for the production planning model. Due to the difficulty of obtaining and running an accurate simulation model, this paper suggests a new prediction model to replace the simulation model in the iterative scheme. Using the same data set used by Hung and Leachman, a new prediction model provides very good results. As a result, this research suggests an efficient way to obtain an accurate production plan for long complex manufacturing processes such as semiconductor industry.