Master Production Schedule Stability Under Conditions of Finite Capacity

ABSTRACT

In this article, we propose a new way to improve master production schedule (MPS) stability under conditions of finite capacity. The purpose is to optimize product availability and customer service for typical situations encountered in the consumer goods industry. Using a comprehensive MPS model, we conduct a simulation study with experimental design to identify factors having a significant influence on MPS stability. Then we perform sensitivity analysis on select factors that hold the greatest promise for improvement by employing a simple predictive equation. Finally, we test a different way to plan safety stocks and report the results. In general, elimination of forecast bias and choice of safety stock method both are particularly important for improving MPS stability and ultimately customer service.

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This study from MIT uses a Six Sigma tool, Experimental Design, to propose a new approach to MPS stability for FMCG companies. Topics include the frozen period, forecast bias, and reducing waste in calculating safety stock