Simulation-Based Performance Assessment of Production Planning Models With Safety Stock and Forecast Evolution in Semiconductor Wafer Fabrication

Abstract

We study the performance of production planning models for wafer fabs in a rolling horizon setting under stochastic demand modeled using the Martingale Model of Forecast Evolution (MMFE). The models differ in how they incorporate lead times and safety stocks. The number of frozen periods is considered as an experimental factor to study the nervousness of the resulting plans. Our simulation experiments show that chance-constrained production planning models that integrate safety stock and production planning decisions outperform others. The formulations with workload-dependent lead times also outperform those with fixed lead times that are an integer multiple of the period length.