Aggregated Simulation Modeling to Assess Product-Specific Safety Stock Targets During Market Up-and Downswings: A Case Study

In this study, we propose an aggregated simulation model of the back-end supply chain for manufacturing semiconductors. The simulation model is applied to real-world data from NXP Semiconductors N.V. to assess the need for safety stock at the die bank during market up- and downswings, respectively. To model demand uncertainty, we use future forecasts and adjust them by sampling from discrete distributions of historical forecast errors. For modeling supply, we propose an aggregated simulation model of the back-end supply chain and assume a front-end process that produces to forecast (Make To Stock) with the addition of safety stock. We conclude from experiments that during market up- or downswings, the impact of safety stock target levels on supply chain performance differs significantly. The proposed method allows supply chain managers to assess the impact of safety stock target levels on key performance indicators.