Simulation-assisted decision making for supply chain disruption in production control

Supply chain disruptions with an unpredictable occurrence such as significant differences between forecasts and actual customer demands are challenging for semiconductor manufacturers. Normally, these events are responded to with a time-consuming mostly manual procedure. This work describes an approach for an automated framework to react faster and with less effort on these unpredictable events. Within this framework simulation is necessary for the evaluation of automated decisions. Therefore, a discrete event simulation and a simulation based on a system dynamics approach have been combined. As a result of this framework's approach, safety stocks can be reduced due to a more accurate cycle time prediction and a reduced number of false alarms regarding supply chain disruptions.