Configuration of manufacturing networks by a multi-objective perspective enabled by simulation and machine learning

Manufacturing companies are facing an increasingly volatile environment today. Internal manufacturing networks are becoming ever more important for ensuring competitive survival. The objective of this research is to introduce an iterative approach for the configuration of manufacturing networks by increasing the transparency for decision making including effects on tactical and operational level. In this context a combined method with discrete event simulation and machine learning is considered. The results of the new approach were validated within a use case at an Austrian company in the railway sector by reconfiguration of the manufacturing network consisting of 4 sites.