Supporting Fab Operations Using Multi-Agent Reinforcement Learning

Over recent years semiconductor operations have grown in scope, dynamics, and complexity and consequently advanced scheduling algorithms and manufacturing engineers can no longer quickly estimate the best performing schedule. In this paper we present how machine learning, in real time, can be used to augment and support manufacturing engineers. The presented results, obtained from production deployments, show that AI assisted scheduling can improve Key Performance Indicators by, on average, over 2% with little to no downside.