Supporting Fab Operations Using Multi-Agent Reinforcement Learning (WinterSim 2024)

The work here has been published during the 2024 version of the annual Winter Simulation Conference. You can read the abstract below, to read the full paper please fill in the information in the form on this page.

ABSTRACT

Over recent years semiconductor operations have grown in scope, dynamics, and complexity. 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 in Micron’s fabs, show that AI assisted scheduling can improve Key Performance Indicators with little to no downside.