Reinforcement Learning for Process Control with Application in Semiconductor Manufacturing

Abstract

Process control is crucial in semiconductor manufacturing to reduce variations and enhance product quality. This study introduces reinforcement learning (RL) methods for process control, proposing a new RL-based controller that outperforms traditional run-to-run controllers, especially in handling complex nonlinear processes.

Juan Du

Assistant Professor

My research interests include knowledge-infused data science for quality improvement, industrial data analytics and machine learning, and system informatics and control for manufacturing applications.