Run-to-Run Fault Prediction for Semiconductor Manufacturing Process Based on Variable Forgetting Factor RLS

Abstract

Run-to-Run (RtR) control has been widely used in semiconductor manufacturing industry nowadays. Recursive Least Squares (RLS) approach is an important data-driven algorithm. Both the drift disturbance and the fault will seriously affect the product quality in semiconductor manufacturing process. This paper proposes a variable forgetting factor RLS output prediction method for semiconductor manufacturing process with a fault and the disturbance without and with a drift. In order to improve the accuracy of predictions, we propose a kind of method which adjusts the forgetting factor online, making predicted values track the wide fluctuations of actual output values well, and predict the output 's future fluctuations in case of faults. It has both a strong ability to track parameters, and a small convergence estimate error. Simulation results show that this prediction method works well, has better portability and higher accuracy, can provide effective information for fault warning, fault-tolerant control and health management, furthermore will avoid huge losses in actual production.