A Multivariate Self-tuning Controller for Run-to-Run Semiconductor Manufacturing Process

• Main Authors: Chih-Hung Jen, 任志宏
• Other Authors: B. C. Jiang
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/51333922255782880902

碩士 === 元智大學 === 工業工程研究所 === 89 === During recent years, “Run-to-Run” (R2R) control techniques have been developed and used to control various semiconductor manufacturing processes. The R2R control methodology combines response surface modeling, engineering process control (EPC), and statistical process control (SPC). The main objective of such control is to manipulate the recipe so as to maintain the process output of each run as close to the nominal target as possible. The primary focus of this research is on the multiple- input-multiple-output (MIMO) control for self-tuning control of R2R processes. The controller compensates for a variety of disturbances frequently encountered in semiconductor manufacturing, that is, a structured noise of an ARIMA form. The controller also compensates for system dynamics, including autocorrelated responses, deterministic drifts, process shifts, and process gains. Self-tuning controllers are developed to provide on-line parameter estimation and control. A recursive least squares (RLS) algorithm is normally employed to provide on-line parameter estimation to the controller. So, this control strategy used in a self-tuning controller applies the principle of minimizing total cost, in a sense of an expected off-target and controllable factors adjustment, to obtain a recipe for the next run. It is shown via experimental study even if control model is nonlinear, the self-tuning controller algorithm presented herein can offer better control performance for R2R applications as compared to those of the control action of linear approach of self-tuning controller and the optimizing adaptive quality controller (OAQC) module. At last, a relevant application to Chemical Mechanical Planarization (CMP) in semiconductor manufacturing, a critical step involving two quality characteristics (removal rate and within-wafer nonuniformity), is used to illustrate the proposed controller.