A Dynamical Model Tuning and Non-linear Minimum Variance Controller for Advanced Photolithography Process Control

• Main Authors: Chih-Ming Hung, 洪志明
• Other Authors: An-Chen LEE
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/53054639220542520545

碩士 === 國立交通大學 === 工學院碩士在職專班精密與自動化工程學程 === 94 === This thesis presents a new run-to-run (R2R) multiple-input-single-out controller for photolithography process. The controller, termed dynamical minimum variance controller, can act both as a dynamical model optimizer and as a controller for given models. In this thesis, the relationships and run-to-run control model among input recipes (Exposure dose and Focus) and output variables (Critical Dimension) are formed by using experimental design method. Then on-line (Recursive) model identification and recipes generation under input and output constraints are performed by using dynamical model optimizer and non-linear minimum variance controller, respectively. Improvements due to advanced control have been quantified in simulations and actual fab operations.