Abstract: Nowadays, TFT-LCD manufacturing has become a very complex process, with many different products being manufactured with many different tools. The ability to predict the quality of product in such a high-mix system is critical to developing and maintaining a high yield. In this paper, a statistical method is proposed for building a virtual metrology model from a number of products using a high-mix manufacturing process. Stepwise regression is used to select “key variables" that really affect the quality of the products. Multivariate analysis of covariance is also proposed for simultaneously applying the selected variables and product effect. This framework provides a systematic method of building a processing quality prediction system for a high-mix manufacturing process. The experimental results show that the proposed quality prognostic system can not only estimate the critical dimension accurately but also detect potentially faulty glasses.

Key words: Stepwise regression, virtual metrology, MANCOVA, Thin Film Transistor Liquid Crystal Display (TFT-LCD), 虚拟量测, 共变异数分析, 薄膜晶体管液晶显示器