TY - JOUR
T1 - A non-linear quality improvement model using SVR for manufacturing TFT-LCDs
AU - Li, Der Chiang
AU - Chen, Wen Chih
AU - Liu, Chiao Wen
AU - Lin, Yao San
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/6
Y1 - 2012/6
N2 - Thin Film Transistor-Liquid Crystal Displays (TFT-LCDs) are widely used in TVs, monitors, and PDAs. The key process of producing a TFT-LCD is using alignment to combine a Thin Film Transistor (TFT) panel with a Color Filter (CF) panel, which is called celling. The defined cell vernier, which indicates the alignment error, is an important quality index in the manufacturing process. In the CF manufacturing process, the cell vernier is difficult to control because it depends on six TPEs (Total Pitch Errors), with each TPE highly dependent on the others. This paper aims to improve the cell vernier forecasting model with the six TPE attributes to enhance the production yield in the CFmanufacturing process. Using the six dependent variables, this study found that the SVR(SupportVector Machine for Regression) model is the fittest for generating quality results that meet the designed specifications.
AB - Thin Film Transistor-Liquid Crystal Displays (TFT-LCDs) are widely used in TVs, monitors, and PDAs. The key process of producing a TFT-LCD is using alignment to combine a Thin Film Transistor (TFT) panel with a Color Filter (CF) panel, which is called celling. The defined cell vernier, which indicates the alignment error, is an important quality index in the manufacturing process. In the CF manufacturing process, the cell vernier is difficult to control because it depends on six TPEs (Total Pitch Errors), with each TPE highly dependent on the others. This paper aims to improve the cell vernier forecasting model with the six TPE attributes to enhance the production yield in the CFmanufacturing process. Using the six dependent variables, this study found that the SVR(SupportVector Machine for Regression) model is the fittest for generating quality results that meet the designed specifications.
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U2 - 10.1007/s10845-010-0440-1
DO - 10.1007/s10845-010-0440-1
M3 - Article
AN - SCOPUS:84862293299
SN - 0956-5515
VL - 23
SP - 835
EP - 844
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
IS - 3
ER -