英文摘要
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In the LCD manufacturing process, the TEG (Test Element Group) electric measure value on Array's process and Array NG Rank are highly correlated in the Cell process. The panel is judged as Array NG Rank 4 will be scrapped. If the Rank in Array NG can be predicted, the waste and the cost can be reduced from unnecessary materials be input into the scrapped panels. Therefore, the research developed a defects rank prediction model by analyzing electric character on Array's process. The model development is divided into two parts. Firstly, using the Logistic regression analysis to find out a better predictive rate in predicting Array NG's Rank and introduce key factors from a group of TEG values. Secondly, according to the analysis results, the models were evaluated based on the predictive accuracy rate of the test sets. The Logistic regression model had 96.17% classification correction rate and the key factors are Vth, Rs1, Rge2, Rsd1 and Rsd2. The prediction model is constructed by analyzing the correlation between TEG electric measure values and Array NG Ranks. The results showed that there is a high ability (96.15%) to predict Array NG Rank 4. The cost saving reaches NT 840,600 dollars with 45 work hours per month.
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