Abstract
In a highly competitive and capital-intensive industry, such as panel industry. To keep its competitive advantage, panel industry try to use the halftone mask into the process. Using halftone mask reduce the process flow into four. However, halftone mask easily lead to resist non-uniformity, these make panel industry need to control the resist uniformity to make sure that product quality is fine. Considering the cost of time and equipmetn, industry always use sampling to monitor the product quality, but sampling does not guarantee total quality management. In this study, we collect history data, using partial least squares to construct a virtual metrology framework to predict the halftone thickness. After the prediction model is built, not only reduce the frequency of measuring but help panel industry to inspect the whole production equipment, react deviant problem and reduce product cycle time then achieve high capacity goals. By cooperating with a well-known Taiwanese panel company to test the method validity and the MAPE of the validation data set was 3.96%, means a good representative of the prediction model.