| Summary: | 碩士 === 中原大學 === 機械工程研究所 === 97 === Abstract
TFT-LCD display has replaced the traditional CRT because of its advantages, such as lightweight, portability, and small volume. However, under the extreme competition, TFT-LCD plants have to not only market but also promote their product quality in order to dominate the market share. Currently, statistical process control (SPC) is a major method adopted by most of fabs to monitor the important process parameters. Once an abnormal operation occurs, SPC system will issue an alarm. Unfortunately, it cannot predict the happening of any abnormal operations. Engineers must also rely on routine metrology to inspect defect products which are out of specifications (beyond process control limits). Usually, the product measurements are not performed after the fabrication process. The lot of product often stands in a queue for metrology. In this situation, several lots of defect products might be not inspected when abnormal operation occurs. It results in yield loss and, moreover, producing many scraps.
Virtual metrology is a technology for predictive detection. It can be regarded as the evolution system of SPC to achieve the quality prediction for TFT-LCD manufacturing. In this study, the developed virtual metrology technique is applied to the prediction of uniformity of surface resistance in the PVD process. It integrates the wavelet transform for predicting the process trend and the fuzzy neural network for estimating the process outcome due to recipe tuning. The virtual metrology technique can effectively predict the uniformity of surface resistance in the PVD process. It promotes the process quality and the overall equipment efficiency.
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