| Summary: | 碩士 === 國立交通大學 === 管理學院碩士在職專班工業工程與管理組 === 96 === Taiwan is the major TFT-LCD (Thin-Film Transistor Liquid-Crystal Display) manufacture and engineering base in the world. Owing to quite huge amount of expense in design and production facilities, the necessary survival criteria for this industry based on how to shorten the manufacturing time, maintain the high quality, cut the product lifecycle and expedite the newer model design on current market, have become critical issue.
This research aims to deduct the TFT-LCD test items on manufacturing process via applying Neural Network approach. We expect to reduce the test time and the facility investment, and hopelly to get the same or less inaccuracy test results between reduced test items and original test items. Moreover, the TFT-LCD quality classified results by reduced test items are approximately the same as them by keeping the original test items. This research uses a real example to demonstrate the validity of Neural Network approach and also does the comparison to the traditional statistic regression analysis.
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