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  • 學位論文

非自然型態之管制圖關鍵影響因素研究-以低溫多晶矽薄膜電晶體液晶顯示器之微影製程為例

Research on Critical Factors of Unnatural Control Chart Patterns- A Case Study of Lithography Process in LTPS TFT LCD

指導教授 : 蘇朝墩
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摘要


管制圖廣泛應用於製造業的品質管理,其目的在於監控產品於生產過程中的加工品質。然而於實際生產中,卻因製程中的關鍵因素的變異,管制圖常會呈現出特殊的特徵。針對這些隱藏於這些管制圖異常的型態的背後的關鍵因素,若能即時釐清及改善,將可提升產品品質。 本論文首先討論傳統產業與LTPS-TFT-LCD 產業於品質制系統方面之差異,以建立巨觀的品質概念。 接著,針對LTPS-TFT-LCD 產業主要關鍵製程之微影製程,運用石川圖 (Ishikawa Diagram) 分析造成品質異常的要因,以提供管制圖異常分析的資訊。最後,透過案例分析,本研究針對管制圖6種異常型態進行解析,發掘造成管制圖異常型態之關鍵因素。並進行相關的討論。

並列摘要


Control chart has been widely implemented in manufacturing for quality management, and its purpose is to monitor the product quality during the manufacturing process. However, caused by key-factors’ variation, Control-chart, collected from actual production process, will appear with special characteristics. Thus, if could identify and improve these key-factors, hidden to contribute the abnormal Control chart, on time, product quality could be improved. Firstly, the differentiation of quality control system between Conventional and LTPS-TFT-LCD industries is discussed; through the discussion, macro quality concept is built. Next, aiming at lithography process, most critical in LTPS-TFT-LCD manufacturing, adopt Ishikawa Diagram to analyze the defect-cause(s), and provide the analysis information for Control chart. Finally, through the real practical case study, the research concentrates on analyzing six abnormal modes in control chart, finding out the critical factors and further discussing the related question.

並列關鍵字

Control Chart LTPS Lithography process CD Overlay accuracy

參考文獻


【4】顧瑞祥,施柄光,2006,「結合製程統計特徵值與類神經網路於管制圖異常形狀之辨識」,中華民國品質學會弟42 屆年會暨第12屆全國品質管理研討會。
【7】Guh, R.S., 2005, A hybrid learning-based model for on-line detection and analysis of control chart patterns, Computers & Industrial Engineering, 49, 35 - 62.
【8】Yang, J.H., Yang, M.S., 2005, A control chart pattern recognition system using a statistical correlation coefficient method, Computers & Industrial Engineering, 48, 205 - 221.
【11】Chrysler, Ford, and General Motors, Statistical Process Control Reference Manual, 1995, AIAG.

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