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國立虎尾科技大學學報

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篇名 應用德爾菲法及分析網路程序法於半導體分析晶片缺點因子改善製程良率之研究
卷期 30:2
並列篇名 Analyzing the Defect Factors to Improve Process Yield of Semiconductor with ANP and Delphi Method
作者 張洝源周大鈞
頁次 017-036
關鍵字 德爾菲法分析網路程序法半導體化學氣相沉積晶片缺點Delphi MethodAnalytic Network ProcessDefects in Semiconductor Chemical Vapor Deposition Chip
出刊日期 201106

中文摘要

台灣為全球半導體產業的生產重鎮,晶圓代工產業市佔率更是居世界第一之要角,為了持續維持晶圓代工產業之優勢,晶片的生產良率一直是半導體製造業的重要指標,然而減少晶片缺點為增加晶片良率的最佳解決方案。本研究針對半導體製造過程中造成化學氣相沉積晶片缺點之因子,進行篩選及評估,從中找出影響產品缺點的關鍵因子,以利於提升產品良率,增加產出並創造公司利潤。本研究經由人力、設備、材料與方法等四大構面,由特性要因圖法找出各影響缺點之重要因子,並且使用德爾菲(Delphi)法以及分析網路程序(Analytical Network Process, ANP)法來決定各因子之重要性權重,以探討造成化學氣相沉積晶片缺點的重要關鍵因子,研究結果顯示影響權重最重要之項目為零件異常之因子,以利半導體製造業解決缺點之參考。

英文摘要

Taiwan, as being the leader of semiconductor industry, as well as the world number one player of the market share in the foundry industry, in order to continuously maintain the advantage for its foundry industry, the
production yield of chip is always the key indicator for Taiwan’s semiconductor manufacturing industry; however, the reduction of defects in chips will be the best solution to improve the chip yield. Therefore, this study is mainly to explore the factors of causing defects of Chemical Vapor Deposition (CVD) Chip in the manufacturing process of semiconductor with conducting the screening and evaluation, and then sorted out the key factors of influencing and causing the defect in products so as to improve the product yield, increase the productivity and create benefit for relevant companies. This study has adopted the literature review and conducted the factor screening and evaluation together with professional personnel of the semiconductor industry, and made use of the Cause-and-Effect Diagram to find out the key factor of each influential defect by way of these 4 major aspects: manpower, equipment, material and methodology. Moreover, Delphi Method and
Analytical Network Process (ANP) have been used to determine the importance weight of each factor in order to explore the key factor in causing defects in CVD Chip. In the research result, it discovered that the most important item of influencing the weight is the factor of abnormal parts, and this result can be provided as the reference to resolve the defects in the semiconductor manufacturing industry.

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