臺灣博碩士論文加值系統

對於半導體製造廠的產品的競爭力而言，良率無疑是最重要的因素。因此使用良率來評估單一產品的競爭力是一個合理的想法。為此我們延伸Chen在這方面的研究，根據產品的良率學習模式，從一個新的觀點-中期競爭力的趨勢，來評估產品的長期競爭力。此外，我們亦建構一非線性規劃模式，對於產能重新分配提出最佳化方案，以提升產品的長期競爭力。本研究用一實例來證明我們所提出的方法的可用性。實驗結果顯示，欲最佳化產品的長期競爭力，每月應給予1.675萬片的多餘產能。另外，最有效率的方法是每月多分配給該產品16,000片晶圓的產能。以上結果有助於產能重新分配的決策。

Yield is undoubtedly the most critical factor to the competitiveness of a product in a semiconductor manufacturing factory. Therefore, evaluating the competitiveness of a product with its yield is a reasonable idea. For this purpose, Chen’s approach is extended in this study to evaluate the long-term competitiveness of a product based on its yield learning model from a new viewpoint – the trend in the mid-term competitiveness. Subsequently, to enhance the long-term competitiveness of a product, a nonlinear programming approach is proposed to optimize the effects of capacity re-allocation. A practical example is used to demonstrate the proposed methodology. Experimental results show that with an additional capacity of 16,750 wafers per month, the long-term competitiveness of the product is maximized. Besides, the most efficient way is to allocate 16,000 more wafers per month to the product. These results are helpful in making capacity re-allocation decisions.

誌謝 I
摘要 II
ABSTRACT III
目 錄 IV
圖 目 錄 VI
表 目 錄 VII
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 研究方法 2
第二章 文獻探討 5
2.1 台灣半導體產業的競爭力 5
2.2 良率與競爭力的關係 7
2.3 良率與其他系統績效之間的關係 14
2.4 良率學習模式 18
2.5 評價產品的中期競爭力 19
2.6 評價產品的長期競爭力 20
2.7 重新分配產能以提高長期競爭力 20
第三章 研究方法 22
3.1 一個新的觀點：中期競爭力的趨勢 22
3.2 提高長期競爭力-NP模型 22
第四章 實例驗證結果與分析 25
4.1評價產品的中期競爭力 25
4.2 評價產品的長期競爭力 26
4.3 重新分配產能以提高長期競爭力 28
4.4 一個新的觀點：中期競爭力的趨勢 30
4.5 提高長期競爭力-NP方案模型 31
第五章 結論和未來的研究方向 36
參考文獻 37
附錄A 評估競爭力的LINGO程式碼 42
附錄B 產能為5,000片時之競爭力 45
附錄C 產能為8,000片時之競爭力 46
附錄D 產能為7,150片時之競爭力 47
附錄E 產能為21,750片時之競爭力 48
附錄F 檢查點的產品中期競爭力驗證VBA程式碼 49

英文部分
【1】Armstrong, E (1989) ‘Principles for competitive semiconductor manufacturing’, Proceedings of IEEE SEMI International Semiconductor Manufacturing Science Symposium’89, pp. 67-72.
【2】Atherton, L.F., and Atherton, R.W.,(1995), ‘Wafer Fabrication: Factory Performance and Analysis, Kluwer Academic Publishers.
【3】Chen, T., Wang, M.-J.J. (1995) ‘Applying fuzzy set approach to signal detection theory’ Fuzzy Sets and Systems Vol. 72, pp. 39–49.
【4】Chen, T. (2007) ‘A fuzzy logic approach for incorporating the effects of managerial actions on semiconductor yield learning’ in: Proc. of 2007 Internat. Conf. on Machine Learning and Cybernetics, Hong Kong, pp. 1979–1984.
【5】Chen, T. (2007) ‘Evaluating the mid-term competitiveness of a product in a semiconductor fabrication factory with a systematic procedure’, Computers & Industrial Engineering, Vol. 53, pp. 499-513.
【6】Chen, T. (2008a) ‘A FNP approach for evaluating and enhancing the long-term competitiveness of a semiconductor fabrication factory through yield learning modeling’, International Journal of Advanced Manufacturing Technology, in press.
【7】Chen, T. (2008b) ‘Estimating and incorporating the effects of a future QE project into the semiconductor yield learning model with a fuzzy set approach’, European Journal of Industrial Engineering, in press.
【8】Chen, T., and Lin Y.-C. (2008) ‘A fuzzy-neural system incorporating unequally important expert opinions for semiconductor yield forecasting’, International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems, Vol. 16, Issue 1, pp. 35-58.
【9】Chen, T., and Wang, M.-J. J. (1999) ‘A fuzzy set approach for yield learning modeling in wafer manufacturing’, IEEE Transactions on Semiconductor Manufacturing, Vol. 12, No. 2, pp. 252-258.
【10】Chen, T., and Wang, Y.-C. (2008) ‘A fuzzy set approach for evaluating and enhancing the mid-term competitiveness of a semiconductor factory’, Fuzzy Sets and Systems, in press.
【11】Crowder, B.C. (1989) ‘Manufacturing science and manufacturing competitiveness’, Proceedings of IEEE SEMI International Semiconductor Manufacturing Science Symposium’89, pp. 32–33.
【12】Cunningham, J. A. (1990) ‘The use and evaluation of yield models in integrated circuit manufacturing’, IEEE Transactions on Semiconductor Manufacturing, Vol. 3, No. 2, pp. 60–71.
【13】Cunningham, S.P., Spanos, C.J.,Voros, K. (1995) ‘Semiconductor Yied Improvement: Results and best Practives’, IEEE Transactions on Semiconductor Manufacturing, Vo1. 8, No. 2, pp. 103-109
【14】Deffree, S. (2007) ‘semiconductor winners and losers split by competitiveness’,http://www.electronicsweekly.com/.
【15】Gruber, H. (1984) ‘Learning and Strategic Product Innovation: Theory and Evidence for the Semiconductor Industry, The Netherlands: Elsevier Science B. V.
【16】Haller, M., Peikert, A., and Thoma, J. (2003) ‘Cycle time management during production ramp-up’, Robotics and Computer Integrated Manufacturing, Vol. 19, pp. 183-188.
【17】Jenkins, T., Phail, F., and Sackman, S. (1990) ‘Semiconductor competitiveness in the 1990s’, Proceedings - Society of Automotive Engineers, Vol. P223, pp. 249-255.
【18】Li, T.-S., Huang, C.-L., and Wu, Z.-Y. (2006) ‘Data mining using genetic programming for construction of a semiconductor manufacturing yield rate prediction system’, International Journal of Advanced Manufacturing Technology, Vol. 17, pp. 355-361.
【19】Liao, S.-H., and Hu, T.-C. (2007) ‘Knowledge transfer and competitive advantage on environmental uncertainty: An empirical study of the Taiwan semiconductor industry’, Technovation, Vol. 27, No. 6-7, pp. 402-411.
【20】Liu, X. (2007) ‘Parameterized defuzzification with maximum entropy weighting function - another view of the weighting function expectation method’, Mathematical and Computer Modelling, Vol. 45, pp. 177-188.
【21】Majd, S., and Pindyck, R. S. (1989) ‘The learning curve and optimal production under uncertainty’, Rand J. Economics, Vol. 20, No. 3, pp. 331-343.
【22】Mazzola, J. B., McCardle, K. F. (1995) ‘A Bayesian approach to managing learning-curve uncertainty’, Management Science, Vol. 42, No. 5, pp. 680-692.
【23】Peng, C.-Y., and Chien, C.-F. (2003) ‘Data value development to enhance competitive advantage: A retrospective study of EDA systems for semiconductor fabrication’, International Journal of Services, Technology and Management, Vol. 4, No. 4-6, pp. 365-383.
【24】Porter, M.E. (1979) ‘How competitive forces shape strategy’, Harvard Business Rev, March/April.
【25】Shimada, Y., and Sakurai, K. (2003) ‘A new accurate yield prediction method for system-LSI embedded memories’, IEEE Transactions on Semiconductor Manufacturing, Vol. 16, No. 3, pp. 436-445.
【26】Spence, A. M. (1981) ‘The learning curve and competition’, Bell J. Economics, Vol. 12, pp. 49-70.
【27】Watada, J., Tanaka, H., and Shimomura, T. (1986) ‘Identification of learning curve based on possibilistic concepts’, Applications of Fuzzy Set Theory in Human Factors, The Netherlands: Elsevier Science Publishers B. V.
【28】Walsh, S.T. , Boylan, R.L. , McDermott, C., Paulson, A. (2005) ‘The semiconductor silicon industry roadmap: Epochs driven by the dynamics between disruptive technologies and core competencies’, Technological Forecasting Social Change,Vol. 72, pp. 213–236.
中文部分
【29】http://www.tsia.org.tw/ 台灣半導體產業協會（TSIA）網站。
【30】http://www.topology.com.tw/TRI/default.asp 拓墣產業研究所網站。
【31】http://cdnet.stpi.org.tw/ 科技政策中心資訊服務處網站。
【32】Michael E. Proter (1996)，「國家競爭優勢」，天下文化。
【33】工研院電子所ITIS計畫(1998)，1998半導體工業年鑑。
【34】王文俊(2001)，「認識Fuzzy-第二版(修訂版)」，全華科技圖書股份有限公司出版，台北市。
【35】呂明澤(2006)，「運用資料挖礦技術進行影響良率學習之因素分析 - 以某半導體廠製程為例」，國立清華大學工業工程與工程管理研究所碩士論文。
【36】陳幸雄等(1997)，「我國IC產業國際競爭力研究」，工研院電子所ITIS計畫。
【37】黃宏文(2002)，晶圓製造廠區段基礎式週期時間估算法，國立交通大學工業工程與管理研究所博士論文。
【38】經濟部(1997)，「經濟部產業技術發展策略規劃報告」，經濟部。
【39】經濟部(2008)，「我國半導體產業新競爭力」，經濟部。
【40】蔡文傑(2003) ，「新晶圓缺陷群聚指標之建構」，國立交通大學工業工程與管理研究所碩士論文。