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Evaluating and Enhancing the Long-Term Competitiveness of a Semiconductor Product through Fuzzy Yield Modeling
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Abstract
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 through yield learning modeling in various ways. Subsequently, to enhance the long-term competitiveness of the product, capacity re-allocation is shown to be helpful. The effects are modeled, and the relationship between them is also discussed. A practical example is used to demonstrate the proposed methodology. Experimental results show that with an additional capacity of 3000 wafers per month, the long-term competitiveness of the product can be elevated up to 25%. Further, the most efficient way is to allocate 15000 more wafers per month to the product.
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References
T. Chen, Evaluating the mid-term competitiveness of a product in a semiconductor fabrication factory with a systematic procedure, Computers & Industrial Engineering, Vol. 57: 931-936, 2009.
T. Chen, M. J. J. Wang, A fuzzy set approach for yield learning modeling in wafer manufacturing, IEEE Transactions on Semiconductor Manufacturing, Vol. 12(Issue 2): 252-258, 1999.
J. A. Cunningham, The use and evaluation of yield models in integrated circuit manufacturing, IEEE Transactions on Semiconductor Manufacturing, Vol. 3(Issue 2): 60–71, 1990.
M. Haller, A. Peikert, and J. Thoma, Cycle time management during production ramp-up, Robotics and Computer Integrated Manufacturing, Vol. 19: 183-188, 2003.
K. L. Hsieh, L. I. Tong, Manufacturing performance evaluation for IC products, International Journal of Advanced Manufacturing Technology, Vol. 28: 610-617, 2006.
Y. Shimada, K. Sakurai, A new accurate yield prediction method for system-LSI embedded memories, IEEE Transactions on Semiconductor Manufacturing, Vol. 16(Issue 3): 436-445, 2003.
T. S. Li, C. L. Huang, and Z. Y. Wu, Data mining using genetic programming for construction of a semiconductor manufacturing yield rate prediction system, International Journal of Advanced Manufacturing Technology Vol. 17: 355-361, 2006.
C. T. Lin, C. W. Chang, and C. B. Chen, Relative control philosophy – balance and continual change for forecasting abnormal quality characteristics in a silicon wafer slicing process, International Journal of Advanced Manufacturing Technology, Vol. 26: 1109-1114, 2006.
L. I. Tong, C. H. Wang, and D. L. Chen, Development of a new cluster index for wafer defects, International Journal of Advanced Manufacturing Technology, Vol. 31: 705-715, 2007.
A. M. Spence, The learning curve and competition, Bell J. Economics, Vol. 12: 49-70, 1981.
S. Majd, R. S. Pindyck, The learning curve and optimal production under uncertainty, Rand J. Economics, Vol. 20(Issue 3): 331-343, 1989.
J. B. Mazzola, K. F. McCardle, A Bayesian approach to managing learning-curve uncertainty, Management Science, Vol. 42(Issue 5): 680-692, 1995.
J. Watada, H. Tanaka, and T. Shimomura, Identification of learning curve based on possibilistic concepts, Applications of Fuzzy Set Theory in Human Factors (Elsevier Science Publishers B. V., 1986).
T. Chen, A fuzzy logic approach for incorporating the effects of managerial actions on semiconductor yield learning, Proceedings of 2007 International Conference on Machine Learning and Cybernetics: 1979-1984, Hong Kong, 2007.
X. Liu, Parameterized defuzzification with maximum entropy weighting function - another view of the weighting function expectation method, Mathematical and Computer Modelling, Vol. 45: 177-188, 2007.
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