IE interfaces (산업공학)

Korean Institute of Industrial Engineers (대한산업공학회)
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Compound Learning Curve Model for Semiconductor Manufacturing

반도체에 적합한 복합 학습곡선 모형

  • Ha, Chung-Hun (School of Information and Computer Engineering, Hongik University)
  • 하정훈 (홍익대학교 정보컴퓨터공학부)
  • Received : 2009.06.04
  • Accepted : 2010.03.22
  • Published : 2010.09.01
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Abstract

The learning curve model is a mathematical form which represents the relationship between the manufacturing experience and its effectiveness. The semiconductor manufacturing is widely known as an appropriate example for the learning effect due to its complicated manufacturing processes. In this paper, I propose a new compound learning curve model for semiconductor products in which the general learning curve model and the growth curve are composed. The dependent variable and the effective independent variables of the model were abstracted from the existing learning curve models and selected according to multiple regression processes. The simulation results using the historical DRAM data show that the proposed compound learning curve model is one of adequate models for describing learning effect of semiconductor products.

Keywords

References

  1. Alchain, A. (1959), Cost and output, Allocation of Economic Resources, Abramoviz, M. (ed.), Stanford University Press, Stanford, 23-40.
  2. Badiru, A. B. (1992), Computational survey of univariate and multivariate learning curve models, IEEE Transactions on Engineering Management, 39(2), 176-188.
  3. Chou, S. K. (1933), What Is the Curve of Forgetting?, The American Journal of Psychology, 45(2), 348-350. https://doi.org/10.2307/1414294
  4. Chung, S. (2001), The learning curve and the yield factor : the case of Korea's semiconductor industry, Applied Economics, 33, 473-483. https://doi.org/10.1080/00036840122474
  5. Cunningham, J. A. (1990), The use of evaluation of yield models in integrated circuit manufacturing, IEEE Transactions on Semiconductor Manufacturing, 3(2), 60-71. https://doi.org/10.1109/66.53188
  6. Cunningham, S. P., Spanos, C. J., and Voros, K. (1995), Semiconductor yield improvement results and best practices, IEEE Transactions on Semiconductor Manufacturing, 8(2), 103-109. https://doi.org/10.1109/66.382273
  7. Gruber, H. (1992), The learning curve in the production of semiconductor memory chips, Applied Economics, 24, 885-894. https://doi.org/10.1080/00036849200000056
  8. Gruber, H. (1994), The yield factor and the learning curve in semiconductor production, Applied Economics, 26, 837-843. https://doi.org/10.1080/00036849400000100
  9. Hatch, N. W. and Mowery, D. C. (1998), Process innovation and learning by doing in semiconductor manufacturing, Management Science, 44(11), 1461- 1477. https://doi.org/10.1287/mnsc.44.11.1461
  10. IC Knowledge (2008), Technology Trends, www.icknowledge.com.
  11. ICE (1997), Yield and Yield Management, Chapter 3 in Cost Effecttive IC Manufacturing 1998-1999, Integrated Circuit Engineering Corporation.
  12. Kara, S. and Kayis, B. (2005), The effect of the learning process in concurrent engineering projects, Concurrent Engineering : Research and Applications, 13(3), 209-217. https://doi.org/10.1177/1063293X05056473
  13. Lieberman, M. B. (1984), The learning curve pricing in the chemical industries, Rand Journal of Economics, 15, 213-228. https://doi.org/10.2307/2555676
  14. Victor, N. M. and Ausubel, J. H. (2002), DRAMs as Model Organisms for Study of Technological Evolution, Technological Forecasting and Social Change, 69(3), 243-262. https://doi.org/10.1016/S0040-1625(01)00149-4
  15. Weber, C. (2004), Yield learning and the source of profitability in semiconductor manufacturing and process development, IEEE Transactions on Semiconductor Manufacturing, 17(4), 590-596. https://doi.org/10.1109/TSM.2004.835724
  16. Wright, T. P. (1936), Factors affecting the cost of airplanes, Journal of Aeronautical Science, 3(2), 122-128.