Establishing the optimal and efficient capacity re-allocation plans for enhancing the long-term competitiveness of a semiconductor product

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 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 non-linear 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 16 780 wafers per month, the long-term competitiveness of the product is maximized. Also, the most efficient way is to allocate 14 500 more wafers per month to the product. These results are helpful in making capacity re-allocation decisions.

Keywords

semiconductor capacity re-allocation yield competitiveness non-linear programming.

References

Armstrong

. Principles for competitive semiconductor manufacturing’ (1989).

Jenkins

Phail

Sackman

. Semiconductor competitiveness in the 1990s. Proc. Soc. Auto. Engrs P223 (1990): 249–255.

Peng

C.-Y.

Chien

C.-F.

. Data value development to enhance competitive advantage: A retrospective study of EDA systems for semiconductor fabrication. Int. J. Serv., Technol. Mgmt 4 (4—6) (2003): 365–383.

Liao

S.-H.

T.-C.

. Knowledge transfer and competitive advantage on environmental uncertainty: An empirical study of the Taiwan semiconductor industry. Technovation 27 (6—7) (2007): 402–411.

Cunningham

J. A.

. The use and evaluation of yield models in integrated circuit manufacturing. IEEE Trans., Semiconductor Mfg 3 (2) (1990): 60–71.

Chen

Wang

M.-J. J.

. A fuzzy set approach for yield learning modeling in wafer manufacturing. IEEE Trans. Semiconductor Mfg 12 (2) (1999): 252–258.

Chen

. A FNP approach for evaluating and enhancing the long-term competitiveness of a semiconductor fabrication factory through yield learning modeling. Int. J. Advd Mfg Technol. 40 (2009): 993–1003.

Chen

. Evaluating the mid-term competitiveness of a product in a semiconductor fabrication factory with a systematic procedure. Comput. Ind. Engng 53 (2007): 499–513.

Chen

Wang

Y.-C.

. A fuzzy set approach for evaluating and enhancing the mid-term competitiveness of a semiconductor factory. Fuzzy Sets and Systems 160 (2009): 569–585.

10.

Spence

A. M.

. The learning curve and competition. Bell J. Economics 12 (1981): 49–70.

11.

Majd

Pindyck

R. S.

. The learning curve and optimal production under uncertainty. Rand J. Economics 20 (3) (1989): 331–343.

12.

Mazzola

J. B.

McCardle

K. F.

. A Bayesian approach to managing learning-curve uncertainty. Mgmt Sci. 42 (5) (1995): 680–692.

13.

Watada

Tanaka

Shimomura

. Identification of learning curve based on possibilistic concepts. Applications of fuzzy set theory in human factors (The Netherlands: Elsevier Science Publishers 1986).

14.

Shimada

Sakurai

. A new accurate yield prediction method for system-LSI embedded memories. IEEE Trans. Semiconductor Mfg 16 (3) (2003): 436–445.

15.

T.-S.

Huang

C.-L.

Z.-Y.

. Data mining using genetic programming for construction of a semiconductor manufacturing yield rate prediction system. Int. J. Advd Mfg Technol. 17 (2006): 355–361.

16.

Chen

Lin

Y.-C.

. A fuzzy-neural system incorporating unequally important expert opinions for semiconductor yield forecasting. Int. J. Uncertainty, Fuzziness, Knowledge-based Systems 16 (1) (2008): 35–58.

17.

Chen

. Estimating and incorporating the effects of a future QE project into the semiconductor yield learning model with a fuzzy set approach. Eur. J. Ind. Engng 3 (2) (2009): 207–226.

18.

Gruber

. Learning and strategic product innovation: Theory and evidence for the semiconductor industry (1984):.

19.

Haller

Peikert

Thoma

. Cycle time management during production ramp-up. Robotics and Computer Integrated Mfg 19 (2003): 183–188.

20.

Liu

. Parameterized defuzzification with maximum entropy weighting function — another view of the weighting function expectation method. Mathl Computer Modelling 45 (2007): 177–188.

21.

Deffree

. Semiconductor winners and losers split by competitiveness’ 2007. Available from http://www.electronicsweekly.com/.

Establishing the optimal and efficient capacity re-allocation plans for enhancing the long-term competitiveness of a semiconductor product — a long-term trend viewpoint

Abstract

Abstract

Keywords

References