Modelling and analysis of waviness reduction in soft-pad grinding of wire-sawn silicon wafers by support vector regression

International Journal of Production Research

Volumn 44, Issue 13, 2006, Pages 2605-2623

  Shen, Judong ^a   Pei, Z J ^a   Lee, E S ^a   Fisher, G R ^b  

^a Sunflower Networking Group   (United States)

^b MEMC Electronic Materials Inc   (United States)

Author keywords

Manufacturing; Modelling; Silicon wafer; Statistical learning theory; Support vector regression; Waviness removal

Indexed keywords

GRINDING (MACHINING); LEARNING SYSTEMS; MANUFACTURE; MATHEMATICAL MODELS; PRODUCTION ENGINEERING; REGRESSION ANALYSIS;

MANUFACTURE PROCESS; STATISTICAL LEARNING THEORY; SUPPORT VECTOR REGRESSION; WAVINESS REMOVAL;

SILICON WAFERS;

EID: 33744989246     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207540600558049     Document Type: Article

References (18)

1. Bazaraa, M. and Shetty, C., Nonlinear Programming: Theory and Algorithms, 1993 (Wiley: New York).
2. Cheng, C.B. and Lee, E.S., Switching regression analysis by fuzzy adaptive network. Eur. J. Oper. Res., 2001, 128, 647-663.
3. Cheng, C.B., Nonparametric fuzzy regression and its applications. PhD dissertation, Kansas Sate University, Manhattan, Kansas, USA, 2000.
4. Cherkassky, V. and Ma, Y., Practical selection of SVM parameters and noise estimation for SVM regression. Neur. Net., 2004, 17, 113-126.
5. Jiao, Y., Wu, J., Lei, S.T., Pei, Z.J. and Lee, E.S., Application of fuzzy adaptive networks in manufacturing: waviness removal in grinding of wire-sawn silicon wafers. in Proceedings of ASME International Mechanical Engineering Congress and Exposition (IMECE), Washington, DC, 16-21 November 2003.
6. Kassir, S.M. and Walsh, T.A., Grinding process and apparatus for planarizing sawed wafers, US Patent 5,964,646, 1999.
7. Kecman, V. Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models, 2001 (MIT Press: Cambridge, MA).
8. Pei, Z.J., Kassir, S., Bhagavat, M. and Fisher, G.R., An experimental investigation into soft-pad grinding of wire-sawn silicon wafers. Int. J. Mach. Tools Manuf., 2004, 44, 297-304.
9. Pei, Z.J., Xin, X.J. and Liu, W.J., Finite element analysis for grinding of wire-sawn silicon wafers: a designed experiment. Int. J. Mach. Tools Manuf., 2003, 43, 7-16.
10. Sun, X.K., Pei, Z.J., Xin, X.J. and Fouts, M., Waviness removal in grinding of wire-sawn silicon wafers: 3D finite element analysis with designed experiments. Int. J. Mach. Tools Manuf., 2004, 44, 1-19.
11. Van Zant, P., Microchip Fabrication: A Practical Guide to Semiconductor Processing, 4th ed., 2000 (McGraw-Hill: New York).
12. Vandamme, R., Xin, Y. and Pei, Z.J., Method of processing semiconductor wafers, US Patent 6,114,245, 2000.
13. Vapnik, V.N., The Nature of Statistical Learning Theory, 1995 (Springer: New York).
14. Vapnik, V.N., An overview of statistical learning theory. IEEE Trans. Neur. Net., 1999, 10, 988-999.
15. Wu, C., Wei, C., Su, D. and Chang, M., Travel time prediction with support vector regression. IEEE Intell. Transport. Sys., 2003, 2, 1438-1442.
16. 5 factorial design, CD-ROM, in Proceedings of the 12th Annual Industrial Engineering Research Conference (IERC-2003), Portland, OR, 18-20 May 2003.
17. Xin, X.J., Liu, W.J. and Pei, Z.J., Modeling of waviness reduction in silicon wafer grinding by finite element method, in Proceedings of the International Conference on Modeling and Analysis of Semiconductor Manufacturing (MASM 2002), Tempe, AZ, 10-12 April 2002, pp. 24-29.
18. Xin, X.J., Pei, Z.J. and Liu, W.J., Finite element analysis on soft-pad grinding of wire-sawn silicon wafers. J. Electron. Packag., 2004, 126, 177-185.