Silicon is the primary semiconductor material used to fabricate microchips, and the quality of microchips depends directly upon the quality of the starting silicon wafers. One of the manufacturing problems in silicon wafer manufacturing is the presence of waviness on the surface as a result of wire-saw slicing. Various factors influence the waviness reduction capacity during soft-pad grinding; the grinding process is very complicated and difficult to define. In this research, fuzzy adaptive network, which is ideally suited to the modeling of vague phenomena, is used to model the waviness problem. Fuzzy adaptive network has the learning ability of a neural network and the linguistic representation of a complex, not well understood phenomenon. Simulation data are used to illustrate the applicability of fuzzy adaptive network. The results, even though based on some very limited data, indicate the influences of the independent parameters clearly.
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November 2006
Technical Papers
A Fuzzy Adaptive Network Model for Waviness Removal in Grinding of Wire-Sawn Silicon Wafers
Yue Jiao,
Yue Jiao
School for Marine Sciences and Technology,
yjiao@umassd.edu
University of Massachusetts Dartmouth
, 706 South Rodney French Boulevard, New Bedford, MA 02744
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Z. J. Pei,
Z. J. Pei
Department of Industrial and Manufacturing Systems Engineering,
Kansas State University
, Manhattan, KS 66506
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Shuting Lei,
Shuting Lei
Department of Industrial and Manufacturing Systems Engineering,
Kansas State University
, Manhattan, KS 66506
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E. Stanley Lee,
E. Stanley Lee
Department of Industrial and Manufacturing Systems Engineering,
Kansas State University
, Manhattan, KS 66506
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Graham R. Fisher
Graham R. Fisher
MEMC Electronic Materials, Inc.
, 501 Pearl Drive, St. Peters, MO 63376
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Yue Jiao
School for Marine Sciences and Technology,
University of Massachusetts Dartmouth
, 706 South Rodney French Boulevard, New Bedford, MA 02744yjiao@umassd.edu
Z. J. Pei
Department of Industrial and Manufacturing Systems Engineering,
Kansas State University
, Manhattan, KS 66506
Shuting Lei
Department of Industrial and Manufacturing Systems Engineering,
Kansas State University
, Manhattan, KS 66506
E. Stanley Lee
Department of Industrial and Manufacturing Systems Engineering,
Kansas State University
, Manhattan, KS 66506
Graham R. Fisher
MEMC Electronic Materials, Inc.
, 501 Pearl Drive, St. Peters, MO 63376J. Manuf. Sci. Eng. Nov 2006, 128(4): 938-943 (6 pages)
Published Online: April 28, 2006
Article history
Received:
December 7, 2005
Revised:
April 28, 2006
Citation
Jiao, Y., Pei, Z. J., Lei, S., Lee, E. S., and Fisher, G. R. (April 28, 2006). "A Fuzzy Adaptive Network Model for Waviness Removal in Grinding of Wire-Sawn Silicon Wafers." ASME. J. Manuf. Sci. Eng. November 2006; 128(4): 938–943. https://doi.org/10.1115/1.2335860
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