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TECHNICAL PAPERS

A Fuzzy Adaptive Network Model for Waviness Removal in Grinding of Wire-Sawn Silicon Wafers

[+] Author and Article Information
Yue Jiao1

School for Marine Sciences and Technology, University of Massachusetts Dartmouth, 706 South Rodney French Boulevard, New Bedford, MA 02744yjiao@umassd.edu

Z. J. Pei, Shuting Lei, 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 63376

1

Author to whom correspondence should be addressed.

J. Manuf. Sci. Eng 128(4), 938-943 (Apr 28, 2006) (6 pages) doi:10.1115/1.2335860 History: Received December 07, 2005; Revised April 28, 2006

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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Copyright © 2006 by American Society of Mechanical Engineers
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Figures

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Figure 1

Structure of FAN III

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Figure 2

Illustration of wafer grinding

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Figure 3

Illustration of soft-pad grinding

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Figure 4

FEA model (waviness is exaggerated for illustration)

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Figure 5

Architecture of the FAN III model for soft-pad grinding of silicon wafers

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Figure 6

FEA simulation results versus model predictions by FAN III

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Figure 7

Effects of independent parameters on REPD

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Figure 8

Effects of independent parameters on WWD

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