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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 672404, 7 pages
Research Article

Semiconductor Yield Forecasting Using Quadratic-Programming-Based Fuzzy Collaborative Intelligence Approach

Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung City 407, Taiwan

Received 26 March 2013; Accepted 17 May 2013

Academic Editor: Yi-Chi Wang

Copyright © 2013 Toly Chen and Yu-Cheng Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Several recent studies have proposed fuzzy collaborative forecasting methods for semiconductor yield forecasting. These methods establish nonlinear programming (NLP) models to consider the opinions of experts and generate fuzzy yield forecasts. Such a practice cannot distinguish between the different expert opinions and can not easily find the global optimal solution. In order to solve some problems and to improve the performance of semiconductor yield forecasting, this study proposes a quadratic-programming- (QP-) based fuzzy collaborative intelligence approach.