NDLI: A Fuzzy Logic Approach for Incorporating the Effects of Managerial Actions on Semiconductor Yield Learning

Content Provider	IEEE Xplore Digital Library
Author	Toly Chen
Copyright Year	2007
Description	Author affiliation: Feng Chia Univ., Taichung (Toly Chen)
Abstract	The competition in the semiconductor industry is becoming more and more fierce, which significantly distorts the learning process of semiconductor yield improvement. For example, if the yield of a product could not reach a certain level before a given deadline, then the competitiveness of the product will disappear and capacity will be re-allocated to other products. To prevent that from happening, some managerial actions, e.g. executing a quality engineering project, quickening the speed of mass production, etc. can be taken to accelerate yield learning. After such actions, the yield learning model has to be modified. In this study, how to incorporate the effects of such managerial actions on semiconductor yield learning is investigated. Subsequently, a new fuzzy yield learning model is developed. The proposed methodology has been applied to the data of four semiconductor products. Experimental results revealed the effectiveness of the proposed methodology.
Starting Page	1979
Ending Page	1984
File Size	591181
Page Count	6
File Format	PDF
ISBN	9781424409723
DOI	10.1109/ICMLC.2007.4370471
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy logic Machine learning Engineering management Uncertainty Cybernetics Conference management Electronics industry Quality management Project management Mass production Yield Learning model Semiconductor
Content Type	Text
Resource Type	Article

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