Application of data mining for improving yield in wafer fabrication system

Authors:
Dong-Hyun Baek;In-Jae Jeong;Chang Hee Han
Affiliations:
Department of Business Administration, Hanyang University, Gyeonggi-do, Korea;Department of Industrial Engineering, Hanyang University, Seoul, Korea;Department of Business Administration, Hanyang University, Gyeonggi-do, Korea
Venue:
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Year:
2005

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Abstract

This paper presents a comprehensive and successful application of data mining methodologies to improve wafer yield in a semiconductor wafer fabrication system. To begin with, this paper applies a clustering method to automatically identify AUF (Area Uniform Failure) phenomenon from data instead of visual inspection that bad chips occurs in a specific area of wafer. Next, sequential pattern analysis and classification methods are applied to find out machines and parameters that are cause of low yield, respectively. Finally, this paper demonstrates an information system, Y2R-PLUS (Yield Rapid Ramp-up, Prediction, analysis & Up Support) that is developed in order to analyze wafer yield in a Korea semiconductor manufacturer.