Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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A Fault Diagnosis Methodology for Module Process of TFT-LCD Manufacture Using Support Vector Machines

SVM을 이용한 TFT-LCD 모듈공정의 불량 진단 방안

  • Shin, Hyun-Joon (Department of Management Engineering, Sangmyung University)
  • 신현준 (상명대학교 경영공학과)
  • Received : 2010.11.30
  • Accepted : 2010.12.17
  • Published : 2010.12.31
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Abstract

Fast incipient fault diagnosis is becoming one of the key requirements for economical and optimal process operation management in high-tech industries. Artificial neural networks have been used to detect faults for a number of years and shown to be highly successful in this application area. This paper presents a novel test technique for fault detection and classification for module process of TFT-LCD manufacture using support vector machines (SVMs). In order to evaluate SVMs, this paper examines the performance of the proposed method by comparing it with that of multilayer perception, one of the artificial neural network techniques, based on real benchmarking data.

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References

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