Journal of the Korean institute of surface engineering (한국표면공학회지)

The Korean Institute of Surface Engineering (한국표면공학회)
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Prediction on the Efficiency of Coated Tool Using Taguchi Design and Neural Network

다꾸지 기법 및 신경망을 이용하여 코팅공구의 성능예측 연구

  • Choi Gwang Jin (Agency for Technology & Standards, MOCIE) ;
  • Lee Wi Ro (KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering) ;
  • Choi Suk Woo (KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering) ;
  • Paik Young Nam (KyungHee Univ. Graduate School, KyungHee Univ. Mechanical and Industrial System Engineering)
  • 최광진 (경희대학교 기계공학부) ;
  • 이위로 (경희대학교 대학원, 기술표준원) ;
  • 최석우 (경희대학교 대학원, 기술표준원) ;
  • 백영남 (경희대학교 대학원, 기술표준원)
  • Published : 2003.06.01
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Abstract

In this study, the prediction on the quality of tools after coating process has been investigated. Under different coating conditions, cutting resistances have been obtained and analyzed with a tool dynamometer to provide optimized coating conditions. The optimized coating conditions Lhave been computed with the most effective factors found by S/N ratio of Taguchi method. To evaluate the influence of the factors on cutting efficiency through the minimum of number of experiment times, the way of neural network design using Taguchi method has been employed.

Keywords

References

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