Process Design of a Hot Forged Product Using the Artificial Neural Network and the Statistical Design of Experiments

신경망과 실험계획법을 이용한 열간 단조품의 공정설계

  • 김동환 (부산대학교 정밀 정형 및 금형가공 연구센터) ;
  • 김동진 (부산대학교 기계 기술연구) ;
  • 김호관 (부산지방중소기업청 조선기자재시험연구센) ;
  • 김병민 (부산대학교 정밀 정형 및 금형가공 연구센) ;
  • 최재찬 (부산대학교 정밀 정형 및 금형가공 연구센터)
  • Published : 1998.09.01

Abstract

In this research. we have proposed a new technique to determine .the combination of design parameters for the process design of a hot forged product using artificial neural network(ANN) and statistical design of experiments(DOE). The investigated problem involves the adequate selection of the aspect ratio of billet, the ram velocity and the friction factor as design parameters. An optimal billet satisfying the forming limitation, die filling, load and energy as well as more uniform distribution of effective strain, is determined by applying the ability of artificial neural network and considering the analysis of mean and variation on the functional requirement. This methodology will be helpful in designing and controlling parameters on the shop floor which would yield the best design solution.

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