Design of Initial Billet using the Artificial Neural Network for a Hot Forged Product

신경망을 이용한 열간단조품의 초기 소재 설계

  • 김동진 (부산대 대학원) ;
  • 김벙민 (부산대 정밀 정형 및 금형 가공연구센터) ;
  • 최재찬 (부산대 정밀 정형 및 금형 가공연구센터)
  • Published : 1995.04.01

Abstract

In the paper, we have proposed a new technique to detemine the initial billet for the forged products using a function approximation in neural network. A three-layer neural network is used and a back propagation algorithm is employed totrain the network. An optimal billet which satisfied the forming limitation, minimum of incomplete filling in the die cavity, load and energyas well as more uniform distribution of effective strain, is determined by applying the ability of function approximation of te neural network. The amount of incomplete filling in the die, load and forming energyas well as effective strain are measured by the rigid-plastic finite element method. The new technique is applied tofind the optimal billet size for the axisymmetric rib-web product in hot forging. This would reduce the number of finite element simulation for determing the optimal billet of forging products, further it is usefully adapted to physical modeling for the forging design.

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