Die Shape Design for Cold Forged Products Using the Artificial Neural Network

신경망을 이용한 냉간단조품의 금형형상 설계

Kim, D.J;Kim, T.H;Kim, B.M;Choi, J.C

  • Published : 1997.01.01


In practice, the design of forging processes is performed based on an experience-oriented technology, that is designer's experience and expensive trial and errors. Using the finite element simulation and the artificial neural network, we propose an optimal die geometry satisfying the design conditions of final product. A three-layer neural network is used and the back propagation algorithm is employed to train the network. An optimal die geometry that satisfied the same between inner extruded rib and outer extruded one is determined by applying the ability of function approximation of neural network. The neural networks may reduce the number of finite element simulation for determine the optimal die geometry of forging products and further they are usefully applied to physical modelling for the forging design.


Artificial Neural Network;Back Propagation Training Algorithm;Function Approximation;Die Geometry;Shoulder Length