대한기계학회논문집A (Transactions of the Korean Society of Mechanical Engineers A)
- 제21권5호
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- Pages.727-734
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- 1997
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- 1226-4873(pISSN)
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- 2288-5226(eISSN)
DOI QR Code
신경망을 이용한 냉간단조품의 금형형상 설계
Die Shape Design for Cold Forged Products Using the Artificial Neural Network
- 김동진 (부산대학교 대학원 기계설계공학과) ;
- 김태형 (부산대학교 대학원 기계설계공학과) ;
-
김병민
(부산대학교 정밀정형 및 금형가공 연구센터)
;
-
최재찬
(부산대학교 정밀정형 및 금형가공 연구센터)
- Kim, D.J (Dept.of Mechanical Design Engineering, Graduate School of Busan National University) ;
- Kim, T.H (Dept.of Mechanical Design Engineering, Graduate School of Busan National University) ;
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Kim, B.M
(Sheet Products Process Research Group, Busan National University)
;
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Choi, J.C
(Sheet Products Process Research Group, Busan National University)
- 발행 : 1997.01.01
초록
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.