Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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A Study on the Application of Fuzzy Neural Network for Troubleshooting of Injection Molding Problems

사출성형 문제해결을 위한 퍼지 신경망 적용에 관한 연구

  • 강성남 (한국기술교육대 대학원 기계공학과) ;
  • 허용정 (한국기술교육대 메카트로닉스공학부) ;
  • 조현찬 (한국기술교육대 정보기술공학부)
  • Published : 2002.11.01
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Abstract

In order to predict the moldability of a injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network (FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the experts' conventional methodology which is similar to the golden section search algorithm.

Keywords

References

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