한국반도체및디스플레이장비학회:학술대회논문집 (Proceedings of the Korean Society Of Semiconductor Equipment Technology)
- 한국반도체및디스플레이장비학회 2002년도 추계학술대회 발표 논문집
- /
- Pages.127-129
- /
- 2002
A Study on Moldability by Using Fuzzy Logic Based Neural Network(FNN)
- Kang, Seong Nam (School of Mechatronics Eng., Korea University of Technology and Education) ;
- Huh, Yong Jeong (School of Mechatronics Eng., Korea University of Technology and Education) ;
- Choi, Man Sung (School of Mechatronics Eng., Korea University of Technology and Education)
- 발행 : 2002.11.01
초록
In order to predict the moldability of an 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 expert's conventional way which is similar to the golden section search algorithm.