National Changhua University of Education Institutional Repository : Item 987654321/13787

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NCUEIR > College of Technology > Department of Industrial Education and Technology > Periodical Articles > Item 987654321/13787

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/13787

Title:	Design of Optimization Parameters with Hybrid Genetic Algorithm Method in Multi-Cavity Injection Molding Process
Authors:	Chen, Wen-Jong;Lin, Jia-Ru
Contributors:	工業教育與技術學系
Keywords:	Artificial Neural Network (ANN);Traditional Genetic Algorithm;Warpage
Date:	2012-02
Issue Date:	2012-08-27T10:55:38Z
Publisher:	Trans Tech Publications, Switzerland.
Abstract:	This paper combines an artificial neural network (ANN) with a traditional genetic algorithm (GA) method, called hybrid genetic algorithm (HGA), to analyze the warpage of multi-cavity plastic injection molding parts. Simulation results indicate that the minimum and the maximum warpage of the hybrid genetic algorithm (HGA) method were lower than that of the traditional GA method and CAE simulation. These results reveal that, when HGA is applied to multi-cavity plastic warpage analysis, the optimal process conditions are significantly better than those using the traditional GA method or CAE simulation.
Relation:	Advanced Materials Research, 463-464: 587-591
Appears in Collections:	[Department of Industrial Education and Technology] Periodical Articles

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