Design of optimization parameters with hybrid genetic algorithm method in multi-cavity injection molding process

Wen Jong Chen, Jia Ru Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationAdvanced Materials Research II
Pages587-591
Number of pages5
DOIs
Publication statusPublished - 2012 Feb 27
Event2012 2nd International Conference on Advanced Material Research, ICAMR 2012 - Chengdu, China
Duration: 2012 Jan 72012 Jan 8

Publication series

NameAdvanced Materials Research
Volume463-464
ISSN (Print)1022-6680

Other

Other2012 2nd International Conference on Advanced Material Research, ICAMR 2012
CountryChina
CityChengdu
Period12-01-0712-01-08

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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