Application and design of artificial neural network for multi-cavity injection molding process conditions

Wen-Jong Chen, Jia Ru Lin

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

1 Citation (Scopus)

Abstract

In this study, an artificial neural network (ANN) with a predictive model for the warpage of multi-cavity plastic injection molding parts. The developed method in this paper indicate that the minimum and the maximum warpage were lower than that of CAE simulation. These simulation results reveal that the optimal process conditions are significantly better than those using the genetic algorithm method or CAE simulation.

Original languageEnglish
Title of host publicationAdvances in Future Computerand Control Systems
Pages33-38
Number of pages6
EditionVOL. 2
DOIs
Publication statusPublished - 2012 May 18
EventFuture Computer and Control Systems, FCCS 2012 - Changsha, China
Duration: 2012 Apr 212012 Apr 22

Publication series

NameAdvances in Intelligent and Soft Computing
NumberVOL. 2
Volume160 AISC
ISSN (Print)1867-5662

Other

OtherFuture Computer and Control Systems, FCCS 2012
CountryChina
CityChangsha
Period12-04-2112-04-22

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Chen, W-J., & Lin, J. R. (2012). Application and design of artificial neural network for multi-cavity injection molding process conditions. In Advances in Future Computerand Control Systems (VOL. 2 ed., pp. 33-38). (Advances in Intelligent and Soft Computing; Vol. 160 AISC, No. VOL. 2). https://doi.org/10.1007/978-3-642-29390-0_7