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.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Chen, WJ., Lin, JR. (2012). Application and Design of Artificial Neural Network for Multi-cavity Injection Molding Process Conditions. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29390-0_7
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DOI: https://doi.org/10.1007/978-3-642-29390-0_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29389-4
Online ISBN: 978-3-642-29390-0
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