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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 690-693Parameter Optimization of the Injection Molding...

Parameter Optimization of the Injection Molding Process for a LED Lighting Lens Using Soft Computing

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Abstract:

This study proposes a parameter optimization system for a multi-LED lighting lens, which uses design of experiment (DOE) for screening the process parameters, computer-aided engineering (CAE) for mold flow analysis, analysis of variance (ANOVA) for determining the significant parameters, and response surface methodology (RSM) for finding the initial parameter settings in terms of multi-objective quality characteristics. In addition, two regression models, obtained from RSM, are employed as the quality predictors which are combined with the particle swarm optimization (PSO) to generate the optimal molding parameter settings. The numerical results show that the proposed approach, RSM with PSO, is beneficial to obtain the better process parameter settings in the injection molding process.

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Materials Design, Processing and Applications

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Periodical:

Advanced Materials Research (Volumes 690-693)

Pages:

2344-2351

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.690-693.2344

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Online since:

May 2013

Authors:

Wen Chin Chen, Li Yi Wang, Cheng Chi Huang, Tung Tsan Lai

Keywords:

ANOVA, Computer Aided Engineering (CAE), Lens Design, Particle Swarm Optimization (PSO), RSM

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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