Optimization of Process Parameters using DOE, RSM, and GA in Plastic Injection Molding

Wen Chin Chen; Denni Kurniawan; Gong Loung Fu

doi:10.4028/www.scientific.net/AMR.472-475.1220

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 472-475Optimization of Process Parameters using DOE, RSM,...

Optimization of Process Parameters using DOE, RSM, and GA in Plastic Injection Molding

Abstract:

In the past, plastic injection molding (PIM) product quality was usually measured by one single quality characteristic or by multiple quality characteristic with independent parameters one another. In this study, optimization of process parameters using design of experiment (DOE), response surface methodology (RSM), and genetic algorithm (GA) were proposed to generate the optimal process parameters settings of multiple-quality characteristics. In the first stage, significant PIM process parameters can be determined by DOE screening experiments. Then the optimal process parameter settings are obtained via computer aided engineering (CAE) simulation integrated with RSM and GA, which are taken as practically initial settings of process-related parameters. The experimental results show that the propose optimization model is very successful and can be used in industrial applications.

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Advanced Manufacturing Technology, ICMSE 2012

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Periodical:

Advanced Materials Research (Volumes 472-475)

Pages:

1220-1223

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.472-475.1220

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Online since:

February 2012

Authors:

Wen Chin Chen, Denni Kurniawan, Gong Loung Fu

Keywords:

Computer Aided Engineering, Design of Experiment (DOE), Genetic Algorithm (GA), Plastic Injection Molding, Response Surface Methodology (RSM)

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