Optimization of Car Hood Injection Molding Process Based on Response Surface Surrogate Model and Genetic Algorithms

HUANG Guan-shan, ZHU Jin-ting

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Plastics Science and Technology ›› 2024, Vol. 52 ›› Issue (12) : 125-128. DOI: 10.15925/j.cnki.issn1005-3360.2024.12.024
Plastic Machinery and Mold

Optimization of Car Hood Injection Molding Process Based on Response Surface Surrogate Model and Genetic Algorithms

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Abstract

The car hood is manufactured through the injection molding process, using acrylonitrile-butadiene-styrene (ABS) copolymer as the material. Moldflow software is utilized for mold flow analysis, and the effects of melt temperature, mold temperature, packing pressure, and packing time on part defects during the molding process are studied using response surface surrogate models and genetic algorithms. The results indicate that the order of influence of each factor on warpage deformation is: Packing pressure > melt temperature > packing time > mold temperature. When the part's packing pressure is 58 MPa, packing time is 20 s, mold temperature is 30 ℃, and melt temperature is 230 ℃, the part's warpage deformation is minimized. After optimization, the part's warpage deformation is reduced by 0.188 6 mm compared to before optimization, and the overall quality is improved by 31.33%. The predicted value calculated by the genetic algorithm is 0.40 mm, with a relative error of 3.2% compared to the final simulation value, which meets the actual production requirements.

Key words

Car hood / Response surface surrogate model / Genetic algorithm / Injection molding / Process optimization

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HUANG Guan-shan , ZHU Jin-ting. Optimization of Car Hood Injection Molding Process Based on Response Surface Surrogate Model and Genetic Algorithms. Plastics Science and Technology. 2024, 52(12): 125-128 https://doi.org/10.15925/j.cnki.issn1005-3360.2024.12.024

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