Multi-objective Optimization of Process Parameters for Dual-Color Injection Molding of the Middle Cover of Electric Vehicle Charging Pile

<div>This article takes the cover of the AC charging pile as the research object and studies the process parameters of dual-color injection molding. First, the optimal Latin hypercube experimental design is carried out by using optimization software by taking the melt temperature and mold temperature of the first shot and the second shot and the holding pressure as the influencing factors. Injection simulation is carried out based on mold flow software. A high-precision neural network model RBF is constructed according to the test factors and results. Second, based on the obtained RBF prediction model, the multi-objective NSGA-II algorithm is used for optimization. The obtained optimal combination of molding process parameters is: the melt temperature of the first shot is 266.8°C, the mold temperature is 107°C, the melt temperature of the second shot is 230.3°C, the mold temperature is 59.5°C, the holding pressure of the first shot is 95 MPa, the holding pressure of the second shot is 89.9 MPa, and the holding time is 10 s. Next, conducting finite element simulation verification on the optimized process parameters, it was found that the total warpage and the first and second volume shrinkage rates were 1.13 mm, 4.57%, and 7.41%, respectively, with a maximum error of only 5.7% compared to the RBF predicted values. The results show that the RBF prediction model established has high accuracy. Compared with before optimization, the warpage amount is reduced by 21.9%, and the volume shrinkage rates are reduced by 34.3% and 11.2%, respectively. Finally, the optimized process parameters were imported into actual production, and the molding quality was effectively improved.</div>

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Publication Details

Journal
SAE International Journal of Materials and Manufacturing
Published
2025-03-26
DOI
https://doi.org/10.4271/05-18-04-0031
Primary Topic
Injection Molding Process and Properties
Type
article
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article

Multi-objective Optimization of Process Parameters for Dual-Color Injection Molding of the Middle Cover of Electric Vehicle Charging Pile

Shan Cheng, Peng Hu, Hongyuan Jiang, Bingyun Jiang et al.
SAE International Journal of Materials and Manufacturing
Injection Molding Process and Properties
article

Multi-objective Optimization of Process Parameters for Dual-Color Injection Molding of the Middle Cover of Electric Vehicle Charging Pile

Shan Cheng, Peng Hu, Hongyuan Jiang, Bingyun Jiang, Hao Liu
article en

Abstract

<div>This article takes the cover of the AC charging pile as the research object and studies the process parameters of dual-color injection molding. First, the optimal Latin hypercube experimental design is carried out by using optimization software by taking the melt temperature and mold temperature of the first shot and the second shot and the holding pressure as the influencing factors. Injection simulation is carried out based on mold flow software. A high-precision neural network model RBF is constructed according to the test factors and results. Second, based on the obtained RBF prediction model, the multi-objective NSGA-II algorithm is used for optimization. The obtained optimal combination of molding process parameters is: the melt temperature of the first shot is 266.8°C, the mold temperature is 107°C, the melt temperature of the second shot is 230.3°C, the mold temperature is 59.5°C, the holding pressure of the first shot is 95 MPa, the holding pressure of the second shot is 89.9 MPa, and the holding time is 10 s. Next, conducting finite element simulation verification on the optimized process parameters, it was found that the total warpage and the first and second volume shrinkage rates were 1.13 mm, 4.57%, and 7.41%, respectively, with a maximum error of only 5.7% compared to the RBF predicted values. The results show that the RBF prediction model established has high accuracy. Compared with before optimization, the warpage amount is reduced by 21.9%, and the volume shrinkage rates are reduced by 34.3% and 11.2%, respectively. Finally, the optimized process parameters were imported into actual production, and the molding quality was effectively improved.</div>

SAE International Journal of Materials and ManufacturingVol. 18(4)
Changzhou Institute of Mechatronic Technology (CN), Zhejiang University (CN)
Openalex Percentile: Top 94%
Injection Molding Process and Properties
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