TY - JOUR
T1 - 高分子注塑成型产品质量关键工艺参数的多目标优化设计
AU - Sun, Zheng
AU - Li, Jun
AU - Wang, Zhuocheng
AU - Bo, Cuimei
AU - Zhang, Yun
AU - Yao, Ke
AU - Gao, Furong
N1 - Publisher Copyright:
© 2023 Zhejiang University. All rights reserved.
PY - 2023/6
Y1 - 2023/6
N2 - A multi-objective optimization design method based on gradient-enhanced Kriging (GEK) model was proposed to optimize the key process parameters of plastic injection molding (PIM) for improving the product qualities. According to the process parameters and quality indicators, an orthogonal experimental design with seven factors and three levels was carried out for the air conditioner cover PIM process, and Moldflow software was used to perform mold flow analysis and calculation. Then signal-to-noise (S/N) and analysis of variance (ANOVA) were used to determine the key parameters affecting product quality. The GEK model was introduced to establish a predictive model between quality index and process parameters. MODE algorithm was used to seek the global optimal solution with the best quality and shortest cycle time, and the optimal design parameters were verified by Moldflow simulation. The result showed that warpage, volume shrinkage and cycle time were reduced by 0.88%, 4.68% and 14.81%, respectively, greatly improving product quality and production efficiency.
AB - A multi-objective optimization design method based on gradient-enhanced Kriging (GEK) model was proposed to optimize the key process parameters of plastic injection molding (PIM) for improving the product qualities. According to the process parameters and quality indicators, an orthogonal experimental design with seven factors and three levels was carried out for the air conditioner cover PIM process, and Moldflow software was used to perform mold flow analysis and calculation. Then signal-to-noise (S/N) and analysis of variance (ANOVA) were used to determine the key parameters affecting product quality. The GEK model was introduced to establish a predictive model between quality index and process parameters. MODE algorithm was used to seek the global optimal solution with the best quality and shortest cycle time, and the optimal design parameters were verified by Moldflow simulation. The result showed that warpage, volume shrinkage and cycle time were reduced by 0.88%, 4.68% and 14.81%, respectively, greatly improving product quality and production efficiency.
KW - gradient-enhanced Kriging model
KW - multi-objective differential evolution
KW - orthogonal experimental design
KW - plastic injection molding
KW - quality defect analysis
UR - http://www.scopus.com/inward/record.url?scp=85165445324&partnerID=8YFLogxK
U2 - 10.3969/j.issn.1003-9015.2023.03.017
DO - 10.3969/j.issn.1003-9015.2023.03.017
M3 - 文章
AN - SCOPUS:85165445324
SN - 1003-9015
VL - 37
SP - 483
EP - 491
JO - Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities
JF - Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities
IS - 3
ER -