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

Translated title of the contribution: Multi-objective optimal design of key process parameters for plastic injection molding product quality

Zheng Sun, Jun Li, Zhuocheng Wang, Cuimei Bo, Yun Zhang, Ke Yao, Furong Gao

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Translated title of the contributionMulti-objective optimal design of key process parameters for plastic injection molding product quality
Original languageChinese (Traditional)
Pages (from-to)483-491
Number of pages9
JournalGao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities
Volume37
Issue number3
DOIs
StatePublished - Jun 2023

Fingerprint

Dive into the research topics of 'Multi-objective optimal design of key process parameters for plastic injection molding product quality'. Together they form a unique fingerprint.

Cite this