Multi-Objective Optimization of Injection Molding Process Parameters of Car Lamp Shell Based on Grey Correlation Analysis.

Ruixia Shan, Anqin Liu, Sen Jia, Changyou Liu, Wenguang Yang

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Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Ruixia ShanSchool of Mechanical and Electrical Engineering, Yantai Institute of Technology, Yantai 264005, China.

Anqin LiuSchool of Mechanical and Electrical Engineering, Yantai Institute of Technology, Yantai 264005, China.

Sen JiaSchool of Mechanical and Electrical Engineering, Yantai Institute of Technology, Yantai 264005, China.

Changyou LiuSchool of Mechanical and Electrical Engineering, Yantai Institute of Technology, Yantai 264005, China.

Wenguang YangSchool of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China.ORCID 0000-0002-1560-665X

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6 · The paper itself

Abstract

In order to improve the injection molding quality of the car lamp shell, orthogonal test, signal-to-noise ratio, gray correlation analysis, and CRITIC weight method were used to analyze the influence of mold temperature, melt temperature, injection time, velocity to pressure control, pressure holding pressure and pressure holding time on the shrinkage index and the total deformation of warpage, and fully consider the difference and correlation between the evaluation parameters. The multi-objective optimization is transformed into single-objective optimization, and the optimal parameter set is obtained. The experimental results show that, compared with the initial analysis results, the indentation index of the headlight shell is reduced by 33.95%, the total warpage deformation is reduced by 13.99%, and the forming quality of the headlight shell is improved. The research results provide a theoretical reference value for multi-objective optimization of plastic injection molding process parameters.

Indexed as

CRITIC methodgrey relational analysisinjection molding process parametermulti-objective optimization

Identifiers

PMID40508765

DOI10.3390/polym17111524

PMCPMC12158006

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LicenceCC BY

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