Quality defect analysis of injection molding based on gradient enhanced Kriging model

Zhuocheng Wang, Cuimei Bo, Zheng Sun, Jun Li, Furong Gao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In plastic injection molding (PIM), the process parameters affect the quality and productivity of molded parts. In this paper, we use orthogonal experiment design, numerical simulation, and metamodeling method to analyze the quality defect of process. The orthogonal experiment is to generate sampling points from the design space at different parameter levels and to determine key factors that affect product quality. For the sampling points, the numerical simulation is implemented to calculate the objective responses. Based on the sampling points and their corresponding response, a gradient enhanced Kriging (GEK) surrogate model strategy is applied to construct the response predictors to calculate the objective responses in the global design space. Last, we can analyze the surrogate model to look for available process parameters to improve product quality and production efficiency.

Original languageEnglish
Title of host publication4th International Conference on Industrial Artificial Intelligence, IAI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665451208
DOIs
StatePublished - 2022
Event4th International Conference on Industrial Artificial Intelligence, IAI 2022 - Shenyang, China
Duration: 24 Aug 202227 Aug 2022

Publication series

Name4th International Conference on Industrial Artificial Intelligence, IAI 2022

Conference

Conference4th International Conference on Industrial Artificial Intelligence, IAI 2022
Country/TerritoryChina
CityShenyang
Period24/08/2227/08/22

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