Optimization of process parameters for sink marks and shrinkage reduction in family molds using Grey-based Taguchi method

Injection molding is a widely used polymer manufacturing process, and integrating sustainability is essential. As material testing demand increases, efficient methods for producing multiple samples are crucial. Family molds enable multiple sample production in a single cycle but pose challenges in a...

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Bibliographic Details
Main Authors: Quoc-Nguyen Banh, Van-Keo Dong, Xuan-Hiep Tran, Anh-Son Tran, Minh-Tuan Ho
Format: Article
Language:English
Published: SAGE Publishing 2025-05-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/16878132251339339
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Summary:Injection molding is a widely used polymer manufacturing process, and integrating sustainability is essential. As material testing demand increases, efficient methods for producing multiple samples are crucial. Family molds enable multiple sample production in a single cycle but pose challenges in achieving balanced flow, leading to sink marks and shrinkage that affect test accuracy. This study addresses these issues by analyzing sink marks, shrinkage, and their variance among specimens. A Grey-based Taguchi method systematically evaluates the effects of injection speed, melt temperature, injection pressure, holding pressure, holding time, and cooling time. Optimal conditions were determined as 40 mm/s injection speed, 170°C melt temperature, 110 MPa injection pressure, 35 MPa holding pressure, and a 7-s holding time. ANOVA results indicate that melt temperature, holding time, and holding pressure significantly influence sink marks and shrinkage. Under optimal conditions, the GRD value improved from 0.638 to 0.643. Furthermore, material testing confirmed the reliability of the optimized specimens, with tensile and flexural strengths within a 5% error margin of datasheet values. These findings validate the effectiveness of the proposed method in enhancing sample quality and consistency in family mold injection molding.
ISSN:1687-8140