Optimization of warpage defects using the Taguchi method: A failure analysis in plastic injection molding

Abstract

This study aims to improve the warpage quality of an injection-molded product, specifically, the Wafer Carrier Cover Tray made from polypropylene (PP). Warpage is a common defect in injection molding that affects product accuracy and manufacturing efficiency. The research focuses on optimizing injection molding parameters to reduce warpage and enhance quality, using the Taguchi method for systematic analysis. Moldflow Simulation Advisor software was employed to model the injection molding process. The study used Taguchi orthogonal arrays and signal-to-noise ratio analysis to find optimal process parameters, while analysis of variance (ANOVA) assessed their significance. Key parameters included mold temperature, cooling time, melt temperature, and injection pressure. Results showed that mold temperature, cooling time, and melt temperature significantly influence warpage, with mold temperature having the greatest impact at 74.96%. The optimal settings identified included a melt temperature of 180 °C. This research highlights the importance of controlling melt temperature, cooling time, and injection pressure to achieve better product quality. The findings are applicable to the injection molding industry, helping manufacturers reduce warpage, improve quality, and enhance efficiency. The use of CAE software and the Taguchi method provides a cost-effective approach to process optimization, which can also benefit other injection-molded products. Overall, this study advances the understanding of warpage control in injection molding for high-precision components across various industries.