Numerical Simulation-Based Design of Experiments for Optimization of Injection Molding Parameters to Minimize Warpage in Plastic Parts
Online First: 29/04/2026
Corressponding author's email:
phunt@hcmute.edu.vnDOI:
https://doi.org/10.54644/jte.2026.2113Keywords:
Numerical simulation, Injection molding, Processing parameters, Warpage, DOEAbstract
This study developed a numerical simulation model of the injection molding process to analyze the influence of processing parameters on product deformation and to determine an optimal parameter set for warpage minimization. The model successfully reproduced the filling, packing, and cooling stages, enabling detailed monitoring of temperature distribution, pressure evolution, and deformation fields throughout the entire molding cycle. The simulation results provide a scientific basis demonstrating that product warpage is primarily governed by two key mechanisms: differential temperature effects and volumetric shrinkage. For Ultramid A3 (PA66), volumetric shrinkage plays a dominant role, directly contributing to post-cooling deformation. By integrating the Design of Experiments (DOE) method with numerical simulation, the optimal processing parameters were determined as follows: melt temperature of 280 °C, mold temperature of 80 °C, packing time of 4 s, and maximum packing pressure of 60%. These conditions ensure a balanced interaction among filling behavior, packing effectiveness, and cooling rate, thereby significantly enhancing dimensional stability and reducing warpage. The proposed approach demonstrates strong effectiveness in injection molding process optimization and exhibits high potential for practical industrial application.
Downloads: 0
References
R. Y. Chang and W. H. Yang, “Numerical simulation of mold filling in injection molding using a three-dimensional finite volume approach,” Int. J. Numer. Methods Fluids, vol. 37, no. 2, pp. 125–148, 2001. DOI: https://doi.org/10.1002/fld.166
B. Ozcelik and T. Erzurumlu, “Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm,” J. Mater. Process. Technol., vol. 171, no. 3, pp. 437–445, 2006. DOI: https://doi.org/10.1016/j.jmatprotec.2005.04.120
B. Ozcelik, A. Ozbay, and E. Demirbas, “Influence of injection parameters and mold materials on mechanical properties of ABS in plastic injection molding,” Int. Commun. Heat Mass Transf., vol. 37, no. 9, pp. 1359–1365, 2010. DOI: https://doi.org/10.1016/j.icheatmasstransfer.2010.07.001
B. Ozcelik, “Optimization of injection parameters for mechanical properties of specimens with weld line of polypropylene using Taguchi method,” Int. Commun. Heat Mass Transf., vol. 38, no. 8, pp. 1067–1072, 2011. DOI: https://doi.org/10.1016/j.icheatmasstransfer.2011.04.025
H. Hassan, N. Regnier, C. Pujos, E. Arquis, and G. Defaye, “Modeling the effect of cooling system on the shrinkage and temperature of the polymer by injection molding,” Appl. Therm. Eng., vol. 30, no. 14–15, pp. 1547–1557, 2010. DOI: https://doi.org/10.1016/j.applthermaleng.2010.02.025
R. Sánchez, J. Aisa, A. Martínez, and D. Mercado, “On the relationship between cooling setup and warpage in injection molding,” Measurement, vol. 45, no. 5, pp. 1051–1056, 2012. DOI: https://doi.org/10.1016/j.measurement.2012.01.039
S. C. Nian, C. Y. Wu, and M. S. Huang, “Warpage control of thin-walled injection molding using local mold temperatures,” Int. Commun. Heat Mass Transf., vol. 57, pp. 24–30, 2015. DOI: https://doi.org/10.1016/j.icheatmasstransfer.2014.12.008
M. Mohan, M. N. M. Ansari, and R. A. Shanks, “Review on the effects of process parameters on strength, shrinkage, and warpage of injection molding plastic component,” Polym.-Plast. Technol. Eng., vol. 55, no. 8, pp. 819–830, 2016.
T. K. Nguyen, C. J. Hwang, and B. K. Lee, “Numerical investigation of warpage in insert injection-molded lightweight hybrid products,” Int. J. Precis. Eng. Manuf., vol. 18, no. 2, pp. 187–195, 2017. DOI: https://doi.org/10.1007/s12541-017-0024-5
S. Sudsawat and W. Sriseubsai, “Warpage reduction through optimized process parameters and annealed process of injection-molded plastic parts,” J. Mech. Sci. Technol., vol. 32, no. 11, pp. 4787–4799, 2018. DOI: https://doi.org/10.1007/s12206-018-0926-x
C. Fernandes, A. J. Pontes, J. C. Viana, and A. Gaspar-Cunha, “Modeling and optimization of the injection-molding process: A review,” Adv. Polym. Technol., vol. 37, no. 2, pp. 429–449, 2018. DOI: https://doi.org/10.1002/adv.21683
Z. Song, S. Liu, X. Wang, and Z. Hu, “Optimization and prediction of volume shrinkage and warpage of injection-molded thin-walled parts based on neural network,” Int. J. Adv. Manuf. Technol., vol. 109, pp. 755–769, 2020. DOI: https://doi.org/10.1007/s00170-020-05558-6
W. C. Chen, M. H. Nguyen, and W. H. Chiu, “Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO,” Int. J. Adv. Manuf. Technol., vol. 83, pp. 1873–1886, 2021. DOI: https://doi.org/10.1007/s00170-015-7683-0
J. Heinisch, Y. Lockner, and C. Hopmann, “Comparison of design of experiment methods for modeling injection molding experiments using artificial neural networks,” J. Manuf. Process., vol. 61, pp. 357–368, 2021. DOI: https://doi.org/10.1016/j.jmapro.2020.11.011
Y. Lockner and C. Hopmann, “Induced network-based transfer learning in injection molding for process modelling and optimization with artificial neural networks,” Int. J. Adv. Manuf. Technol., vol. 112, pp. 3501–3513, 2021. DOI: https://doi.org/10.1007/s00170-020-06511-3
T. P. Nguyen, T. L. Le, and M. T. U. Tran, “Numerical simulation on the effect of the cooling channel design on the warpage of a thin-wall injection molding product,” Mater. Sci. Forum, vol. 1075, pp. 95–101, 2022. DOI: https://doi.org/10.4028/p-8186h5
T. P. Nguyen and T. A. Bui, “Numerical optimization of the process conditions to improve the warpage inside the product and reduce the cooling time in the injection molding product,” Lect. Notes Mech. Eng., vol. 1, pp. 1–8, 2022. DOI: https://doi.org/10.1007/978-981-19-1968-8_25
T. P. Nguyen, H. X. L. Nguyen, X. V. Nguyen, and T. L. Le, “Reduce the displacement and the roundness of the round plastic product by the baffle cooling channel in the injection molding system,” Int. J. Appl. Sci. Eng., vol. 21, no. 4, Art. no. 430, 2024. DOI: https://doi.org/10.6703/IJASE.202409_21(4).009
C. C. Kuo and Y. X. Xu, “A simple method of improving warpage and cooling time of injection molded parts simultaneously,” Int. J. Adv. Manuf. Technol., vol. 122, pp. 619–637, 2022. DOI: https://doi.org/10.1007/s00170-022-09925-3
N. Y. Zhao, J. Y. Lian, and P. F. Wang, “Recent progress in minimizing the warpage and shrinkage deformations by the optimization of process parameters in plastic injection molding: A review,” Int. J. Adv. Manuf. Technol., vol. 120, pp. 85–101, 2022. DOI: https://doi.org/10.1007/s00170-022-08859-0
N. B. Guerra, T. M. Reis, T. Scopel, M. S. de Lima, C. A. Figueroa, and A. F. Michels, “Influence of process parameters and post-molding condition on shrinkage and warpage of injection-molded plastic parts with complex geometry,” Int. J. Adv. Manuf. Technol., vol. 128, pp. 479–490, 2023. DOI: https://doi.org/10.1007/s00170-023-11782-7
V. L. Trinh, “Reducing warpage of injection molding products using response surface methodology,” Eng. Technol. Appl. Sci. Res., vol. 15, no. 3, pp. 22355–22359, 2025. DOI: https://doi.org/10.48084/etasr.10495
CoreTech System Co., Ltd., “Moldex3D material database,” in Moldex3D Simulation Software. Hsinchu, Taiwan: CoreTech System Co., Ltd., 2025.
Downloads
Published
How to Cite
License
Copyright (c) 2026 Journal of Technical Education Science
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright © JTE.
