Simulation of the filling stage for the PC+ABS blend during the injection molding process https://doi.org/10.15332/24222399.2939
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Published:
Feb 27, 2024
Keywords:
Injection molding, Filling phase, Mold design, PC ABS blends, Process parameters, Cross-viscosity model
Main Article Content
Abstract
The computational fluid dynamics simulation presented shows the behavior of the PC+ABS blends during the injection phase through a transient analysis of the injection molding process. The Fluent® computational fluid dynamic analysis module of Ansys Workbench® makes it possible to know the behavior of the injected material according to its properties and the design of the geometry of the injected product, represented by the mold cavities (fluid domain). The implementation of simulation allows engineers and processors to efficiently analyze the filling phase from early design stages due to obtaining the results of maximum filling pressure, visualization of the polymer flow front, pressure increase at the inlet, and the temperature of the flow front at the end of the injection phase. In conclusion, the computational simulation generates a prior understanding of the filling phase while minimizing the failures found until the advanced stages of production (injection mold and injected product manufactured). In addition, it guarantees the reduction of time and costs of the injection molding process through a completely computer-assisted environment.
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How to Cite
Benitez Prada , J. E., Aguilera Gómez, E., Plascencia Mora , H., Méndez Hernández , J. M., & Reveles Arredondo, J. F. (2024). Simulation of the filling stage for the PC+ABS blend during the injection molding process: https://doi.org/10.15332/24222399.2939 . Ingenio Magno, 14(2), 22 -32. Retrieved from http://revistas.ustatunja.edu.co/index.php/ingeniomagno/article/view/2939
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Articulos
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References
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[18] Kalwik, A., Humienny, R., & Mordal, K. (2022). Assessment of the Impact of Injection Moulding Process Parameters on the Properties of Mouldings Made of Low-Density Poly(ethylene) Recyclate LDPE. Archives of Metallurgy and Materials, 67(3), 1043–1049. https://doi.org/10.24425/amm.2022.139700
[19] Kashyap, S., & Datta, D. (2015). Process parameter optimization of plastic injection molding: a review. International Journal of Plastics Technology, 19(1), 1–18. https://doi.org/10.1007/s12588-015-9115-2
[20] Khosravani, M. R., & Nasiri, S. (2020). Injection molding manufacturing process: review of case-based reasoning applications. Journal of Intelligent Manufacturing, 31(4), 847–864. https://doi.org/10.1007/s10845-019-01481-0
[21] Lucyshyn, T., Enffans D’Avernas, L. V. Des, & Holzer, C. (2021). Influence of the mold material on the injection molding cycle time and warpage depending on the polymer processed. Polymers, 13(18). https://doi.org/10.3390/polym13183196
[22] Myers, M., Mulyana, R., Castro, J. M., & Hoffman, B. (2023). Experimental Development of an Injection Molding Process Window. Polymers, 15(15). https://doi.org/10.3390/polym15153207
[23] Oliaei, E., Heidari, B. S., Davachi, S. M., Bahrami, M., Davoodi, S., Hejazi, I., & Seyfi, J. (2016). Warpage and Shrinkage Optimization of Injection-Molded Plastic Spoon Parts for Biodegradable Polymers Using Taguchi, ANOVA and Artificial Neural Network Methods. Journal of Materials Science and Technology, 32(8), 710–720. https://doi.org/10.1016/j.jmst.2016.05.010
[24] Páramo, J. J., Reveles Arredondo, J. F., Mora, H. P., & Gómez, E. A. (2019). Análisis de un proceso de inyección de plástico por interacción fluido estructural y cambio de estado. Acta Universitaria, 29, 1–18. https://doi.org/10.15174/au.2019.2150
[25] Rusdi, M. S., Abdullah, M. Z., Mahmud, A. S., Khor, C. Y., Abdul Aziz, M. S., Ariff, Z. M., & Abdullah, M. K. (2016). Numerical Investigation on the Effect of Pressure and Temperature on the Melt Filling During Injection Molding Process. Arabian Journal for Science and Engineering, 41(5), 1907–1919. https://doi.org/10.1007/s13369-016-2039-0
[26] Shen, Y. K., Wu, C. W., Yu, Y. F., & Chung, H. W. (2008). Analysis for optimal gate design of thin-walled injection molding. International Communications in Heat and Mass Transfer, 35(6), 728–734. https://doi.org/10.1016/j.icheatmasstransfer.2008.01.014
[27] Veltmaat, L., Mehrens, F., Endres, H. J., Kuhnert, J., & Suchde, P. (2022). Mesh-free simulations of injection molding processes. Physics of Fluids, 34(3), 1–39. https://doi.org/10.1063/5.0085049
[28] Wang, J., Hopmann, C., Kahve, C., Hohlweck, T., & Alms, J. (2020). Measurement of specific volume of polymers under simulated injection molding processes. Materials and Design, 196, 109136. https://doi.org/10.1016/j.matdes.2020.109136
[29] Yu, S., Zhang, T., Zhang, Y., Huang, Z., Gao, H., Han, W., Turng, L. S., & Zhou, H. (2020). Intelligent setting of process parameters for injection molding based on case-based reasoning of molding features. Journal of Intelligent Manufacturing, 33(1), 77–89. https://doi.org/10.1007/s10845-020-01658-y
[2] Araújo, C., Pereira, D., Dias, D., Marques, R., & Cruz, S. (2023). In-cavity pressure measurements for failure diagnosis in the injection moulding process and correlation with numerical simulation. The International Journal of Advanced Manufacturing Technology, 126(1–2), 291–300. https://doi.org/10.1007/s00170-023-11100-1
[3] ASTM D3641-02. (2002). Standard Practice for Injection Molding Test Specimens of Thermoplastic Molding and Extrusion Materials. ASTM International. https://doi.org/10.1520/D3641-02
[4] ASTM D638-02a. (2002). Standard Test Method for Tensile Properties of Plastics. ASTM International. https://doi.org/10.1520/D0638-02A
[5] Baum, M., Jasser, F., Stricker, M., Anders, D., & Lake, S. (2022). Numerical simulation of the mold filling process and its experimental validation. The International Journal of Advanced Manufacturing Technology, 120(5–6), 3065–3076. https://doi.org/10.1007/s00170-022-08888-9
[6] Chung, C. Y., Hwang, S. S., Chen, S. C., & Lai, M. C. (2021). Effects of injection molding process parameters on the chemical foaming behavior of polypropylene and polystyrene. Polymers, 13(14). https://doi.org/10.3390/polym13142331
[7] Czepiel, M., Bańkosz, M., & Sobczak-Kupiec, A. (2023). Advanced Injection Molding Methods: Review. Materials, 16(17). https://doi.org/10.3390/ma16175802
[8] De Miranda, D. A., & Nogueira, A. L. (2019). Simulation of an injection process using a CAE tool: Assessment of operational conditions and mold design on the process efficiency. Materials Research, 22(2). https://doi.org/10.1590/1980-5373-MR-2018-0564
[9] Deng, L., Fan, S., Zhang, Y., Huang, Z., Zhou, H., Jiang, S., & Li, J. (2021). Multiscale modeling and simulation of polymer blends in injection molding: A review. Polymers, 13(21), 1–26. https://doi.org/10.3390/polym13213783
[10] Fu, H., Xu, H., Liu, Y., Yang, Z., Kormakov, S., Wu, D., & Sun, J. (2020). Overview of Injection Molding Technology for Processing Polymers and Their Composites. ES Materials and Manufacturing, 8, 3–23. https://doi.org/10.30919/esmm5f713
[11] Fu, J., & Ma, Y. (2019). A method to predict early-ejected plastic part air-cooling behavior towards quality mold design and less molding cycle time. Robotics and Computer-Integrated Manufacturing, 56(July 2018), 66–74. https://doi.org/10.1016/j.rcim.2018.08.004
[12] Galuppo, W. de C., Magalhães, A., Ferrás, L. L., Nóbrega, J. M., & Fernandes, C. (2021). New boundary conditions for simulating the filling stage of the injection molding process. Engineering Computations, 38(2), 762–778. https://doi.org/10.1108/EC-04-2020-0190
[13] Godec, D., Brnadić, V., & Breški, T. (2021). Optimisation of Mould Design for Injection Moulding – Numerical Approach. Technical Journal, 15(2), 258–266. https://doi.org/10.31803/tg-20210531204548
[14] Hentati, F., Hadriche, I., Masmoudi, N., & Bradai, C. (2019). Optimization of the injection molding process for the PC/ABS parts by integrating Taguchi approach and CAE simulation. The International Journal of Advanced Manufacturing Technology, 104(9–12), 4353–4363. https://doi.org/10.1007/s00170-019-04283-z
[15] Huszar, M., Belblidia, F., Davies, H. M., Arnold, C., Bould, D., & Sienz, J. (2015). Sustainable injection moulding: The impact of materials selection and gate location on part warpage and injection pressure. Sustainable Materials and Technologies, 5, 1–8. https://doi.org/10.1016/j.susmat.2015.07.001
[16] Jachowicz, T., Gajdoš, I., Cech, V., & Krasinskyi, V. (2021). The use of numerical analysis of the injection process to select the material for the injection molding. Open Engineering, 11(1), 963–976. https://doi.org/10.1515/eng-2021-0094
[17] Jurado Páramo, J., Plascencia Mora, H., & Aguilera Gómez, E. (2021). Simulación numérica de una prueba de reología capilar para un polímero PC+ABS. Ingenio Magno, 12(1), 66–76.
[18] Kalwik, A., Humienny, R., & Mordal, K. (2022). Assessment of the Impact of Injection Moulding Process Parameters on the Properties of Mouldings Made of Low-Density Poly(ethylene) Recyclate LDPE. Archives of Metallurgy and Materials, 67(3), 1043–1049. https://doi.org/10.24425/amm.2022.139700
[19] Kashyap, S., & Datta, D. (2015). Process parameter optimization of plastic injection molding: a review. International Journal of Plastics Technology, 19(1), 1–18. https://doi.org/10.1007/s12588-015-9115-2
[20] Khosravani, M. R., & Nasiri, S. (2020). Injection molding manufacturing process: review of case-based reasoning applications. Journal of Intelligent Manufacturing, 31(4), 847–864. https://doi.org/10.1007/s10845-019-01481-0
[21] Lucyshyn, T., Enffans D’Avernas, L. V. Des, & Holzer, C. (2021). Influence of the mold material on the injection molding cycle time and warpage depending on the polymer processed. Polymers, 13(18). https://doi.org/10.3390/polym13183196
[22] Myers, M., Mulyana, R., Castro, J. M., & Hoffman, B. (2023). Experimental Development of an Injection Molding Process Window. Polymers, 15(15). https://doi.org/10.3390/polym15153207
[23] Oliaei, E., Heidari, B. S., Davachi, S. M., Bahrami, M., Davoodi, S., Hejazi, I., & Seyfi, J. (2016). Warpage and Shrinkage Optimization of Injection-Molded Plastic Spoon Parts for Biodegradable Polymers Using Taguchi, ANOVA and Artificial Neural Network Methods. Journal of Materials Science and Technology, 32(8), 710–720. https://doi.org/10.1016/j.jmst.2016.05.010
[24] Páramo, J. J., Reveles Arredondo, J. F., Mora, H. P., & Gómez, E. A. (2019). Análisis de un proceso de inyección de plástico por interacción fluido estructural y cambio de estado. Acta Universitaria, 29, 1–18. https://doi.org/10.15174/au.2019.2150
[25] Rusdi, M. S., Abdullah, M. Z., Mahmud, A. S., Khor, C. Y., Abdul Aziz, M. S., Ariff, Z. M., & Abdullah, M. K. (2016). Numerical Investigation on the Effect of Pressure and Temperature on the Melt Filling During Injection Molding Process. Arabian Journal for Science and Engineering, 41(5), 1907–1919. https://doi.org/10.1007/s13369-016-2039-0
[26] Shen, Y. K., Wu, C. W., Yu, Y. F., & Chung, H. W. (2008). Analysis for optimal gate design of thin-walled injection molding. International Communications in Heat and Mass Transfer, 35(6), 728–734. https://doi.org/10.1016/j.icheatmasstransfer.2008.01.014
[27] Veltmaat, L., Mehrens, F., Endres, H. J., Kuhnert, J., & Suchde, P. (2022). Mesh-free simulations of injection molding processes. Physics of Fluids, 34(3), 1–39. https://doi.org/10.1063/5.0085049
[28] Wang, J., Hopmann, C., Kahve, C., Hohlweck, T., & Alms, J. (2020). Measurement of specific volume of polymers under simulated injection molding processes. Materials and Design, 196, 109136. https://doi.org/10.1016/j.matdes.2020.109136
[29] Yu, S., Zhang, T., Zhang, Y., Huang, Z., Gao, H., Han, W., Turng, L. S., & Zhou, H. (2020). Intelligent setting of process parameters for injection molding based on case-based reasoning of molding features. Journal of Intelligent Manufacturing, 33(1), 77–89. https://doi.org/10.1007/s10845-020-01658-y