Simulación de la etapa de llenado de la mezcla PC+ABS durante el proceso de moldeo por inyección
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Publicado:
feb 27, 2024
Palabras clave:
Moldeo por inyección, Fase de llenado, diseño de molde, Mezcla de PC ABS, Parámetros de proceso, Modelo de viscosidad de Cross.
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Resumen
La simulación computacional de la dinámica del fluido presentada muestra el comportamiento de la mezcla PC+ABS durante la fase de inyección mediante un análisis transitorio del proceso de moldeo por inyección. El módulo de análisis fluidodinámico computacional Fluent® de Ansys Workbench® posibilita conocer el comportamiento del material inyectado de acuerdo a sus propiedades y al diseño de la geometría del producto inyectado, representado por las cavidades del molde (domino fluido). La implementación de la simulación permite a los ingenieros y procesadores analizar de manera eficiente la fase de llenado desde etapas tempranas de diseño debido a la obtención de los resultados de presión máxima de llenado, visualización del frente de flujo del polímero, el incremento de la presión a la entrada, y la temperatura del frente de flujo al final de la fase de inyección. En conclusión, la simulación computacional genera una comprensión previa de la fase de llenado al tiempo que minimiza las fallas encontradas hasta etapas avanzadas de la producción (molde de inyección y producto inyectado fabricados). Además, garantiza la reducción de tiempos y costos del proceso de moldeo por inyección mediante un entorno completamente asistido por ordenador.
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Benitez Prada , J. E., Aguilera Gómez, E., Plascencia Mora , H., Méndez Hernández , J. M., & Reveles Arredondo, J. F. (2024). Simulación de la etapa de llenado de la mezcla PC+ABS durante el proceso de moldeo por inyección. Ingenio Magno, 14(2), 22 -32. Recuperado a partir de http://revistas.ustatunja.edu.co/index.php/ingeniomagno/article/view/2939
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Por medio del presente documento, certifico(amos) que el artículo que se presenta para posible publicación en la revista institucional INGENIO MAGNO del Centro de Investigaciones de Ingeniería Alberto Magno CIIAM de la Universidad Santo Tomás, seccional Tunja, es de mi (nuestra) entera autoría, siendo su contenido producto de mi (nuestra) directa contribución intelectual y aporte al conocimiento.
Todos los datos y referencias a publicaciones hechas están debidamente identificados con su respectiva nota bibliográfica y en las citas que se destacan como tal. De requerir alguna clase de ajuste o corrección, comunicaré(emos) de tal procedimiento con antelación a los responsables de la revista.
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Citas
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[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
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[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
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[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
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[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
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[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
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[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
[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