Multi - response optimization of injection molding process parameters using moldex 3D
Các tác giả
DOI: https://doi.org/10.59294/HIUJS.VOL.4.2023.393Từ khóa:
Injection molding, Moldex 3D, multi - response optimizationTóm tắt
The research is an approach to multi - response optimization of injection molding process parameters. In this author uses Moldex 3D to analyse the injection molding process. The experiments are plotted using L9 orthogonal array, which is generated with the help of DOE module in Moldex3D software. The process parameters melt temperature, packing time, Max. packing pressure are optimized by multiple response consideration of max cooling time and warpage. With the help of Moldex 3D software, the desirability function analysis optimal values of process parameters are obtained. The analysis shows optimized process parameters combination of melt temperature, packing time and max- packing pressure which are 250 oC, 6s, and 140 Mpa respectively. The confirm run results show that by this injection molding machine performance can be improved. However, the future work should be needed to analyze multi cavity molding for the part which is more appliable before we can make the real run.
Abstract
The research is an approach to multi - response optimization of injection molding process parameters. In this author uses Moldex 3D to analyse the injection molding process. The experiments are plotted using L9 orthogonal array, which is generated with the help of DOE module in Moldex3D software. The process parameters melt temperature, packing time, Max. packing pressure are optimized by multiple response consideration of max cooling time and warpage. With the help of Moldex 3D software, the desirability function analysis optimal values of process parameters are obtained. The analysis shows optimized process parameters combination of melt temperature, packing time and max- packing pressure which are 250 oC, 6s, and 140 Mpa respectively. The confirm run results show that by this injection molding machine performance can be improved. However, the future work should be needed to analyze multi cavity molding for the part which is more appliable before we can make the real run.
Tài liệu tham khảo
[1] A. H. Ahmad, Leman, Z., Azmir, M. A., Muhamad, K. F., Harun, W. S. W., Juliawati, A., & Alias, "ABS In Modelling & Simulation," AMS'09, Third Asia International Conference on pp. 470-474, 2009.
DOI: https://doi.org/10.1109/AMS.2009.120[2] A. Tootoonchi, "A.International Journal of Modeling and Optimization," 2011.
[3] M. F. Ghazali, Shayfull, Z., Shuaib, N. A., Nasir, S. M., & Salleh, "Int J of Basic & Appl Sci," IJBAS-IJENS, no. 11(01), 2011.
[4] M. G. Villarreal, Mulyana, R., Castro, J. M., & Cabrera-Ríos, "In Simulation Conference," IEEE, no. WSC 2008. Winter (2008) -1995-2003, 2008.
DOI: https://doi.org/10.1109/WSC.2008.4736294[5] C.-W. Su et al., "Optimization process parameters and adaptive quality monitoring injection molding process for materials with different viscosity," Polymer Testing, vol. 109, p. 107526, 2022/05/01/ 2022.
DOI: https://doi.org/10.1016/j.polymertesting.2022.107526[6] G. Singh, M. K. Pradhan, and A. Verma, "Multi Response optimization of injection moulding Process parameters to reduce cycle time and warpage," Materials Today: Proceedings, vol. 5, no. 2, Part 2, pp. 8398-8405, 2018/01/01/ 2018.
DOI: https://doi.org/10.1016/j.matpr.2017.11.534[7] M. L. Wang, R. Y. Chang, and C. H. Hsu, Molding Simulation: Theory and Practice. Carl Hanser Verlag GmbH & Company KG, 2018.
[8] R. K. Roy and R. Rāẏa, A Primer on the Taguchi Method. Van Nostrand Reinhold, 1990.
Tải xuống
Tải xuống: 77
Đã xuất bản
Cách trích dẫn
Số
Chuyên mục
