FDM KULLANILARAK ÜRETİLEN PLA NUMUNELERİNİN BASMA MUKAVEMETİNİ OPTİMİZE ETMEK İÇİN TAGUCHİ YÖNTEMİ
Year 2024,
, 133 - 140, 03.03.2024
Oğuz Tunçel
,
Mehmet Said Bayraklılar
Abstract
Bu çalışmada, Eriyik yığma modelleme (EYM) kullanarak üretilen PLA numunelerinin basma mukavemetini optimize etmek amacıyla Taguchi yöntemi uygulanmıştır. Çalışma, üç farklı işlem parametresini (duvar kalınlığı, dolgu deseni ve baskı hızı) optimize etmek için Taguchi L9 deney tasarımını kullanmıştır. Deneylerin analizi için S/N oranları ve ANOVA yöntemleri kullanılmıştır. Taguchi tekniği kullanılarak yapılan deneylerin sonuçları, S/N oranlarına göre analiz edilmiş ve en iyi sonuçlar elde edilen parametre seviyeleri belirlenmiştir. Duvar kalınlığı, dolgu deseni ve yazdırma hızı parametreleri için en iyi seviyeler belirlenmiş ve bu parametrelerin etkileri incelenmiştir. Duvar kalınlığının en etkili parametre olduğu ve dolum deseni ile baskı hızının ise daha az etkili olduğu sonucuna varılmıştır. ANOVA analizi, parametrelerin basma mukavemeti üzerindeki etkisini doğrulamıştır. Duvar kalınlığının en fazla katkı sağladığı (%70.20) ve dolgu deseninin ikinci yüksek katkı sağladığı (%29.11) görülmüştür.
References
- Bakar, N. S. A., Alkahari, M. R., & Boejang, H. (2010). Analysis on fused deposition modelling performance. Journal of Zhejiang University: Science A, 11(12), 972–977. https://doi.org/10.1631/jzus.A1001365
- Demir, S., & Yüksel, C. (2023). Evaluation of effect and optimizing of process parameters for fused deposition modeling parts on tensile properties via Taguchi method. Rapid Prototyping Journal, 29(4), 720–730. https://doi.org/10.1108/RPJ-06-2022-0201
- Dixit, N., & Jain, P. K. (2022). Effect of Fused Filament Fabrication Process Parameters on Compressive Strength of Thermoplastic Polyurethane and Polylactic Acid Lattice Structures. Journal of Materials Engineering and Performance, 31(7), 5973–5982. https://doi.org/10.1007/s11665-022-06664-0
- Hikmat, M., Rostam, S., & Ahmed, Y. M. (2021). Investigation of tensile property-based Taguchi method of PLA parts fabricated by FDM 3D printing technology. Results in Engineering, 11, 100264. https://doi.org/10.1016/j.rineng.2021.100264
- Hsueh, M. H., Lai, C. J., Wang, S. H., Zeng, Y. S., Hsieh, C. H., Pan, C. Y., & Huang, W. C. (2021). Effect of printing parameters on the thermal and mechanical properties of 3d-printed pla and petg, using fused deposition modeling. Polymers, 13(11). https://doi.org/10.3390/polym13111758
- Kafshgar, A. R., Rostami, S., Aliha, M. R. M., & Berto, F. (2021). Optimization of Properties for 3D Printed PLA Material Using Taguchi, ANOVA and Multi-Objective Methodologies. Procedia Structural Integrity, 34, 71–77. https://doi.org/10.1016/j.prostr.2021.12.011
- Lee, C. S., Kim, S. G., Kim, H. J., & Ahn, S. H. (2007). Measurement of anisotropic compressive strength of rapid prototyping parts. Journal of Materials Processing Technology, 187–188, 627–630. https://doi.org/10.1016/j.jmatprotec.2006.11.095
- Liu, X., Zhang, M., Li, S., Si, L., Peng, J., & Hu, Y. (2017). Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method. International Journal of Advanced Manufacturing Technology, 89(5–8), 2387–2397. https://doi.org/10.1007/s00170-016-9263-3
- Mohamed, O. A., Masood, S. H., & Bhowmik, J. L. (2015). Optimization of fused deposition modeling process parameters: a review of current research and future prospects. Advances in Manufacturing, 3(1), 42–53. https://doi.org/10.1007/s40436-014-0097-7
- Mohan, N., Senthil, P., Vinodh, S., & Jayanth, N. (2017). A review on composite materials and process parameters optimisation for the fused deposition modelling process. Virtual and Physical Prototyping, 12(1), 47–59. https://doi.org/10.1080/17452759.2016.1274490
- Nathaphan, S., & Trutassanawin, W. (2021). Effects of process parameters on compressive property of FDM with ABS. Rapid Prototyping Journal, 27(5), 905–917. https://doi.org/10.1108/RPJ-12-2019-0309
- Darbar, R., & Patel, P.M. (2017). Optimization of Fused Deposition Modeling Process Parameter for Better Mechanical Strength and Surface Roughness. International Journal of Mechanical Engineering (IJME), 6(6), 7–18.
- Sai, T., Pathak, V. K., & Srivastava, A. K. (2020). Modeling and optimization of fused deposition modeling (FDM) process through printing PLA implants using adaptive neuro-fuzzy inference system (ANFIS) model and whale optimization algorithm. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 42(12), 1–19. https://doi.org/10.1007/s40430-020-02699-3
- Sood, A. K., Ohdar, R. K., & Mahapatra, S. S. (2012). Experimental investigation and empirical modelling of FDM process for compressive strength improvement. Journal of Advanced Research, 3(1), 81–90. https://doi.org/10.1016/j.jare.2011.05.001
- Torres, J., Cotelo, J., Karl, J., & Gordon, A. P. (2015). Mechanical property optimization of FDM PLA in shear with multiple objectives. Jom, 67(5), 1183–1193. https://doi.org/10.1007/s11837-015-1367-y
THE APPLICATION OF THE TAGUCHI METHOD FOR OPTIMIZING THE COMPRESSION STRENGTH OF PLA SAMPLES PRODUCED USING FDM
Year 2024,
, 133 - 140, 03.03.2024
Oğuz Tunçel
,
Mehmet Said Bayraklılar
Abstract
In this study, the Taguchi method was applied to optimize the compressive strength of PLA samples produced using Fused Deposition Modelling (FDM). The study used Taguchi L9 experimental design to optimize three different process parameters (wall thickness, filling pattern, and printing speed). S/N ratios and ANOVA methods were used to analyze the experiments. The results of the experiments using the Taguchi technique were analyzed according to S/N ratios and the parameter levels with the best results were determined. The best levels for wall thickness, filling pattern, and print speed parameters were determined and the effects of these parameters were analyzed. It was concluded that wall thickness was the most effective parameter and filling pattern and print speed were less effective. ANOVA analysis confirmed the influence of the parameters on the compressive strength. It was observed that wall thickness contributed the most (70.20%) and filling pattern contributed the second most (29.11%).
References
- Bakar, N. S. A., Alkahari, M. R., & Boejang, H. (2010). Analysis on fused deposition modelling performance. Journal of Zhejiang University: Science A, 11(12), 972–977. https://doi.org/10.1631/jzus.A1001365
- Demir, S., & Yüksel, C. (2023). Evaluation of effect and optimizing of process parameters for fused deposition modeling parts on tensile properties via Taguchi method. Rapid Prototyping Journal, 29(4), 720–730. https://doi.org/10.1108/RPJ-06-2022-0201
- Dixit, N., & Jain, P. K. (2022). Effect of Fused Filament Fabrication Process Parameters on Compressive Strength of Thermoplastic Polyurethane and Polylactic Acid Lattice Structures. Journal of Materials Engineering and Performance, 31(7), 5973–5982. https://doi.org/10.1007/s11665-022-06664-0
- Hikmat, M., Rostam, S., & Ahmed, Y. M. (2021). Investigation of tensile property-based Taguchi method of PLA parts fabricated by FDM 3D printing technology. Results in Engineering, 11, 100264. https://doi.org/10.1016/j.rineng.2021.100264
- Hsueh, M. H., Lai, C. J., Wang, S. H., Zeng, Y. S., Hsieh, C. H., Pan, C. Y., & Huang, W. C. (2021). Effect of printing parameters on the thermal and mechanical properties of 3d-printed pla and petg, using fused deposition modeling. Polymers, 13(11). https://doi.org/10.3390/polym13111758
- Kafshgar, A. R., Rostami, S., Aliha, M. R. M., & Berto, F. (2021). Optimization of Properties for 3D Printed PLA Material Using Taguchi, ANOVA and Multi-Objective Methodologies. Procedia Structural Integrity, 34, 71–77. https://doi.org/10.1016/j.prostr.2021.12.011
- Lee, C. S., Kim, S. G., Kim, H. J., & Ahn, S. H. (2007). Measurement of anisotropic compressive strength of rapid prototyping parts. Journal of Materials Processing Technology, 187–188, 627–630. https://doi.org/10.1016/j.jmatprotec.2006.11.095
- Liu, X., Zhang, M., Li, S., Si, L., Peng, J., & Hu, Y. (2017). Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method. International Journal of Advanced Manufacturing Technology, 89(5–8), 2387–2397. https://doi.org/10.1007/s00170-016-9263-3
- Mohamed, O. A., Masood, S. H., & Bhowmik, J. L. (2015). Optimization of fused deposition modeling process parameters: a review of current research and future prospects. Advances in Manufacturing, 3(1), 42–53. https://doi.org/10.1007/s40436-014-0097-7
- Mohan, N., Senthil, P., Vinodh, S., & Jayanth, N. (2017). A review on composite materials and process parameters optimisation for the fused deposition modelling process. Virtual and Physical Prototyping, 12(1), 47–59. https://doi.org/10.1080/17452759.2016.1274490
- Nathaphan, S., & Trutassanawin, W. (2021). Effects of process parameters on compressive property of FDM with ABS. Rapid Prototyping Journal, 27(5), 905–917. https://doi.org/10.1108/RPJ-12-2019-0309
- Darbar, R., & Patel, P.M. (2017). Optimization of Fused Deposition Modeling Process Parameter for Better Mechanical Strength and Surface Roughness. International Journal of Mechanical Engineering (IJME), 6(6), 7–18.
- Sai, T., Pathak, V. K., & Srivastava, A. K. (2020). Modeling and optimization of fused deposition modeling (FDM) process through printing PLA implants using adaptive neuro-fuzzy inference system (ANFIS) model and whale optimization algorithm. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 42(12), 1–19. https://doi.org/10.1007/s40430-020-02699-3
- Sood, A. K., Ohdar, R. K., & Mahapatra, S. S. (2012). Experimental investigation and empirical modelling of FDM process for compressive strength improvement. Journal of Advanced Research, 3(1), 81–90. https://doi.org/10.1016/j.jare.2011.05.001
- Torres, J., Cotelo, J., Karl, J., & Gordon, A. P. (2015). Mechanical property optimization of FDM PLA in shear with multiple objectives. Jom, 67(5), 1183–1193. https://doi.org/10.1007/s11837-015-1367-y