Optimization of Fused Deposition Modeling Process Parameters to Achieve Maximum Mechanical Properties Using Response Surface Methodology

Subject Areas :

Ali  Hasanabadi ¹ (Department of Mechanical Engineering, University of Birjand, Iran)
Hossein  Afshari ² (Mechanical Engineering, Department University of Birjand , Iran)
Seyyed Mohammad Bagher  Mirafzali ³ (Mechanical Engineering Department, University of Birjand, Birjand, Iran)

Received: 2023-08-01 Accepted : 2023-11-17 Published : 2023-08-01

Keywords: response surface methodology, Mechanical Properties, Fused deposition modeling, Polylactic Acid,

Abstract :

In this study, the researchers investigated the impact of various parameters, including layer raster angle, infill extrusion width, and layer height, on mechanical properties such as tensile strength, elongation, and Young's modulus of polylactic acid printed samples. To reduce experimental costs, the Box-Behnken method was employed along with response surface methodology using Minitab software to establish the relationship between input and output variables. The results of the tension test indicated that the raster angle had a significant impact on all three properties. Furthermore, the regression equations showed that changes in infill extrusion width and layer height had a strong effect on tensile strength but had a less significant impact on elongation and Young's modulus. The optimal output parameters were determined to be 38.67 MPa tensile strength, 3.42% elongation, and 1117.47 MPa Young's modulus using input parameters of 10 degree raster angle, 170% infill extrusion width, and 0.2 mm layer height. The study validated the results obtained through experimental testing and concluded that the response surface methodology could predict part properties with high accuracy (less than 6% error) based on input parameters.

References:

[1] Shahrubudin, N., Lee, T.C., and Ramlan, R. 2019. An Overview on 3D Printing Technology: Technological Materials, and Applications. Procedia Manufacturing. 35:1286-1296. doi: 10.1016/j.promfg.2019.06.089.
[2]Arumaikkannu, G., Anilkumar, N., and Saravanan, R. 2008. Study on the influence of rapid prototyping parameters on product quality in 3D printing. International Solid Freeform Fabrication Symposium. Texas, USA.
[3]Chua, C.K., Leong, K.F. and Lim, C.S. 2010. Rapid prototyping: principles and applications. World Scientific Publishing Company. Singapore.
[4]Yao, T., Deng, Z., Zhang, K. and Li, S. 2019. A method to predict the ultimate tensile strength of 3D printing polylactic acid (PLA) materials with different printing orientations. Composites Part B: Engineering.163:393-402. doi:10.1016/j.compositesb.2019.01.025.
[5]Srivastava, M., Maheshwari, S., and Kundra, T. 2015. Virtual modelling and simulation of functionally graded material component using FDM technique. Materials Today: Proceedings. 2:3471-3480. doi: 10.1016/j.matpr.2015.07.323.
[6]Waran, V., Narayanan, V., Karuppiah, R. Owen, S. and Aziz, T. 2013. Utility of multimaterial 3D printers in creating models with pathological entities to enhance the training experience of neurosurgeons. Technical note. Journal of neurosurgery, 120(2):489-492. doi: 10.3171/2013.11.JNS131066.
[7]Vaezi, M., Chianrabutra, S., Mellor, B., and Yang, S. 2013. Multiple material additive manufacturing–Part 1: a review: Virtual and Physical Prototyping. 8:19-50. doi: 10.1080/17452759.2013.778175
[8]Han, S.H., Cha, M., Jin, Y.Z., Lee, K.M. and Lee, J.H. 2020. BMP-2 and hMSC dual delivery onto 3D printed PLA-Biogel scaffold for critical-size bone defect regeneration in rabbit tibia. Biomedical Materials. 16(1):015019. doi:10.1088/1748-605X/aba879.
[9]Moreno, R., Carou, D., Alvarez, D.C. and Gupta, M.K. 2020. Statistical models for the mechanical properties of 3D printed external medical aids. Rapid Prototyping Journal. 27(1):176-186. doi: 10.1108/RPJ-02-2020-0033.
[10] Pucci, J.U., Christophe, B.R., Sisti, J.A. and Connolly E.S. 2017. Three-dimensional printing: technologies, applications, and limitations in neurosurgery. Biotechnology advances. 35(5):521-529. doi:10.1016/j.biotechadv.2017.05.007.
[11] Zein, I., Hutmacher, D.W, Tan, K.C. and Teoh, S. H. 2002. Fused deposition modeling of novel scaffold architectures for tissue engineering applications. Biomaterials. 23(4):1169-1185. doi:S0142-9612(01)00232-0.
[12] Peng, A., Xiao, X. and Yue, R. 2014. Process parameter optimization for fused deposition modeling using response surface methodology combined with fuzzy inference system. The International Journal of Advanced Manufacturing Technology. 73:87-100. doi:10.1007/s00170-014-5796-5.
[13] Hongyao, S., Xiaoxiang, Y. and Jianzhong, F. 2018. Research on the flexible support platform for fused deposition modeling. The International Journal of Advanced Manufacturing Technology. 97:3205-3221. doi:10.1007/s00170-018-2046-2.
[14] Hasanzadeh, R. and Azdast, T. 2021. Optimization of FDM 3D Printing Process Parameters of Biodegradable Poly Lactic Acid Polymeric Samples (in Persian). Modares Mechanical Engineering. 21(2):69-78. dor:20.1001.1.10275940.1399.21.2.2.8.
[15] Patterson, A.E., Chadha, C. and Jasiuk, I.M. 2021. Identification and Mapping of Manufacturability Constraints for Extrusion-Based Additive Manufacturing. Journal of Manufacturing and Materials Processing. 5(2):33. doi:10.3390/jmmp5020033.
[16] Nabipour, M., Behravesh, A.H. and Akhoundi, B. 2017. Effect of printing parameters on Mechanical Strength of Polymer-Metal composites Printed via FDM 3D printer (in Persian). Modares Mechanical Engineering. 17(1):145-150. dor:20.1001.1.10275940.1396.17.1.38.8.
[17] Bottini, L. and Boschetto. 2014. Surface Characterization in Fused Deposition Modeling in Surface Engineering Techniques and Applications: Research Advancements. IGI Global publishing. doi:10.4018/978-1-4666-5141-8.ch008.
[18] Brajlih, T., Valentan, B., Balic, J. and Igor, D. 2011. Speed and accuracy evaluation of additive manufacturing machines. Rapid Prototyping Journal. 17(1):64-75. doi:10.1108/13552541111098644.
[19] Žarko, J.,Vladić, G., Pál, M. and Dedijer, S. 2017. Influence of printing speed on production of embossing tools using FDM 3D printing technology. Journal of Graphic Engineering and Design. 8(1):19-27. doi:10.24867/JGED-2017-1-019.
[20] Rinanto, A., Nugroho, A., Prasetyo, H.and Pujiyanto, E. 2018. Simultaneous Optimization of Tensile Strength, Energy Consumption and Processing Time on FDM Process Using Taguchi and PCR-TOPSIS. 4th International Conference on Science and Technology (ICST). Yogyakarta. Indonesia. doi:10.1109/ICSTC.2018.8528667.
[21] Feng, L. Wang, Y. and Wei, Q. 2019. PA12 powder recycled from SLS for FDM. Polymers. 11(4):727. doi:10.3390/polym11040727.
[22] Faramarzian Haghighi, A., Haerian Ardakani, A., Kafaee Razavi, M. and Moloodi, A. 2019. Simulation of Mechanical Behavior and Construction of Regular PLA Scaffolds (in Persian). Modares Mechanical Engineering. 19(8):1953-1958. dor: 20.1001.1.10275940.1398.19.8.9.7
[23] Shadvar, N., Badrossamay, M. and Foroozmehr, E. 2016. Modelling of polycaprolactone extrusion in additive manufacturing process by fused deposition modelling in ansys-polyflow software. Modares Mechanical Engineering. 15(13):440-444.
[24] Amouhadi, I., Foroozmehr, E. and Badrossamay, M. 2016. Experimental analysis of the effects of contour width and built orientation on dimensional accuracy of FDM made parts and introducing an error prediction model. Modares Mechanical Engineering. 15(13):445-449.
[25] Naghieh, S., Karamooz Ravari, M.R., Badrossamay, M., Foroozmehr, E. and Kadkhodaei, M. 2016. Finite element analysis for predicting the mechanical properties of bone scaffolds fabricated by fused deposition modeling (FDM). Modares Mechanical Engineering. 15(13):450-454.
[26] Karnan, B., Pavan, M., Ali, S.K. and Gnaniar, K. 2021. Compression and flexural study on PLA-Cu composite filament using FDM. Materials Today: Proceedings. 44(1):1687-1691. doi:10.1016/j.matpr.2020.11.858.
[27] Patil, P., Singh, D., Raykar, S. and Bhamu, J. 2021. Multi-objective optimization of process parameters of Fused Deposition Modeling (FDM) for printing Polylactic Acid (PLA) polymer components. Materials Today: Proceedings. 45(6):4880-4885. doi:10.1016/j.matpr.2021.01.353.
[28] Giri, J., Shahane, P., Jachak, S., Chadge, R. and Giri, P. 2021. Optimization of FDM process parameters for dual extruder 3D printer using Artificial Neural network. Materials Today: Proceedings. 43(5):3242-3249. doi:10.1016/j.matpr.2021.01.899.
[29] Dey, A. andYodo, N. 2019. A Systematic Survey of FDM Process Parameter Optimization and Their Influence on Part Characteristics. Journal of Manufacturing and Materials Processing. 3(3):64. doi:10.3390/jmmp3030064.
[30] Suniya, N.K., Verma, A.K. 2023. A review on optimization of process parameters of fused deposition modeling. Research on Engineering Structures & Materials. 9(2):631-659. doi:10.17515/resm2022.520ma0909
[31] Choopani, Y. and Razfar, M.R. 2014. Investigation of the Effective Parameters on Surface Roughness in Magnetic Abrasive Finishing Process Using Design of Experiments. Journal of Modern Processes in Manufacturing and Production. 3(1):17-25.
[32] Lotfi, M., Amini, S., Sajjady, S.A. and Juaifer, A.H. 2018. The Effectiveness of Ceramic Wiper Tool in Turning of Monel K500. Journal of Modern Processes in Manufacturing and Production. 7(2):47-64.
[33] Casasola, R., Thomas, N.L., Trybala, A. and Georgiadou, S. 2014. Electrospun poly lactic acid (PLA) fibres: Effect of different solvent systems on fibre morphology and diameter. Polymer. 55(18):4728-4737 doi:10.1016/j.polymer.2014.06.032.
[34] Balakrishnan, H., Hassan, A., Imran, M. and Wahit, M.U. 2012. Toughening of Polylactic Acid Nanocomposites: A Short Review. Polymer-Plastics Technology and Engineering. 51(2):175-192. doi:10.1080/03602559.2011.618329.
[35] Liu, X., Zhang, M., Li, S., Si, L., Peng, J. and Hu, Y. 2017. Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method. The International Journal of Advanced Manufacturing Technology. 89:2387-2397. doi:10.1007/s00170-016-9263-3.
[36] Samykano, M. 2021. Mechanical property and prediction model for FDM-3D printed polylactic acid (PLA). Arabian Journal for Science and Engineering. 46:7875-7892. doi:10.1007/s13369-021-05617-4.
[37] Yao, T., Ye, J., Deng, Z., Zhang, K. Ma, Y. and Ouyang, H. 2020. Tensile failure strength and separation angle of FDM 3D printing PLA material: Experimental and theoretical analyses. Composites Part B: Engineering. 188:107894. doi:10.1016/j.compositesb.2020.107894.
[38] Isapour Rudy, M., Vahdati, M. and Mirnia, M.J. 2023. Statistical analysis and optimization of variables affecting the end diameter of AISI 304 steel tube produced by flaring process. Amirkabir Journal of Mechanical Engineering. 54(12):2861-2876. doi:10.22060/MEJ.2022.21622.7479.
[39] Vahdati, M., Mahdavinejad, R. and Amini, S. 2015. Statistical analysis and optimization of factors affecting the spring-back phenomenon in UVaSPIF process using response surface methodology. International Journal of Advanced Design and Manufacturing Technology (ADMT). 8(1):13-23.
[40] D’Addona, D., Raykar, S.J., Singh, D. and Kramar, D. 2021. Multi Objective Optimization of Fused Deposition Modeling Process Parameters with Desirability Function. Procedia CIRP. 99(1):707-710. doi:10.1016/j.procir.2021.03.117.