Improving the Finished Product’s Quality and Mechanical Properties in Manufacturing of Prototyping Using Fused Deposition Modelling
DOI:
https://doi.org/10.24425/mper.2025.153933Abstract
In today’s expanding market, customers prefer components with excellent mechanical properties and smooth surfaces. Additive manufacturing (AM) has been traditionally limited in full-scale manufacturing due to its mechanical strength and surface roughness. As a result, AM has been primarily utilized for prototyping and job shop production. Fused Deposition Modelling (FDM) involves the extrusion of wax or plastic materials through nozzles and layering them on a bed or platform to achieve the desired cross-sectional shape. There is a growing demand in industries for high-quality parts produced at a low cost and in a shorter time frame. It becomes crucial to optimize the machine’s process parameters. However, it can be challenging to consistently achieve optimal values, even for a skilled operator. Understanding the FDM system parameters that affect the quality and mechanical properties of the final product is essential. Consequently, this study focuses on optimizing process variables to enhance the surface roughness of FDM products. The response surface methodology (RSM) has been utilized to determine the optimal FDM machining conditions. To plan and analyze experiments, a Design of Experiments (DOE) has been employed, considering factors such as layer thickness, printing temperature, and printing velocity. By integrating these parameters, we have determined the optimal layer thickness to be 0.20 mm, printing temperature to be 205.01 degrees, and printing velocity to be 50 mm/s, resulting in a surface roughness of 0.0510 microns. A confirmation test based on the optimal parameters has demonstrated good agreement with the predicted surface roughness result.References
Abdulhameed, O., Al-Ahmari, A., Ameen, W., & Mian, S.H. (2019). Additive manufacturing: Challenges, trends, and applications. Advances in Mechanical Engineering, 11(2). DOI: 10.1177/1687814018822880
Anitha, R., Arunachalam, S., & Radhakrishnan, P. (2001). Critical parameters influencing the quality of prototypes in fused deposition modelling. Journal of Materials Processing Technology, 118(1–3), 385–388. DOI: 10.1016/S0924-0136(01)00980-3
Aydar, A.Y. (2018). Utilization of Response Surface Methodology in Optimization of Extraction of Plant Materials. Statistical Approaches With Emphasis on Design of Experiments Applied to Chemical Processes.. DOI: 10.5772/intechopen.73690
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. DOI: 10.1631/jzus.A1001365
de Oliveira, L.G., de Paiva, A.P., Balestrassi, P.P., Ferreira, J.R., da Costa, S.C., & da Silva Campos, P.H. (2019). Response surface methodology for advanced manufacturing technology optimization: theoretical fundamentals, practical guidelines, and survey literature review. International Journal of Advanced Manufacturing Technology, 104(5–8), 1785–1837. DOI: 10.1007/s00170-019-03809-9
DeStefano, V., Khan, S., & Tabada, A. (2020). Applications of PLA in modern medicine. Engineered Regeneration, 1, 76–87. DOI: 10.1016/j.engreg.2020.08.002
Dey, A., & Yodo, N. (2019). A systematic survey of FDM process parameter optimization and their influence on part characteristics. Journal of Manufacturing and Materials Processing, 3(3). DOI: 10.3390/jmmp3030064
Durgun, I., & Ertan, R. (2014). Experimental investigation of FDM process for improvement of mechanical properties and production cost. Rapid Prototyping Journal, 20(3), 228–235. DOI: 10.1108/ RPJ-10-2012-0091
Farah, S., Anderson, D.G., & Langer, R. (2016). Physical and mechanical properties of PLA, and their functions in widespread applications - A comprehensive review. Advanced Drug Delivery Reviews, 107, 367–392. DOI: 10.1016/j.addr.2016.06.012
Gurrala, P.K., & Regalla, S.P. (2014). Multi-objective optimisation of strength and volumetric shrinkage of FDM parts: A multi-objective optimization scheme is used to optimize the strength and volumetric shrinkage of FDM parts considering different process parameters. Virtual and Physical Prototyping, 9(2), 127–138. DOI: 10.1080/17452759.2014.898851
Hanrahan, G., & Lu, K. (2006). Application of factorial and response surface methodology in modern experimental design and optimization. Critical Reviews in Analytical Chemistry, 36(3–4), 141–151. DOI: 10.1080/10408340600969478
Horvath, D., Noorani, R., & Mendelson, M. (2007). Improvement of Surface Roughness on ABS 400 Polymer Using Design of Experiments (DOE). Materials Science Forum, 561–565, 2389–2392. DOI: 10.4028/www.scientific.net/msf.561-565.2389
Jami, H., Masood, S.H., & Song, W.Q. (2013). Dynamic response of FDM made ABS parts in different part orientations. Advanced Materials Research, 748, 291–294. DOI: 10.4028/www.scientific.net/AMR.748.291
Jiang, S., Liao, G., Xu, D., Liu, F., Li, W., Cheng, Y., Li, Z., & Xu, G. (2019). Mechanical properties analysis of polyetherimide parts fabricated by fused deposition modelling. High Performance Polymers, 31(1), 97–106. DOI: 10.1177/0954008317752822
Kumar, N., Jain, P. K., Tandon, P., & Pandey, P.M. (2018). The effect of process parameters on tensile behavior of 3D printed flexible parts of ethylene vinyl acetate (EVA). Journal of Manufacturing Processes, 35, 317–326. DOI: 10.1016/j.jmapro.2018.08.013
Kumar, R., Singh, R., & Farina, I. (2018). On the 3D printing of recycled ABS, PLA and HIPS thermoplastics for structural applications. PSU Research Review, 2(2), 115–137. DOI: 10.1108/prr-07-2018-0018
Kumar, S.A., & Prasad, R.V.S. (2021). Basic principles of additive manufacturing: different additive manufacturing technologies. Additive Manufacturing, 17–35. DOI: 10.1016/b978-0-12-822056-6.00012-6
Myers, W.R. (2010). Response Surface Methodology. Encyclopedia of Biopharmaceutical Statistics, 1171–1179. DOI: 10.3109/9781439822463.187
Nancharaiah, T. (2011). Optimization of Process Parameters in FDM Process Using Design of Experiments. International Journal on Emerging Technologies 2(1), 100–102.
Penumakala, P.K., Santo, J., & Thomas, A. (2020). A critical review on the fused deposition modeling of thermoplastic polymer composites. Composites Part B: Engineering, 201. DOI: 10.1016/j.compositesb.2020.108336
Raut, S., Jatti, V. S., Khedkar, N.K., & Singh, T.P. (2014). Investigation of the Effect of Built Orientation on Mechanical Properties and Total Cost of FDM Parts. Procedia Materials Science, 6, 1625–1630. DOI: 10.1016/j.mspro.2014.07.146
Sandanamsamy, L., Harun, W.S.W., Ishak, I., Romlay, F.R.M., Kadirgama, K., Ramasamy, D., Idris, S.R.A., & Tsumori, F. (2022). A comprehensive review on fused deposition modelling of polylactic acid. Progress in Additive Manufacturing. DOI: 10.1007/s40964-022-00356-w
Sin, L.T., Rahmat, A.R., & Rahman, W.A.W.A. (2013). Chemical Properties of Poly(lactic Acid). Polylactic Acid, 143–176. DOI: 10.1016/b978-1-4377-4459-0.00004-4
Sung-Hoon, A., Michael, M., Dan, O., Shad, R., & K., W.P. (2002). Anisotropic material properties of fused deposition modeling ABS. Rapid Prototyping Journal, 8(4), 248–257.
Thrimurthulu, K., Pandey, P.M., & Reddy, N.V. (2004). Optimum part deposition orientation in fused deposition modeling. International Journal of Machine Tools and Manufacture, 44(6), 585–594. DOI: 10.1016/j.ijmachtools.2003.12.004
Wang, C.C., Lin, T.W., & Hu, S.S. (2007). Optimizing the rapid prototyping process by integrating the Taguchi method with the Gray relational analysis. Rapid Prototyping Journal, 13(5), 304–315. DOI: 10.1108/13552540710824814
Zhang, Y., & Chou, K. (2008). A parametric study of part distortions in fused deposition modelling using three-dimensional finite element analysis. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 222(8), 959–967. DOI: 10.1243/09544054JEM990
