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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.
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Bibliogr. 27 poz., rys., tab., wykr., zdj.
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- nstitute of Rural Management, Anand, (IRMA), India
autor
- Symbiosis Institute of Business Management, Nagpur, Symbiosis International (Deemed University), Pune, India
autor
- Mechanical Engineering Department, Bharati Vidyapeeth College of Engineering, Navi Mumbai, India
Bibliografia
- 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
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fffa1c7b-ee9c-48fe-aa4f-5eb456a1d4d7
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