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Optimization of fused deposition modeling parameters to enhance tensile strength and surface roughness of polyethylene terephthalate glycol

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The wide examination of FDM as an industrial additive manufacturing technique appears because it provides design freedom alongside improved material efficiency and reasonable cost. This study's main objective is to investigate the relationship of Fused Deposition Modeling (FDM) process parameters with the tensile properties and surface roughness of Polyethylene terephthalate glycol (PETG) parts. A response surface methodology (RSM) utilizing Box–Behnken design methodology studied three essential parameters consisting of infill density and layer height, together with plate temperature. The analysis demonstrated that layer height proved to be the main element affecting tensile strength because it contributed 80.9% of the experimental variations, while infill density stood out as the leading determinant of surface roughness, which was responsible for 78% of the contribution. Experimental testing proved that the predictive model showed accurate results when validated through measurements of tensile strength, which produced maximum errors of 1.28%, and surface roughness, which yielded maximum errors of 6.54%. A desirability analysis indicated that the ideal parameters of the roughness and tensile strength of the printed parts included an infill density of 64.24% combined with a layer height of 0.1813 mm and plate temperature of 51.46°C. These outcomes provide a comprehensive understanding of process parameter effects that result in quality PETG parts with mechanical performance. The two-axis optimization methodology for PETG also enhances its use in functional engineering systems that require simultaneous mechanical durability and manufacturing accuracy.
Twórcy
  • Department of Production Engineering and Metallurgy, University of Technology, Baghdad, Iraq
  • Department of Production Engineering and Metallurgy, University of Technology, Baghdad, Iraq
  • Civil Engineering, University of Technology, Baghdad, Iraq
  • Department of Production Engineering and Metallurgy, University of Technology, Baghdad, Iraq
Bibliografia
  • 1. Cao L, Xiao J, Kim JK, Zhang X. Effect of post-process treatments on mechanical properties and surface characteristics of 3D printed short glass fiber reinforced PLA/TPU using the FDM process. CIRP Journal of Manufacturing Science and Technology. 2023 Apr 1; 41:135–43. https://doi.org/10.1016/j.cirpj.2022.12.008.
  • 2. Khan I, Barsoum I, Abas M, Al Rashid A, Koç M, Tariq M. A review of extrusion-based additive manufacturing of multi-materials-based polymeric laminated structures. Composite Structures. 2024 Aug 21:118490. https://doi.org/10.1016/j.compstruct.2024.118490.
  • 3. Mansor KK, Shabeeb AH, Hussein EA, Abbas TF, Bedan AS. A Statistical investigation and prediction of the effect of FDM variables on flexural stress of PLA prints. Tikrit Journal of Engineering Sciences. 2024 Jul 2; 31(3):10–7. https://doi.org/10.25130/tjes.31.3.2.
  • 4. Al-Bdairy AMJ, Ghazi SK, Abed AH. Prediction of the mechanical properties for 3D printed rapid prototypes based on artificial neural network. Advances in Science and Technology Research Journal. 2025; 19(3): 96–107.
  • 5. Al-Duroobi AAA, Al-Bdairy AM, Al-Juboori L. Rapid prototyping of sculpture surfaces based on discrete algorithm using 3D printer technique. 2024 Advances in Science and Engineering Technology International Conferences (ASET). IEEE, 2024.
  • 6. Sani AR, Zolfagharian A, Kouzani AZ. Artificial intelligence‐augmented additive manufacturing: insights on closed‐loop 3D printing. Advanced Intelligent Systems. 2024 Oct;6(10):2400102. https://doi.org/10.1002/aisy.202400102.
  • 7. Samykano M, Kumaresan R, Kananathan J, Kadirgama K, Pandey AK. An overview of fused filament fabrication technology and the advancement in PLA-biocomposites. The International Journal of Advanced Manufacturing Technology. 2024 May; 132(1):27-62. https://doi.org/10.1007/s00170-024-13394-1.
  • 8. Frunzaverde D, Cojocaru V, Bacescu N, Ciubotariu CR, Miclosina CO, Turiac RR, Marginean G. The influence of the layer height and the filament color on the dimensional accuracy and the tensile strength of FDM-printed PLA specimens. Polymers. 2023 May 19; 15(10):2377. https://doi.org/10.3390/polym15102377.
  • 9. Sudin MN, Shamsudin SA, Daud NM, Yusuff MA. Examining the effect of annealing parameters on surface quality and tensile strength of ABS 3D-printed materials. El-Cezeri. 2024 Jan 9; 11(3):307–16. https://doi.org/10.31202/ecjse.1369831.
  • 10. Farashi S, Vafaee F. Effect of printing parameters on the tensile strength of FDM 3D samples: a meta-analysis focusing on layer thickness and sample orientation. Progress in Additive Manufacturing. 2022 Jan 16:1–8. https://doi.org/10.1007/s40964-021-00247-6.
  • 11. Lalegani Dezaki M, Ariffin MK, Serjouei A, Zolfagharian A, Hatami S, Bodaghi M. Influence of infill patterns generated by CAD and FDM 3D printer on surface roughness and tensile strength properties. Applied Sciences. 2021 Aug 7; 11(16):7272. https://doi.org/10.3390/app11167272.
  • 12. Shirmohammadi M, Goushchi SJ, Keshtiban PM. Optimization of 3D printing process parameters to minimize surface roughness with hybrid artificial neural network model and particle swarm algorithm. Progress in Additive Manufacturing. 2021 May; 6:199–215. https://doi.org/10.1007/s40964-021-00166-6.
  • 13. Mat MA, Ramli FR, Sudin MN, Herawan SG, Alkahari MR. The effect of tensile strength and surface roughness by varying oxygen level in 3D printer chamber. J. Tribol. 2022; 33:80–96.
  • 14. Mani M, Karthikeyan AG, Kalaiselvan K, Muthusamy P, Muruganandhan P. Optimization of FDM 3-D printer process parameters for surface roughness and mechanical properties using PLA material. Materials Today: Proceedings. 2022 Jan 1; 66:1926–31. https://doi.org/10.1016/j.matpr.2022.05.422.
  • 15. Abdulridha HH, Abbas TF. Analysis and investigation the effect of the printing parameters on the mechanical and physical properties of PLA parts fabricated via FDM printing. Advances in Science and Technology Research Journal. 2023; 17(6). http://dx.doi.org/10.12913/22998624/173562.
  • 16. Fadillah F, Suryanto H, Suprayitno S. Study on effect of 3D printing parameters on surface roughness and tensile strength using analysis of variance. Journal of Mechanical Engineering Science and Technology (JMEST). 2023; 7(2):96.
  • 17. Hamat S, Ishak MR, Sapuan SM, Yidris N, Hussin MS, Abd Manan MS. Influence of filament fabrication parameter on tensile strength and filament size of 3D printing PLA-3D850. Materials Today: Proceedings. 2023 Jan 1; 74:457–61. https://doi.org/10.1016/j.matpr.2022.11.145.
  • 18. Kónya G. Investigating the impact of productivity on surface roughness and dimensional accuracy in FDM 3D printing. Periodica Polytechnica Transportation Engineering. 2024 Feb 12; 52(2):128–33. https://doi.org/10.3311/PPtr.22952.
  • 19. Özkül M, Kuncan F, Ulkir O. Predicting mechanical properties of FDM‐produced parts using machine learning approaches. Journal of Applied Polymer Science. 2025:e56899. https://doi.org/10.1002/app.56899.
  • 20. Abdullah MA, et al. Comparison between low-carbon steel and galvanized steel by deep drawing under the influence of different parameters. Management Systems in Production Engineering. 2025; 33(2):163–170. https://doi.org/10.2478/mspe-2025-0016.
  • 21. Mohsein ZH, Abdulwahhab AB, Abbas A. Study effect of active flux on mechanical properties of TIG welding process. Results in Engineering. 2025; 26:104681. https://doi.org/10.1016/j.rineng.2025.104681.
  • 22. Mohammed AR, Jawad WK. Practical test and FEA to evaluation of the thickness distribution for octagonal cup generated by deep drawing. AIP Conference Proceedings. 2024; 1:3002. AIP Publishing.
  • 23. Ghazi SK, Abdullah MA, Abdulridha HH. Investigating the impact of EDM parameters on surface roughness and electrode wear rate in 7024 aluminum alloy. Engineering, Technology & Applied Science Research. Feb. 2025; 15(1):19401–19407. https://doi.org/10.48084/etasr.9252.
  • 24. Abdullah MA, Ahmed BA, Ghazi SK. Enhancing of material removal rate and surface roughness in wire EDM process using grey relational analysis. Engineering, Technology & Applied Science Research. Oct. 2024; 14(5):17422–17427. https://doi.org/10.48084/etasr.8450.
  • 25. Abdullah MA, Abbas TF. Numerical developing the internet of things to remotely monitor the performance of a three dimensions printer for free-form surface. Journal of Engineering Science and Technology. 2023 Dec; 18(6):2809–22.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6a63587f-4422-4185-9dc9-49b76ceb7929
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