E3S Web Conf.
Volume 399, 2023International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
|Number of page(s)
|12 July 2023
Optimization of the Printing Parameters to Improve the Surface Roughness in Fused Deposition Modeling
1 Research Scholar, Institute of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105
2 Associate professor, Institute of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105
* Corresponding author: firstname.lastname@example.org
A better surface finish is an essential requirement of any component in particular medical components. The recent development in additive manufacturing technology produces components with a good surface finish. However, the optimization of process parameters helps to achieve a better surface finish. This paper focuses on the optimization of printing parameters of the surface roughness of a flat object developed from an FDM printer. FDM (Fused Deposition Modeling) is a layer-by-layer deposition process to develop 3D objects. It uses solid-state material (Filament) to print the product by melting and depositing the material on the printing bed. Several factors in the FDM process can affect the product’s quality. The parameters such as printing temperature, bed temperature, printing speed, fill density, layer thickness, and air gap influence the quality of the printed products. This investigation has considered printing temperature, layer height, and printing as process parameters. In addition, the parameter affecting the printed object’s surface finish is determined using ANOVA optimization and S/N ratios. PLA (Polylactic Acid) is taken as study material which is one of the feedstocks used in polymer filament and finds its applications in implant printing and medical tools.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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