@ARTICLE{Srinivasa_Chari_V._Optimization_2024,
 author={Srinivasa, Chari V. and Jhavar, Suyog and Suresh, R.},
 volume={vol. 69},
 number={No 1},
 journal={Archives of Metallurgy and Materials},
 pages={223-230},
 howpublished={online},
 year={2024},
 publisher={Institute of Metallurgy and Materials Science of Polish Academy of Sciences},
 publisher={Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences},
 abstract={The study aimed to optimize the Plasma Beam Polishing process for 316L stainless steel components to reduce anisotropy and poor surface roughness using statistical analysis. An experimental design investigated the impacts of managing factors on surface roughness, with scanning speed having the ultimate impact, followed by beam power and energy density. For lower values of plasma energy density and scanning speed, and a focal location without changes on the metal surface, there was a strong tendency for the estimated Ra to drop with increasing laser power. The process parameters were changed throughout a broad range of values, making it challenging to model the dependent variable across the whole range of experimental trials. The study supports the potential of PBP as a post-processing method for additive manufacturing components.},
 type={Article},
 title={Optimization of Surface Finish of Plasma Metal Deposited Stainless Steel 316L Parts by Utilization of Plasma Beam Remelting (PBR) and Taguchi Methodology},
 URL={http://journals.pan.pl/Content/130940/PDF/AMM-2024-1-38-Jhavar.pdf},
 doi={10.24425/amm.2024.147812},
 keywords={Metal Additive manufacturing, High beam energy, ANOVA, Surface roughness, Plasma Beam Remelting (PBR)},
}