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2 2024

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Mass reduction method for topology optimisation of a Ti6Al4V part for additive manufacturing

Erőss László Dániel, Markovits Tamás

Production Engineering Archives

2024

Vol. 30, Iss. 3

354-360

Additive manufacturing and topology optimization provide new possibilities to produce complex parts. They can be used separately but with joint applications as a mutually reinforcing solution in component development tasks. The results obtained using the design software can be refined even further depending on the specific goal set. This paper deals with mass reduction with stiffness-based topology optimization of a structural component. The effect of different design spaces, load cases, and design parameters were examined. Then, the new part was validated with FEA simulation. After the validation, the part was prepared for 3D metal printing. Based on the research results, we present a methodology that can be used as a solution considering the software’s limitations and the development of the specific component. Applying the methodology developed in the research makes it possible to achieve mass minimization on other parts with a similar method.

Optimization of Surface Finish of Plasma Metal Deposited Stainless Steel 316L Parts by Utilization of Plasma Beam Remelting (PBR) and Taguchi Methodology

Srinivasa Chari V., Jhavar Suyog, Suresh R.

Archives of Metallurgy and Materials

2024

Vol. 69, iss. 1

223--230

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.