Microstructure and Hardness Properties of Additively Manufactured AISI 316L Welded by Tungsten Inert Gas and Laser Welding Techniques.

In this study, 316L austenitic stainless-steel (ASS) plates fabricated using an additive manufacturing (AM) process were joined using tungsten inert gas (TIG) and laser welding techniques. The 316L ASS plates were manufactured using a laser powder bed fusion (LPBF) technique, with building orientations (BOs) of 0° and 90°, designated as BO-0 and BO-90, respectively. The study examined the relationship between indentation resistance and microstructure evolution within the fusion zone (FZ) of the welded joints considering the effects of different BOs. Microstructural analysis of the weldments was conducted using optical and laser confocal scanning microscopes, while hardness measurements were obtained using a micro-indentation hardness (H) technique via the Berkovich approach. The welded joints produced with the TIG technique exhibited FZs with a greater width than those created by laser welding. The microstructure of the FZs in TIG-welded joints was characterized by dendritic austenite and 1-4 wt.% δ-ferrite phases, while the corresponding microstructure in laser-welded joints consisted of a single austenite phase with cellular structures. Additionally, the grain size values of FZs produced using the laser welding technique were lower than those produced using the TIG technique. Therefore, TIG-welded joints showcased hardness values lower than those welded by laser welding. Furthermore, welded joints with the BO-90 orientation displayed the greatest cooling rates following welding processing, leading to FZs with hardness values greater than BO-0. For instance, the FZs of TIG-welded joints with BO-0 and BO-90 had H values of 1.75 ± 0.22 and 2.1 ± 0.09 GPa, whereas the corresponding FZs produced by laser welding had values of 1.9 ± 0.16 and 2.35 ± 0.11 GPa, respectively. The results have practical implications for the design and production of high-performance welded components, providing insights that can be applied to improve the efficiency and quality of additive manufacturing and welding processes.