Laser cladding (LC) is a versatile additive manufacturing process where strands of metallic material are deposited and melted by a laser. However, there are some limitations associated with this process that may affect the performance of the final manufactured parts. In the present work, the influence of laser shock peening (LSP) on the fatigue life of 304 stainless steel flat specimens with a cobalt-based alloy (Stellite 6) coating applied by LC was investigated. The analysis was carried out both experimentally and numerically. In the LSP simulation, the ABAQUS/Explicit code was used to determine the residual stress distribution of specimens with double central notches with a radius of curvature of 5, 10, 15, and 20 mm. From the numerical results, an improvement was found regarding fatigue life up to 48% in samples with LSP. Experimentally, 14% in fatigue life enhancement was observed. The residual stress, determined by the contour method, showed good agreement with the LSP simulation. The SEM images revealed that the fatigue failure started at the Stellite 6 coating and propagated towards the center of the specimen. LSP has been shown to be a suitable postprocessing alternative for laser-cladded parts that will be subjected to fatigue loading since it led to fatigue improvement through the introduction of compressive residual stresses on clad coatings.

Additive manufacturing (AM) or 3D printing of metals is gaining popularity due to its flexibility when fabricating parts with highly complex designs, as well as when simplifying manufacturing steps and optimizing process times. In this investigation, 17-4 PH stainless steel was additively manufactured using Laser Powder Bed Fusion (L-PBF), followed by functionalization through a DUPLEX treatment. This treatment involved a plasma-assisted nitriding process, followed by the deposition of an arc-PVD c-Al_0.7Cr_0.3N hard coating. The microstructural modifications resulting from plasma nitriding (such as the formation of Fe_2,3N and Fe₄N and the αN or expanded martensite phases) and the surface improvements with the c-Al_0.7Cr_0.3N coating on the 3D-printed 17-4 PH steel are evaluated in comparison to conventionally manufactured 17-4 PH steel. These microstructural characteristics are correlated with the mechanical response of the treated surfaces. As a result of the plasma nitriding process, the hardness of the 3D-printed 17-4 PH SS increased by approximately 260%. The wear, measured through dynamic and static scratch testing, was reduced by approximately 31%. This improvement was attributed to the modification of adhesive failure mechanisms, leading to a reduction in wear volume, improved coating adhesion, and enhanced scratch resistance.

Additive manufacturing (AM) or 3D printing of metals is gaining popularity due to its flexibility in fabricating parts with highly complex designs, as well as simplifying manufacturing steps and optimizing process times. In this investigation, 17-4 PH stainless steel was additively manufactured using Laser-Powder Bed Fusion (L-PBF), followed by functionalization through a DUPLEX treatment. This treatment involved a plasma-assisted nitriding process, followed by deposition of an arc-PVD c-Al0.7Cr0.3N hard coating. The microstructural modifications resulting from plasma nitriding (such as the formation of Fe2,3N and Fe4N, and the αN or expanded martensite phases), and the surface improvements with the c-Al0.7Cr0.3N coating on the 3D-printed 17-4 PH steel, are evaluated in comparison to conventionally manufactured 17-4 PH steel. These microstructural characteristics are correlated with the mechanical response of the treated surfaces. As a result of the plasma nitriding process, the hardness of the 3D-printed 17-4 PH SS increased by approximately 260%. The wear, measured through dynamic and static scratch-testing, was reduced by approximately 31%. This improvement was attributed to the modification of adhesive failure mechanisms, leading to a reduction in wear volume, improved coating adhesion, and enhanced scratch resistance.

This study presents an experimental analysis and computational fluid dynamics (CFD) model for studying single-track formation in the Laser Powder Bed Fusion (LPBF) process, implemented in OpenFOAM. The model incorporates key physical phenomena, including Marangoni convection, recoil pressure, and phase change, to accurately capture melt pool dynamics. A stochastic powder size distribution, statistically characterized from experimental observations, is used as the initial condition to enhance the fidelity of the simulations. AlSi10Mg single-track deposits were performed using a Concept Laser M2 LPBF system, varying laser powers, scan velocities, and spot sizes. Cross-sectional microscopy and porosity analyses revealed transitions from lack-of-fusion to keyhole-induced porosity as a function of volumetric energy density (VED). Numerical results showed good qualitative and quantitative agreement with experimental observations, with relative errors in melt pool dimensions below 12\(\%\). Simulations further revealed transient flow patterns and melt pool instabilities difficult to capture experimentally. The findings demonstrate that the combination of experimental observations and simulation tools can be used to construct map process windows, predict defects, and support process optimization in LPBF, understanding the multiphysics phenomena at different building conditions, which is particularly important for high-conductivity aluminum alloys.