The poor surface roughness associated with additively manufactured parts can influence the surface integrity and geometric tolerances of produced components. In response to this issue, laser polishing (LP) has emerged as a potential technique for improving the surface finish and producing parts with enhanced properties. Many studies have been conducted to investigate the effect of LP on parts produced using additive manufacturing. The results showed that applying such a unique treatment can significantly enhance the overall performance of the part. In LP processes, the surface of the part is re-melted by the laser, resulting in smaller peaks and shallower valleys, which enable the development of smoother surfaces with the help of gravity and surface tension. Precise selection of laser parameters is essential to achieve optimal enhancement in the surface finish, microstructure, and mechanical properties of the treated parts. This paper aims to compile state-of-the-art knowledge in LP of additively manufactured metals and presents the optimal process parameters experimentally and modeling using artificial machine learning. The effects of laser power, the number of laser re-melting passes, and scanning speed on the final surface roughness and mechanical properties are comprehensively discussed in this work.

Fe-Mn-Al-Ni is an Fe-based shape memory alloy (SMA) featuring higher stability and low temperature dependency of superelasticity stress over a wide range of temperatures. Additive manufacturing (AM) is a promising technique for fabricating Fe-SMA with enhanced properties, which can eliminate the limitations associated with conventional fabrication and allow for the manufacture of complicated shapes with only a single-step fabrication. The current work investigates the densification behavior and fabrication window of an Fe-Mn-Al-Ni SMA using laser powder bed fusion (LPBF). Experimental optimization was performed to identify the optimum processing window parameters in terms of laser power and scanning speed to fabricate Fe-Mn-Al-Ni SMA samples. Laser remelting was also employed to improve the characteristics of Fe-Mn-Al-Ni-fabricated samples. Characterization and testing techniques were carried out to assess the densification behavior of Fe-Mn-Al-Ni to study surface roughness, density, porosity, and hardness. The findings indicated that using a laser power range of 175–200 W combined with a scanning speed of 800 mm/s within the defined processing window parameters can minimize the defects with the material and lead to decreased surface roughness, lower porosity, and higher densification.