The Role of Process Parameters in Shaping the Microstructure and Porosity of Metallic Components Manufactured by Additive Technology

Laser Powder Bed Fusion (LPBF) technology represents one of the most promising additive manufacturing methods, enabling the production of components with high geometric complexity and a wide range of industrial and biomedical applications. In this study, the influence of both standard and high-productivity process parameters on the microstructure, porosity, surface roughness, and hardness of three commonly used materials, stainless steel 316L, aluminum alloy AlSi10Mg, and titanium alloy Ti6Al4V, was analyzed. The investigations were carried out on samples fabricated using the EOS M290 system, and their characterization was performed with scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), porosity analysis by point counting, Vickers hardness measurements, and optical profilometry. The obtained results revealed significant differences depending on the alloy and the applied parameters. For stainless steel 316L, the high-productivity variant led to grain refinement and stronger crystallographic orientation, albeit at the expense of increased porosity (0.11% vs. 0.05% for the standard variant). In the case of AlSi10Mg alloy, high-productivity parameters enabled a substantial reduction in porosity (from 0.82% to 0.27%) accompanied by an increase in hardness (from 115 HV1 to 122 HV1), highlighting their particular suitability for engineering applications. For the Ti6Al4V alloy, a decrease in porosity (from 0.17% to 0.07%) was observed; however, the increase in mechanical anisotropy resulting from a stronger texture may limit its application in cases requiring isotropic material behavior. The presented research confirms that optimization of LPBF parameters must be strictly tailored to the specific alloy and intended application, ranging from industrial components to biomedical implants. The results provide a foundation for further studies on the relationship between microstructure and functional properties, as well as for the development of hybrid strategies and predictive models of the LPBF process.