A simplified analytical model of the laser powder bed fusion (LPBF) process was used to develop a novel density prediction approach that can be adapted for any given powder feedstock and LPBF system. First, calibration coupons were built using IN625, Ti64 and Fe powders and a specific LPBF system. These coupons were manufactured using the predetermined ranges of laser power, scanning speed, hatching space, and layer thickness, and their densities were measured using conventional material characterization techniques. Next, a simplified melt pool model was used to calculate the melt pool dimensions for the selected sets of printing parameters. Both sets of data were then combined to predict the density of printed parts. This approach was additionally validated using the literature data on AlSi10Mg and 316L alloys, thus demonstrating that it can reliably be used to optimize the laser powder bed metal fusion process.

The laser powder bed fusion (L-PBF) technology was adapted for use with non-spherical low-cost water-atomized iron powders. A simplified numerical and experimental modeling approach was applied to determine—in a first approximation—the operation window for the selected powder in terms of laser power, scanning speed, hatching space, and layer thickness. The operation window, delimited by a build rate ranging from 4 to 25 cm³/h, and a volumetric energy density ranging from 50 to 190 J/mm³, was subsequently optimized to improve the density, the mechanical properties, and the surface roughness of the manufactured specimens. Standard L-PBF-built specimens were subjected to microstructural (porosity, grain size) and metrological (accuracy, shrinkage, minimum wall thickness, surface roughness) analyses and mechanical testing (three-point bending and tensile tests). The results of the microstructural, metrological and mechanical characterizations of the L-PBF-built specimens subjected to stress relieve annealing and hot isostatic pressing were then compared with those obtained with conventional pressing-sintering technology. Finally, by using an energy density of 70 J/mm³ and a build rate of 9 cm³/h, it was possible to manufacture 99.8%-dense specimens with an ultimate strength of 330 MPa and an elongation to failure of 30%, despite the relatively poor circularity of the powder used.

The additive manufacturing (AM) process induces high uncertainty in the mechanical properties of 3D-printed parts, which represents one of the main barriers for a wider AM processes adoption. To address this problem, a new time-efficient microstructure prediction algorithm was proposed in this study for the laser powder bed fusion (LPBF) process. Based on a combination of the melt pool modeling and the design of experiment approaches, this algorithm was used to predict the microstructure (grain size/aspect ratio) of materials processed by an EOS M280 LPBF system, including Iron and IN625 alloys. This approach was successfully validated using experimental and literature data, thus demonstrating its potential efficiency for the optimization of different LPBF powders and systems.

Laser powder bed fusion (LPBF) additive manufacturing technology was used to produce functional prototypes of powder metallurgy (PM) components from high carbon content, iron-based water-atomized powders. The melt pool modeling and design of experiment approaches were combined in order to determine the LPBF operation window allowing to print parts with components similar to the PM in terms of density, microstructure and mechanical properties. The size, morphology and distribution of processing-induced pores were evaluated using computed tomography, while a microstructure analysis was carried out using X-ray diffraction and scanning electron microscopy, and the mechanical properties were evaluated using tensile and unnotched Charpy testing. It was demonstrated that LPBF technology could effectively be used for the just-in-time manufacture of high-fidelity functional prototypes of PM parts from iron-based powders.