RESUMEN
Laser powder bed fusion (LPBF) is an additive manufacturing technology that implies using metal powder as a raw material. The powders suitable for this kind of technology must respect some specific characteristics. Controlled gas atomization and post-processing operations can strongly affect the final properties of the powders, and, as a consequence, the characteristics of the bulk components. In fact, a complete characterization of the powders is mandatory to fully determine their properties. Beyond the most used tests, such as the volume particle size distribution (PSD) and flowability, the PSD number, the Hausner ratio and the oxidation level can give additional information otherwise not detectable. The present work concerns the complete characterization of two AlSi10Mg powders: a commercial-grade gas atomized powder and a laboratory-scale gas atomized counterpart. The laboratory-scale gas atomization allows to better manage the amount of the fine particles and the oxidation level. As a consequence, a higher particle packing can be reached with an increase in the final density and tensile strength of the LPBF bulk samples.
RESUMEN
The production of dense samples produced by laser powder bed fusion (LPBF) is mainly determined by the choice of the best combination of construction parameters. Parameter optimization is the first step in the definition of an LPBF process for new alloys or systems. With this goal, much research uses the single scan track (SST) approach for a preliminary parameter screening. This study investigates the definition of a computer-aided method by using an automatic on top analysis for the characterization of SSTs, with the aim of finding ranges of laser power and scan speed values for massive production. An innovative algorithm was implemented to discard non-continuous scans and to measure the SSTs quality using three regularity indexes. Only open source software were used to fine tune this approach. The obtained results on Al4Cu and AlSi10Mg realized with two different commercial systems suggest that it is possible to use this method to easily narrow the process parameter window that allows the production of dense samples.