A series of 11 identical laser-based powder bed fusion (PBF) builds were completed with varying amounts of virgin and recycled nitrogen gas atomized S17-4 PH stainless steel powder following a specific powder recycling strategy that simulates industrial practice. Mechanical properties of parts were evaluated using tensile and hardness tests. Recycled powder properties, such as particle size distribution, flowability, chemical composition, and microstructure were evaluated. The recycled powder showed no significant changes in its particle size (PS), particle size distribution (PSD), and particle shape but apparent density and powder bed density increased while flow time improved. Recycling the powder in a nitrogen atmosphere caused a slight increase of the martensitic-ferritic phase in the predominately austenitic S17-4 PH powder. Laser-based PBF fabricated austeniticmartensitic-ferritic S17-4 PH showed a ratio of approximately 1:1 between austenitic and martensitic-ferritic phases. The specimens were heat treated for stress relief. Tensile tests on the specimens did not show dramatic change in the tensile properties with recycling up to 11 times. The fine dendritic austenitic-martensitic-ferritic microstructure of the heattreated S17-4-PH reached a 0.2 % offset yield strength (YS0.2) above 520 MPa, and an elongation after fracture (A) of 28 %. Mechanical and material properties from specimens fabricated from powder recycled up to 11 times were similar to specimens fabricated from virgin powder.
Many factors influence the performance of additive manufacturing (AM) processes, resulting in a high degree of variation in process outcomes. Therefore, quantifying these factors and their correlations to process outcomes are important challenges to overcome to enable widespread adoption of emerging AM technologies. In the powder bed fusion AM process, the density of the powder layers in the powder bed is a key influencing factor. This paper introduces a method to determine the powder bed density (PBD) during the powder bed fusion (PBF) process. A complete uncertainty analysis associated with the measurement method was also described. The resulting expanded measurement uncertainty, U PBD (k = 2), was determined as 0.004 g • cm −3 . It was shown that this expanded measurement uncertainty is about three orders of magnitude smaller than the typical powder bed density. This method enables establishing correlations between the changes in PBD and the direction of motion of the powder recoating arm.
In laser powder bed fusion (LPBF) processes, the powder size characteristics, like particle shape, particle size (PS), particle size distribution (PSD), and the resulting powder bed density (PBD), are key influencing factors of the built material properties. To better understand the correlations between the powder size characteristics and the powder properties influencing the LPBF process, apparent density (AD), flowability, and PBD were measured corresponding to two commercial metal powders with different PS and PSD. The powder samples were taken from different locations on the build platform to also investigate the variations of these powder characteristics resulting from the spreading process by the stiff recoater blade. It was shown that the PS and PSD had a significant effect on the AD and the PBD. Powders with a wide PSD and with particle sizes in the range of the effective powder layer thickness, led to a higher PBD than powder with a high proportion of finer particles. No significant differences in PS and PSD were observed as powder was pushed across a build plate by the recoater blade. Key wordsadditive manufacturing; apparent density; metal powder; particle size distribution; powder bed density; powder bed fusion; powder layer; powder layer thickness; powder spreading; selective laser melting; selective laser sintering. iv This publication is available free of charge from: https://doi
Due to the evolution of cleanness of bearing steels, the failures observed in service conditions move from deep initiated spalling on non-metallic inclusions to surface damage due to machining marks, lack or contaminated lubrication (dents). To take into account, by the most economic way, these request for more demanding applications, ASCOMETAL, SNR et VALTI have developed a new steel grade [1,2] based on the classical analysis of 100Cr6 (SAE 52100), with higher characteristics in terms of in-service properties (sustaining high loading, high temperature and contaminated lubrication) without deteriorated steelmaking or forming process by an optimised composition of the steel.
Six different organizations participated in this interlaboratory study to quantify the variability in the tensile properties of Inconel 625 specimens manufactured using laser-powder-bed-fusion additive manufacturing machines. The tensile specimens were heat treated and tensile tests conducted until failure. The properties measured were yield strength, ultimate tensile strength, elastic modulus, and elongation. Statistical analysis revealed that between-participant variability for yield strength, ultimate tensile strength, and elastic modulus values were significantly higher (up to 4 times) than typical within-participant variations. Only between-participant and within-participant variability were both similar for elongation. A scanning electron microscope was used to examine one tensile specimen for fractography. The fracture surface does not have many secondary cracks or other features that would reduce the mechanical properties. In fact, the features largely consist of microvoid coalescence and are entirely consistent with ductile failure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.