The influence of material properties and process parameters on the spreading process in additive manufacturing

Abstract

Laser powder bed fusion (LPBF) is an additive manufacturing (AM) technology. To achieve high product quality, the powder is best spread as a uniform, dense layer. The challenge for LPBF manufacturers is to develop a spreading process that can produce a consistent layer quality for the many powders used, which show considerable differences in spreadability. Therefore, we investigate the influence of material properties, process parameters and the type of spreading tool on the layer quality. The discrete particle method is used to simulate the spreading process and to define metrics to evaluate the powder layer characteristics. We found that particle shape and surface roughness in terms of rolling resistance and interparticle sliding friction as well as particle cohesion all have a major (sometimes surprising) influence on the powder layer quality: more irregular shaped particles, rougher particle surfaces and/or higher interfacial cohesion usually, but not always, lead to worse spreadability. Our findings illustrate that there is a trade-off between material properties and process parameters. Increasing the spreading speed decreases layer quality for non-and weakly cohesive powders, but improves it for strongly cohesive ones. Using a counter-clockwise rotating roller as * Corresponding author.

Physics‐based modeling and predictive simulation of powder bed fusion additive manufacturing across length scales

“…In contrast, mesoscale approaches resolve the length scale of individual powder particles. Usually, domains smaller than one powder layer are considered to either study the melt pool thermo-fluid dynamics during melting [30,51,58,59,66,76,86,94,101,106,115,118] or the cohesive powder dynamics during the previous powder spreading process [21,38,39,41,43,60,65,74,78,82,103,113]. The former category of models aims at the prediction of melt pool instabilities (e.g., Rayleigh-Plateau or keyhole instabilities) and associated part defects such as residual porosity, lack of fusion, pure surface finish and insufficient layer-to-layer adhesion.…”

Physics-Based Modeling and Predictive Simulation of Powder Bed Fusion Additive Manufacturing Across Length Scales

“…In contrast, mesoscale approaches resolve the length scale of individual powder particles. Usually, domains smaller than one powder layer are considered to either study the melt pool thermo-fluid dynamics during melting [14,15,16,17,18,19,20,21,22,23,24,25] or the cohesive powder dynamics during the previous powder spreading process [26,27,28,29,30,31,32,33,34,35,36,37]. The former category of models aims at the prediction of melt pool instabilities (e.g., Rayleigh-Plateau or keyhole instabilities) and associated part defects such as residual porosity, lack of fusion, pure surface finish and insufficient layer-to-layer adhesion.…”