16:10 〜 16:30
[15C-T1-24] Study of Post-Atomization Treatments Aimed at Optimizing the Rheology of Water Atomized Tool Steel Powders for Laser Powder-Bed Fusion Additive Manufacturing
キーワード:Water-atomization, Machine Learning, Particles Morphology, Rheology
From an economical perspective, the use of water atomization for the production of feedstock for laser powder-bed fusion represents an interesting alternative to plasma and gas atomization. However, water-atomized powders are characterized by lower flowability. In this regard, it was previously shown that post-processing water-atomized tool steel powders with a thermo-mechanical spheroidization treatment (TMST) could improve average particle sphericity, and thus, flow properties and apparent density. In this work, the dynamic rheological properties of water-atomized tool steel powder lots that were subjected to different TMST conditions were characterized using a rotating drum apparatus and a Hall flowmeter. Additionally, an unsupervised machine learning algorithm was employed to characterize the morphological features of each powder lot. This study not only determined optimal TMST conditions to maximize flowability, but also revealed valuable insights on the relative importance of particle morphology and surface properties in governing the rheological behavior of water-atomized powders.