A Method for Predicting Powder Flowability for Selective Laser Sintering

This work investigates a method for pre-screening material systems selective laser sintering using combination of revolution powder analysis (RPA) and machine learning. To develop this method, nylon was mixed with alumina or carbon fibers in different wt.% to form varying flowability. The materials were measured custom RPA device the results compared as-spread layer density surface roughness. Machine learning used attempt classification all powders each method. Ultimately, it found that is able reliably classify based on their flowability, but roughness not be classified.