Particle size and shape analyses for powder bed additive manufacturing

Abstract

Technical advances in dynamic imaging have enabled routine sampling and analysis of particle shape and shape distributions. Size and shape distributions are relevant to many particulate processes involving flow, spreading, packing and densification. Powder bed additive manufacturing is a prime example requiring uniform spreading, packing and sintering of fine metal powders. This study focuses on quantitative representations of shape described in the International Standards Organization specifications and considers three aspects for improvement thereof: (1) reduced-order mapping of shape distributions using principal component analysis of shape descriptors; (2) uncertainty of shape distribution statistics based on pixel resolution; and (3) opportunities for analysis using machine learning for enhanced image resolution.