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Volume 101
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Feltner, L., Korte, E., Bahr, D. F., & Mort, P. (2025). Particle size and shape analyses for powder bed additive manufacturing. Particuology, 101, 33-42. https://doi.org/10.1016/j.partic.2023.09.001
Particle size and shape analyses for powder bed additive manufacturing
Langdon Feltner, Ethan Korte, David F. Bahr, Paul Mort *
School of Materials Engineering, Purdue University, West Lafayette, IN, USA
10.1016/j.partic.2023.09.001
Volume 101, June 2025, Pages 33-42
Received 17 July 2023, Revised 23 August 2023, Accepted 4 September 2023, Available online 18 September 2023, Version of Record 29 May 2025.
E-mail: pmort@purdue.edu
Highlights

• Dynamic imaging provides large data sets for particle size and shape analyses.

• Case study of fine metal powders used in additive manufacturing.

• Powder production process affects size and shape distributions.

• Principal component analysis of shape data clusters around form factors and elongation.

• Statistical uncertainty of shape analysis depends on pixel-scale resolution.


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.

Graphical abstract
Keywords
Dynamic image analysis; Powder bed additive manufacturing; Clustering of particle shape descriptors; Pixilation; Machine learning
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