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Meeting Materials Science & Technology 2019
Symposium Additive Manufacturing: Effective Production, Characterization, and Recycling of Powder Materials
Presentation Title Understanding Powder Morphology and Its Effect on Flowability through Computer Vision and Machine Learning In Additive Manufacturing
Author(s) Srujana Rao Yarasi, Andrew R Kitahara, Anthony D Rollett, Elizabeth A Holm
On-Site Speaker (Planned) Srujana Rao Yarasi
Abstract Scope The use of computer vision and machine learning tools in the additive manufacturing domain have enabled the quantitative investigation of qualitative factors like powder morphology, which affects the flowability in powder bed fusion processes. Flowability is measured through rheological experiments conducted with the FT4 rheometer and the GranuDrum. The use of Convolutional Neural Networks (CNN) to generate hypercolumn descriptors is proposed as part of a framework to generate powder fingerprints that describe characteristics of the powder feedstock such as particle size distribution, sphericity, surface defects, and other morphological features. These descriptors are then correlated to their respective flowability properties for numerous powder systems to evaluate powder performance. This framework is intended as a powder qualification system to differentiate powder systems and serve as a method to indicate the usability of recycled powder lots.
Proceedings Inclusion? Planned: At-meeting proceedings

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Additive Manufacturing Alloys: Influence of Powder Preparation Method in Aluminum Matrix Composites
Assessment of 316L Stainless Steel Powder Produced from Recycled Machining Chips for Closed Lifecycle Additive-Subtractive Manufacturing
Characterization of Gas Atomized Aluminum Alloy Powder for Additive Manufacturing Applications
Characterization of Nickel-base Superalloy MAR-M247 Powders by Synchrotron X-ray Computed Tomography
Characterization of Titanium Powder Produced from Battlefield Scrap for Additive Manufacturing
Determination of Viscosity of Metal Melts by High Temperature Rheometry
Effects of Recycling PREP and Plasma Atomized Ti-6Al-4V Powder from LENS Process
Exploring the Feasibility of Cryomilled Aluminum Alloy 5083 as Feed Stock Material for Additive Manufacturing
Hydrogen Assisted Magnesiothermic Reduction (HAMR) for Making Low-oxygen Ti Powder
Metal Particulate Produced by Modulation-assisted Machining
P3-26: Identifying Correlations between Metal Powder Properties and Binder Jet Print Settings to Optimize Process
Potentials and Risks in Hybrid Manufacturing
Powder Specification Needs for Steels in the LPBF Process
Surface Area as a Powder Morphology Probe
Synchrotron X-ray CT of AM Feedstock Metal Powder: A Validation of Metallographic Porosity Measurements.
Understanding Powder Morphology and Its Effect on Flowability through Computer Vision and Machine Learning In Additive Manufacturing
Understanding Surface Area Measurement for Improved Powder Characterization

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