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Additive manufacturing powder feedstock characterization using X-ray tomography

Fabrice Bernier (1), Rui Tahara (2), Mathieu Gendron (3)

Metal Powder Report, 73, Number 3, 2018:158-162. DOI:10.1016/j.mprp.2018.01.002.

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Keywords

Additive manufacturing; Image analysis; X-ray tomography (XCT); Powder feedstock; Porosity

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Abstract

To answer the need for efficient quality control protocols for additive manufacturing processes and materials, specific testing methods for powder feedstocks should be developed. A powder feedstock may contain some defects, such as porosities, that will remain in the final parts after the building process. X-ray tomography combined with 3D image analysis offers unique advantages over other characterization methods, such as pycnometry and metallography, in respect to quantifying internal porosity in the individual particles of the feedstock. This paper presents the effect of X-ray tomography parameters on the quality of the obtained images and its impact on the image analysis. An automated image analysis routine was also developed to allow the visualization of the pores inside the particles but also, more importantly, to quantify this internal porosity contents, as well as to provide information on the morphological features of these pores, such a size distribution, number of particles containing pores and the volume fraction of a pore inside a particle…

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How Our Software Was Used

Advanced image visualization, processing, and analysis.

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Author Affiliation

(a) National Research Council Canada, Boucherville, QC, Canada
(b) McGill University, QC, Canada
(c) Object Research Systems, Montreal, QC, Canada

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