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The Influence of X-Ray Computed Tomography Acquisition Parameters on Image Quality and Probability of Detection of Additive Manufacturing Defects

Published

Author(s)

Felix Kim, Adam L. Pintar, Shawn P. Moylan, Edward Garboczi

Abstract

X-ray computed tomography (XCT) is a promising non-destructive evaluation technique for additively manufactured (AM) parts with complex shapes. Industrial XCT scanning is a relatively new development, and XCT has several acquisition parameters a user can change for a scan whose effects are not fully understood. An artifact incorporating simulated defects of different sizes was produced using laser-based powder bed fusion AM. The influence of six XCT acquisition parameters was investigated experimentally based on a fractional factorial designed experiment. Twenty experimental runs were performed. The noise level of the XCT images was affected by the acquisition parameters, and the importance of acquisition parameters was ranked. The measurement results were further extended to understanding the probability of detection (POD) of the simulated defects. The process of determining the POD is detailed, including estimating confidence limit of POD curve using boot-strapping method, and the results are interpreted in light of the AM process and XCT acquisition parameters.
Citation
Journal of Materials Processing Technology
Volume
141

Keywords

X-ray computed tomography, defect, noise, acquisition parameters, additive manufacturing, powder bed, laser melting, probability of detection

Citation

Kim, F. , Pintar, A. , Moylan, S. and Garboczi, E. (2019), The Influence of X-Ray Computed Tomography Acquisition Parameters on Image Quality and Probability of Detection of Additive Manufacturing Defects, Journal of Materials Processing Technology, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=926707 (Accessed October 14, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created November 28, 2019, Updated October 5, 2021