SBIR/STTR Award attributes
X-ray computed tomography (XCT/CT) is a widely used nondestructive evaluation (NDE) method for quality control and post-build inspection in additively manufactured (AM) components. AM practitioners increasingly recognize the limitations of such NDE methods and the need to validate the capability of these methods on an ongoing basis. Automated, metallography-based serial sectioning offers a reliable method to establish ground truth data on the flaw populations as well as microstructural variations of AM components. UES proposes a project aimed at establishing comparison methods and workflows for validating CT with ground truth from serial sectioning, and developing probability of detection (POD) curves for multiple materials and defect types. The knowledge gained from these efforts will inform CT scan strategies for improved flaw detection in AM components, evaluate flaw detectability in CT using serial sectioning as a ground truth comparison, and quantify the risk of the flaws absent from the CT data sets. In addition, improving the capabilities of an automated defect recognition (ADR) algorithm can improve NDE throughput.
