Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning
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Summary
A significant leap forward is demonstrated in AM characterization by integrating advanced XCT, XRM, and DL techniques, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.
- Type
- article
- Published
- 2025-08-18
- Cited by
- 8
- References
- 52
- Access
- Open access
- OpenAlex
- https://openalex.org/W4413292966
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:280835370
Keywords
Characterization (materials science), Solid mechanics, Materials science, Tomography, Microscopy
References
- INDUSTRIAL COMPUTER TOMOGRAPHY - A UNIVERSAL INSPECTION TOOL
- The Shannon sampling theorem—Its various extensions and applications: A tutorial review
- Practical cone-beam algorithm
- The metallurgy and processing science of metal additive manufacturing
- Porosity Measurements and Analysis for Metal Additive Manufacturing Process Control
- X-ray computed tomography for additive manufacturing: a review
- Porosity testing methods for the quality assessment of selective laser melted parts
- Progress Towards Metal Additive Manufacturing Standardization to Support Qualification and Certification
- Investigation of pore structure in cobalt chrome additively manufactured parts using X-ray computed tomography and three-dimensional image analysis
- Additive manufacturing of metallic components – Process, structure and properties
- Additive Manufacturing: The Rise of a Technology and the Need for Quality Control and Inspection Techniques
- X-Ray Microcomputed Tomography in Additive Manufacturing: A Review of the Current Technology and Applications
- Powders for Additive Manufacturing Processes: Characterization Techniques and Effects on Part Properties
- X-ray computed tomography: from medical imaging to dimensional metrology
- X-ray CT and image analysis methodology for local roughness characterization in cooling channels made by metal additive manufacturing
- Effect of the number of projections on dimensional measurements with X-ray computed tomography
- Internal surface roughness measurement of metal additively manufactured samples via x-ray CT: the influence of surrounding material thickness
- New technologies for x-ray microscopy: phase correction and fully automated deep learning based tomographic reconstruction
- Improving the dimensional accuracy of 3D x-ray microscopy data
- Assessing rechargeable batteries with 3D X-ray microscopy, computed tomography, and nanotomography
Cited by
- Towards the measurement of porous materials: a comparison between computed X-ray tomography and serial sectioning
- Characterization of medical devices and pharmaceutical formulations with 3D X-ray imaging and deep learning
- Multi-scale imaging of additively manufactured Al–Ta composites
- Defect and failure detection in laser powder bed fusion: a comprehensive review and experimental validation on AlSi10Mg metal blade
- Probability of detection based evaluation of XCT resolution limits and voxel sizing errors in defect detection
- Accelerating in situ X-ray tomography using sparse projections and deep learning
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