A project to design and develop a probabilistic model that accurately describes the likelihood of defect formation with respect to part geometry in additively manufactured metal/alloy parts through the use of deep learning and statistical analysis on micro computed tomography data.
- Simon Mason
- Justin Unger
- James Guest
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