Summary

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.

Team

  • Simon Mason
  • Justin Unger

Faculty

  • James Guest

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