Oct-26-2023
  • Researchers developed a machine learning framework for identifying flaws in 3D-printed products using sensor data gathered simultaneously with production, saving time and money while maintaining comparable accuracy to traditional post-inspection.
  • The ability to quantify this level of confidence during the printing process is new and enables manufacturers to vouch for a product’s safety and reliability when it is created with the most common metal 3D printing process.
  • The approach, developed in partnership with aerospace and defense company RTX, utilizes a machine learning algorithm trained on CT scans to identify flaws in printed products.