PrintRite3D? AI/ML for In-Situ Additive Manufacturing Defect Detection

Additive manufacturing (AM) increases the speed and flexibility of production and enables traditional part concatenation for advanced manufacturing capabilities. The ability for U.S. manufacturers to 3D-print advanced components in-house reduces reliance on traditional subtractive supply chains and bolsters national security readiness. While AM affords unique flexibility in design for manufacturability, its variance in lack of repeatability and reproducibility introduced various defects, including lack of fusion, gas entrapment, powder agglomeration, balling, internal cracks, and thermal stress, that degrades mechanical properties of final parts. The cost associated with performing post process inspection is an economic limiter and its efficacy is limited by material and material geometry, that is solved by in process nondestructive inspection methodologies. Kitware, in collaboration with Sigma Additive Solutions, proposes to bring the latest advances in deep neural network artificial intelligence and signal fusion to optimize and extend PrintRite3D® for the Navy’s unique needs. PrintRite3D is a platform-independent, interactive, in-process quality assurance system that combines inspection, feedback, data collection and critical analysis. Optimizing PrintRite3D defect detection accuracy will improve confidence in and reduce part-rejection false-alarm rates. Our proposed method builds on an existing proof of concept for in-situ defect detection and extends our capabilities to cover a wider range of builds, printers, locations, and sensors.