ORNL researcher Zackary Snow compares data from different types of images collected during and after metal parts were additively manufactured using a powder bed printer like the one behind him. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Inspection method increases confidence in laser powder bed fusion 3D printing

ORNL researchers are demonstrating an automation system for this portable system, currently based in Colorado, for treatment of non-traditional water sources to drinking water standards. Credit: Tzahi Cath/Colorado School of Mines

With automated treatment, affordable water from nontraditional sources can flow to underserved communities

ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.

ZEISS, ORNL sign licensing agreement for inspection of 3D-printed parts

Multimodal Sensor Analytics

Multimodal Sensor Analytics

Conducts advanced research, design and development of algorithms and systems employing computational sensing approaches with Images and signals.