Phase3D
Phase3D has correlated measurable metal powder bed fusion build anomalies to final part defects in real-time for the United States Air Force and NASA.
Working with two leading users of additive manufacturing, Phase3D validated the work with two materials on two different laser powder bed fusion machines. The company believes this work to be a 'significant leap forward' in additive manufacturing to ensure build quality and reliability.
Phase3D has worked closely with the U.S. Air Force and NASA to develop Fringe Research, an in-situ monitoring product which measures, in microns, every layer of a powder-based AM build. The system is said to automatically identify anomalies from the build process to help improve the AM process. Phase 3D believes it is the first inspection company for AM to measure anomalies during the build that lead to porosity, a major cause of part rejection for the US Air Force and NASA.
The resulting Fringe Research in-situ monitoring product can be used on most powder-based additive manufacturing systems and employs structured light technology. Fringe Research does not, however, use artificial intelligence (AI) or machine learning (ML) to create measurements or identify anomalies.
Phase3D
"PHASE3D IS FIRST TO CORRELATE AM BUILD ANOMALIES TO PART DEFECTS FOR THE US AIR FORCE AND NASA - 6
During the work with the US Air Force and NASA, Phase3D printed with Ti64 for the former and GRCop-42 for the latter to determine the effect of detectable build variation on part quality. The builds included an anomaly generator, which created realistic, geometry-based powder and melted anomalies, including hops and streaks patterns seen in most AM builds. While measuring the build, Fringe Research automatically identified hops and streaks that were later correlated to porosity in the final part. Parts were then inspected using CT scanning, with correlation being done in Fringe Research and a commercial CT inspection software.
Fringe Research measures the entire build surface three times during every layer and has been designed to provide the user with the tools to identify the cause of failure and improve the process quickly. Historically, Phase3D customers have relied on visual images from the machine to either identify anomalies using AI/ML or an engineer watching a video of the visual images or scroll through them, but this was deemed not to be reliable enough. Phase3D says its heightmaps and Fringe Research, however, 'allow everyone the opportunity to identify how build anomalies impact part quality, including CT-identified defects, fatigue life, tensile strength, and more.'
For Ti64 printed on an EOS M290 for the U.S. Air Force, 81% of Fringe Research identified anomalies correlated to part defects detected by CT and 100% of Fringe Research identified anomalies ≥47um depressions correlated to defects detected by CT. For GRCop-64 on a Colibrium Additive (previously GE Additive) M2 for NASA, 83% of test specimen identified defects were correlated to layers with Fringe Research identified anomalies and 100% of Fringe Research identified anomalies ≥42um depressions correlated to defects detected by CT.
“Providing our customers a high correlation of measurable build anomalies to part defects is changing what is possible for AM,” said Niall O’Dowd, Founder and CEO of Phase3D. “Our customers continue to request objective data that can identify part defects when they occur. With the data Fringe Research collects, we predict our aerospace customers will be able to increase machine throughput by more than 10% every year by stopping parts that will fail inspection early.”
Phase3D will be showcasing the correlation data for the U.S. Air Force and NASA during RAPID + TCT 2024 in Los Angeles, California from June 25-27, 2024.
