The University of Oklahoma and Oak Ridge National Laboratory have launched Phase II of an $8.8 million additive manufacturing research program in partnership with the Air Force Sus...

The University of Oklahoma and Oak Ridge National Laboratory have launched Phase II of an $8.8 million additive manufacturing research program in partnership with the Air Force Sustainment Center, Air Force Research Laboratory, and the Oklahoma City Air Logistics Complex. This initiative, running through 2028, focuses on developing a standardized qualification framework for 3D printed parts on legacy aircraft, specifically targeting both new component manufacturing and repair processes. Key stakeholders include Zahed Siddique from the University of Oklahoma and Moe Khaleel from ORNL, who are integrating AI-driven in situ monitoring and the Peregrine software platform to streamline airworthiness certification.

This program addresses the critical bottleneck of part qualification in the aerospace sector, where current requirements for individual testing of materials, geometry, and machines make sustainment of legacy fleets cost-prohibitive. By shifting toward a digital thread approach that tracks the manufacturing process as a unified data stream, the partnership aims to reduce the reliance on machine-specific certifications. This effort aligns with broader Department of Defense initiatives to democratize national laboratory capabilities and accelerate the adoption of LPBF and other metal AM technologies for critical sustainment operations.

The success of this program hinges on the ability to translate digital process monitoring into repeatable, airworthy outcomes that satisfy military safety standards. Stakeholders should focus on the integration of the Peregrine software into existing supply chain workflows, as this will determine whether the standardized qualification framework can effectively scale across diverse machine platforms. The practical value lies in moving away from rigid, machine-specific testing toward a data-centric model that prioritizes part performance over hardware constraints.