AI-Driven Model Generation for Rapid, Cost-Effective On-Demand Part Repair and Redesign

Novineer proposes an AI-driven model generation solution to address inefficiencies in producing on-demand repair or redesigned parts, a challenge faced by the Department of Defense and commercial sectors. The U.S. Army, Navy, GSA, and DLA are exploring additive manufacturing to produce these parts; however, the creation of 3D models remains a manual, time-consuming, and error-prone process. Novineerĺs solution automates this process through a three-step machine learning workflow: Capture, Locate, and Model. The process involves capturing images of damaged parts, generating detailed surface meshes via a feature extraction and mesh deformation network, and using a deep learning-based autoencoder to match existing models in a database or create new CAD models using quadrilateral meshing. The technology is currently at TRL 3, and Phase I aims to achieve TRL 5 prototype testing. This innovation can reduce lead times by up to 80% and production costs by 40%, enhancing mission readiness and operational efficiency while addressing parts obsolescence in legacy systems.