Fast and Accurate Quality Inspection using AI and XR

The scope of Phase II effort is to research and develop a prototype of an affordable, accelerated quality inspection and defection detection solution using AI and XR for improving quality control of hydroforming mold process. The solution will enable the quality inspectors at 76 CMXG to analyze parts and molds in a digital environment, enabling real-time defect detection and analysis, resulting in early identification of defects, minimizing the risk of faulty parts and reducing the need for costly rework or replacements.  The current non-defense commercial solution will need key adaptations to obtain TRL 8 with an actual system completed and qualified through test and demonstration. It will require the following R &D for successful transition to production environment:R&D is required to extend 3D AI capability for selected hydroforming molds/dies of parts/components of KC-135 and other aircrafts. Perform 3D scanning, automatic object detection and segmentation on the selected form molds, development of 3D workflows, training of the AI models for defect detection and quality inspection.R&D for tracking and the recording the evolution of the 3D scene during the hydroforming process to enable predictive analysis of the process and provide active guidance minimizing errors in production.Testing and evaluation of the solution in the operational environment at OC-ALC.