Image-R: Handheld Maintenance Inspection Technology to Enable Agile Combat Employment

Aircraft sustainment is critical to Agile Combat Employment (ACE), yet current Non-Destructive Inspection (NDI) methods are slow, labor-intensive, and reliant on depot-level infrastructure. This project introduces a modified Image-R M2.5 handheld inspection tool equipped with Laser Excitation Thermography (LET) to rapidly detect fatigue cracks in metallic airframes. The system combines high-performance infrared imaging with pulsed NdYAG laser illumination to reveal microscopic defects in coated metal surfaces. By integrating artificial intelligence (AI) for real-time defect detection, the LET-enabled Image-R automates inspections, reducing reliance on highly specialized technicians. Its lightweight, portable design enables Airmen to conduct field-based inspections in austere environments, directly supporting the Air Force’s ACE strategy. The proposed Phase II effort will evaluate the LET-enabled Image-R at Oklahoma City Air Logistics Complex (OC-ALC), refining its AI-powered defect mapping, improving LiDAR-based SLAM mapping of airframes, and enhancing usability for expeditionary maintenance teams. By reducing inspection time by 50% and improving defect detection accuracy by 70% compared to legacy methods, this technology enhances operational readiness, extends aircraft service life, and ensures mission success in contested environments where rapid sustainment is critical.