AI-Powered Quality Control with AR

René Matériaux Composites (RMC), a NanoXplore company in Quebec, produces high-quality truck parts. Ensuring defect-free parts is critical for paint quality, but traditional inspections involved two manual steps, creating opportunities for error and inefficiency. RMC aimed to streamline defect tracking, improve data accuracy, and lay the groundwork for AI-driven quality control. We designed an AR solution using Microsoft HoloLens 2, allowing inspectors to tag defects directly on parts via 3D CAD models and intuitive hand gestures. This hands-free approach integrates defect logging into the inspection workflow, reducing time and improving consistency. The AR app also overlays corrections during final inspections, ensuring precise verification. Beyond immediate efficiency gains, the solution generates structured data ideal for training AI models. Future iterations will leverage machine learning to automatically detect defects in real time, combining AR visualization with AI insights. Inspectors will see AI-identified defects overlaid directly on the part, enhancing speed, accuracy, and quality control. By merging AR and AI, we’re enabling RMC to transform inspection processes, create scalable quality assurance solutions, and prepare for the next generation of automated manufacturing. This project demonstrates how AI can turn hands-on manufacturing tasks into data-driven, precise, and efficient processes, unlocking new possibilities for small to mid-size manufacturers.