Augmented Remote Assistance for Quality Inspection: A Cross-Reality Collaborative System With Virtual Replicas

Abstract

Remote expert assistance is critical for complex quality inspection in industrial manufacturing and emergency maintenance. Current Cross-Reality (XR) solutions face significant limitations: predominantly single-user focused, lack effective AI-human expertise integration, and insufficient evaluation of human factors in collaborative contexts. We developed a Cross-Reality collaborative system integrating AI-assisted defect detection with virtual replicas, enabling real-time collaboration between remote experts and local workers via head-mounted displays. Our controlled evaluation with 26 participants inspecting industrial products demonstrated that our system outperformed traditional and screen-based remote assistance methods, reducing error rates from 20.19% (no assistance) to 2.88% (XR-assisted). The system substantially improved social presence, collaboration efficiency, and usability, with 88.5% of remote experts preferring our solution. Our study advances Industry 5.0 principles by combining human-centric design with intelligent technological integration in industrial quality inspection scenarios.