An Augmented Reality‐Based Smart Manufacturing Training System for Practice Experience
Naichang Dai, Haifeng Chen · Computer Applications in Engineering Education · 2025
ABSTRACT Intelligent manufacturing training rooms are pivotal for translating theoretical knowledge into practical applications and enhancing operational skills. To address the limitations of traditional teaching models—specifically their inability to facilitate large‐scale, complex, or high‐risk professional experiments, which result in insufficient comprehensive practical training for students—this study introduces an augmented reality (AR)‐based intelligent manufacturing comprehensive teaching and training system (AR‐IMCTTS). The system establishes an integrated framework for teaching, hands‐on practice, and assessment, enabling students to master the knowledge and production processes of intelligent manufacturing equipment comprehensively. Three aspects of experimental verification were conducted. First, questionnaire results indicate that students widely acknowledge the system's effectiveness in deepening their understanding of IM equipment operations and improving practical skills. Second, quantitative data reveal that students using AR‐IMCTTS achieved an average score increase of 10.82% compared to traditional teaching methods. Third, results demonstrate that the hybrid approach of traditional education and AR‐IMCTTS significantly enhances participants' learning motivation and practical knowledge retention. Through interactive engagement with virtual objects in AR environments, students develop a profound grasp of experimental equipment. Simultaneously, the experimental group's increased practice opportunities boost learning confidence and reduce cognitive load.