The Role of Task Familiarity in AR HMD-based Guidance and Training for Industrial Repair and Maintenance Tasks

Augmented Reality (AR) technology can enhance training and task guidance in industrial settings by overlaying digital information onto the physical environment. Although studies report the benefits of AR in maintenance tasks, its effectiveness remains contentious, particularly regarding task familiarity. This dissertation investigates how AR can boost productivity in repair tasks and serve as an effective medium for on-the-job training. The research shows that AR head-mounted display (HMD) guidance considerably improves the efficiency and effectiveness of repair tasks, especially for procedures unfamiliar to technicians. Empirical evidence indicates that AR benefits are most pronounced during initial executions, diminishing as familiarity increases. Moreover, AR-based training facilitates superior knowledge retention compared to traditional methods and offers potential economic and environmental advantages. Based on findings from three comprehensive experiments, this thesis validates the practical application of AR HMDs. It introduces an AR assistive system to improve the training and guidance of service technicians. The research concludes with design recommendations for organisations, emphasising adaptive user support, optimal device selection, and seamless integration of AR systems into existing workflows. Collectively, these insights provide a solid foundation for optimising and scaling AR technologies in industrial contexts, particularly within the automotive sector.