Barriers and Facilitators to Integrating AI and XR Technologies for Aircraft Inspection

Abstract

This study examines the barriers and facilitators associated with the integration of artificial intelligence (AI) and extended reality (XR) technologies in aircraft inspection, aiming to enhance operational efficiency and ease of use as well as to reduce inspection time. Semi-structured interviews were conducted with 43 aircraft technicians, including 10 online and 33 in-person participants. The in-person interviews focused on understanding current challenges in aviation maintenance and perceptions about integrating AI, whereas the online interviews used four hypothetical inspection scenarios to examine specific barriers and facilitators to adopting AI and XR technologies. A thematic analysis revealed key challenges, including the need for explainable and transparent AI systems to foster user trust, the collection of historical data for predictive maintenance, subsurface defect detection, the impact of fatigue and high workload on task performance, and the cost of inspection training. The study also identified key facilitators, including reduced inspection time through AI and XR assistance, improved ease of inspection and training, and better transfer of expert knowledge to novices. These findings could be useful in developing evidence-based strategies for integrating AI and XR into aircraft inspection processes.