Enhancing Aviation Maintenance Training Through Augmented Reality: A Case Study on AR-Based Engine Maintenance Simulation

Aviation maintenance training requires precise skill acquisition, hands-on experience, and technical expertise to ensure aircraft safety and operational efficiency. Traditional training methods, which depend on physical aircraft components and theoretical instruction, often pose challenges related to cost, accessibility, and scalability. This study evaluates the effectiveness of an Augmented Reality (AR)-based training model, utilizing a real F4 aircraft engine donated by the Turkish Air Force, to assess its impact on training speed, procedural accuracy, and cost efficiency. A quantitative evaluation was conducted through structured expert assessments, comparing AR-assisted and traditional training methodologies. Using 3D laser scanning, a high-resolution digital model of the engine was created and integrated into an AR training platform, allowing trainees to engage in interactive maintenance simulations. The results indicate that AR training enhances learning outcomes, reducing task completion time by 38%, lowering maintenance errors by 57%, and improving skill retention rates by 25%. Expert feedback confirms that AR minimizes reliance on physical training resources, supports remote learning, and lowers operational costs, making it a cost-effective solution for aviation training institutions. While initial investment in AR infrastructure presents a challenge, its long-term benefits suggest a strong potential for large-scale adoption in aviation maintenance education. This study provides empirical validation for the integration of AR into aviation training curricula, reinforcing its role in modernizing and improving aviation maintenance training methodologies.