The rapid integration of Artificial Intelligence (AI) in aircraft maintenance is a transformative development for the aviation industry, promising unprecedented improvements in operational efficiency, safety, and environmental sustainability. This paper explores the evolution from traditional maintenance practices to AI-enhanced methodologies, highlighting the critical role of AI in predictive maintenance, fault diagnosis, inventory management, and maintenance scheduling. Through a mixed-methods approach encompassing case studies, AI performance analysis, and expert interviews, this study provides comprehensive insights into the effectiveness of AI-driven maintenance practices. Findings reveal that AI applications significantly enhance predictive maintenance accuracy, reduce unscheduled maintenance events, and optimize cost management, operational efficiency, and safety compliance. Moreover, AI-driven practices contribute to environmental sustainability by improving fuel efficiency and reducing waste. The study underscores the importance of Key Performance Indicators (KPIs) in measuring the success of AI integrations and guiding continuous operational improvements. Despite the promising outcomes, challenges such as data integrity, skill gaps, and the need for standardized regulatory frameworks are identified, setting the direction for future research. This paper concludes that AI in aircraft maintenance represents a strategic imperative for airlines, necessitating ongoing innovation, collaboration, and research to fully realize its potential. The integration of AI technologies into maintenance operations stands as a cornerstone for achieving operational excellence in the modern aviation landscape.
MoghadasNian et al. (Tue,) studied this question.