Technical Journal, Vol. 20 No. 4, 2026.
Review article
https://doi.org/10.31803/tg-20250504123321
Advancing Aircraft Maintenance through Predictive Technologies and Artificial Intelligence
Belma Atapek-Yagan
; Department of Materials and Technology, Faculty of Electrical Engineering, University of West Bohemia, Univerzitní 2795/26, 301 00 Pilsen, Czech Republic
*
Jiri Tupa
; Department of Materials and Technology, Faculty of Electrical Engineering, University of West Bohemia, Univerzitní 2795/26, 301 00 Pilsen, Czech Republic
František Steiner
; Department of Materials and Technology, Faculty of Electrical Engineering, University of West Bohemia, Univerzitní 2795/26, 301 00 Pilsen, Czech Republic
* Corresponding author.
Abstract
This paper explores the transition in aircraft maintenance from conventional preventative methods to predictive maintenance driven by artificial intelligence (AI). Predictive maintenance utilizes data-driven methodologies to predict failures, reduce downtime and enhance safety. Artificial intelligence plays a pivotal role by processing substantial data to identify patterns and predict maintenance requirements with a high degree of accuracy. The present study addresses the fundamental challenges associated with integrating AI into aircraft maintenance, including robust data collection, algorithm transparency and cybersecurity risks. By addressing these issues, the paper provides actionable insights and solutions to effectively utilize AI while minimizing the associated risks. This study offers a novel perspective on the use of AI to revolutionize aircraft maintenance and improve efficiency and reliability, building on existing research and identifying opportunities to advance AI-driven maintenance strategies in aviation.
Keywords
artificial intelligence; Industry 4.0; passenger aircraft; predictive maintenance; quality process
Hrčak ID:
351744
URI
Publication date:
15.12.2026.
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