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Statistical Data Processing Technologies for Sustainable Aviation: A Case Study of Ukraine

Author

Listed:
  • Viktoriia Ivannikova

    (Business School, Dublin City University, D09V209 Dublin, Ireland)

  • Maksym Zaliskyi

    (Telecommunication and Radioelectronic Systems Department, State University “Kyiv Aviation Institute”, 03058 Kyiv, Ukraine)

  • Oleksandr Solomentsev

    (Telecommunication and Radioelectronic Systems Department, State University “Kyiv Aviation Institute”, 03058 Kyiv, Ukraine)

  • Ivan Ostroumov

    (Air Navigation Systems Department, State University “Kyiv Aviation Institute”, 03058 Kyiv, Ukraine)

  • Nataliia Kuzmenko

    (Air Navigation Systems Department, State University “Kyiv Aviation Institute”, 03058 Kyiv, Ukraine)

Abstract

Aviation is widely recognised as a system of systems where interconnected components interact dynamically within a structured framework. Failures in aviation equipment, inconsistencies in technological procedures, and operational inefficiencies contribute to stochastic variability, making robust data-driven approaches essential for enhancing sustainability and resilience. This study proposes a comprehensive statistical data processing framework aimed at enhancing the sustainability and resilience of civil aviation systems, using Ukraine as a case study. Our analysis identifies two major gaps: an insufficient application of modern data processing techniques and a lack of consideration for the changepoint effect—a critical factor influencing reliability indicators, diagnostic parameters, and technological process trends. The scientific novelty and value of this article lie in the development of a new approach to data processing in civil aviation, which includes a set of methods for changepoint detection, the estimation of the model parameters after the changepoint, and the prediction of future values in trends of processed data. The practical value is associated with the possibility of implementing such processing for all components of civil aviation, where process parameters and trends of diagnostic variables for components of civil aviation systems are monitored. The analysis of the efficiency of the proposed approach to data processing showed the possibility of reducing operating costs, which can be considered within the framework of sustainable development of civil aviation. An important practical result is that the authors propose a Datahub model to facilitate the efficient collection, processing, and usage of aviation-related statistical data, supporting both sustainable decision-making and cost minimisation. A case study on aviation radio equipment demonstrates the application of statistical data processing techniques, incorporating the changepoint effect through Monte Carlo simulations.

Suggested Citation

  • Viktoriia Ivannikova & Maksym Zaliskyi & Oleksandr Solomentsev & Ivan Ostroumov & Nataliia Kuzmenko, 2025. "Statistical Data Processing Technologies for Sustainable Aviation: A Case Study of Ukraine," Sustainability, MDPI, vol. 17(13), pages 1-33, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:5781-:d:1685655
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    References listed on IDEAS

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    1. Hana Pačaiová & Peter Korba & Michal Hovanec & Jozef Galanda & Patrik Šváb & Ján Lukáč, 2021. "Use of Simulation Tools for Optimization of the Time Duration of Winter Maintenance Activities at Airports," Sustainability, MDPI, vol. 13(3), pages 1-14, January.
    2. Shiva Zargar & Miyuru Kannangara & Giovanna Gonzales-Calienes & Jianjun Yang & Jalil Shadbahr & Cyrille Decès-Petit & Farid Bensebaa, 2024. "Data Hub for Life Cycle Assessment of Climate Change Solutions—Hydrogen Case Study," Data, MDPI, vol. 9(11), pages 1-18, November.
    3. Tong Si & Yunge Wang & Lingling Zhang & Evan Richmond & Tae-Hyuk Ahn & Haijun Gong, 2024. "Multivariate Time Series Change-Point Detection with a Novel Pearson-like Scaled Bregman Divergence," Stats, MDPI, vol. 7(2), pages 1-19, May.
    4. Michael Stiebe, 2023. "Stakeholder Perceptions on Sustainability Challenges and Innovations in General Aviation," Sustainability, MDPI, vol. 15(23), pages 1-29, December.
    5. Sean Jewell & Paul Fearnhead & Daniela Witten, 2022. "Testing for a change in mean after changepoint detection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1082-1104, September.
    6. Ostroumov, Ivan & Ivannikova, Viktoriia & Kuzmenko, Nataliia & Zaliskyi, Maksym, 2025. "Impact analysis of Russian-Ukrainian war on airspace," Journal of Air Transport Management, Elsevier, vol. 124(C).
    7. Ricardo Jorge Raimundo & Maria Emilia Baltazar & Sandra P. Cruz, 2023. "Sustainability in the Airports Ecosystem: A Literature Review," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    8. Ki Han Song & Solsaem Choi & Ik Hyun Han, 2020. "Competitiveness Evaluation Methodology for Aviation Industry Sustainability Using Network DEA," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    9. Igor Kabashkin & Vladimir Perekrestov & Timur Tyncherov & Leonid Shoshin & Vitalii Susanin, 2024. "Framework for Integration of Health Monitoring Systems in Life Cycle Management for Aviation Sustainability and Cost Efficiency," Sustainability, MDPI, vol. 16(14), pages 1-40, July.
    10. Igor Davydenko & Hans Hilbers, 2024. "Decarbonization Paths for the Dutch Aviation Sector," Sustainability, MDPI, vol. 16(3), pages 1-14, January.
    11. Toshio Nakagawa, 2005. "Maintenance Theory of Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-221-8, July.
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