Statistical models for the utilization process of aviation radio equipment
DOI: https://doi.org/10.3846/aviation.2025.24453Abstract
The reliability of aviation equipment is a critical factor that directly influences the efficiency of tasks associated with flight operations. To assess reliability, various indicators are commonly employed, including mean time between failures, mean time between repairs, steady-state availability, availability function, downtime ratio, and utilization factor. However, in modern aviation, the operation of radio equipment often neglects considerations of economic impact, socio-political factors, and a comprehensive analysis of the efficiency of all components within the civil aviation infrastructure. Reliability indicators are typically stochastic in nature, necessitating the development of statistical models, the application of advanced statistical data processing methods, and the enhancement of decision-making technologies, including those leveraging artificial intelligence. External influences, operational conditions, degradation of electrical components, and instability in both autonomous and external power supplies often result in nonstationary trends across the range of parameters being monitored. These dynamic changes highlight the need for advancements in traditional data processing methods, particularly in areas such as dataset formation, classification, evaluation, and forecasting. This article focuses on the development of statistical models for the downtime ratio and utilization factor, specifically addressing scenarios characterized by nonstationary trends in diagnostic parameters.
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data processing, operation system, aviation radio equipment, nonstationarity, downtime ratio, utilization factorHow to Cite
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Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
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References
Andre, J. (2019). Industry 4.0: paradoxes and conflicts. Wiley. https://doi.org/10.1002/9781119644668
Cusick, S. K., Cortes, A. I., & Rodrigues, C. C. (2017). Commercial aviation safety (6th ed.). McGraw-Hill Education.
Dhillon, B. S. (2006). Maintainability, maintenance, and reliability for engineers. Taylor & Francis Group. https://doi.org/10.1201/9781420006780
Gališanskis, A. (2004). Aspects of quality evaluation in aviation maintenance. Aviation, 8(3), 18–26. https://doi.org/10.3846/16487788.2004.9635877
Gallo, M. A., Wheeler, B. E., & Silver, I. M. (2023). Fundamentals of statistics for aviation research. Routledge. https://doi.org/10.4324/9781003308300
Goncharenko, A. (2018). Development of a theoretical approach to the conditional optimization of aircraft maintenance preference uncertainty. Aviation, 22(2), 40–44. https://doi.org/10.3846/aviation.2018.5929
Hahn, G. J., & Shapiro, S. S. (1994). Statistical models in engineering. Wiley.
Humphreys, B. (2023). The regulation of air transport. From protection to liberalisation, and back again. Routledge. https://doi.org/10.4324/9780429448973
Karadžić, R., Petković, D., & Šabić, M. (2012). A model for the maintenance of old aircraft. Aviation, 16(1), 16–24. https://doi.org/10.3846/16487788.2012.680756
Kearns, S. K. (2021). Fundamentals of international aviation. Routledge. https://doi.org/10.4324/9781003031154
Maleviti, E. (2023). Fundamentals of sustainable aviation. Routledge. https://doi.org/10.4324/9781003251231
Meijer, G. (2021). Fundamentals of aviation operations. Routledge. https://doi.org/10.4324/9780429318801
Mitra, A. (2016). Fundamentals of quality control and improvement (4th ed.). Wiley.
Modarres, M., & Groth, K. (2023). Reliability and risk analysis. CRC Press. https://doi.org/10.1201/9781003307495
Nakagawa, T. (2005). Maintenance theory of reliability. Springer. https://doi.org/10.1007/1-84628-221-7
Okoro, O. C., Zaliskyi, M., Dmytriiev, S., Solomentsev, O., & Sribna, O. (2022). Optimization of maintenance task interval of aircraft systems. International Journal of Computer Network and Information Security, 14(2), 77–89. https://doi.org/10.5815/ijcnis.2022.02.07
Ostroumov, I., Ivannikova, V., Kuzmenko, N., & Zaliskyi, M. (2025). Impact analysis of Russian-Ukrainian war on airspace. Journal of Air Transport Management, 124, Article 102742. https://doi.org/10.1016/j.jairtraman.2025.102742
Palicot, J. (2013). Radio engineering: From software radio to cognitive radio. Wiley.
Poberezhna, Z. (2017). Comprehensive assessment of the airlines’ competitiveness. Economic Annals-XXI, 167(9–10), 32–36. https://doi.org/10.21003/ea.V167-07
Prokopenko, I. (2021). Nonparametric change point detection algorithms in the monitoring data. In Z. Hu, S. Petoukhov, I. Dychka, & M. He (Eds), Advances in Computer Science for Engineering and Education IV. ICCSEEA 2021. Lecture Notes on Data Engineering and Communications Technologies (Vol 83, pp. 347–360). Springer. https://doi.org/10.1007/978-3-030-80472-5_29
Rausand, M. (2004). System reliability theory: Models, statistical methods and applications. Wiley.
Raza, A., & Ulansky, V. (2021). Through-life maintenance cost of digital avionics. Applied Sciences, 11(2), Article 715. https://doi.org/10.3390/app11020715
Smerichevskyi, S., Mykhalchenko, O., Poberezhna, Z., & Kryvovyazyuk, I. (2023). Devising a systematic approach to the implementation of innovative technologies to provide the stability of transportation enterprises, Eastern-European Journal of Enterprise Technologies, 3(13(123)), 6–18. https://doi.org/10.15587/1729-4061.2023.279100
Smith, D. J. (2021). Reliability, maintainability and risk. Practical methods for engineers (10th ed.). Elsevier.
Solomentsev, O., Zaliskyi, M., & Zuiev, O. (2013). Radioelectronic equipment availability factor models. In Proceedings of Signal Processing Symposium 2013 (pp. 1–4), Serock, Poland. IEEE. https://doi.org/10.1109/SPS.2013.6623616
Solomentsev, O., Zaliskyi, M., & Zuiev, O. (2016). Estimation of quality parameters in the radio flight support operational system. Aviation, 20(3), 123–128. https://doi.org/10.3846/16487788.2016.1227541
Solomentsev, O., Zaliskyi, M., Herasymenko, T., Kozhokhina, O., & Petrova, Yu. (2019). Efficiency of operational data processing for radio electronic equipment. Aviation, 23(3), 71–77. https://doi.org/10.3846/aviation.2019.11849
Stacey, D. (2008). Aeronautical radio communication systems and networks. John Wiley & Sons. https://doi.org/10.1002/9780470035108
Tachinina, O., Lysenko, O., Alekseeva, I., Novikov, V. & Sushyn, I. (2021). Methods for parametric adjustment of a digital system and precision automatic stabilization of an Unmanned Aerial Vehicle. In Proceedings of IEEE 6th International Conference on Actual Problems of Unmanned Aerial Vehicles Development (pp. 76–79), Kyiv, Ukraine. IEEE. https://doi.org/10.1109/APUAVD53804.2021.9615436
Ulansky, V., & Raza, A. (2024). A historical survey of corrective and preventive maintenance models with imperfect inspections: Cases of constant and non-constant probabilities of decision making. Aerospace, 11(1), Article 92. https://doi.org/10.3390/aerospace11010092
Zaliskyi, M., Solomentsev, O., Holubnychyi, O., Ostroumov, I., Sushchenko, O., Averyanova, Yu., Bezkorovainyi, Yu., Cherednichenko, K., Sokolova, O., Ivannikova, V., Voliansky, R., Kuznetsov, B., Bovdui, I., & Nikitina, T. (2024). Methodology for substantiating the infrastructure of aviation radio equipment repair centers. CEUR Workshop Proceedings, 3732, 136–148. https://ceur-ws.org/Vol-3732/paper11.pdf
Zhukov, I., Dolintse, B., & Balakin, S. (2024). Enhancing data processing methods to improve UAV positioning accuracy. International Journal of Image, Graphics and Signal Processing, 16(3), 100–110. https://doi.org/10.5815/ijigsp.2024.03.08
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