Statistical models for the utilization process of aviation radio equipment

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.

Authors

Institutions

Publication Details

Journal
Aviation
Published
2025-09-24
DOI
https://doi.org/10.3846/aviation.2025.24453
Primary Topic
Advanced Control and Stabilization in Aerospace Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Statistical models for the utilization process of aviation radio equipment

Олександр Соломенцев, Nataliia Kuzmenko, Maksym Zaliskyi, Viktoriia Ivannikova et al.
Aviation
Advanced Control and Stabilization in Aerospace Systems
article

Statistical models for the utilization process of aviation radio equipment

Олександр Соломенцев, Nataliia Kuzmenko, Maksym Zaliskyi, Viktoriia Ivannikova, Ivan Ostroumov
article en

Abstract

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.

AviationVol. 29(3)
Dublin City University (IE), National University "Kyiv Aviation Institute" (UA)
European Commission, Dublin City University
Openalex Percentile: Top 66%
Advanced Control and Stabilization in Aerospace Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.