The approach to optimization of the structure of the repair process of aviation radio equipment
DOI: https://doi.org/10.3846/transport.2025.24012Abstract
The Operation System (OS) of Aviation Radio Equipment (ARE) includes such elements as equipment, organizational structure, processes, documentation, personnel, measuring equipment, consumables and information resources, and others. When considering the problems of primary design and modernization of OSs, a large number of problems arise that can be solved with the help of intelligent decision support systems. During the operation of ARE, significant material resources are consumed, the amount of which is usually random. Therefore, during design, one of the main tasks is to ensure the minimum costs. This article considers the task of cost optimization within the organizational structure of the repair process. At the same time, the article provides analytical equations that allow to calculate and estimate operational costs for a given organizational structure, tariffs for repair and delivery of equipment components, and failure flow parameters. Attention is also paid to the task of rationalizing the organizational structure of the repair process, taking into account the efficiency of the decision-making procedures depending on the failure type (simple or complex). In addition, the article considers an example of several scenarios for the possible placement of repair enterprises in the airports of Ukraine during the post-war reconstruction period.
Keywords:
operational cost optimization, organizational structure, airport planning, intelligent systems, aviation radio equipment, operation, repairHow to Cite
Share
License
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Anand, A.; Ram, M. 2018. System Reliability Management: Solutions and Technologies. CRC Press. 276 p. https://doi.org/10.1201/9781351117661
André, J.-C. 2019. Industry 4.0: Paradoxes and Conflicts. John Wiley & Sons, Inc. 320 p. https://doi.org/10.1002/9781119644668
Ayers, J. B. 2000. Handbook of Supply Chain Management. CRC Press. 488 p. https://doi.org/10.1201/9781420025705
Bourassa, D.; Gauthier, F.; Abdul-Nour, G. 2016. Equipment failures and their contribution to industrial incidents and accidents in the manufacturing industry, International Journal of Occupational Safety and Ergonomics 22(1): 131–141. https://doi.org/10.1080/10803548.2015.1116814
Boylan, J. E.; Syntetos, A. A. 2010. Spare parts management: a review of forecasting research and extensions, IMA Journal of Management Mathematics 21(3): 227–237. https://doi.org/10.1093/imaman/dpp016
Chen, J.; Gusikhin, O.; Finkenstaedt, W.; Liu, Y.-N. 2019. Maintenance, repair, and operations parts inventory management in the era of Industry 4.0, IFAC-PapersOnLine 52(13): 171–176. https://doi.org/10.1016/j.ifacol.2019.11.171
De Jonge, B.; Scarf, P. A. 2020. A review on maintenance optimization, European Journal of Operational Research 285(3): 805–824. https://doi.org/10.1016/j.ejor.2019.09.047
Dhillon, B. S. 2006. Maintainability, Maintenance, and Reliability for Engineers. CRC Press. 240 p. https://doi.org/10.1201/9781420006780
Duda, J.; Gąsior, A. 2021. Industry 4.0: a Glocal Perspective. Routledge. 252 p. https://doi.org/10.4324/9781003186373
Freisinger, E.; McCarthy, I. P. 2024. What fails and when? A process view of innovation failure, Technovation 133: 102995. https://doi.org/10.1016/j.technovation.2024.102995
Frenz, W. 2022. Handbook Industry 4.0: Law, Technology, Society. Springer. 1240 p. https://doi.org/10.1007/978-3-662-64448-5
Galar, D.; Sandborn, P.; Kumar, U. 2017. Maintenance Costs and Life Cycle Cost Analysis. CRC Press. 516 p. https://doi.org/10.1201/9781315154183
Gąsiorkiewicz, L. 2020. The process approach in the financial management of insurance firms, Foundations of Management 12(1): 7–18. https://doi.org/10.2478/fman-2020-0001
Gertsbakh, I. 2000. Reliability Theory: with Applications to Preventive Maintenance. Springer. 219 p. https://doi.org/10.1007/978-3-662-04236-6
Goncharenko, A. 2017. Aircraft operation depending upon the uncertainty of maintenance alternatives, Aviation 21(4): 126–131. https://doi.org/10.3846/16487788.2017.1415227
Gonçalves Machado, C.; Winroth, M.; Carlsson, D.; Almström, P.; Centerholt, V.; Hallin, M. 2019. Industry 4.0 readiness in manufacturing companies: challenges and enablers towards increased digitalization, Procedia CIRP 81: 1113–1118. https://doi.org/10.1016/j.procir.2019.03.262
Grall, A.; Dieulle, L.; Berenguer C.; Roussignol, M. 2002. Continuous-time predictive-maintenance scheduling for a deteriorating system, IEEE Transactions on Reliability 51(2): 141–150. https://doi.org/10.1109/TR.2002.1011518
Jardine, A. K. S.; Tsang, A. H. C. 2021. Maintenance, Replacement, and Reliability: Theory and Applications. CRC Press. 412 p. https://doi.org/10.1201/9780429021565
Kant, R.; Gurung, H. 2023. Industry 4.0: Concepts, Processes and Systems. CRC Press. 282 p. https://doi.org/10.1201/9781003246466
Karakoc, T. H.; Kostić, I. A.; Grbović, A.; Svorcan, J.; Dalkiran, A.; Ercan, A. H.; Peković, O. M. (Eds.). 2024. Novel Techniques in Maintenance, Repair, and Overhaul: Proceedings of the International Symposium on Aviation Technology, MRO, and Operations 2022. 14–16 September 2022, Belgrade, Serbia. 456 p. https://doi.org/10.1007/978-3-031-42041-2
Liu, J. 2021. Maintenance model of aircraft structure based on three-stage degradation process, Computers & Industrial Engineering 157: 107335. https://doi.org/10.1016/j.cie.2021.107335
McPherson, J. W. 2019. Reliability Physics and Engineering: Time-to-Failure Modeling. Springer. 463 p. https://doi.org/10.1007/978-3-319-93683-3
Modarres, M.; Groth, K. 2023. Reliability and Risk Analysis. CRC Press. 480 p. https://doi.org/10.1201/9781003307495
Mygal, G. 2024. Problems of the human factor in transport systems, Transport Technologies 5(1): 31–43. https://doi.org/10.23939/tt2024.01.031
Nakagawa, T. 2006. Maintenance Theory of Reliability. Springer. 270 p. 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
Poberezhna, Z. 2021. Comprehensive approach to the efficiency assessment of the business model of the aviation enterprise based on business process innovation, Eastern-European Journal of Enterprise Technologies 5(13): 44–57. https://doi.org/10.15587/1729-4061.2021.243118
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
Poole, D. L.; Mackworth, A. K. 2017. Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press. 792 p. https://doi.org/10.1017/9781108164085
Rahito, R.; Wahab, D. A.; Azman, A. H. 2019. Additive manufacturing for repair and restoration in remanufacturing: an overview from object design and systems perspectives, Processes 7(11): 802. https://doi.org/10.3390/pr7110802
Rausand, M.; Barros, A.; Hoyland, A. 2021. System Reliability Theory: Models, Statistical Methods, and Applications. John Wiley & Sons, Inc. 864 p. https://doi.org/10.1002/9781119373940
Raza, A.; Ulansky, V. 2021. Through-life maintenance cost of digital avionics, Applied Sciences 11(2): 715. https://doi.org/10.3390/app11020715
Ren, H.; Chen, X.; Chen, Y. 2017. Reliability Based Aircraft Maintenance Optimization and Applications: a Volume in Aerospace Engineering. Academic Press. 260 p. Available from Internet: https://www.sciencedirect.com/book/9780128126684
Smith, D. J. 2022. Reliability, Maintainability and Risk: Practical Methods for Engineers. Elsevier. 494 p. https://doi.org/10.1016/C2021-0-00257-1
Solomentsev, O.; Zaliskyi, M.; Herasymenko, T.; Kozhokhina, O.; Petrova, Y. 2019. Efficiency of operational data processing for radio electronic equipment, Aviation 23(3): 71–77. https://doi.org/10.3846/aviation.2019.11849
Solomentsev, O.; Zaliskyi, M.; Holubnychyi, O.; Ostroumov, I.; Sushchenko, O.; Bezkorovainyi, Y.; Averyanova, Y.; Ivannikova, V.; Kuznetsov, B.; Bovdui, I.; Nikitina, T.; Voliansky, R.; Cherednichenko, K.; Sokolova, O. 2024. Efficiency analysis of current repair procedures for aviation radio equipment, Lecture Notes in Networks and Systems 992: 281–295. https://doi.org/10.1007/978-3-031-60196-5_21
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
Srivastava, M. K.; Khan, A. H.; Srivastava, N. 2014. Statistical Inference: Theory of Estimation. PHI learning. 808 p.
Sugier, J.; Anders, G. J. 2010. Modelling equipment deterioration vs. maintenance policy in dependability analysis, in A.-D. Ali (Ed.). Computational Intelligence and Modern Heuristics, 29–42. https://doi.org/10.5772/7826
Tachinina, O.; Lysenko, O.; Alekseeva, I.; Sushyn, I.; Novikov, V. 2022. Method of algorithmic correction of dynamic properties of special-purpose electric drive, in 2022 IEEE 3rd KhPI Week on Advanced Technology (KhPIWeek), 3–7 October 2022, Kharkiv, Ukraine, 1–4. https://doi.org/10.1109/KhPIWeek57572.2022.9916481
Ucar, A.; Karakose, M.; Kırımça, N. 2024. Artificial intelligence for predictive maintenance applications: key components, trustworthiness, and future trends, Applied Sciences 14(2): 898. https://doi.org/10.3390/app14020898
Yıldız, G. B.; Soylu, B. 2023. Integrating preventive and predictive maintenance policies with system dynamics: a decision table approach, Advanced Engineering Informatics 56: 101952. https://doi.org/10.1016/j.aei.2023.101952
Zhao, J.; Gao, C.; Tang, T. 2022. A review of sustainable maintenance strategies for single component and multicomponent equipment, Sustainability 14(5): 2992. https://doi.org/10.3390/su14052992
View article in other formats
CrossMark check
Published
Issue
Section
Copyright
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.