Okoro O. Optimization of aircraft maintenance processes for continuing airworthiness in Nigeria.

Українська версія

Thesis for the degree of Doctor of Philosophy (PhD)

State registration number

0824U000802

Thesis Registration Form

0824U000802.pdf

Applicant for

Specialization

  • 272 - Авіаційний транспорт

14-02-2024

Specialized Academic Board

Разова спеціалізована вчена рада №2761

National Aviation University

Essay

The operations phase of the aircraft life cycle is the most expensive; it costs 10-20 times the design and manufacturing phase. For instance, in Nigeria, even though domestic and international passenger traffic has grown tremendously, recording a post-COVID-19 pandemic annual growth rate of 43.41% and 57.61% respectively, aircraft maintenance costs are still significantly higher than the global average. Aircraft operators spend 75% of the estimated $1 billion annual cost in West Africa; this justifies the need for a shift away from traditional maintenance actions, which are corrective or preventive. Corrective Maintenance (CM) tasks are connected to run-to-failure maintenance strategies, while Preventive Maintenance (PM) work is performed as part of a fixed interval to replace, repair, or restore. It includes work carried out under a fixed-interval restoration/repair strategy and conducted based on a time or machine-run-based schedule that detects, precludes, or mitigates degradation. Unfortunately, these traditional aircraft maintenance strategies lack predictive capability and often lead to maintenance being performed too early, i.e., before the end of a machine's useful life, or too late, i.e., after a costly failure Therefore, the aviation industry needs realism in mathematical models, and the way optimization problem is formulated; system reliability, maintenance processes, and cost must be considered from the design phase of the aircraft lifecycle. Recent research highlights that statistical data processing algorithms can be used to improve the efficiency of aircraft operations given diagnostic variables and reliability parameters as initial data. These algorithms can be developed using statistical data generated from the operations phase of the aircraft lifecycle, which generates a wealth of real-time data, which is collected, transferred, and processed with 70 miles of wire and over 18 million lines of code. The resulting algorithms can estimate the time of possible failure with the aim of preventing it based on correct and timely operational actions. Furthermore, the data-driven Predictive Maintenance (PdM) approach based on industry 4.0 techniques will result in lower maintenance costs, avoid unnecessary PM actions and reduce unexpected failures. A combination of PM and PdM results in 18.5 % less unplanned downtime and 87.3% fewer defects for more reliance on predictive than preventive maintenance.

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Research papers

1. Okoro O.C., Zaliskyi M., Dmytriiev S., Solomentsev O., Sribna O. Optimization of Maintenance Task Interval of Aircraft Systems. International Journal of Computer Network & Information Security. 2022. Volume 14. No 2. P. 77–89.

2. Okoro O.C., Zaliskyi M., Serhii D., Abule I. An approach to reliability analysis of aircraft systems for a small dataset. Scientific Journal of Silesian University of Technology. Series Transport. 2023. Volume 118. P. 207–217.

3. Zaliskyi M., Okoro O.C., Dmytriiev S., Fayoyiwa O.S. Software Support for Simulation and Prediction of Failures and Faults During Aircraft Operations. Lecture Notes in Networks and Systems. 2023. Volume 736. P. 247–259.

4. Zaliskyi M., Yashanov I., Okoro O.C., Shcherbyna O. Analysis of Learning Efficiency of Expert System for Decision-Making Support in Aviation. Advanced Computer Information Technologies (ACIT): Proceedings of IEEE 12th International Conference, Ruzomberok (Slovakia). 26-28 September 2022. P. 172–175.

5. Okoro O.C., Chukwu C.N., Zaliskyi M., Holubnychyi O. A Method for Planning Spare Parts Inventory During Aircraft Operation Advanced Computer Information Technologies (ACIT): Proceedings of IEEE 12th International Conference, Ruzomberok (Slovakia). 26-28 September 2022. P. 168–171.

6. Okoro O.C., Zaliskyi M., Dmytriiev S., Qudus S. Data-Driven Approach to Optimal Aircraft MaintenanceTheInternational Council of the Aeronautical Sciences: Proceedings of 33rd Congress, Stockholm (Sweden). 4 – 9 September 2022. P. 7114–7124.

7. Okoro O.C. Reliability Analysis of Aircraft Fleet in Nigeria. Proceedings of National Aviation University. 2020, Volume 83 (2). P.49–53.

8. Окоро О. Ч., Дмитрієв С. О., Заліський М. Ю., Осіпчук А. О. Моделі для аналізу надійності авіаційних компонентів, систем та конструкцій повітряних суден. Системи управління, навігації та зв’язку. Збірник наукових праць. 2022. Том 4 (№ 70). С. 16–21.

9. Окоро О.Ч., Дмитрієв С. О., Заліський М. Ю., Осіпчук А. О. Статистичні імітаційні моделі оптимізації технічного обслуговування повітряних суден. Системи управління, навігації та зв’язку. Збірник наукових праць. 2022. Том 3 (№ 69). С. 8–12.

10. Okoro O.C. Optimization of Aircraft Maintenance Processes Using Regression Analysis. Current Security Problems in Transport, Energy, and Infrastructure: Proceedings of Conference, Kherson. 2021. P. 244.

11. Okoro O.C., Zaliskyi M., Dmytriiev S. Statistical simulation regression models for efficient aircraft operations. Aviation in the XXI-st century - Safety in aviation and space technology: Proceedings of The Tenth World Congress, Kyiv. 28 – 30 September 2022. P. 1–5.

12. Zaliskyi M., Okoro O.C., Dmytriiev S. Statistical Simulation of Failures of the Systems and Structures of S-76 C++ Helicopters in Nigeria. Cyber Hygiene & Conflict Management in Global Information Networks: Proceedings of 2nd International Conference, Kyiv-Lviv. 30 November 2020. P. 1–10.

13. Okoro O.C., Zaliskyi M., Dmytriiev S. Statistical Simulation Models for the Optimization of Aircraft Maintenance Processes. Problems of Transportation Organization and Air Transport Management: Proceedings of International Scientific-Practical Conference, Kyiv, NAU, 20 October 2021. P-3.

14. Okoro O.C., Zaliskyi M., Dmytriiev S. Models for Optimizing Aircraft Maintenance Processes. Condition-based Maintenance in Aerospace: Proceedings of 1st International Conference, Delft (Netherlands). 24 – 25 May 2022. P. 1–10.

15. Okoro O.C., Zaliskyi M. Models and Algorithms for Optimizing Aircraft Maintenance Processes. Air Transport Research Society: Proceedings of 25th World Conference, Antwerp (Belgium). 24 – 27 August 2022. P. 1 – 5.

16. Okoro O.C., Zaliskyi M. Optimizing Aircraft Maintenance Processes – An Operations Data-Driven Methodology. Ontario Aircraft Maintenance Conference; The Future of Aircraft Maintenance – Performance, Professionalism and Pride: Proceedings of Conference, Toronto, (Canada). 2-3 November 2022. P.1-18.

17. Okoro O.C., Zaliskyi M., Dmytriiev S. An Approach to Optimizing Aircraft Maintenance. In: Karakoc, T.H., Atipan, S., Dalkiran, A., Ercan, A.H., Kongsamutr, N., Sripawadkul,V. (eds). Research Developments in Sustainable Aviation. ISSA SARES 2021 (Proceedings of International Symposium on Sustainable Aviation, Bangkok, Thailand). Sustainable Aviation. 2023, Springer, Cham, pp. 263–269.

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