Simulation of Ageing of Aircraft

Mohammed Mudabbiruddin; Pokorádi László

doi:10.32560/rk.2022.2.3

Simulation of Ageing of Aircraft

Mohammed Mudabbiruddin
https://orcid.org/0000-0002-2216-7229
Pokorádi László
https://orcid.org/0000-0003-2857-1887

doi: 10.32560/rk.2022.2.3

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

In today’s world, there is increasing demand of new technologies. As the world is growing, new technologies are emerging. To sustain the new technologies, technologies used for its maintenance must be developed. In the aviation industry with respect to the Industry 4.0 system, its maintenance strategies are also developing. The aim to this study is to present a mathematical model which is used to predict the ageing of any technical system. The authors used the Markov process theory to model the ageing process. As per the model, results and future work are determined and discussed briefly.

Keywords:

Maintenance Ageing Process Aviation Markov Process mathematical model

How to Cite

[1]

M. Mohammed and L. Pokorádi, “Simulation of Ageing of Aircraft”, RepTudKoz, vol. 34, no. 2, pp. 29–36, Mar. 2023.

References

I. de Pater, A. Reijns and M. Mitici, ‘Alarm-Based Predictive Maintenance Scheduling for Aircraft Engines with Imperfect Remaining Useful Life Prognostics’. Reliability Engineering and System Safety, Vol. 221. pp. 108–341. 2022. Online: https://doi.org/10.1016/j.ress.2022.108341

M. D. Anis, ‘Identifying a Mathematical Model to Optimize Pump Maintenance Planning Decisions – A Case of Irrigation Asset Management in K.S.A’. 2018 Condition Monitoring and Diagnosis, CMD 2018 – Proceedings. pp. 1–6. 2018. Online: https://doi.org/10.1109/CMD.2018.8535792

L. Zhou, Y. Wang, Y. Li, M. Zhu and X. Du, ‘A Maintenance Decision Optimization Method Based on Life Cycle Cost of Converter Transformer’. 2016 IEEE Electrical Insulation Conference (EIC). pp. 288–291. 2016. Online: https://doi.org/10.1109/EIC.2016.7548603

R. M. Arias Velásquez, J. V. Mejía Lara and A. Melgar, ‘Reliability Model for Switchgear Failure Analysis Applied to Ageing’. Engineering Failure Analysis, Vol. 101. pp. 36–60. 2019. Online: https://doi.org/10.1016/j.engfailanal.2019.03.004

M. D. Dangut, Z. Skaf and I. K. Jennions, ‘An Integrated Machine Learning Model for Aircraft Components Rare Failure Prognostics with Log-Based Dataset’. ISA Transactions, Vol. 113. pp. 127–139. 2021. Online: https://doi.org/10.1016/j.isatra.2020.05.001

M. D. Dangut, I. K. Jennions, S. King and Z. Skaf, ‘Application of Deep Reinforcement Learning for Extremely Rare Failure Prediction in Aircraft Maintenance’. Mechanical Systems and Signal Processing, Vol. 171. 2022. Online: https://doi.org/10.1016/j.ymssp.2022.108873

S. K. Kolawole, F. O. Kolawole, A. B. O. Soboyejo and W. O. Soboyejo, ‘Modeling Studies of Corrosion Fatigue in a Low Carbon Steel’. Cogent Engineering, Vol. 6, no 1. 2019. Online: https://doi.org/10.1080/23311916.2019.1695999

A. Shard, R. Chand, S. Nauriyal, V. Gupta, M. P. Garg and N. K. Batra, ‘Fabrication and Analysis of Wear Properties of Polyetherimide Composite Reinforced with Carbon Fiber’. Journal of Failure Analysis and Prevention, Vol. 20, no 4. pp. 1388–1398. 2020. Online:

https://doi.org/10.1007/s11668-020-00943-5

M. fang Zuo, Y. li Chen, Z. li Mi, Y. de Wang and H. tao Jiang, ‘Effects of Cr Content on Corrosion Behaviour and Corrosion Products of Spring Steels’. Journal of Iron and Steel Research International, Vol. 26, no 9. pp. 1000–1010. 2019. Online: https://doi.org/10.1007/s42243-019-00250-w

D. Stadnicka, D. Arkhipov, O. Battaïa and R. M. C. Ratnayake, ‘Skills Management in the Optimization of Aircraft Maintenance Processes’. IFAC-PapersOnLine, Vol. 50, no 1. pp. 6912–6917. 2017. Online: https://doi.org/10.1016/j.ifacol.2017.08.1216

Y. Cheng, D. Song, C. Lu, J. Ma and L. Tao, ‘Performance Degradation Assessment for Aircraft Environmental Control System: A Method Based on Visual Cognition’. ISA Transactions, Vol. 113. pp. 64–80. 2021. Online: https://doi.org/10.1016/j.isatra.2020.04.002

S. Pant, Z. Sharif Khodaei and M. G. Droubi, ‘Monitoring Tasks in Aerospace’. In M.G.R. Sause and E. Jasiūnienė (eds), Structural Health Monitoring Damage Detection Systems for Aerospace. Springer Aerospace Technology. Cham: Springer. pp. 5–14. 2021. Online:

https://doi.org/10.1007/978-3-030-72192-3_2

M. Di Nardo, M. Gallab, M. Madonna and P. Addonizio, ‘A Mapping Analysis of Maintenance in Industry 4.0’. Journal of Applied Research and Technology, Vol. 6, no 3. pp. 204–217. 2021. Online: https://doi.org/10.22201/icat.24486736e.2021.19.6.1460

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