Abstract

Airports are major economic hubs that have exhibited substantial growth and profits in recent years. Although airport infrastructure represents an important part in the economy of cities, studies have shown that many incidents that have led to flight disruptions have often occurred in airport buildings. Also, maintenance cost of airport buildings has increased significantly necessitating a call from professionals to investigate efficient methods of curbing the same. Hence, cost reduction is possible by innovating methods thanks to predictive maintenance techniques, which are based on artificial intelligence. However, working on the innovation of techniques that modernize maintenance in airport buildings is very hard due to the many types of cause incidents that exist. In fact, incidents can be caused due to different reasons (Structural, Electrical, Hydraulic, Computing, Unknown, etc.) This paper tackles this challenge by investigating and identifying the most frequent damages and their origins in airport infrastructure. The result showed that cracks are the most frequent type of damages and that wear is the most frequent origin of incidents in airport infrastructure. These findings help in better understanding the problem and serve as the point of departure for researchers who are interested in solving it.

References

Adam, A. (2020). Sample Size Determination in Survey Research. Journal of Scientific Research and Reports, 26, 90–97. https://doi.org/10.9734/JSRR/2020/v26i530263

Agarwal, S., Kant, R., & Shankar, R. (2019). Humanitarian supply chain management frameworks.

Benchmarking: An International Journal, 26(6), 1749–1780. https://doi.org/10.1108/BIJ-08-2018-0245

Airbus. (2020). A Statistical Analysis of Commercial Aviation Accidents 1958-2020.

Anil Kapur. (1995). Airport Infrastructure - The Emerging role of the private sector.

https://pdfslide.net/documents/airport-infrastructure-the-emerging-role-of-the-privatesector.html?page=47

Bouwer et al. (2021). Back to the future? Airline sector poised for change post-COVID-19.

Burbidge, R. (2016). Adapting European Airports to a Changing Climate. Transportation Research Procedia,

14, 14–23. https://doi.org/10.1016/j.trpro.2016.05.036

Coibion, O., Gorodnichenko, Y., & Weber, M. (2020). The Cost of the COVID-19 Crisis: Lockdowns,

Macroeconomic Expectations, and Consumer Spending. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3593469

Dai, C. (2020). The Disruptive Effects of COVID-19 on the Aviation Industry, Food Industry, and E-commerce

Industry. https://doi.org/10.2991/aebmr.k.201128.012

Flores-Colen, I., de Brito, J., & de Freitas, V. P. (2010). Discussion of Criteria for Prioritization of Predictive

Maintenance of Building Façades: Survey of 30 Experts. Journal of Performance of Constructed

Facilities, 24, 337–344.

ICAO. (2021). Effects of Novel Coronavirus (COVID-19) on Civil Aviation: Economic Impact Analysis.

Bouwer et al. (2022). Taking stock of the pandemic’s impact on global aviation.

https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/taking-stockof-

the-pandemics-impact-on-global-aviation

Kawashima, K., Kanai, S., & Date, H. (2014). As-built modeling of piping system from terrestrial laserscanned point clouds using normal-based region growing. Journal of Computational Design and

Engineering, 1(1), 13–26. https://doi.org/https://doi.org/10.7315/JCDE.2014.002

Kovacs, G., Moshtari, M., Kachali, H., & Polsa, P. (2019). Research methods in humanitarian logistics.

Journal of Humanitarian Logistics and Supply Chain Management, 9(3), 325–331.

https://doi.org/10.1108/JHLSCM-12-2019-082

Shen, X., Cai, C., Yang, Q., Anagnostou, E. N., & Li, H. (2021). The US COVID-19 pandemic in the flood

season. The Science of the Total Environment, 755(Pt 2), 142634.

https://doi.org/10.1016/j.scitotenv.2020.142634

Xue, D., Liu, Z., Wang, B., & Yang, J. (2021). Impacts of COVID-19 on aircraft usage and fuel consumption: A

case study on four Chinese international airports. Journal of Air Transport Management, 95, 102106.

https://doi.org/10.1016/j.jairtraman.2021.102106