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Ocena przepustowości systemu kontroli bezpieczeństwa cargo w porcie lotniczym w warunkach zakłóceń
Języki publikacji
Abstrakty
Cargo shipments are a growing part of the transport carried out by many air carriers. One of the critical elements in this area of activity is shipment security inspection, which is a mandatory part of the transportation process. This article aimed to study the inspection system's capacity under disruption conditions and determine its dependence on possible technical and organizational improvements. For this purpose, simulation modeling was applied using a microscale model of the cargo security inspection process realized in a colored, timed, stochastic Petri net. Bayesian networks representing the actual process were used to validate the model. As a result of the research, experiments showed that for Katowice Airport in Pyrzowice, more advanced technical solutions can increase capacity by up to 50%. On the other hand, introducing modifications to the procedure, involving at least two checks using specialized assistive devices, can reduce it by up to 40%. Relatively small changes in capacity are expected with changes in the training and experience of screening operators. Based on these results, it can be recommended that airport managers consider using technical solutions with the parameters analyzed in the article. In addition, it is necessary to maintain the level of training at least at the current level. At the same time, any changes in control procedures should be made prudently, only when necessary, due to the need to strengthen the effectiveness of controls during periods of increased terrorist threat.
Przesyłki cargo stanowią coraz większą część przewozów realizowanych przez wielu przewoźników lotniczych. Jednym z kluczowych elementów w tym obszarze działalności jest kontrola bezpieczeństwa przesyłek, która jest obowiązkowym elementem procesu przewozowego. Celem artykułu było zbadanie przepustowością systemu kontroli w warunkach zakłóceń, a także określenie jej zależności od możliwych ulepszeń technicznych i organizacyjnych. W tym celu zastosowano modelowanie symulacyjne z wykorzystaniem mikroskalowego modelu procesu kontroli bezpieczeństwa cargo zrealizowanego w postaci kolorowanej, czasowej, stochastycznej sieci Petriego. Do walidacji modelu wykorzystano sieci Bayesowskie reprezentujące rzeczywisty przebieg procesu. W wyniku przeprowadzonych eksperymentów badawczych wykazano dla lotniska Katowice w Pyrzowicach, że użycie bardziej zaawansowanych rozwiązań technicznych może zwiększyć przepustowość nawet o 50%. Z kolei wprowadzenie modyfikacji procedury, polegające na co najmniej dwukrotnej kontroli z wykorzystaniem specjalizowanych urządzeń wspomagających, może doprowadzić do jej zmniejszenia nawet o 40%. Stosunkowo niewielkie zmiany przepustowości są spodziewane w przypadku zmian w zakresie wyszkolenia i doświadczenia operatorów kontroli bezpieczeństwa. Na podstawie tych wyników można rekomendować, aby zarządzający portem lotniczym rozważyli użycie rozwiązań technicznych o parametrach, które były analizowane w artykule. Dodatkowo, konieczne jest utrzymanie poziomu wyszkolenia na co najmniej dotychczasowym poziomie, zaś wszelkie zmiany procedur kontroli należy wprowadzać rozważnie, tylko wówczas kiedy jest to niezbędne z powodu konieczności wzmocnienia skuteczności kontroli w okresach zwiększonego zagrożenia terrorystycznego.
Rocznik
Tom
Strony
101--122
Opis fizyczny
Bibliogr. 31 poz., rys., tab., wykr.
Twórcy
autor
- Warsaw University of Technology, Faculty of Transport, Warsaw, Poland
autor
- WSB University, Faculty of Transport and Informatics, Dąbrowa Górnicza, Poland
Bibliografia
- 1. AlKheder, S., A. Alomair and B. Aladwani (2019). Hold baggage security screening system in Kuwait International Airport using Arena software. Ain Shams Engineering Journal, 11(3), 687-696.
- 2. da Cunha, D., R. Macário and V. Reis (2017). Keeping cargo security costs down: A risk-based approach to air cargo airport security in small and medium airports. Journal of Air Transport Management, 61, 115-122.
- 3. Davidrajuh, R. and Lin, B., 2011. Exploring airport traffic capability using Petri net based model. Expert Systems with Applications, 38 (9), 10923–10931.
- 4. Domingues, S., R. Macário, T. Pauwels, E. van de Voorde, T.y Vanelslander and J. Vieira (2014). An assessment of the regulation of air cargo security in Europe: A Belgian case study. Journal of Air Transport Management, 34, 131-139.
- 5. European Commission, 2015. Commission Implementing Regulation (EU) 2015/1998 of 5 November 2015 laying down detailed measures for the implementation of the common asic standards on aviation security, Official Journal of the European Union, 58, L 299.
- 6. Florowski, A. and Skorupski, J., 2016. Method for evaluating the landing aircraft sequence under disturbed conditions with the use of Petri nets. The Aeronautical Journal, 120 (1227), 819–844.
- 7. Gillen, D. and W. Morrison (2015). Aviation security: Costing, pricing, finance and performance. Journal of Air Transport Management, 48, 1-12.
- 8. Huegli, D., S. Merks and A. Schwaninger (2020). Automation reliability, human–machine system performance, and operator compliance: A study with airport security screeners supported by automated explosives detection systems for cabin baggage screening, Applied Ergonomics, 86, 103094.
- 9. Kirschenbaum, A. (2013). The cost of airport security: The passenger dilemma. Journal of Air Transport Management, 30, 39-45.
- 10. Kovács, A., Németh, E., and Hangos, K.M., 2005. Modeling and Optimization of Runway Traffic Flow Using Coloured Petri Nets. International Conference on Control and Automation (ICCA), 881–886.
- 11. Knol, A., A. Sharpanskykh and S. Janssen (2019). Analyzing airport security checkpoint performance using cognitive agent models, Journal of Air Transport Management, 75, 39-50.
- 12. Lee, A.J. and H.J. Sheldon (2011). The impact of aviation checkpoint queues on optimizing security screening effectiveness. Reliability Engineering & System Safety, 96(8), 900-911.
- 13. Leone, K. and R. Liu (2005). The key design parameters of checked baggage security screening systems in airports, Journal of Air Transport Management, 11(2), 69-78.
- 14. Li, Y., X. Gao, Z. Xu and X. Zhou (2018). Network-based queuing model for simulating passenger throughput at an airport security checkpoint. Journal of Air Transport Management, 66, 13-24.
- 15. Michel, S., M. Mendes, J. de Ruiter, G. Koomen and A. Schwaninger (2014). Increasing X-ray image interpretation competency of cargo security screeners. International Journal of Industrial Ergonomics, 44(4), 551-560.
- 16. Mota, M.M., P. Scala, A. Murrieta-Mendoza, A. Orozco and A. Di Bernardi (2021). Analysis of security lines policies for improving capacity in airports: Mexico City Case, Case Studies on Transport Policy, 9(4), 1476-1494.
- 17. Oberheid, H. and Söffker, D., 2008. Cooperative Arrival Management in Air Traffic Control - A Coloured Petri Net Model of Sequence Planning. In: K. van Hee and R. Valk, eds. Applications and Theory of Petri Nets. Springer Berlin / Heidelberg, 348–367.
- 18. Price, J. and J. Forrest (2016). Air cargo security. In J. Price and J. Forrest (Eds.), Practical Aviation Security (Third Edition), pp. 437-459. Butterworth-Heinemann.
- 19. Ratzer Wells, L., Lassen, H.M., Laursen, M., Qvortrup, J.F., Stissing, M.S., Westergaard, M., Christensen, S., and Jensen, K., 2003. CPN Tools for Editing, Simulating, and Analysing Coloured Petri Nets. In: Proc. of 24th International Conference on Applications and Theory of Petri Nets (Petri Nets 2003), LNCS 2679. Berlin: Springer-Verlag, 450–462.
- 20. Skorupski, J., 2011. Method of analysis of the relation between serious incident and accident in air traffic. Advances in Safety, Reliability and Risk Management, 2 (11), 2393–2401.
- 21. Skorupski, J., 2015. The risk of an air accident as a result of a serious incident of the hybrid type. Reliability Engineering & System Safety, 140 (140), 37-52.
- 22. Skorupski, J. and P. Uchroński (2015). A fuzzy model for evaluating airport security screeners' work, Journal of Air Transport Management, 48, 42-51.
- 23. Skorupski, J. and P. Uchroński (2018). Evaluation of the effectiveness of an airport passenger and baggage security screening system. Journal of Air Transport Management, 66, 53-64.
- 24. Skorupski, J. and P. Uchroński (2020). Multi-criteria group decision-making approach to the modernization of hold baggage security screening system at an airport, Journal of Air Transport Management, 87, 101841.
- 25. Skorupski, J. and P. Uchroński (2023). Data-driven analysis of the airport cargo screening process, in Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023), Southampton, United Kingdom.
- 26. Skorupski, J., P. Uchroński and A. Łach (2018). A method of hold baggage security screening system throughput analysis with an application for a medium-sized airport. Transportation Research Part C: Emerging Technologies, 88, 52-73.
- 27. Smieszek, H. and Karl, C., 2013. An approach to cognitive simulation of air traffic controllers based on coloured petri nets. In: D. Soeffker and A. Kluge, eds. Kognitive Systeme. Duisburg: DuEPublico, Duisburg-Essen Publication.
- 28. Smiths Detection (2021). HI-SCAN 145180-2is, Technical Information, Smiths Detection Group, Wiesbaden, Germany.
- 29. Vidosavljević, A. and Toŝić, V., 2010. Modeling of turnaround process using petri nets. In: Proceedings (CD) of the 14th ATRS World Conference. Porto, Portugal, 1–13.
- 30. Werther, N., Moehlenbrink, C., and Rudolph, M., 2007. Colored Petri Net based formal airport control model for simulation and analysis of airport control processes. In: V.G. Duffy, ed. Proceedings of the 1st international conference on Digital human modeling (ICDHM'07). Berlin, Heidelberg: Springer-Verlag, 1027-1036.
- 31. Wong, S. and N. Brooks (2015). Evolving risk-based security: A review of current issues and emerging trends impacting security screening in the aviation industry. Journal of Air Transport Management, 48, 60-64.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-012e4e52-97c9-4921-9585-c8d8e380d9d8