Araştırma Makalesi
BibTex RIS Kaynak Göster

Havacılıkta Ekip Yorgunluk Yönetim Stratejilerinin Değerlendirilmesi: Bulanık bir DEMATEL Yaklaşımı

Yıl 2025, Cilt: 24 Sayı: 52, 111 - 145, 27.06.2025
https://doi.org/10.46928/iticusbe.1579872

Öz

Mürettebat yorgunluğu havacılıkta hem güvenliği hem de operasyonel performansı etkileyen önemli bir sorundur. Bu çalışma, 12 havacılık profesyonelinden alınan uzman girdilerine dayanarak mürettebat yorgunluğunu yönetmeye yönelik stratejileri değerlendirmek ve önceliklendirmek için Bulanık DEMATEL yöntemini uyguluyor. Analiz, dinlenme programları ve uçuş süresi kontrolü gibi diğer önemli unsurlar üzerinde doğrudan etkisi olan iş yükü yönetimini en etkili faktör olarak tanımlıyor. Gerçek zamanlı izleme teknolojileri de, mürettebat programlarını ayarlamak ve riskleri gerçek zamanlı olarak azaltmak için eyleme dönüştürülebilir veriler sağlayarak daha etkili yorgunluk yönetimini mümkün kılan kritik bir araç olarak ortaya çıktı. Özellikle uzun mesafeli operasyonlarda uçuş süresinin kümülatif yorgunluğa önemli bir katkı sağladığı vurgulandı. Bu çalışmanın yeniliği, havacılık yönetiminde karar alma için yapılandırılmış, veriye dayalı bir çerçeve sağlayarak, yorgunluk faktörleri arasındaki karmaşık karşılıklı bağımlılıkları haritalamak için Bulanık DEMATEL'in kullanılmasında yatmaktadır. Bulgular, yorgunluğun en etkili nedenlerini doğrudan hedef alan stratejilere öncelik vererek mürettebat performansını ve güvenliğini artırmaya yönelik pratik bilgiler sunuyor. Bu bilgiler, özellikle gerçek zamanlı izleme ve iş yükü ayarlamalarının uygulanması yoluyla yorgunluk riski yönetim sistemlerini geliştirmek isteyen havacılık şirketleri için değerlidir. Gelecekteki araştırmalar, bu bulguları daha fazla doğrulamak için gerçek operasyonlardan elde edilen niceliksel verileri birleştirmeyi keşfetmeli ve yorgunluk yönetimi için ortaya çıkan karar verme modellerini incelemelidir.

Kaynakça

  • Bendak, S., & Rashid, H. S. (2020). Fatigue in aviation: A systematic review of the literature. International Journal of Industrial Ergonomics, 76, 102928.
  • Bérastégui, P., & Nyssen, A. S. (2022). Fatigue Risk Management System as a Practical Approach to Improve Resilience in 24/7 Operations. In Advancing resilient performance (pp. 27-40). Springer.
  • Bongo, M. F., & Seva, R. R. (2023). Evaluating the performance-shaping factors of air traffic controllers using fuzzy DEMATEL and fuzzy BWM approach. Aerospace, 10(3), 252.
  • Bourgeois-Bougrine, S. (2020). The illusion of aircrews' fatigue risk control. Transportation Research Interdisciplinary Perspectives, 4, 100104.
  • Bourgeois-Bougrine, S., Gabon, P., Mollard, R., Coblentz, A., & Speyer, J. J. (2018). Fatigue in aircrew from shorthaul flights in civil aviation: The effects of work schedules. In Human factors and aerospace safety (pp. 177-187). Routledge.
  • Cabon, P., Deharvengt, S., Grau, J. Y., Maille, N., Berechet, I., & Mollard, R. (2012). Research and guidelines for implementing Fatigue Risk Management Systems for the French regional airlines. Accident Analysis & Prevention, 45, 41-44.
  • Chang, B., Chang, C. W., & Wu, C. H. (2011). Fuzzy DEMATEL method for developing supplier selection criteria. Expert Systems with Applications, 38(3), 1850-1858.
  • Dyall, M., Peachey, K. L., & Lower, T. (2025). Fatigue-related incidents and prevention strategies in Australian grain farming: A mixed-methods feasibility study. Safety Science, 184, 106773.
  • Efthymiou, M., Whiston, S., O'Connell, J. F., & Brown, G. D. (2021). Flight crew evaluation of the flight time limitations regulation. Case Studies on Transport Policy, 9(1), 280-290.
  • Göker, Z. (2018). Fatigue in the aviation: An overview of the measurements and countermeasures. Journal of Aviation, 2(2), 185-194.
  • Huang, H. C., Huang, C. N., Lo, H. W., & Thai, T. M. (2023). Exploring the mutual influence relationships of international airport resilience factors from the perspective of aviation safety: Using fermatean fuzzy DEMATEL approach. Axioms, 12(11), 1009.
  • Kandera, B., Škultéty, F., & Mesárošová, K. (2019). Consequences of flight crew fatigue on the safety of civil aviation. Transportation Research Procedia, 43, 278-289.
  • Li, Y., He, J., Cao, S., Zheng, J., Dou, Y., Liu, C., & Liu, X. (2023). Assessing Flight Crew Fatigue under Extra Augmented Crew Schedule Using a Multimodality Approach. Aerospace, 10(11), 933.
  • Maisey, G., Cattani, M., Devine, A., & Dunican, I. C. (2022). Fatigue risk management systems diagnostic tool: validation of an organizational assessment tool for shift work organizations. Safety and Health at Work, 13(4), 408-414.
  • Mallis, M., Banks, S., Dorrian, J., & Dinges, D. F. (2023). Aircrew fatigue, sleep need, and circadian rhythmicity. In Human Factors in Aviation and Aerospace (pp. 309-339). Academic Press.
  • Mannawaduge, C. D., Pignata, S., Banks, S., & Dorrian, J. (2024). Evaluating fatigue management regulations for flight crew in Australia using a new Fatigue Regulation Evaluation Framework (FREF). Transport Policy, 151, 75-84.
  • Mizrak, F., & Akkartal, G. R. (2024). Prioritizing cybersecurity initiatives in aviation: A dematel-QSFS methodology. Heliyon, 10(16).
  • Quental, N., Rocha, J., Silva, J., Menezes, L., & Santos, J. (2021). The impact of cognitive fatigue on airline pilots performance. Journal of Airline and Airport Management, 11(1), 16-33.
  • Rodrigues, T. E., Fischer, F. M., Helene, O., Antunes, E., Furlan, E., Morteo, E., ... & Helene, A. F. (2023). Modelling the root causes of fatigue and associated risk factors in the Brazilian regular aviation industry. Safety science, 157, 105905.
  • Signal, T. L., van den Berg, M. J., Zaslona, J. L., Wu, L., Hughes, M., Johnston, B., ... & Glover, M. (2024). Managing the challenge of fatigue for pilots operating ultra-long range flights. Frontiers in Environmental Health, 2, 1329203.
  • Sprajcer, M., Thomas, M. J., Sargent, C., Crowther, M. E., Boivin, D. B., Wong, I. S., ... & Dawson, D. (2022). How effective are fatigue risk management systems (FRMS)? A review. Accident Analysis & Prevention, 165, 106398.
  • Sun, J., Sun, R., Li, J., Wang, P., & Zhang, N. (2022). Flight crew fatigue risk assessment for international flights under the COVID-19 outbreak response exemption policy. BMC Public Health, 22(1), 1843.
  • Sun, J. Y., Liao, Y., Lu, F., Sun, R. S., & Jia, H. B. (2023). Assessment of pilot fatigue risk on international flights under the prevention and control policy of the Chinese civil aviation industry during the COVID-19. Journal of Air Transport Management, 112, 102466.
  • Xiao, X., Li, L., Zeng, L., Liu, X., Wei, P., & Xue, K. (2024, February). Fatigue risk management based pilot sleep monitoring validation experiment. In Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023): Vol. 13064. (pp. 370-376). SPIE.
  • Wilson, M. K., Strickland, L., Ballard, T., & Griffin, M. A. (2024). The next generation of fatigue prediction models: evaluating current trends in biomathematical modelling. Theoretical Issues in Ergonomics Science, 25(1), 21-43.
  • You, Y., Cai, B., Pham, D. T., Liu, Y., & Ji, Z. (2025). A human digital twin approach for fatigue-aware task planning in human-robot collaborative assembly. Computers & Industrial Engineering, 200, 110774.

Evaluating Crew Fatigue Management Strategies in Aviation: A Fuzzy DEMATEL Approach

Yıl 2025, Cilt: 24 Sayı: 52, 111 - 145, 27.06.2025
https://doi.org/10.46928/iticusbe.1579872

Öz

Crew fatigue is a significant issue in aviation, affecting both safety and operational performance. This study applies the Fuzzy DEMATEL method to evaluate and prioritize strategies for managing crew fatigue, based on expert input from 12 aviation professionals. The analysis identifies workload management as the most influential factor, with direct impacts on other key elements such as rest schedules and flight duration control. Real-time monitoring technologies also emerged as a critical tool, enabling more effective fatigue management by providing actionable data for adjusting crew schedules and mitigating risks in real-time. Flight duration, particularly on long-haul operations, was highlighted as a major contributor to cumulative fatigue. The novelty of this study lies in its use of Fuzzy DEMATEL to map the complex interdependencies between fatigue factors, providing a structured, data-driven framework for decision-making in aviation management. The findings offer practical insights for improving crew performance and safety by prioritizing strategies that directly target the most influential causes of fatigue. These insights are valuable for aviation companies seeking to enhance fatigue risk management systems, particularly through the implementation of real-time monitoring and workload adjustments. Future research should explore integrating quantitative data from actual operations to further validate these findings and examine emerging decision-making models for fatigue management.

Kaynakça

  • Bendak, S., & Rashid, H. S. (2020). Fatigue in aviation: A systematic review of the literature. International Journal of Industrial Ergonomics, 76, 102928.
  • Bérastégui, P., & Nyssen, A. S. (2022). Fatigue Risk Management System as a Practical Approach to Improve Resilience in 24/7 Operations. In Advancing resilient performance (pp. 27-40). Springer.
  • Bongo, M. F., & Seva, R. R. (2023). Evaluating the performance-shaping factors of air traffic controllers using fuzzy DEMATEL and fuzzy BWM approach. Aerospace, 10(3), 252.
  • Bourgeois-Bougrine, S. (2020). The illusion of aircrews' fatigue risk control. Transportation Research Interdisciplinary Perspectives, 4, 100104.
  • Bourgeois-Bougrine, S., Gabon, P., Mollard, R., Coblentz, A., & Speyer, J. J. (2018). Fatigue in aircrew from shorthaul flights in civil aviation: The effects of work schedules. In Human factors and aerospace safety (pp. 177-187). Routledge.
  • Cabon, P., Deharvengt, S., Grau, J. Y., Maille, N., Berechet, I., & Mollard, R. (2012). Research and guidelines for implementing Fatigue Risk Management Systems for the French regional airlines. Accident Analysis & Prevention, 45, 41-44.
  • Chang, B., Chang, C. W., & Wu, C. H. (2011). Fuzzy DEMATEL method for developing supplier selection criteria. Expert Systems with Applications, 38(3), 1850-1858.
  • Dyall, M., Peachey, K. L., & Lower, T. (2025). Fatigue-related incidents and prevention strategies in Australian grain farming: A mixed-methods feasibility study. Safety Science, 184, 106773.
  • Efthymiou, M., Whiston, S., O'Connell, J. F., & Brown, G. D. (2021). Flight crew evaluation of the flight time limitations regulation. Case Studies on Transport Policy, 9(1), 280-290.
  • Göker, Z. (2018). Fatigue in the aviation: An overview of the measurements and countermeasures. Journal of Aviation, 2(2), 185-194.
  • Huang, H. C., Huang, C. N., Lo, H. W., & Thai, T. M. (2023). Exploring the mutual influence relationships of international airport resilience factors from the perspective of aviation safety: Using fermatean fuzzy DEMATEL approach. Axioms, 12(11), 1009.
  • Kandera, B., Škultéty, F., & Mesárošová, K. (2019). Consequences of flight crew fatigue on the safety of civil aviation. Transportation Research Procedia, 43, 278-289.
  • Li, Y., He, J., Cao, S., Zheng, J., Dou, Y., Liu, C., & Liu, X. (2023). Assessing Flight Crew Fatigue under Extra Augmented Crew Schedule Using a Multimodality Approach. Aerospace, 10(11), 933.
  • Maisey, G., Cattani, M., Devine, A., & Dunican, I. C. (2022). Fatigue risk management systems diagnostic tool: validation of an organizational assessment tool for shift work organizations. Safety and Health at Work, 13(4), 408-414.
  • Mallis, M., Banks, S., Dorrian, J., & Dinges, D. F. (2023). Aircrew fatigue, sleep need, and circadian rhythmicity. In Human Factors in Aviation and Aerospace (pp. 309-339). Academic Press.
  • Mannawaduge, C. D., Pignata, S., Banks, S., & Dorrian, J. (2024). Evaluating fatigue management regulations for flight crew in Australia using a new Fatigue Regulation Evaluation Framework (FREF). Transport Policy, 151, 75-84.
  • Mizrak, F., & Akkartal, G. R. (2024). Prioritizing cybersecurity initiatives in aviation: A dematel-QSFS methodology. Heliyon, 10(16).
  • Quental, N., Rocha, J., Silva, J., Menezes, L., & Santos, J. (2021). The impact of cognitive fatigue on airline pilots performance. Journal of Airline and Airport Management, 11(1), 16-33.
  • Rodrigues, T. E., Fischer, F. M., Helene, O., Antunes, E., Furlan, E., Morteo, E., ... & Helene, A. F. (2023). Modelling the root causes of fatigue and associated risk factors in the Brazilian regular aviation industry. Safety science, 157, 105905.
  • Signal, T. L., van den Berg, M. J., Zaslona, J. L., Wu, L., Hughes, M., Johnston, B., ... & Glover, M. (2024). Managing the challenge of fatigue for pilots operating ultra-long range flights. Frontiers in Environmental Health, 2, 1329203.
  • Sprajcer, M., Thomas, M. J., Sargent, C., Crowther, M. E., Boivin, D. B., Wong, I. S., ... & Dawson, D. (2022). How effective are fatigue risk management systems (FRMS)? A review. Accident Analysis & Prevention, 165, 106398.
  • Sun, J., Sun, R., Li, J., Wang, P., & Zhang, N. (2022). Flight crew fatigue risk assessment for international flights under the COVID-19 outbreak response exemption policy. BMC Public Health, 22(1), 1843.
  • Sun, J. Y., Liao, Y., Lu, F., Sun, R. S., & Jia, H. B. (2023). Assessment of pilot fatigue risk on international flights under the prevention and control policy of the Chinese civil aviation industry during the COVID-19. Journal of Air Transport Management, 112, 102466.
  • Xiao, X., Li, L., Zeng, L., Liu, X., Wei, P., & Xue, K. (2024, February). Fatigue risk management based pilot sleep monitoring validation experiment. In Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023): Vol. 13064. (pp. 370-376). SPIE.
  • Wilson, M. K., Strickland, L., Ballard, T., & Griffin, M. A. (2024). The next generation of fatigue prediction models: evaluating current trends in biomathematical modelling. Theoretical Issues in Ergonomics Science, 25(1), 21-43.
  • You, Y., Cai, B., Pham, D. T., Liu, Y., & Ji, Z. (2025). A human digital twin approach for fatigue-aware task planning in human-robot collaborative assembly. Computers & Industrial Engineering, 200, 110774.
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Hava Taşımacılığı ve Nakliye Hizmetleri
Bölüm Araştırma Makalesi
Yazarlar

Tuncel Öz 0000-0001-6603-0841

Yayımlanma Tarihi 27 Haziran 2025
Gönderilme Tarihi 5 Kasım 2024
Kabul Tarihi 22 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 24 Sayı: 52

Kaynak Göster

APA Öz, T. (2025). Evaluating Crew Fatigue Management Strategies in Aviation: A Fuzzy DEMATEL Approach. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 24(52), 111-145. https://doi.org/10.46928/iticusbe.1579872