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From the Guantanamo Bay Crash to Objective Fatigue Hazard Identification in Air Transport
- Maria Papanikou ,
- Christos A. Frantzidis ,
- Frenchez Pietersz ,
- Anna Nikolaidou ,
- Christina S. Plomariti - Aristotle University of Thessaloniki, Greece ,
- Maria Karagianni - Aristotle University of Thessaloniki, Greece ,
- Vasilis D. Nigdelis - Aristotle University of Thessaloniki, Greece ,
- Aliki Karkala ,
- Christiane M. Nday - Aristotle University of Thessaloniki, Greece ,
- Georgios Ntakakis - Aristotle University of Thessaloniki, Greece ,
- Agisilaos Krachtis - Aristotle University of Thessaloniki, Greece ,
- Odysseas Papaefthymiou ,
- Panagiotis D. Bamidis ,
- Chrysoula Kourtidou-Papadeli
ISSN: 1946-3855, e-ISSN: 1946-3901
Published October 19, 2020 by SAE International in United States
Citation: Papanikou, M., Frantzidis, C., Pietersz, F., Nikolaidou, A. et al., "From the Guantanamo Bay Crash to Objective Fatigue Hazard Identification in Air Transport," SAE Int. J. Aerosp. 13(2):225-242, 2020, https://doi.org/10.4271/01-13-02-0017.
Sleep quality and maintenance of the optimal cognitive functioning is of crucial importance for aviation safety. Fatigue Risk Management (FRM) enables the operator to achieve the objectives set in their safety and FRM policies. As in any other risk management cycle, the FRM value can be realized by deploying suitable tools that aid robust decision-making. For the purposes of our article, we focus on fatigue hazard identification to explore the possible developments forward through the enhancement of objective tools in air transport operators. To this end we compare subjective and objective tools that could be employed by an FRM system. Specifically, we focus on an exploratory survey on 120 pilots and the analysis of 250 fatigue reports that are compared with objective fatigue assessment based on the polysomnographic (PSG) and neurocognitive assessment of three experimental cases. We highlight the significance of predictive objective tools that should be deployed by contemporary FRM models. We also report the need for utilization of scientific-based tools for predictive FRM, in which objective sleep quality and neurocognitive assessment should be the core aspect. We note the period of restructuring ahead as an opportunity for operators to rethink and restructure their FRM.