Safety is the backbone of the airline industry, and a lot of effort and investment is made to ensure that all flight processes are properly executed. Pilot performance is one of the most important elements of flight safety. As such, fatigue, which has been found to have a significant adverse impact on pilot performance, is one of the industry’s top concerns.
According to the International Civil Aviation Organization, fatigue is a state of reduced mental and physical performance capability resulting from sleep loss, extended wakefulness, circadian disruption, or workload that impairs the pilot’s alertness flight-deck performance.
Prescriptive time-limits regulating pilots’ working and flying hours do not eliminate the risk of the creation of fatiguing rosters by airlines. Therefore, the FAA now requires operators to have fatigue management plans on top of the prescriptive rules, as part of their safety management system. For one, airlines should avoid assigning potentially fatiguing pilots’ rosters, and pilots should not fly if they are experiencing an unsafe level of fatigue.
To respond to these new regulations, airlines are turning to software packages that claim to determine, with scientific accuracy, how fatiguing a roster will be. Let’s look at how these systems work and whether they can really predict pilot fatigue during a given roster.
The commercial systems in the market are integrated with airlines’ existing rostering systems to predict fatigue levels when generating new crew schedules. Most of the systems are based on the Two-Process Model, a scientific model of sleep regulation that uses an individual’s sleep-wake history and circadian rhythm to estimate their fatigue levels.
Key pieces of information from the pilots’ roster, such as work duties, the departure and arrival time, and time zone shifts, are added to the system. The system then makes predictions about when and for how long the pilot flying is likely to sleep and estimates likely fatigue levels based on the planned roster’s estimated impact on alertness.
Using software packages to inform pilot rosters provides a proactive, rather than a reactive, approach to fatigue monitoring. These systems can also be used in a retrospective analysis of fatigue-related factors that might have contributed to an error or a safety-related incident.
Different airlines conduct their own ongoing testing and validation of the commercial systems they use. They also make personalized adjustments to them to reflect their flight schedules. Since the commercial providers are usually reluctant to share the nature of these adjustments, or the methods and data they have used to calculate them, it is difficult for the systems to be independently reviewed and checked for accuracy.
Secondly, there are concerns on the level of understanding of how fatigue prediction models work, especially when airlines use them as the sole indicator of pilot fatigue and ignore individual self-evaluation reports concerns. Pilots should make their own go/no-go decisions as they are the best judges of their personal fatigue levels.
It is important to note that these models’ predictions are based on what the average person is most likely to experience under certain circumstances. They can, therefore, not be generalized to everyone since people experience fatigue differently. Similarly, there are other factors such as medical issues, and genetics may also contribute to fatigue.
They should be used as indicators of possible fatigue levels in an airline’s schedule or given roster, but not equal to a pilot’s personal judgment on their level of fatigue.
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