Third, the cruise portions of those flights occurring at night seem to show a lower second-to-second variability of workload than the corresponding parts of day-time flights even though the average level of workload is about the same.
Measuring crew workload in airline operations: cruise segment example
This is indicated by their relatively flat timeline curves compared with the “sawtooth” appearance of the timelines for the daytime flights. This suggests that workload variability measures may be a viable predictor of episodes of low crew alertness. Underload may represent the shedding of “discretionary workload” (e.g. loss non-flying tasks, no conversation) which pilots may choose not to generate. This can result in reduced activation levels and increased chances of alertness decrement.
2.4.4. RESULTS FROM AIRCREW LOGGING
Timewise logging of flight events to produce a narrative description of the flights allowed to regroup sequences where both crew-members PF and PNF would actively cooperate.
Two categories emerged:
. long regroupings or blocks where both pilots would execute strings of coordinated tasks linked with increased cross-monitoring (e.g. descent preparation),
. short regroupings or knots where both pilots would promptly act in concert with each other in short transactions (e.g. navigation monitoring after an ATC message).
. These operational stimuli cause a flight to be structured around a series of blocks and knots where vigilance and cross-monitoring can be expected accrued as compared to routine conditions. These formal meeting periods or points, distinguish themselves from periods, where crew-members’ interaction is more lax.
Overall sequence regroupings were found to be naturally related to operational requirements (ATC, FMS, fuel, navigation, systems), key events (weather, traffic, incidents/failures) and crew resource management behaviors (communications, decision-marking and planning, workload and vigilance management).
Comparing workload measurements with a subset of flights where alertness measures (EEG/EOG) were recorded allowed us to observe that:
. alertness decrements would tend to concur with flat workload curves and be located between blocks and knots discussed in the above, with little or no crew conversation,
. variable workload profiles would rarely concur with decreased alertness encounters.
The combined workload and reduced alertness data effectively suggest that periods of high and highly variable workload often seem to prevent or stop brief alertness decrements. Extended periods of low workload are often punctuated by low alertness episodes. Workload for both crewmembers appears to decrease during extended periods of low alertness associated with planned rest or napping. 中国航空网 www.aero.cn 航空翻译 www.aviation.cn 本文链接地址：Getting to grips with Fatigue & Alertness Management(13)
