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SCIENCE IN AN OPERATIONAL SETTING. Philippa Gander Sleep/Wake Research Centre, Massey University Jim Mangie Delta Air Lines. Outline. What to measure When to measure Interpreting the data Safety Performance Indicators Conclusions.

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Science in an operational setting

SCIENCE IN AN OPERATIONAL SETTING

Philippa Gander

Sleep/Wake Research Centre, Massey University

Jim Mangie

Delta Air Lines


Outline
Outline

  • What to measure

  • When to measure

  • Interpreting the data

    • Safety Performance Indicators

  • Conclusions


What to measure in frms operational data crew fatigue measures
What to Measure in FRMSoperational data / crew fatigue measures

Operators need to be able to:

  • Identify (monitor) level of fatigue hazard(s)

  • Assess fatigue-related safety risk

    • Probability/severity

    • ICAO tolerability matrix

  • Define and monitor fatigue safety performance indicators

  • Investigate role of fatigue in incidents/accidents


What to measure crew fatigue
What to Measure: Crew Fatigue

ICAO definition of fatigue:

A physiological state of reduced mental or physical performance capability resulting from sleep loss or extended wakefulness,circadian phase, or workload (mental and/or physical activity) that can impair a crew member’s alertness and ability to safely operate an aircraft or perform safety related duties.

  • Functional status (subjective ,objective)

  • Sleep history

  • Circadian phase

  • Workload


Samn perelli fatigue ratings
Samn-Perelli Fatigue Ratings

1=fully alert, wide awake

2=very lively, responsive, but not at peak

3=OK, somewhat refreshed

4=a little tired, less than fresh

5=moderately tired, let down

6=extremely tired, difficult to concentrate

7=completely exhausted, unable to function effectively


Karolinska sleepiness ratings
Karolinska Sleepiness Ratings

1= extremely alert

2=

3= alert

4=

5= neither sleepy nor alert

6=

7= sleepy, but no difficulty remaining awake

8=

9= extremely sleepy, fighting sleep


Pvt performance reaction speed
PVT Performance (Reaction Speed)

Press this if you

are left-handed

Press this if you

are right-handed


Sleep actigraphy and diaries
Sleep: Actigraphy and Diaries


When to measure crew fatigue
When to Measure Crew Fatigue

  • Monitoring for FRM Processes

    • In response to a series of fatigue reports

      • to identify extent and severity of hazard

    • In response to an incident

    • SPIs to evaluate effectiveness of fatigue mitigations and controls

    • Validation of a new route

  • Monitoring for FRMS Assurance Processes

    • SPIs set in FRMS Policy objectives

    • SPIs for regulatory audit

      Crew fatigue measures may not always be needed


Safety performance indicators spis
Safety Performance Indicators(SPIs)

5 FRMS Components

3. Risk Management Processes

1. Policy

Fatigue Safety

Action Group

4.Safety Assurance Processes

SMS

5. Promotion Processes

2. Documentation


Comparing fatigue on ulr and lr flights

Safety Performance Indicators: Example

Comparing fatigue on ULR and LR flights


Fatigue status at start of duty spi sleep in the last 24 hrs
Fatigue Status at Start of DutySPI – sleep in the last 24 hrs


Fatigue status at start of duty spi mean pvt reaction speed early in flight
Fatigue Status at Start of DutySPI – mean PVT reaction speed early in flight


Fatigue status at top of climb spi median total in flight sleep
Fatigue Status at Top of ClimbSPI – median total in-flight sleep


Fatigue status at top of climb spi mean pvt reaction speed late in flight
Fatigue Status at Top of ClimbSPI – mean PVT reaction speed late in flight


Fatigue status at top of climb spi crew with kss 7
Fatigue Status at Top of ClimbSPI – % crew with KSS ≥ 7


Operational spis examples
Operational SPIs: Examples

  • Track data on number of :

    • exceedances of planned crew duty day (e.g. > 14 hrs)

    • flight duty periods ending > 30 mins later than scheduled

    • flight duty periods starting / ending within window of circadian low (WOCL)

    • reserve crew call-outs (on particular flights, at a particular crew base, etc)

      Monitoring of FRM processes

      Monitoring of FRMS safety assurance processes


Conclusions
Conclusions

  • Challenge

    • Developing in-house expertise versus using consultants ($$)

  • Data sharing

    • Operators don’t have to reinvent the wheel

    • Rich data source for improving fatigue science

  • Needs

    • Paradigms for data sharing

    • Better indicators of fatigue-related performance impairment

    • Better fatigue measurement technologies

    • Better fatigue risk assessment (safety consequences of being fatigued in a given context)

    • Better fatigue risk controls and mitigations

      Cooperation is the key


Acknowledgements
Acknowledgements

  • Dr Jarnail Singh, Singapore CAA

  • Participants in B-777 study

  • Scientific Steering Committee, FAA 3-airline study


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