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Copyright 2008, IBR Copyright 2010, IBR SAFTE/FAST Evidence-based Aviation Fatigue Risk Management Steven R. Hursh, Ph.D. President, IBR and Professor,

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Presentation on theme: "Copyright 2008, IBR Copyright 2010, IBR SAFTE/FAST Evidence-based Aviation Fatigue Risk Management Steven R. Hursh, Ph.D. President, IBR and Professor,"— Presentation transcript:

1 Copyright 2008, IBR Copyright 2010, IBR SAFTE/FAST Evidence-based Aviation Fatigue Risk Management Steven R. Hursh, Ph.D. President, IBR and Professor, Johns Hopkins University School of Medicine September 1, 2011

2 Copyright 2008, IBR Major Fatigue Factors ●Time of Day: between midnight and 0600 hrs. ●Recent Sleep: less than eight hours in last 24 hrs. ●Continuous Hours Awake: more than 17 hours since last major sleep period. ●Cumulative Sleep Debt: more than eight hours accumulation since last full night of sleep (includes disrupted sleep). ●Time on Task/Work Load: continuous work time without a break or intensity of work demands.

3 Copyright 2008, IBR An Objective Fatigue Metric ●No Blood Test for fatigue, yet ●The conditions that lead to fatigue are well known. ● A fatigue model simulates the specific conditions and determines if fatigue could be present. ●The model can estimate the level of degradation in performance and provide an estimate of schedule induced fatigue risk.

4 Copyright 2008, IBR SAFTE ●The Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) Model is based on 12 years of fatigue modeling experience. ●Validated against laboratory and simulator measures of fatigue. ●Validated and calibrated to predict accident risk by the Department of Transportation. ●Peer reviewed and found to have the least error of any available fatigue model. ●Accepted by the US DOD (Air Force, Army, Navy, Marines) as the common warfighter fatigue model.

5 Copyright 2008, IBR SAFTE Model Components

6 Copyright 2008, IBR Least Error for Conditions of Sleep Restriction 2002 Seattle Fatigue & Performance Modeling Workshop, of all models tested against laboratory measurements: ●SAFTE had least error predicting objective vigilance performance. ●SAFTE had least error predicting subjective ratings of fatigue. ●Advances since 2002 have further validated the sleep and performance assumptions and prediction of accident risk and severity. 6 Von Dongen, Aviation, Space, and Environmental Medicine, March, 2004, vol. 75, no. 3, section II

7 Copyright 2008, IBR Accuracy of Predicting Sleep Pattern and Duration 7 MeasureSignalman Maintenance of Way Dispatchers (less night workers) Train and Engine Mean Agreement 92% 90%88% Daily Sleep (Est.- Log) -24 min-21 min-3 min- 10.8 min

8 Copyright 2008, IBR Economic Risk and Effectiveness No FatigueHigh Fatigue Railroad Accident Relative Risk

9 Copyright 2008, IBR SAFTE/FASTSAFTE/FAST Validated Fatigue Modeling Tools Fatigue Science has the exclusive license from the US Army to commercialize SAFTE model.

10 Copyright 2008, IBR Practical Software for Implementation ●Fatigue Avoidance Scheduling Tool (FAST)  Fatigue assessment tool using the SAFTE model  Developed for the US Air Force and the US Army  DOT / FRA sponsored work has lead to enhancements for transportation applications ●FAST Features  Sleep estimation algorithm  Graphical analysis tools  Dashboard of fatigue factors  Data based of all effectiveness scores

11 Copyright 2008, IBR FAST Aviation Sleep Estimation ●Accurate estimation of sleep is critical:  Measure: actigraphy or log books  Estimate: algorithm to simulate sleep behavior ●Aviation specific estimates that can be refined with actrigraphic measurement. ●Considers time zone changes and is valid for any city pair.

12 Copyright 2008, IBR Sleep Estimator Tailored to Aviation Environment:

13 Copyright 2008, IBR FAST Aviation Specific AutoSleep ●Mimics typical sleep patterns ●Tailored to workgroup and schedule demands ●Considers total duty period and commuting ●Naps prior to anticipated late starts ●Considers time zones ●Slits sleep when appropriate ●Automatically inserts in-flight sleep for augmented crews. User defined parameters:  amount of augmentation and  quality of sleep environment ●Adjustable settings can be saved to file 13

14 Copyright 2008, IBR Fatigue Risk Management System FRM Steering Committee Involves all stakeholders at each stage: management, labor, aided by science Enablers Employee training Medical screening Economic analysis Technology aids Measure Define the situation Schedule evaluation Actigraph recordings Model & Analyze Model the fatigue problem Analyze sources and Fatigue factors Manage Collaborate for solutions Obtain commitment to solve problem Modify/Mitigate Shared Responsibility Operating practices Labor agreements Individual “life style” Monitor Assess operational indicators Individual self-evaluation Feedback to process Continuous Improvement Process SAFTE/FAST

15 Copyright 2008, IBR FAST Aviation Fatigue Assessment Process Airline Specific Schedule Database XML format City-pairs/Trips or 30-day Bids Airline Specific Schedule Database XML format City-pairs/Trips or 30-day Bids FAST Aviation Modeler FAST Aviation Modeler Aviation AutoSleep SAFTE Model Output results to folder Links to Manager FAST Aviation Manager Sorts by Criterion Displays results Links to Analyzer Fleet level reports FAST Analyzer Individual Schedules FAST Analyzer Individual Schedules Examine schedules Effectiveness Graph Fatigue Factors “What-If” Drills Individual reports Modular Process for Speed and Flexibility Standard FAST schedule is created by FAST Aviation Modeler Translation Tools available for any scheduling system

16 Copyright 2008, IBR FAST Aviation Modeler Model the schedules: 1.Set AutoSleep parameters if necessary 2.Name the Output folder a unique name 3.Choose either a City Pairs file or a Bid Schedules file for modeling Airline Schedule Database Processed Schedules Modeling Results

17 Copyright 2008, IBR FAST Aviation Manager Sort by:  Flight Time Below Criterion Level (FTBCL)  Critical TBCL (30 min associated with takeoff/landing)  Average Effectiveness  Minimum Effectiveness overall  Minimum Effectiveness during critical periods  Maximum Workload (high workload score in schedule)  Median Workload (central score across schedule) Save table to text file Click on any line in Aviation Manager and schedule opens in FAST for detailed analysis.

18 Copyright 2008, IBR If fatigue is present, what do you do about it? ●Modeling tools must do more than give you a fatigue score:  It must estimate fatigue risk  It must show detail of each schedule  It must calculate fatigue factors  It must suggest conditions that lead to fatigue so mitigations can be implemented by an FRMS 18

19 Copyright 2008, IBR Detailed Analysis Results ●Creates detailed database that shows:  All duty periods and estimated sleep intervals  Effectiveness in each half hour of each duty period  Effectiveness at each half hour of the clock  Distribution of duty time in effectiveness categories  Allows results be sorted based on user defined categories  Individual ID reports with effectiveness at the 1 min resolution 19

20 Copyright 2008, IBR FAST Aviation Analyzer In-flight sleep 14.5 hr flight Pre-flight nap Sleep Timing based on both physiological and social cues Dashboard with Fatigue Factors Schedules in Aviation Manager link to FAST for detailed analysis. San Francisco to Sydney Pairing

21 Copyright 2008, IBR Dashboard Information CriteriaValue at point in schedule Flags are fatigue indicators Content based on fatigue analysis workshop hosted by NTSB and conducted by Drs. Mark Rosekind & David Dinges, funded by FRA Office of Safety. Sleep (last 24 hrs) Chronic Sleep Debt Hours Awake Time of Day Out of Phase Performance Values Effectiveness (vigilance) Mean Cognitive Lapse Index Reaction Time Reservoir

22 Copyright 2008, IBR Schedule Files for Evaluation ●Translated the spread sheets using Access database into the required XML file structure. ●Batch processed through FAST Aviation ●Used FAST Manager to rank order Pairings and Rosters ●Used output spread sheet to rank order segments 22 A: 90 Short haul pairings, 1094 active flights B: 56 Short haul monthly rosters, 3963 active flights C: 47 Long haul pairings, 188 active flights D: 64 Long haul monthly rosters, 1006 active flights

23 Copyright 2008, IBR Fatigue Metrics ●Typically, FAST is used to assess the “tail of the distribution” – how much critical duty time is spent at low effectiveness. ●For this exercise, we were asked to rank order all segments and schedules, not just the extreme cases. ●We rank ordered segments by minimum effectiveness at critical times of flight – take-offs and landings. ●We rank ordered pairings and rosters by minimum effectiveness and “critical time below criterion” which is more useful for entire schedules. 23

24 Copyright 2008, IBR 24 Rank A SH PairingsStartEndMin Critical TimeMinimum E Rank 1A10040LAXATL5/15/2010 5:555/15/2010 10:0870.843 2A10002LPBIQQ2/4/2011 8:152/4/2011 9:1974.647 3A10045ATLSEA5/14/2010 1:305/14/2010 6:5774.88 4A10002VVILPB2/4/2011 6:302/4/2011 7:4474.999 5A10002IQQSCL2/4/2011 10:102/4/2011 12:2475.6510 C LH Pairings 1C10027ANCLAX9/16/2010 15:059/16/2010 20:0970.321 2C10014PDXNRT5/17/2010 21:105/18/2010 7:5970.452 3C10033DFWBRU9/23/2010 18:159/24/2010 3:3472.064 4C10025BRUSHJ9/27/2010 16:409/27/2010 23:0973.625 5C10030LAXAMS9/16/2010 23:109/17/2010 9:4973.816 B SH Rosters 1B10049ARISCL12/22/2010 5:4512/22/2010 8:0972.596 2B10046IQQSCL1/10/2011 5:301/10/2011 7:4472.847 3B10052ANFSCL1/8/2011 3:401/8/2011 5:2973.668 4B10049ARISCL1/16/2011 2:551/16/2011 5:1974.179 5B10044IQQSCL1/10/2011 4:251/10/2011 6:3974.3910 D LH Rosters 1D10029GUMNRT5/26/2010 5:005/26/2010 8:5466.821 2D10032LIMSCL1/4/2011 6:151/4/2011 9:3467.762 3D10024SLCANC5/18/2010 3:355/18/2010 8:2967.783 4D10052HKGHEL11/17/2010 17:1511/18/2010 4:1968.594 5D10024SLCANC6/2/2010 3:356/2/2010 8:2968.885 SAFTE/FAST - Segment Analysis

25 Copyright 2008, IBR 25 Rank A SHPairings Critical TBCL (77)TBCL Overall RankMinimum E Rank 1A100021492 2 2A10001884 4 3A10008616 5 4A10040539 1 5A100004110 8 C LHPairings 1C100141821 3 2C100331433 4 3C10019775 7 4C10038616 1 5C10027616 2 B SHRosters 1B100492011 1 2B100501942 6 3B100461264 2 4B100451245 8 5B100471236 5 D LHRosters 1D100241803 3 2D100431117 9 3D10044918 6 4D10022859 16 5D100297910 1 SAFTE/FAST - Roster Analysis

26 Copyright 2008, IBR SEGMENTS Minimum Critical Time Effectiveness 26

27 Copyright 2008, IBR Short Haul Pairing A 10040 LAX to ATL Segment 27 Early StartDaytime Rest Night flight

28 Copyright 2008, IBR LH Pairing - C 10027 Anchorage-LAX Segment 28 5 hrs 86% reservoir

29 Copyright 2008, IBR LH Pairing - C 10014 – Narita Segment 29 Narita

30 Copyright 2008, IBR Short Haul Pairing - A 10002 Santa Cruz, Bolivia – Santiago, Chile 30 1.5 hr Nap

31 Copyright 2008, IBR A 10002, continued Santa Cruz, Bolivia – Santiago, Chile Possible Mitigation 31 3 hr Nap

32 Copyright 2008, IBR Long Haul Pairing - C 10014 Honolulu to Salt Lake 32 93% Res 3:15 Base Narita Honolulu Salt Lake

33 Copyright 2008, IBR C 10014 Honolulu to Salt Lake Altered Sleep Pattern 33 Altered Sleep Pattern

34 Copyright 2008, IBR Long Haul Pairing C 10033 Kuala Lumpur Based Pilot 34

35 Copyright 2008, IBR ROSTERS Greatest Time Below Criterion 35

36 Copyright 2008, IBR Long Haul Roster - D 10029 36 11 Day - Closer Examination

37 Copyright 2008, IBR D 10029 Detroit– Narita- Guam Segment 37

38 Copyright 2008, IBR Long Haul Roster D 10029 Guam – Narita Segment 38

39 Copyright 2008, IBR 39 Short Haul Roster - B 10049 92 Segments in 57 Days 25 th Ranking Workload of 56

40 Copyright 2008, IBR B 10049 Early Start on 12/19 40

41 Copyright 2008, IBR B 10049 Multiple Segments at Night on 12/21 starting 1730 to 0510 41

42 Copyright 2008, IBR B 10049 Multiple Segments at Night 42

43 Copyright 2008, IBR Long Haul Roster - D 10024 Salt Lake-Anchorage-Minn 43

44 Copyright 2008, IBR D 10024 Six Day Series Salt Lake-Anchorage-Minn 44

45 Copyright 2008, IBR Two Early Starts (0700 and 0500) Two Consecutive Night Flights (2235 and 0020) Daytime Recovery D 10024 Salt Lake-Anchorage-Minn Explanation 45 6 hrs5 hrs

46 Copyright 2008, IBR Workload Factor ●According to the NTSB: “One factor that contributes to self-reported pilot fatigue, especially in short-haul flight operations, is the number of legs flown in a duty period.”* ●The highest workload in a flight occurs at take-off and landing; increasing segments multiplies these high stress periods. ●FAST Aviation is the first fatigue assessment tool to provide an automated method to assess this source of fatigue. *NTSB Safety Recommendation, A-09-61 through -66, August 7, 2009

47 Copyright 2008, IBR Sample Workload Pattern Median Workload increases with segments Workload dissipates over time Maximum

48 Copyright 2008, IBR B 10007 Top Ranking Workload 58 Segments in 12 Days 48

49 Copyright 2008, IBR Advantages of Modeling Approach ●Validated model with history of outstanding performance under independent review. ●Explicit Sleep Estimator (AutoSleep) tailored to habits and policies of the airline. ●Aviation specific drivers of fatigue.  Cognitive fatigue  Workload related fatigue ●Analysis tools that lead to specific fatigue factors and mitigation approaches. ●Modular design can be tailored to customers needs.

50 Copyright 2008, IBR SummarySummary

51 Fatigue Risk Management System Involves all stakeholders at each stage: management, labor, aided by science Enablers Employee training Medical screening Economic analysis Technology aids Measure Define the situation Schedule evaluation Actigraph recordings Model & Analyze Model the fatigue problem Analyze sources and Fatigue factors Manage Collaborate for solutions Obtain commitment to solve problem Modify/Mitigate Shared Responsibility Operating practices Labor agreements Individual “life style” Monitor Assess operational indicators Individual self-evaluation Feedback to process Continuous Improvement Process Mitigations are Proportional to the Risk Evolutionary, Incremental Improvement Responsive to Changing Circumstances Mitigations are Proportional to the Risk Evolutionary, Incremental Improvement Responsive to Changing Circumstances

52 Copyright 2008, IBR Fatigue Risk Pyramid Measures & Barriers Fatigue Modeling Measures & Barriers Fatigue Modeling Measures & Barriers Fatigue Modeling Diagnosis Fatigue Modeling Job Performance Changes Subjective Awareness Event Sequence Employee sleep habits, traits, & conditions Work demands, schedules, and sleep opportunities Fatigue Related Errors Accidents & Incidents Based on James Reason, “Managing the Risks of Organizational Accidents”, Figure 1.6, Stages in the development and investigation of an organizational accident. Level 1 Defense Level 2 Defense Level 3 Defense

53 Copyright 2008, IBR If fatigue is present, what do you do about it? ●Modeling tools must do more than give you a fatigue score:  It must estimate fatigue risk  It must show detail of each schedule  It must calculate fatigue factors  It must provide context of conditions that lead to fatigue so mitigations can be implemented by an FRMS 53

54 Copyright 2008, IBR Steven R. Hursh, PhD and Reid Blank Institutes for Behavior Resources 2104 Maryland Avenue Baltimore, MD 21218 (410) 752-6080 shursh@ibrinc.org rblank@ibrinc.org Chris Hallman Baines Simmons America 17 Greenville St., Suite 221 Newnan, GA 30263 (678) 343-1635 Office (770) 251-5654 Fax chris@bainessimmonsamericas.com www.safetyfromknowledge.com 54 Questions:

55 Copyright 2008, IBR Wrist movements are recorded 24/7 and downloaded over the internet Downloaded data are converted to daily sleep/wake/work times Daily sleep/wake/work times are fed into the SAFTE risk evaluation model SAFTE evaluates the fatigue risk and effectiveness of each individual driver Individual fatigue risk levels are amalgamated into a group report FS Actigraph Data Processing Personnel wear the actigraph that measures wrist movements


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