Copyright 2008, IBR Copyright 2010, IBR SAFTE/FAST Evidence-based Aviation Fatigue Risk Management...

Copyright 2008, IBRCopyright 2010, IBR

SAFTE/FASTEvidence-based

Aviation Fatigue Risk Management

Steven R. Hursh, Ph.D.President, IBR and

Professor, Johns Hopkins University School of Medicine

September 1, 2011

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.

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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.

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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.

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SAFTE Model Components

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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.

6Von Dongen, Aviation, Space, and Environmental Medicine, March, 2004, vol. 75, no. 3, section II

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Accuracy of Predicting Sleep Pattern and Duration

7

Measure Signalman Maintenance of Way

Dispatchers(less night workers)

Train and Engine

Mean Agreement

92% 92% 90% 88%

Daily Sleep(Est.- Log)

-24 min -21 min -3 min - 10.8 min

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516%

49%25%

142%

103%

70%

0

1

2

3

4

5

6

Less than or equal to 7777 to 90Greater than 90

Re

lati

ve R

isk

Crew Effectiveness Score

Economic Risk - Damage & Casualty Cost

Accident Risk

$

#$ $ #

#

1 = Unchanged relative risk

Economic Risk and Effectiveness

No Fatigue High Fatigue

Railroad Accident Relative Risk

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SAFTE/FAST

Validated Fatigue Modeling Tools

Fatigue Science has the exclusive license from the US Army to commercialize SAFTE model.

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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

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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.

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Sleep EstimatorTailored to Aviation Environment:

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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 file13

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Fatigue Risk Management System

FRM Steering Committee

Involves all stakeholdersat each stage:

management, labor, aided by science

EnablersEmployee trainingMedical screening

Economic analysisTechnology aids

MeasureDefine the situationSchedule evaluationActigraph recordings

Model & AnalyzeModel the fatigue problem

Analyze sources and Fatigue factors

ManageCollaborate for solutionsObtain commitment to

solve problem

Modify/MitigateShared Responsibility

• Operating practices• Labor agreements• Individual “life style”

MonitorAssess operational indicators

Individual self-evaluationFeedback to process

Continuous Improvement Process

SAFTE/FAST

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FAST Aviation Fatigue Assessment ProcessAirline Specific Schedule Database

XML formatCity-pairs/Trips or

30-day Bids

FAST AviationModeler

• 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 AnalyzerIndividual Schedules

• Examine schedules• Effectiveness Graph• Fatigue Factors• “What-If” Drills• Individual reports

Modular Process for Speed and Flexibility

Standard FASTschedule is created by FAST Aviation Modeler

Translation Tools available for any scheduling system

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FAST Aviation Modeler

Model the schedules: 1. Set AutoSleep parameters if necessary2. Name the Output folder a unique name3. Choose either a City Pairs file or a Bid

Schedules file for modeling

Airline Schedule DatabaseProcessed Schedules Modeling Results

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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 fileClick on any line in Aviation Manager and schedule opens in

FAST for detailed analysis.

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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 FRMS18

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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 resolution19

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FAST Aviation Analyzer

In-flight sleep

14.5 hr flight

Pre-flight napPre-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

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Dashboard Information

CriteriaValue at pointin 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

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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

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A: 90 Short haul pairings, 1094 active flightsB: 56 Short haul monthly rosters, 3963 active flightsC: 47 Long haul pairings, 188 active flightsD: 64 Long haul monthly rosters, 1006 active flights

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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.

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RankA SH Pairings Start End Min Critical Time Minimum E Rank

1 A10040 LAX ATL 5/15/2010 5:55 5/15/2010 10:08 70.84 32 A10002 LPB IQQ 2/4/2011 8:15 2/4/2011 9:19 74.64 73 A10045 ATL SEA 5/14/2010 1:30 5/14/2010 6:57 74.8 84 A10002 VVI LPB 2/4/2011 6:30 2/4/2011 7:44 74.99 95 A10002 IQQ SCL 2/4/2011 10:10 2/4/2011 12:24 75.65 10

C LH Pairings

1 C10027 ANC LAX 9/16/2010 15:05 9/16/2010 20:09 70.32 12 C10014 PDX NRT 5/17/2010 21:10 5/18/2010 7:59 70.45 23 C10033 DFW BRU 9/23/2010 18:15 9/24/2010 3:34 72.06 44 C10025 BRU SHJ 9/27/2010 16:40 9/27/2010 23:09 73.62 55 C10030 LAX AMS 9/16/2010 23:10 9/17/2010 9:49 73.81 6

B SH Rosters

1 B10049 ARI SCL 12/22/2010 5:45 12/22/2010 8:09 72.59 62 B10046 IQQ SCL 1/10/2011 5:30 1/10/2011 7:44 72.84 73 B10052 ANF SCL 1/8/2011 3:40 1/8/2011 5:29 73.66 84 B10049 ARI SCL 1/16/2011 2:55 1/16/2011 5:19 74.17 95 B10044 IQQ SCL 1/10/2011 4:25 1/10/2011 6:39 74.39 10

D LH Rosters1 D10029 GUM NRT 5/26/2010 5:00 5/26/2010 8:54 66.82 12 D10032 LIM SCL 1/4/2011 6:15 1/4/2011 9:34 67.76 23 D10024 SLC ANC 5/18/2010 3:35 5/18/2010 8:29 67.78 34 D10052 HKG HEL 11/17/2010 17:15 11/18/2010 4:19 68.59 45 D10024 SLC ANC 6/2/2010 3:35 6/2/2010 8:29 68.88 5

SAFTE/FAST - Segment Analysis

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RankA SH Pairings

Critical TBCL (77) TBCL Overall Rank Minimum E Rank

1 A10002 149 2 2

2 A10001 88 4 4

3 A10008 61 6 5

4 A10040 53 9 1

5 A10000 41 10 8

C LH Pairings1 C10014 182 1 3

2 C10033 143 3 4

3 C10019 77 5 7

4 C10038 61 6 1

5 C10027 61 6 2

B SH Rosters1 B10049 201 1 1

2 B10050 194 2 6

3 B10046 126 4 2

4 B10045 124 5 8

5 B10047 123 6 5

D LH Rosters1 D10024 180 3 3

2 D10043 111 7 9

3 D10044 91 8 6

4 D10022 85 9 16

5 D10029 79 10 1

SAFTE/FAST - Roster Analysis

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SEGMENTSMinimum Critical Time Effectiveness

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Short Haul PairingA 10040 LAX to ATL Segment

27

Early Start Daytime Rest

Night flight

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LH Pairing - C 10027 Anchorage-LAX Segment

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5 hrs

86% reservoir

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LH Pairing - C 10014 – Narita Segment

29

Narita

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Short Haul Pairing - A 10002 Santa Cruz, Bolivia – Santiago,

Chile

30

1.5 hr Nap

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A 10002, continued Santa Cruz, Bolivia – Santiago,

ChilePossible Mitigation

313 hr Nap

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Long Haul Pairing - C 10014 Honolulu to Salt Lake

32

93% Res

3:15 Base

Narita Honolulu Salt Lake

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C 10014 Honolulu to Salt Lake

Altered Sleep Pattern

33

Altered Sleep Pattern

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Long Haul PairingC 10033 Kuala Lumpur Based

Pilot

34

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ROSTERSGreatest Time Below Criterion

35

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Long Haul Roster - D 10029

36

11 Day - Closer Examination

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D 10029 Detroit– Narita- Guam Segment

37

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Long Haul RosterD 10029 Guam – Narita

Segment

38

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Short Haul Roster - B 10049 92 Segments in 57 Days

25th Ranking Workload of 56

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B 10049 Multiple Segments at Night

on 12/21 starting 1730 to 0510

41

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Two Early Starts (0700 and 0500) Two Consecutive Night Flights (2235 and 0020)

Daytime Recovery

D 10024 Salt Lake-Anchorage-Minn

Explanation

45

6 hrs 5 hrs

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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

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0

2

4

6

8

10

12

14

87654321

Num

ber o

r Fac

tor

Days from Start of Schedule

Workload Calculation

Workload

Segments

Sample Workload Pattern

Median

Workload incre

ases with

segmentsW

orkload dissipates over time

Maximum

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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.

Copyright 2008, IBR

Fatigue Risk Management System

Involves all stakeholdersat each stage:

management, labor, aided by science

EnablersEmployee trainingMedical screening

Economic analysisTechnology aids

MeasureDefine the situationSchedule evaluationActigraph recordings

Model & AnalyzeModel the fatigue problem

Analyze sources and Fatigue factors

ManageCollaborate for solutionsObtain commitment to

solve problem

Modify/MitigateShared Responsibility

• Operating practices• Labor agreements• Individual “life style”

MonitorAssess operational indicators

Individual self-evaluationFeedback to process

Continuous Improvement Process

Mitigations are Proportional to the RiskEvolutionary, Incremental ImprovementResponsive to Changing Circumstances

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Fatigue Risk Pyramid

Mea

sure

s & B

arrie

rs

Fatigu

e M

odeli

ng

Mea

sure

s & B

arrie

rs

Mea

sure

s & B

arrie

rs

Fatigu

e M

odeli

ng

Mea

sure

s & B

arrie

rs

Fatigu

e M

odeli

ng

Diagno

sis

Fatigu

e M

odeli

ng

Job Performance ChangesSubjective Awareness

Even

t Seq

uenc

e

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

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

Copyright 2008, IBR

Steven R. Hursh, PhD and Reid BlankInstitutes for Behavior Resources

2104 Maryland AvenueBaltimore, MD 21218

(410) [email protected]@ibrinc.org

Chris HallmanBaines Simmons America

17 Greenville St., Suite 221Newnan, GA 30263

(678) 343-1635 Office(770) 251-5654 Fax

[email protected]

54

Questions:

mailto:[email protected]



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Wrist movements are recorded 24/7 and downloaded over the internet

Downloaded data are converted to daily sleep/wake/work timesDaily sleep/wake/work times are

fed into the SAFTE risk evaluation model

SAFTE evaluates the fatigue risk and effectiveness of each individualdriver

Individual fatigue risk levels are amalgamated into a group report

FS Actigraph Data ProcessingPersonnel wear the actigraph that measures wrist movements

Copyright 2008, IBR Copyright 2010, IBR SAFTE/FAST Evidence-based Aviation Fatigue Risk Management...

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