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:
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
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.
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.
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.
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
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
Copyright 2008, IBR Economic Risk and Effectiveness No FatigueHigh Fatigue Railroad Accident Relative Risk
Copyright 2008, IBR SAFTE/FASTSAFTE/FAST Validated Fatigue Modeling Tools Fatigue Science has the exclusive license from the US Army to commercialize SAFTE model.
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
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.
Copyright 2008, IBR Sleep Estimator Tailored to Aviation Environment:
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
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
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
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
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.
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
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
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
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
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
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
Copyright 2008, IBR Long Haul Roster D 10029 Guam – Narita Segment 38
Copyright 2008, IBR 39 Short Haul Roster - B 10049 92 Segments in 57 Days 25 th Ranking Workload of 56
Copyright 2008, IBR B 10049 Early Start on 12/19 40
Copyright 2008, IBR B 10049 Multiple Segments at Night on 12/21 starting 1730 to 0510 41
Copyright 2008, IBR B 10049 Multiple Segments at Night 42
Copyright 2008, IBR Long Haul Roster - D 10024 Salt Lake-Anchorage-Minn 43
Copyright 2008, IBR D 10024 Six Day Series Salt Lake-Anchorage-Minn 44
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
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
Copyright 2008, IBR Sample Workload Pattern Median Workload increases with segments Workload dissipates over time Maximum
Copyright 2008, IBR B 10007 Top Ranking Workload 58 Segments in 12 Days 48
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.
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
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
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 Blank Institutes for Behavior Resources 2104 Maryland Avenue Baltimore, MD 21218 (410) 752-6080 firstname.lastname@example.org email@example.com Chris Hallman Baines Simmons America 17 Greenville St., Suite 221 Newnan, GA 30263 (678) 343-1635 Office (770) 251-5654 Fax firstname.lastname@example.org www.safetyfromknowledge.com 54 Questions:
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