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Overview Who we are Development of FAID® and FAID TZ Analysis of data packages Some practical considerations Q & A
A global business Developing and delivering decision support methodologies and software Assisting clients to manage RISK Enabling clients to safely and productively deploy their resources. Working with corporate & government sector clients in the aviation & other high risk industries in Australia & around the world to develop & implement Fatigue Risk Management Systems. Integrated Safety Support is committed to improving safety through the effective management of fatigue-related risk.
Launched late 1999 >>>> • Rail (Australia, NZ, UK, USA & Canada = UP, BN, NS, CP, SEPTA, Metro-North RR & Long Island Rail Road) • General Aviation, easyJet (UK), German Wings, Brussels Airline, Air Pacific, Jetstar, Virgin Blue, Qantas Operations, WestJet, Delta Air Lines (TZ). • Government Agencies – Customs, Police • Road Transport – BP, Shell • Energy – Australia, NZ & Canada (Hydro Ottawa) • Mining – BHP Billiton, RTZ, Xtrata • Marine – Pilots in Australia, NZ & Holland • Health – Queensland Health Doctors
Context for the use of FRMS Fatigue cannot be eliminated We can, however, control the risk associated with fatigue in the workplace No one-system approach can address fatigue Certain principles, knowledge & understanding are required to manage this complex Human Factors issue
Fatigue Risk Management System Model • Corporate Responsibility • Fatigue Awareness Training • Ensuring Adequate Sleep Opportunity • FAID Analysis /Action Plans Level One (L1) • Individual Responsibility • Using Time off for Rest Level Two (L2) • Behavioral Symptoms • Screening Tools • Peer Identification Level Three (L3) Level Four (L4) • Continuous Improvement Process • FAID Analysis • Measurement Critical Incident!! Concept Taken From “Managing The Risks Of Organizational Accidents” by James Reason
Establish the ‘context’ • Fatigue is the context of how we look at the hazard associated with the task (i.e. task such as operating an aircraft). • Fatigue itself is not the hazard. • Hence, FRMS is really about Task Risk Management in the context of Fatigue. Definition provided by Zurich Risk Engineering
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Enough energy for the journey zzzzzzzzzz Sleep Aircraft fuel
Consequencesof Fatigue Mood↓ Communication↓ Speed↓ Accuracy↓ Micro-sleeps↑ Fully rested Highlyfatigued • Focus of attention can narrow/tunnel • Integrating information, even routine information, can degrade then stop • Impairment of ability to self-assess whether safety &/or productivity can be maintained • Confidence remains high Image courtesy of Integrated Safety Support
Fatigue-related Context To establish this context, it is necessary to first gain an appreciation of the indicative fatigue level amongst the organisation’s workforce. This is achieved by determining the ‘apparent’ Fatigue Tolerance Level – FTL via analysis using a scientifically-proven fatigue model, such as FAID®
Hours of Work (Sleep Opportunity) Job/other factors FAID® Modeling RiskManagement Non-Work-relatedFatigue Work-relatedFatigue
Estimates of work-related fatigue are based on statistical modelling of the amount of sleep likely to be obtained by an average population based on the time of day and duration of work and non-work periods over a 7 day period. • Indicative fatigue is inferred from the estimate of sleep obtained.
…uses the following Specific Determinants to Predict Work-Related Fatigue: The time of day of work & non-work periods The duration of work & non-work periods Work history in the preceding seven days The biological limits on recovery sleep Based on Hours of Work
8.5h break = 5.8h sleep 8.5h break = 1.0h sleep The Significance of Time of Day on Sleep Quality 48 hours 1.0 0.9 0.8 work 0.7 leisure 0.6 sleep 0.5 Proportion of Drivers 0.4 0.3 0.2 0.1 0.0 3:00 PM 6:00 PM 9:00 PM 6:00 PM 3:00 PM 9:00 PM 3:00 AM 6:00 AM 9:00 AM 3:00 AM 6:00 AM 9:00 AM 12:00 PM 12:00 PM 12:00 AM 12:00 AM Time of Day Results are from the original CFSR research study
Fatigue Scores are Indicators Only • Fatigue scores only provide an indication of the impact of sleep deprivation. • They are based on a statistical analysis of research performed into fatigue levels over a broad sample of population and provide guidance on the fatigue of an ‘average’ individual.
Peak FAID® scores - what do they actually mean? 40 Monday – Friday Work Week 60 Commercialairline pilots 80 5, 12h day shifts in a row 2, 12h night shifts in a row 100 7, 8h night shifts in a row 120 Train Drivers 140 Truck Drivers & Mining
easyJet Project Experience: • Twenty crew rosters evaluated across study timeframe • Performance trends correlate with LOSA FTR (Pearson correlation sign. @ 5% level) • FAID® provides a useful means of predicting cumulative fatigue effects
Performance Trends – Failure to Respond (FTR) • Cumulative fatigue effects on performance throughout roster pattern.
FAID TZ For Transmeridian Operations Developed in conjunction with Dr Adam Fletcher from Integrated Safety Support
Transmeridian Operations • Research is not 100% conclusive regarding how adaptation to time zones exists. There are, however, some principles that are generally agreed. • For example, TZ shifts of 1-3 hours are understood to have a relatively small impact on performance. The variance associated with such shifts is probably no greater than that from individual differences. • Eastward travel takes, on average, two thirds as many days as the number of time zones crossed. That is, a 9E TZ crossing takes 6 days;6E takes 4 days, etc.
Transmeridian Operations • In contrast, the adaptation to westward travel takes, on average, one half as many days as the number of time zones crossed. That is, an 8W TZ crossing takes 4 days; 6W takes 3 days, etc. • Therefore, the normal maximum adaptation for eastward travel in any 24 hour period is 1.5 hours and for westward travel is 2 hours. • All of these principles are reflected in FAID TZ.
Transmeridian Operations • Also, it is now generally considered reasonable to make predictions up to 9 Hours East and 12 Hours West. • Between these there is a ‘grey’ zone in which adjustment can often occur in the opposite direction to the physical direction of travel. • For example, a 10-hour Easterly trip (by the body) can be associated with a 14-hour adjustment (by the brain) West.
Transmeridian Operations • Since adapting to time zone shifts isn’t the best strategy for all travel (e.g. fast turnarounds), models need to accommodate options. • For example, where crew are staying in a port for <24h then going in the ‘home’ direction the adaptation will be zero or negligible. • If they stay a longer time (e.g. >48h) then adaptation will be much more likely. • FAID TZ currently includes an inflection point at 36h to address this issue (and thiscan be updated followingnew research).
Setting up for Analysis: • A: Short haul pairings • B: Short haul monthly rosters • C: Long haul pairings* • D: Long haul monthly rosters* * On-board sleep valued at 50% of normal sleep
Work history consideration for pairing evaluation • FAID takes into consideration work in the prior week • In normal operation we quote valid FAID scores after the 1st week of data • As many pairings are less than 1 week long there are two options: • One is to assume the prior working week with a nominal working pattern • Or assume no work performed in the prior week • We have analysed the pairings assuming no work in prior week • This may be useful for relative comparison between pairings but may not be representative of the absolute scores within an actual roster
FATIGUE TOLERANCE LEVEL Example of FTL settings for data analysis