model review. 1. who we are 2. development of faid® and faid tz 3. analysis of data packages 4....
TRANSCRIPT
Model review
1. Who we are2. Development of FAID® and FAID
TZ3. Analysis of data packages4. Some practical considerations5. Q & A
Overview
• 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
• Continuous Improvement Process • FAID Analysis
• Measurement
Fatigue Risk Management System Model
Level One (L1)
Level Two (L2)
• Behavioral Symptoms• Screening Tools• Peer Identification
• Corporate Responsibility• Fatigue Awareness Training
• Ensuring Adequate Sleep Opportunity • FAID Analysis /Action Plans
Concept Taken From “Managing The Risks Of Organizational Accidents” by James Reason
Level Three (L3)
Critical Incident!!
Level Four (L4)
• Individual Responsibility• Using Time off for Rest
FRMS
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
Aircraft fuel
Aircraft fuel
zzzzzzzzzzSleep
Enough energy for the journey
Aircraft fuel
Sleepzzzzzzzzzz
• 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
Fully rested
Highly fatigued
Mood↓ Communication↓ Speed↓ Accuracy↓ Micro-sleeps↑
Consequences of Fatigue
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®
Non-Work-related FatigueWork-related
Fatigue
Job/other factors
RiskManagement
Hours of Work(Sleep Opportunity)
FAID®
Modeling
• 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.
• 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
…uses the following Specific Determinants to Predict Work-
Related Fatigue:
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.01
2:0
0 P
M
3:0
0 P
M
6:0
0 P
M
9:0
0 P
M
12
:00
AM
3:0
0 A
M
6:0
0 A
M
9:0
0 A
M
12
:00
PM
3:0
0 P
M
6:0
0 P
M
9:0
0 P
M
12
:00
AM
3:0
0 A
M
6:0
0 A
M
9:0
0 A
M
Time of Day
Pro
po
rtio
n o
f D
riv
ers work
leisure
sleep
48 hours
8.5h break = 1.0h sleep 8.5h break = 5.8h sleep
Results are from the original CFSR research study
The Significance of Time of Day on Sleep Quality
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.
40
60
80
100
120
140
Peak FAID® scores - what do they actually mean?
Commercial airline pilots
5, 12h day shifts in a row
7, 8h night shifts in a row
Truck Drivers & Mining
Train Drivers
2, 12h night shifts in a row
Monday – Friday Work Week
Peak Fatigue Index vs. Duty Day
0
10
20
30
40
50
60
day1 day2 day3 day4 day5 day6
PFI
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.
% Fail To Respond (unmitigated errors) vs. Duty Day
0
10
20
30
40
50
60
day 1 day 3 day 4 day 6
Duty Day
% FT
R
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
Operational Risk
Operational Duty
FAID® Score
Low Deadhead 80
Moderate Ground Duties 60
High Flying Duties 50
Example of FTL settings for data analysis
A: Short haul pairing
B: Short haul monthly roster
C: Long haul pairing
D: Long haul monthly roster
“ A TOOL, NOT A RULE ”
• Uses within an FRMS: Roster & Pairing Design – STD or DLL Crew Roster Planning – STD or DLL Compliance Monitoring Occurrence Investigation Fatigue Exposure Diagnostic – risk
assessment & tolerance Day of Operation support (STD or DLL)
• FAID® and FAID TZ are to be used as an integral part of a risk-based Integrated Fatigue Management System.
• They are not intended to be used by themselves as decision-making tools, but supporting decisions using them can be appropriate.
• Although it goes without saying, used in isolation, FAID® and FAID TZ are not a Risk-based Integrated Fatigue Management Systems.
FRMS structure
Consultation
Audit & Assurance
FRMS tools Training
Reporting
Data Analysis
Procedures
FRM Policy
Communications
Environment
Image courtesy of Integrated Safety Support
Practical considerations
• Bio-mathematical models are used in conjunction with other factors to assess fatigue-related risk.
• Most models, including FAID, have been developed after extensive scientific research, validation and industry testing, this cannot be said of all such models.
• All models are subject to limitations.
What does this mean to operators?
• Model users need to know and understand the limitations of the models they use.
• Users need to understand how the research that their model(s) is based on relates to their particular operation/context.
• Models generally estimate average fatigue levels using research data gathered froma group of individuals.
• Estimated fatigue levels from bio-mathematical models cannot be interpreted as applying to any one individual.
• Generally, bio-mathematical models should only be used strategically(i.e. when planning or designing rosters or as part of periodic reviews of actual hours, occurrence investigation etc.)
What does this mean to operators?
• If an operator has a mature FRMS, bio-mathematical models may be used as tactical decision-making tools on (or close to) the day of operation.
• If an FRMS is not mature, bio-mathematical models should not be used as tactical decision-making tools.
What does this mean to operators?
Conclusion drawn from this data set example:
Based on the results of the FAID® TZ analyses, it is reasonable to conclude that the subject operator is quite well organised, as none of the scenarios give rise to excessive fatigue exposure
• Continuous Improvement Process • FAID Analysis
• Measurement
Fatigue Risk Management System Model
Level One (L1)
Level Two (L2)
• Behavioral Symptoms• Screening Tools• Peer Identification
• Corporate Responsibility• Fatigue Awareness Training
• Ensuring Adequate Sleep Opportunity • FAID Analysis /Action Plans
Concept Taken From “Managing The Risks Of Organizational Accidents” by James Reason
Level Three (L3)
Critical Incident!!
Level Four (L4)
• Individual Responsibility• Using Time off for Rest
QUESTIONS?
FRMS CONSIDERATIONS!
• ICAO view is that an FRMS is a data-driven system
• We agree 100%• This analysis shows that a model, such as
FAID®TZ , can provide valid fatigue-related data for the purpose of an FRMS
• Clearly it is also vital that the Risk Management methodology employed uses this data appropriately and with understanding of the individual operator’s risk appetite
www.faidsafe.com
www.integratedsafety.com.au
