Model review
Overview
1.
2.
3.
4.
5.
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 fatiguerelated 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
• Individual Responsibility
• Using Time off for Rest
Level One (L1)
Level Two (L2)
Level Three (L3)
Level Four (L4)
• Behavioral Symptoms
• Screening Tools
•Peer Identification
• Continuous Improvement
Process
• FAID Analysis
• Measurement
Concept Taken From “Managing The
Risks Of Organizational Accidents” by
James Reason
Critical Incident!!
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
zzzzzzzzzz
Sleep
Aircraft fuel
Enough energy
for the journey
Aircraft fuel
zzzzzzzzzz
Sleep
Consequences of Fatigue
Mood↓
Communication↓
Speed↓ Accuracy↓
Micro-sleeps↑
Fully
rested
Highly
fatigued
• 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®
Work-related
Fatigue
Hours of Work
Non-Work-related
Fatigue
(Sleep Opportunity)
Job/other
factors
FAID®
Modeling
Risk
Management
• 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 WorkRelated 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
The Significance of Time of Day on Sleep Quality
48 hours
8.5h break = 5.8h sleep
8.5h break = 1.0h sleep
1.0
0.9
Proportion of Drivers
0.8
0.7
work
0.6
leisure
0.5
sleep
0.4
0.3
0.2
0.1
Time of Day
Results are from the original CFSR research study
9:00 AM
6:00 AM
3:00 AM
12:00 AM
9:00 PM
6:00 PM
3:00 PM
12:00 PM
9:00 AM
6:00 AM
3:00 AM
12:00 AM
9:00 PM
6:00 PM
3:00 PM
12:00 PM
0.0
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
Commercial airline pilots
80
5, 12h day shifts in a row
100
2, 12h night shifts in a row
120
7, 8h night shifts in a row
140
Train Drivers
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
Peak Fatigue Index vs. Duty Day
60
50
PFI
40
30
20
10
0
day1
day2
day3
day4
day5
day6
Performance Trends – Failure to
Respond (FTR)
% FTR
% Fail To Respond (unmitigated errors) vs. Duty
Day
• Cumulative fatigue
60
50
40
effects on performance
throughout roster
pattern.
30
20
10
0
day 1
day 3
Duty Day
day 4
day 6
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 this
can be updated following
new 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
Low
Moderate
High
Operational
Duty
FAID®
Score
Deadhead
80
Ground Duties
60
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)
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


• 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 Riskbased Integrated Fatigue Management Systems.
FRMS structure
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 from
a group of individuals.
What does this mean to operators?
• Estimated fatigue levels from biomathematical 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, biomathematical 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.
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
Fatigue Risk Management System Model
• Corporate Responsibility
• Fatigue Awareness Training
• Ensuring Adequate Sleep Opportunity
• FAID Analysis /Action Plans
• Individual Responsibility
• Using Time off for Rest
Level One (L1)
Level Two (L2)
Level Three (L3)
Level Four (L4)
• Behavioral Symptoms
• Screening Tools
•Peer Identification
• Continuous Improvement
Process
• FAID Analysis
• Measurement
Concept Taken From “Managing The
Risks Of Organizational Accidents” by
James Reason
Critical Incident!!
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
len.pearson@interdynamics.com
richard@integratedsafety.com.au