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Model review. 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

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Model review

Model review


Model review

Overview

Who we are

Development of FAID® and FAID TZ

Analysis of data packages

Some practical considerations

Q & A


Model review

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.


Model review

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

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

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


Model review

FRMS


Establish the context

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


Model review

Aircraft fuel


Model review

zzzzzzzzzz

Sleep

Aircraft fuel


Model review

Enough energy for the journey

zzzzzzzzzz

Sleep

Aircraft fuel


Model review

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

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®


Model review

Hours of Work

(Sleep Opportunity)

Job/other factors

FAID®

Modeling

RiskManagement

Non-Work-relatedFatigue

Work-relatedFatigue


Model review

  • 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.


Model review

…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


Model review

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 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.


Model review

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


Model review

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

Performance Trends – Failure to Respond (FTR)

  • Cumulative fatigue effects on performance throughout roster pattern.


Faid tz

FAID TZ

For Transmeridian Operations

Developed in conjunction with Dr Adam Fletcher from Integrated Safety Support


Transmeridian operations

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 operations1

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 operations2

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 operations3

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).


Model review

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

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

FATIGUE TOLERANCE LEVEL

Example of FTL settings for data analysis


A short haul pairing

A: Short haul pairing


B short haul monthly roster

B: Short haul monthly roster


C long haul pairing

C: Long haul pairing


D long haul monthly roster

D: Long haul monthly roster


Model review

  • “ A TOOL, NOT A RULE ”


Model review

  • 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)


Model review

  • 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

FRMS structure

FRM Policy

Procedures

Consultation

FRMS tools

Training

Reporting

Audit & Assurance

Data Analysis

Environment

Communications

Image courtesy of Integrated Safety Support


Model review

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.


Model review

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.


Model review

What does this mean to operators?

  • 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.)


Model review

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.


Conclusion drawn from this data set example

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 model1

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


Questions

QUESTIONS?


Frms considerations

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


Model review

www.faidsafe.com

www.integratedsafety.com.au

[email protected]

[email protected]


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