Airport resilience
One corner of the performance diamond
Dr Michael Fairbanks
10 November 2011
Before we start, some preliminary definitions
•

Resilience
•
•

•

…the abilities to anticipate, withstand and recover qu...
Statistics gives us a convenient way of analysing
the situation
•

•

•

•

2

System is not deterministic –
suffers from ...
Different performance indicators have very
different distributions
Airborne holding distribution
RE
AL

•
•
3

EX
AM
PL
E
...
Using cancellations as a KPI, we can categorise
resilience into three main regimes
Characterisation of resilience regimes ...
Focus on the severe days is anticipation and
recovery
•
•

•
•

5

Anticipate the event and
prepare
Graceful and equitable...
Numerous hotspots cause delay and uncertainty
in the flight even under normal conditions
Schematic of hotspots in aircraft...
Analysis confirms the queuing theory relationship
between delays & the demand/capacity ratio
Delay distribution for airbor...
The hotspots are therefore a set of queues
Contribution of different components into the overall flight time
ATFM
ATFM
Ave...
Probability of success is increased by including
buffers in block times
Relationship between undelayed, average and planne...
Buffering against delays becomes self-defeating
though
Impact of buffering by flight stage
on block time

Vicious circle o...
As demand/capacity increases, unpredictability
increases faster than average delay
Delay curves for average delay per flig...
Increasing capacity at constant demand realises
benefits in both average delay and buffer
Impact of lowering the demand/ca...
The cost of failure savings achieved by increasing
capacity might be expected to be significant

Based on the approach def...
There are also benefits of de-risking the last
rotations of the day
Outbound

Turn

Return

Buffer
Curfew

•

•
•

14

Ill...
We need, however, to consider a three-way balance:
increased demand, cost of prevention & costs of failure
Illustration of...
Resilience, therefore, is a key component of the
tensioned framework of competing objectives
Some of the tensions between ...
Improved performance can only be sustained by a wide
range of coordinated actions
Potential actions for improving punctual...
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Airport resilience: one corner of the performance diamond

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Presentation at GAD2011, Barcelona, November 2011
Presenter: Mike Fairbanks of Helios
mike.fairbanks@askhelios.com
_______________________________________________________________________
Follow Helios via Linkedin, www.twitter.com/askhelios and www.facebook.com/askhelios

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Airport resilience: one corner of the performance diamond

  1. 1. Airport resilience One corner of the performance diamond Dr Michael Fairbanks 10 November 2011
  2. 2. Before we start, some preliminary definitions • Resilience • • • …the abilities to anticipate, withstand and recover quickly from difficult conditions (derived from: Oxford English Dictionary) best balance of buffer (spare capacity) & utilisation Punctuality • • the difference between the actual time & the scheduled time for a flight early is as bad as late (at least for some stakeholders) • • 1 Delay (the other side of the capacity coin) • wasted time associated with queuing • many components (ATFM, airborne holding, taxi, start-up…) • different components can be traded-off Cancellations
  3. 3. Statistics gives us a convenient way of analysing the situation • • • • 2 System is not deterministic – suffers from random fluctuations Performance indicators are in effect probability density functions Describe performance in terms of the statistical parameters defining the distributions • mean • standard deviation • skewness/kurtosis • mode Often have to apply first principles, generalised analysis because distributions are nonnormal Idealised punctuality distribution Real punctuality distribution RE AL EX AM PL E
  4. 4. Different performance indicators have very different distributions Airborne holding distribution RE AL • • 3 EX AM PL E Ground holding distribution RE AL EX AM PL E “Simple” statistical definitions – e.g. mean average – might not be meaningful Understanding of both operations and statistics is essential
  5. 5. Using cancellations as a KPI, we can categorise resilience into three main regimes Characterisation of resilience regimes for a busy airport Cancelations Red days (severe disruption ~ 15 days) Amber days (moderate disruption ~ 50 days Green days (normal operations ~300 day) Number of days 4
  6. 6. Focus on the severe days is anticipation and recovery • • • • 5 Anticipate the event and prepare Graceful and equitable degradation of service to minimise disruption Focus on recovering as quickly as possible Passenger welfare is paramount €3 th .5 e bi fir lli st on w in ee k Source: Flightpath 2050, Europe’s vision for aviation
  7. 7. Numerous hotspots cause delay and uncertainty in the flight even under normal conditions Schematic of hotspots in aircraft flows Airborne holding Constraining (stacks, trombones, airspace blocks vectoring) Constraining airspace blocks Destination(s) SIDs ATFM at origin(s) Other airports’ SIDs Taxi-in Taxi-out Apron and Stands Arrivals Outstation performance Outstation performance Airspace/ATC Airspace/ATC Arrival runway capacity Arrival runway capacity •• ATFM ATFM •• airborne holding airborne holding •• Stands Stands •• •• •• 6 Departures Landside •Passenger flow •Baggage flow •• •• •• •• •• •• Turnaround Turnaround Runway capacity Runway capacity Taxiway capacity/congestion Taxiway capacity/congestion SIDs SIDs En route airspace/ATC En route airspace/ATC Destination airports Destination airports
  8. 8. Analysis confirms the queuing theory relationship between delays & the demand/capacity ratio Delay distribution for airborne holding Delay curve for airborne holding Applies to ATFM, airborne & ground holding, start-up & taxi delays (Also applies to other queues: pax security screening, control posts, etc) 7
  9. 9. The hotspots are therefore a set of queues Contribution of different components into the overall flight time ATFM ATFM Average Standard deviation 3 minutes ±3 minutes Taxi-out Taxi-out 15 minutes ±4 minutes Airborne Airborne holding holding Flying Flying 48 minutes ±5 minutes Taxi-in Taxi-in 5 minutes ±7 minutes 8 minutes ±2 minutes Illustrative probability density functions Combined μ =79 minutes σ =11 minutes 8 Turnaround Turnaround 40 minutes ±14 minutes
  10. 10. Probability of success is increased by including buffers in block times Relationship between undelayed, average and planned gate-to-gate times for flights arriving at a busy airport at capacity 9
  11. 11. Buffering against delays becomes self-defeating though Impact of buffering by flight stage on block time Vicious circle of increasing block times Off blocks Most likely bock-time Taxi time On blocks Taxi Taxi 10 Fly Fly Flight stage Hold Hold Taxi Taxi Delta Time with buffer Holding time Planned block-time with buffers Flying time Time Taxi time Most likely time
  12. 12. As demand/capacity increases, unpredictability increases faster than average delay Delay curves for average delay per flight and standard deviation of delay per flight Delay (minutes per flight) M OM RO A FR T D F ATA ED VE L DA IIV AL D R ER E DE REA D R Demand/capacity ratio 11 Derived by application of queuing theory Applies to ATFM, airborne & ground holding, start-up & taxi delays (Also applies to other queues: pax security screening, control posts, etc)
  13. 13. Increasing capacity at constant demand realises benefits in both average delay and buffer Impact of lowering the demand/capacity ratio 12
  14. 14. The cost of failure savings achieved by increasing capacity might be expected to be significant Based on the approach defined in the UK CAA’s 2008 runway resilience report assuming average aircraft type is typically B737 13
  15. 15. There are also benefits of de-risking the last rotations of the day Outbound Turn Return Buffer Curfew • • • 14 Illustrative example • based on above block times • assumes 15 minute buffer in schedule between last arrival and curfew At 100% demand/capacity there is a 5% chance of the return arriving after the start of the curfew At 85% demand/capacity there is a 0.2% chance of the return arriving after the start of the curfew
  16. 16. We need, however, to consider a three-way balance: increased demand, cost of prevention & costs of failure Illustration of the balance of the benefits of additional capacity against the associated costs (assuming no additional infrastructure) Benefits from increased demand • Revenue • aeronautical • non-aeronautical • Consumer surplus • Slots • APD • Connectivity 15 Cost of prevention Cost of failure • Schedule buffers • block times • MCT • Pax • System solutions e.g. CDM • Process improvement • strategic • tactical • Compensation • Poor use of resource • Aircraft & crew • Handling • Airport resources • Pax value of time • Emissions • Competitive disadvantage
  17. 17. Resilience, therefore, is a key component of the tensioned framework of competing objectives Some of the tensions between an airport’s objectives Capacity utilisation e.g. Schedule buffers Performance e.g. Departure punctuality vs taxi time e.g. Spare capacity vs average throughput Efficiency Environmental impact Resilience e.g. Completed departures vs night jet movements Ideally achieve optimum balance And.. deliver high quality, cost effective, passenger experience 16 Concept courtesy of XPX Consulting Capacity utilisation Capacity utilisation •• Runway Runway •• Terminal utilisation Terminal utilisation •• Aircraft utilisation Aircraft utilisation •• Airspace utilisation Airspace utilisation Resilience Resilience •• Programme completion Programme completion •• Recovery Recovery Environmental impact Environmental impact •• Noise Noise •• Night jet movements Night jet movements •• Track adherence Track adherence •• Emissions (ground & air) Emissions (ground & air) Performance Performance •• Punctuality Punctuality •• Service delivery (queues & Service delivery (queues & baggage) baggage) •• Connectivity Connectivity •• Infrastructure condition Infrastructure condition
  18. 18. Improved performance can only be sustained by a wide range of coordinated actions Potential actions for improving punctuality, reducing delays & adding resilience Scheduling Scheduling • Optimise the schedule • Optimise the schedule considering: considering: • all delays • all delays • resilience • resilience • design/masterplanning • design/masterplanning • environment • environment • commercial implications • commercial implications • slot value • slot value • consumer surplus • consumer surplus • In addition to on/off• In addition to on/offblocks, schedule to other blocks, schedule to other milestones in the flight milestones in the flight over which the airline has over which the airline has more control, e.g. stack fix more control, e.g. stack fix 17 Performance management Performance management • All stakeholders must be • All stakeholders must be aligned aligned • Graceful and planned • Graceful and planned degradation in the case of degradation in the case of disruption disruption • Ongoing measurement • Ongoing measurement • Identification of offenders • Identification of offenders • Establishment of root causes • Establishment of root causes • directly from data, e.g. • directly from data, e.g. delay codes delay codes • in dialogue with airlines • in dialogue with airlines • • • • • • • • Incentives & penalties Incentives & penalties no perverse incentives no perverse incentives contractual contractual regulatory regulatory Processes Processes • Command & control • Command & control • Better balance of ATFM, local • Better balance of ATFM, local & tactical measures & tactical measures • Improved predictability of • Improved predictability of flows at critical points flows at critical points • approach fix (arrival • approach fix (arrival management) management) • start-up • start-up • line-up (pre-departure • line-up (pre-departure management) management) • CDM • CDM

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