Airport Collaborative Decision
Making (A-CDM
Isometric Scene of Pitstop (in progress)
Airport CDM
Fuel Efficiency
Airline & Ground handling procedures
Gap Analysis / Site Surveys
DMAN / AMAN / ASMGCS
Flow Management
Capacity Enhancement
Training / Transfer of knowledge
Worldwide Services Operational Efficiency
enhancement includes:
Dave Hogg – Chief Operating Officer
Caroline Schmeits- Senior Airports & CDM Expert Aviation
“...On both a professional and personal level, I would like to thank you for your
professionalism, your dedication to the CDM process and your hard work
and effort in accomplishing this important mission…”
Mark Libby, ATCSCC, FAA
“... It was a great pleasure working with you in Geneva. Over the years we
valued your expertise in guiding Geneva Airport to implement Airport CDM
in a mature way. The criteria for Airport CDM were a challenge to us,
and with your help we are now ready to be soon one of Europe’s
next CDM airports. ” Francois Duret - Head of projects & planning
Operations
Recent & Current A-CDM involvement
IC- Recent A-CDM initiatives on
behalf of IATA
Changi A-CDM workshop
Beijing A-CDM workshop
Shanghai A-CDM briefing
Narita A-CDM workshop
Haneda A-CDM Workshop
CDM55 Gatwick
Changi A-CDM
Dubai DMAN
Abu Dhabi Workshop
Hong Kong Training
Introduction to A-CDM
Where did the CDM story begin & Why?
USA
Europe
Enroute & only one ANSP
Global CDM only possible in a harmonised way
EUROCONTROL, IATA, ICAO and ACI are
ensuring this standardisation
Airports were the bottleneck
Limited infrastructure & capacity growth
Many European ANSP, Airspace Users & Airport Partners
Different procedures & technology shortfall
Airport CDM is growing
USA adopting European CDM
Asia- Pacific & Middle East following
South America & Africa showing interest
What ARE the inefficiencies today?
Possible Causes?
No optimal use of Airport infrastructure
Not using all available data
Being reactive rather than pro-active
Keeping our operations to ourselves
We have a blaming culture today
Sitting on Information
Lack of having the full picture
Buffering of planning
Lack of procedures amongst partners
Different Definitions
The symptoms…
No single partner has the complete picture
Information is passed too late for partners to respond – and has not the same meaning
Examples:
Airport & ATC don’t know when the aircraft are ready for departure
(Ground handler knows)
Airlines don’t know when the aircraft can start up until getting
clearance. (hard for ATC to plan in advance)
Airport & GHA only know the estimated arrival time when aircraft
enter FIR boundary (Airline knows earlier)
Have you ever asked yourself
WHY?Have you ever considered the impact
on the operations of others?
The cure…
What if we’re able to share and predict the aircraft readiness time?
departure sequence can be planned earlier.
runway / taxiway congestion can be managed in a better way.
aircraft holding at stand instead of taxiway, save fuel.
pilot will know in advance the engine start-up time.
What if we’re able to get a better ETA much earlier than today?
airport will have more time to resolve gate conflict, better passenger
experience
ground handlers will be able to deploy resources more efficiently
Airport Collaborative
Decision Making
(A-CDM)
ETA – Estimated Time of Arrival
ATC ACC: arrival on TMA entry
ATC TWR: landing time on runway
GH / Airport / Airline: arrival on stand
Different Definitions…
ATC TWR: take off time
GH / Airport / Airline: pushback from stand
ETD - Estimated Time of Departure
Inaccurate Information
Taxi time calculated based on
standard taxi times
EOBT (FPL) not updated by Airlines, despite
knowledge of delay
Flights have equal EOBT even though
capacity cannot accommodate Take off
time unpredictable due to large holding queue
A-CDM will improve:
resources usage
decision making
infrastructure usage
predictability
situational Awareness
NEED FOR COLLABORATION
Amongst all Airport Parties for
A-CDM to WORK
A-CDM Stakeholders
AIS
MET Aircraft Operator
ATC
ATC Flow
GA
Airport Operator
Airport CDM is about
PEOPLE, not just tools!
CULTURE CHANGE
Pick any card and concentrate on only that card…
Pick any card and concentrate on only that card…
Card Gone?
You see; the six cards and the subsequent
group of 5 cards never contained the same cards…
This power-game is a metaphor for our inability
to see change – or the need to change.
Why share data, oar why not?
Confidentiality of data
Fear of the ‘unknown’?
Why are partners reluctant to change?
It is easier for companies to come up with new ideas than to let go of old ones"
no understanding of partners’ operations
If they are not involved in the changes?
The Challenge
How to convince to change
Who to convince to change
No Charging
for DATA &
share data
Understand
each others
operations &
difficulties
Being
prepared to
work with
new
procedures
No Blame
culture
created
All partners
involved &
working
together
A-CDM is not a
IT tool
Change
Management
The Airlines are critical in the A-CDM project, both in local implementation of A-CDM and
in protecting their interests in multiple A-CDM destinations
Pilots
Operations Control Centers (OCC)
Airline ground staff
Hub Control Centers
Airlines are involved from the outset of any A-CDM initiative
Airlines delegate TOBT responsibility to GH if needed
A-CDM procedures are agreed by the partners i.e. Airlines
e.g. some airports applying rules with no consultation
Airlines proactively share data with other partners
Operational requirements to protect theAirlines
In development
To safe guard airline input in procedures
In implementation
To safe-guard benefits as an outcome
Airline involvement worldwide & support
In general to safe-guard global harmonization
Additional help from Organisations
To engage partners
To maintain commitment
To have a need for common procedures
To safe-guard interests of all involved
IATA & IACA efforts
In relation to Member Airlines
Recommend Airlines to be A-CDM compliant
Recommend a uniform way of executing A-CDM
Need to look at delay codes?
In relation to Ground Handler Organisation
Need for harmonised SLA with Airlines
Next
What data is shared and how
New terminology
Best planned best served
What can it do for you in adverse conditions
Airport CDM
Elements
Air Traffic Flow Management
Adverse Conditions
Pre Departure Sequencing
Variable Taxi Times
Flight Progress
Information Sharing
Airport CDM Elements
Information Sharing is the Foundation
The right information At the right time To the right people
Information Sharing
A-CDM Platform Requirements
Airport database: the best platform to store,
process and share Airport CDM information
Tailor to each partner’s needs
Avoid extra display
Create consistent look and feel
Avoid information overload
Clearly link arrivals & deprtures
2. Milestone Approach
Milestones link the three phases:
Inbound (Arrival)
Turnaround
Outbound (Departure)
Local Radar
Update
Take Off from
Outstation
Taxi In
(EXIT)
EOBT-2 hrs
ATC Flight Plan
Activation
(EOBT – 3 hrs)
Final
Approach
Landing
ALDT
A-CDM INFORMATION SHARING & MILESTONE APPROACH
INBOUND TURN ROUND OUTBOUND
In-Block /
Actual Ground
Handling Starts
Boarding
Starts
TSAT
Start Up
Approved
TOBT
Update Prior
to TSAT
TOBT Towing
Aircraft Ready
Start Up
Request
Taxi Out
(EXOT)
Off-Block
AOBT
Take Off
ATOT
3. Variable Taxi Times
To have accurate TAKE OFF prediction for network ATFM capacity – demand balancing
To have accurate IN BLOCK prediction to start turnround process
Default Taxi Times are inaccurate
Need for Airport partners ;
…improved Network
Planning for the ATFM
…better Stand & Gate
Planning at the airport
…increased Resource
efficiency
…economical benefits
…environmental gains
Variable Taxi Times provide…
4. Pre-departure sequencing
Reactive handling method of flights by ATC
Positive on FCFS
Equality of all flights – all flights get same treatment
No disputes – everybody listens to same frequency
Problem with FCFS
Unpredictable
Less balanced use of resources (e.g. runway)
Today:
First Come First Serve!
Best Planned Best Served?
Objectives;
Improve prediction of push back order
Improve management of queuing aircraft at holding point
By using Principles;
Transparency
Replace “first come first served” principle
Target Effect of Sequencing
Benefits
Reduced:
Improved:
Predictability for Airline
Stand & Gate management
Ground Handler planning
Safety
Queuing, fuel burn, emissions and noise
workload for ATC
5. A-CDM in Adverse Conditions?
Major reduction in Capacity
Slow Recovery due to
Disruption to Adverse Condition =
Lack of information
Lack of communication
Lack of prioritization
Objectives:
A-CDM will:
How?
Improve management of disruptions
Enhance Utilisation of Available Capacity
Improve Situational Awareness
Facilitate recovery after disruptions
Anticipate strong capacity reductions
Crisis management with A-CDM procedures & tools
Full, same operational picture
Gap in ATOT predictability
6. Linking to the ATFM Network
Conclusion
No Airline confirmation of EOBT
No Airline update of deviating from EOBT
No Airport information about changing conditions
No ATC sequence confirmation
No accurate ETOT prediction due to default taxi time
The Airports are black boxes for ATFM
Example: CDM Messages to ATFM
Departure Planning Information (DPI) Message
Aims to send frequent airport status and flight TOBT-
TTOT and TSAT predictions
Integrated Airports receive priority in ATFM regulations
Initiatives in Asia Pacific
Development of Regional ATFM
Thailand’s capacity enhancement initiatives
(with A-CDM) Interim Framework for
Collaborative ATFM?
Sub-regional ATFM network operational trial
2013-2014 (with A-CDM) - Hong Kong
China, Indonesia, Malaysia, Singapore,
Thailand and Viet Nam
Others?
A-CDM will both feed
ATFM with dynamic data
and receive network
updates
A-CDM
BENEFITS
Improved communication and situational awareness
Better arrival times and sequence information = pro-active decision making
Improved ground handling processes = improved resource efficiency
Improved punctuality = improved image
Reduced taxi- & runway queuing = reduced fuel and improved safety
Operational benefits
Inbound;
Turnaround;
Outbound;
High level Benefits Airlines
Improved situational
awareness, more
accurate fleet
predictions
Significant decrease in
fuel costs & engine
running
Accurate Arrival &
Departure times and
planning
Better use of resources
and communication
High level benefits Ground Handling
Accurate Arrival & Departure times and planning.
Better use of resources and communication
Operational examples and benefits for Airlines and Ground Handlers
Late arrival = late departure?
Transfer pax?
Earlier and different decision making based on TOBT & TSAT mechanism
Visibility of towing aircraft?
Ground radar display and TOBT for towings
Daily programme of flight operations and turn-round times on schedule – enhanced punctuality
Possible schedule disruptions predicted early, thus managed efficiently
Preferences and priorities taken into account
Less equipment has to be moved and less often (less fuel and maintenance)
Benefits Airports
Accurate Arrival & Departure times and planning = operational efficiency
Better use of resources
Airport image on punctuality
Airport revenue (more customers?)
Benefits passengers
reduced delays and missed connections
better reliability on flights meaning improved customer
satisfaction
Benefits environment
less noise & emissions (NoX, CO2)
ATC benefits
Reduced / Improved
workload with predictability of traffic
Improved planning
RWY waiting time
taxi times
The Proven Benefits
Munich –
Paris CDG -
Paris CDG -
= 5400 tons of fuel to airlines = € 2.7M
source: www.euro-cdm.org (“CDM special bulletin Dec 2011”)
Improved punctuality and reduced delays
20% (approx.)reduction in taxi times for departures
2.75 M € annual fuel savings
93% ATFM slot adherence
source: www.eurocontrol.int (“CDM@CDG”)
13% reduction in taxi times for departures (average 2 min per flight)
40% reduction in waiting time at the runway
90% ATFM slot adherence
source: www.euro-cdm.org
25% reduction in taxi times for departures (average 3 min per flight)
17022 tons carbon dioxide (Co2) & 22 tons of nitrogen oxides (NoX)
Madrid – source: International Airport Review – Aug 2014 8% reduction in taxi
times (average 2 min per flight)Over 1 million liters kerosene
in savings
Lessons learned in implementation
Lessons Learned from other Airports?
Clear project driver
Establish MoU from outset
Dedicated Project Manager
Lack of PMP with tasks, accountability and timeframes
Project overlapping
Poor Communication
A-CDM cherry picking
Working Groups too large or not consistent
participation
Steering Groups slow in resolving issues & politics
Too many ‘talkers 'and lack of ‘doer’s’
Platform developed around CDM Procedures
Involving ALL and maintaining Commitment of
all partners
Harmonised, standardised Global A-CDM
Isometric Scene of Pitstop (in progress)
Questions & Answers
Likes and concerns of what you heard?
Dislike Like
What will be the changes?
Is this rocket science?
Nothing is impossible, the impossible just takes a bit longer
THANKYOU

More Related Content

PPTX
Airport Collaborative Decision Making
PPT
Pelabuhan dan bandar udara sehat
PDF
Introduction to Airline Industry
PDF
Alexei Vladishev - Zabbix - Monitoring Solution for Everyone
PPTX
Doppler VHF Omni Directional Range (DVOR)
PPTX
Design and planning of airport
PPTX
Airport apron and holding bays
PPTX
Separation
Airport Collaborative Decision Making
Pelabuhan dan bandar udara sehat
Introduction to Airline Industry
Alexei Vladishev - Zabbix - Monitoring Solution for Everyone
Doppler VHF Omni Directional Range (DVOR)
Design and planning of airport
Airport apron and holding bays
Separation

What's hot (20)

PPT
Alazen ACDM Overview
PDF
Procedure for Safe Ground Handling Practices - (Sample for Edition)
PPTX
Air traffic control & air navigation
PPTX
PPTX
Navegación aerea diapositivas
PDF
Collaborative Decision Making in Aviation
PPT
Aircraft performance 2
PPT
Fundamentals of Air Traffic Control
PPTX
Airport Collaborative Decision Making: Systems Approach
PPTX
Crew Resource Management : General
PPT
overview on airport operation
PPT
6 Airport Economics.ppt
PPTX
AIRPORT OPERATIONS.pptx
PPT
Aircraft ground handling
PPT
Airport_Technical_Services.ppt
PPT
separation.ppt
PPT
airside operation 3
PPTX
Scheduling and Revenue Management
PPTX
PTC15 A-CDM & next frontier
PPTX
SITA Airport CDM - global end2end experience - Apr2017
Alazen ACDM Overview
Procedure for Safe Ground Handling Practices - (Sample for Edition)
Air traffic control & air navigation
Navegación aerea diapositivas
Collaborative Decision Making in Aviation
Aircraft performance 2
Fundamentals of Air Traffic Control
Airport Collaborative Decision Making: Systems Approach
Crew Resource Management : General
overview on airport operation
6 Airport Economics.ppt
AIRPORT OPERATIONS.pptx
Aircraft ground handling
Airport_Technical_Services.ppt
separation.ppt
airside operation 3
Scheduling and Revenue Management
PTC15 A-CDM & next frontier
SITA Airport CDM - global end2end experience - Apr2017
Ad

Viewers also liked (7)

PDF
AEROPORTO MARCO POLO - Save Group - 2010 12M Results
PPTX
IGHC 27Revised
PPT
Airport Cdm
PPTX
Winter Ops & Safety 2015, Helsinki: A-CDM perspectives
PPTX
Global Global Air Traffic Management
PDF
Airport security 2013 steve batt
PDF
Introduction to Air Traffic Management
AEROPORTO MARCO POLO - Save Group - 2010 12M Results
IGHC 27Revised
Airport Cdm
Winter Ops & Safety 2015, Helsinki: A-CDM perspectives
Global Global Air Traffic Management
Airport security 2013 steve batt
Introduction to Air Traffic Management
Ad

Similar to A-CDM (20)

PPTX
AAO - Session 12 - Airport Collaborative Decision Making_2022 V1 2.pptx
PPT
India Aviation ICT Forum 2013 - Manish Sinha, Deputy COO, Hyderabad Internati...
PDF
INFORM-Measuring and Monitoring Aircraft Turn Operations v3
PDF
Profit maximization
PPT
Airlines Mis
PDF
Context Driven Delivery of Aeronautical Information
PDF
Cloud security expo 2017
PPT
capacity managment and slot allocation.ppt
DOCX
FAA Advanced Qualification Program (AQP) and CRM for Military & .docx
DOCX
FAA Advanced Qualification Program (AQP) and CRM for Military & .docx
PPT
Airport Seminar - Federal Aviation Administration
PDF
Flight Data Monitoring
PPT
Simplified vehicle ops
PPTX
Airline Operation Solutions
PDF
CDM Aviation Point of View
PPT
ADM and Pilotage
PPTX
Incorporating Gate Variability in Airline Block Planning
PPTX
AAO - Session 2 - The Airport Master Plan_2022 V1.pptx
PDF
Jeff Poole, CANSO, SITA Europe Aviation ICT Forum 2013
AAO - Session 12 - Airport Collaborative Decision Making_2022 V1 2.pptx
India Aviation ICT Forum 2013 - Manish Sinha, Deputy COO, Hyderabad Internati...
INFORM-Measuring and Monitoring Aircraft Turn Operations v3
Profit maximization
Airlines Mis
Context Driven Delivery of Aeronautical Information
Cloud security expo 2017
capacity managment and slot allocation.ppt
FAA Advanced Qualification Program (AQP) and CRM for Military & .docx
FAA Advanced Qualification Program (AQP) and CRM for Military & .docx
Airport Seminar - Federal Aviation Administration
Flight Data Monitoring
Simplified vehicle ops
Airline Operation Solutions
CDM Aviation Point of View
ADM and Pilotage
Incorporating Gate Variability in Airline Block Planning
AAO - Session 2 - The Airport Master Plan_2022 V1.pptx
Jeff Poole, CANSO, SITA Europe Aviation ICT Forum 2013

More from Grafic.guru (20)

PPTX
Drone presentation
PPTX
All inclusive social
PPTX
Startup series module10 - v02
PPTX
Drone presentation (1)
PPTX
Sqeeqee
PPTX
PPTX
Vorlage
PPTX
Virtual
PPTX
Urban promise
PPTX
PPTX
Tinyhr
PPTX
The three chain links
PPTX
The advanced
PPTX
Students
PPTX
Sqeeqee
PPTX
PPTX
Security digital
PPTX
Santa monica community day
PPTX
Sacred Oak Medical center
PPTX
S3M business overview
Drone presentation
All inclusive social
Startup series module10 - v02
Drone presentation (1)
Sqeeqee
Vorlage
Virtual
Urban promise
Tinyhr
The three chain links
The advanced
Students
Sqeeqee
Security digital
Santa monica community day
Sacred Oak Medical center
S3M business overview

Recently uploaded (20)

PDF
August Patch Tuesday
PPTX
Web Crawler for Trend Tracking Gen Z Insights.pptx
PDF
Architecture types and enterprise applications.pdf
PDF
DP Operators-handbook-extract for the Mautical Institute
PDF
A contest of sentiment analysis: k-nearest neighbor versus neural network
PPTX
Modernising the Digital Integration Hub
PDF
Getting started with AI Agents and Multi-Agent Systems
PPT
Geologic Time for studying geology for geologist
PDF
Hindi spoken digit analysis for native and non-native speakers
PPTX
MicrosoftCybserSecurityReferenceArchitecture-April-2025.pptx
PDF
Taming the Chaos: How to Turn Unstructured Data into Decisions
PDF
sustainability-14-14877-v2.pddhzftheheeeee
PDF
From MVP to Full-Scale Product A Startup’s Software Journey.pdf
PDF
A review of recent deep learning applications in wood surface defect identifi...
PDF
Video forgery: An extensive analysis of inter-and intra-frame manipulation al...
PDF
STKI Israel Market Study 2025 version august
PDF
Univ-Connecticut-ChatGPT-Presentaion.pdf
PDF
Zenith AI: Advanced Artificial Intelligence
PDF
Getting Started with Data Integration: FME Form 101
PDF
1 - Historical Antecedents, Social Consideration.pdf
August Patch Tuesday
Web Crawler for Trend Tracking Gen Z Insights.pptx
Architecture types and enterprise applications.pdf
DP Operators-handbook-extract for the Mautical Institute
A contest of sentiment analysis: k-nearest neighbor versus neural network
Modernising the Digital Integration Hub
Getting started with AI Agents and Multi-Agent Systems
Geologic Time for studying geology for geologist
Hindi spoken digit analysis for native and non-native speakers
MicrosoftCybserSecurityReferenceArchitecture-April-2025.pptx
Taming the Chaos: How to Turn Unstructured Data into Decisions
sustainability-14-14877-v2.pddhzftheheeeee
From MVP to Full-Scale Product A Startup’s Software Journey.pdf
A review of recent deep learning applications in wood surface defect identifi...
Video forgery: An extensive analysis of inter-and intra-frame manipulation al...
STKI Israel Market Study 2025 version august
Univ-Connecticut-ChatGPT-Presentaion.pdf
Zenith AI: Advanced Artificial Intelligence
Getting Started with Data Integration: FME Form 101
1 - Historical Antecedents, Social Consideration.pdf

A-CDM

  • 2. Isometric Scene of Pitstop (in progress)
  • 3. Airport CDM Fuel Efficiency Airline & Ground handling procedures Gap Analysis / Site Surveys DMAN / AMAN / ASMGCS Flow Management Capacity Enhancement Training / Transfer of knowledge Worldwide Services Operational Efficiency enhancement includes:
  • 4. Dave Hogg – Chief Operating Officer Caroline Schmeits- Senior Airports & CDM Expert Aviation “...On both a professional and personal level, I would like to thank you for your professionalism, your dedication to the CDM process and your hard work and effort in accomplishing this important mission…” Mark Libby, ATCSCC, FAA “... It was a great pleasure working with you in Geneva. Over the years we valued your expertise in guiding Geneva Airport to implement Airport CDM in a mature way. The criteria for Airport CDM were a challenge to us, and with your help we are now ready to be soon one of Europe’s next CDM airports. ” Francois Duret - Head of projects & planning Operations
  • 5. Recent & Current A-CDM involvement IC- Recent A-CDM initiatives on behalf of IATA Changi A-CDM workshop Beijing A-CDM workshop Shanghai A-CDM briefing Narita A-CDM workshop Haneda A-CDM Workshop CDM55 Gatwick Changi A-CDM Dubai DMAN Abu Dhabi Workshop Hong Kong Training
  • 7. Where did the CDM story begin & Why? USA Europe Enroute & only one ANSP Global CDM only possible in a harmonised way EUROCONTROL, IATA, ICAO and ACI are ensuring this standardisation Airports were the bottleneck Limited infrastructure & capacity growth Many European ANSP, Airspace Users & Airport Partners Different procedures & technology shortfall Airport CDM is growing USA adopting European CDM Asia- Pacific & Middle East following South America & Africa showing interest
  • 8. What ARE the inefficiencies today? Possible Causes? No optimal use of Airport infrastructure Not using all available data Being reactive rather than pro-active Keeping our operations to ourselves We have a blaming culture today Sitting on Information Lack of having the full picture Buffering of planning Lack of procedures amongst partners Different Definitions
  • 9. The symptoms… No single partner has the complete picture Information is passed too late for partners to respond – and has not the same meaning Examples: Airport & ATC don’t know when the aircraft are ready for departure (Ground handler knows) Airlines don’t know when the aircraft can start up until getting clearance. (hard for ATC to plan in advance) Airport & GHA only know the estimated arrival time when aircraft enter FIR boundary (Airline knows earlier) Have you ever asked yourself WHY?Have you ever considered the impact on the operations of others?
  • 10. The cure… What if we’re able to share and predict the aircraft readiness time? departure sequence can be planned earlier. runway / taxiway congestion can be managed in a better way. aircraft holding at stand instead of taxiway, save fuel. pilot will know in advance the engine start-up time. What if we’re able to get a better ETA much earlier than today? airport will have more time to resolve gate conflict, better passenger experience ground handlers will be able to deploy resources more efficiently Airport Collaborative Decision Making (A-CDM)
  • 11. ETA – Estimated Time of Arrival ATC ACC: arrival on TMA entry ATC TWR: landing time on runway GH / Airport / Airline: arrival on stand Different Definitions… ATC TWR: take off time GH / Airport / Airline: pushback from stand ETD - Estimated Time of Departure
  • 12. Inaccurate Information Taxi time calculated based on standard taxi times EOBT (FPL) not updated by Airlines, despite knowledge of delay Flights have equal EOBT even though capacity cannot accommodate Take off time unpredictable due to large holding queue
  • 13. A-CDM will improve: resources usage decision making infrastructure usage predictability situational Awareness NEED FOR COLLABORATION Amongst all Airport Parties for A-CDM to WORK
  • 14. A-CDM Stakeholders AIS MET Aircraft Operator ATC ATC Flow GA Airport Operator
  • 15. Airport CDM is about PEOPLE, not just tools! CULTURE CHANGE
  • 16. Pick any card and concentrate on only that card…
  • 17. Pick any card and concentrate on only that card…
  • 19. You see; the six cards and the subsequent group of 5 cards never contained the same cards… This power-game is a metaphor for our inability to see change – or the need to change.
  • 20. Why share data, oar why not? Confidentiality of data Fear of the ‘unknown’? Why are partners reluctant to change? It is easier for companies to come up with new ideas than to let go of old ones" no understanding of partners’ operations If they are not involved in the changes?
  • 21. The Challenge How to convince to change Who to convince to change No Charging for DATA & share data Understand each others operations & difficulties Being prepared to work with new procedures No Blame culture created All partners involved & working together A-CDM is not a IT tool Change Management
  • 22. The Airlines are critical in the A-CDM project, both in local implementation of A-CDM and in protecting their interests in multiple A-CDM destinations Pilots Operations Control Centers (OCC) Airline ground staff Hub Control Centers
  • 23. Airlines are involved from the outset of any A-CDM initiative Airlines delegate TOBT responsibility to GH if needed A-CDM procedures are agreed by the partners i.e. Airlines e.g. some airports applying rules with no consultation Airlines proactively share data with other partners Operational requirements to protect theAirlines
  • 24. In development To safe guard airline input in procedures In implementation To safe-guard benefits as an outcome Airline involvement worldwide & support In general to safe-guard global harmonization
  • 25. Additional help from Organisations To engage partners To maintain commitment To have a need for common procedures To safe-guard interests of all involved
  • 26. IATA & IACA efforts In relation to Member Airlines Recommend Airlines to be A-CDM compliant Recommend a uniform way of executing A-CDM Need to look at delay codes? In relation to Ground Handler Organisation Need for harmonised SLA with Airlines
  • 27. Next What data is shared and how New terminology Best planned best served What can it do for you in adverse conditions
  • 28. Airport CDM Elements Air Traffic Flow Management Adverse Conditions Pre Departure Sequencing Variable Taxi Times Flight Progress Information Sharing Airport CDM Elements
  • 29. Information Sharing is the Foundation The right information At the right time To the right people Information Sharing
  • 30. A-CDM Platform Requirements Airport database: the best platform to store, process and share Airport CDM information Tailor to each partner’s needs Avoid extra display Create consistent look and feel Avoid information overload Clearly link arrivals & deprtures
  • 31. 2. Milestone Approach Milestones link the three phases: Inbound (Arrival) Turnaround Outbound (Departure)
  • 32. Local Radar Update Take Off from Outstation Taxi In (EXIT) EOBT-2 hrs ATC Flight Plan Activation (EOBT – 3 hrs) Final Approach Landing ALDT A-CDM INFORMATION SHARING & MILESTONE APPROACH INBOUND TURN ROUND OUTBOUND In-Block / Actual Ground Handling Starts Boarding Starts TSAT Start Up Approved TOBT Update Prior to TSAT TOBT Towing Aircraft Ready Start Up Request Taxi Out (EXOT) Off-Block AOBT Take Off ATOT
  • 33. 3. Variable Taxi Times To have accurate TAKE OFF prediction for network ATFM capacity – demand balancing To have accurate IN BLOCK prediction to start turnround process Default Taxi Times are inaccurate Need for Airport partners ;
  • 34. …improved Network Planning for the ATFM …better Stand & Gate Planning at the airport …increased Resource efficiency …economical benefits …environmental gains Variable Taxi Times provide…
  • 35. 4. Pre-departure sequencing Reactive handling method of flights by ATC Positive on FCFS Equality of all flights – all flights get same treatment No disputes – everybody listens to same frequency Problem with FCFS Unpredictable Less balanced use of resources (e.g. runway) Today: First Come First Serve!
  • 36. Best Planned Best Served? Objectives; Improve prediction of push back order Improve management of queuing aircraft at holding point By using Principles; Transparency Replace “first come first served” principle
  • 37. Target Effect of Sequencing
  • 38. Benefits Reduced: Improved: Predictability for Airline Stand & Gate management Ground Handler planning Safety Queuing, fuel burn, emissions and noise workload for ATC
  • 39. 5. A-CDM in Adverse Conditions? Major reduction in Capacity Slow Recovery due to Disruption to Adverse Condition = Lack of information Lack of communication Lack of prioritization
  • 40. Objectives: A-CDM will: How? Improve management of disruptions Enhance Utilisation of Available Capacity Improve Situational Awareness Facilitate recovery after disruptions Anticipate strong capacity reductions Crisis management with A-CDM procedures & tools Full, same operational picture
  • 41. Gap in ATOT predictability 6. Linking to the ATFM Network Conclusion No Airline confirmation of EOBT No Airline update of deviating from EOBT No Airport information about changing conditions No ATC sequence confirmation No accurate ETOT prediction due to default taxi time The Airports are black boxes for ATFM
  • 42. Example: CDM Messages to ATFM Departure Planning Information (DPI) Message Aims to send frequent airport status and flight TOBT- TTOT and TSAT predictions Integrated Airports receive priority in ATFM regulations
  • 43. Initiatives in Asia Pacific Development of Regional ATFM Thailand’s capacity enhancement initiatives (with A-CDM) Interim Framework for Collaborative ATFM? Sub-regional ATFM network operational trial 2013-2014 (with A-CDM) - Hong Kong China, Indonesia, Malaysia, Singapore, Thailand and Viet Nam Others? A-CDM will both feed ATFM with dynamic data and receive network updates
  • 46. Improved communication and situational awareness Better arrival times and sequence information = pro-active decision making Improved ground handling processes = improved resource efficiency Improved punctuality = improved image Reduced taxi- & runway queuing = reduced fuel and improved safety Operational benefits Inbound; Turnaround; Outbound;
  • 47. High level Benefits Airlines Improved situational awareness, more accurate fleet predictions Significant decrease in fuel costs & engine running Accurate Arrival & Departure times and planning Better use of resources and communication
  • 48. High level benefits Ground Handling Accurate Arrival & Departure times and planning. Better use of resources and communication
  • 49. Operational examples and benefits for Airlines and Ground Handlers Late arrival = late departure? Transfer pax? Earlier and different decision making based on TOBT & TSAT mechanism Visibility of towing aircraft? Ground radar display and TOBT for towings Daily programme of flight operations and turn-round times on schedule – enhanced punctuality Possible schedule disruptions predicted early, thus managed efficiently Preferences and priorities taken into account Less equipment has to be moved and less often (less fuel and maintenance)
  • 50. Benefits Airports Accurate Arrival & Departure times and planning = operational efficiency Better use of resources Airport image on punctuality Airport revenue (more customers?)
  • 51. Benefits passengers reduced delays and missed connections better reliability on flights meaning improved customer satisfaction Benefits environment less noise & emissions (NoX, CO2)
  • 52. ATC benefits Reduced / Improved workload with predictability of traffic Improved planning RWY waiting time taxi times
  • 53. The Proven Benefits Munich – Paris CDG - Paris CDG - = 5400 tons of fuel to airlines = € 2.7M source: www.euro-cdm.org (“CDM special bulletin Dec 2011”) Improved punctuality and reduced delays 20% (approx.)reduction in taxi times for departures 2.75 M € annual fuel savings 93% ATFM slot adherence source: www.eurocontrol.int (“CDM@CDG”) 13% reduction in taxi times for departures (average 2 min per flight) 40% reduction in waiting time at the runway 90% ATFM slot adherence source: www.euro-cdm.org 25% reduction in taxi times for departures (average 3 min per flight) 17022 tons carbon dioxide (Co2) & 22 tons of nitrogen oxides (NoX) Madrid – source: International Airport Review – Aug 2014 8% reduction in taxi times (average 2 min per flight)Over 1 million liters kerosene in savings
  • 54. Lessons learned in implementation
  • 55. Lessons Learned from other Airports? Clear project driver Establish MoU from outset Dedicated Project Manager Lack of PMP with tasks, accountability and timeframes Project overlapping Poor Communication A-CDM cherry picking Working Groups too large or not consistent participation Steering Groups slow in resolving issues & politics Too many ‘talkers 'and lack of ‘doer’s’ Platform developed around CDM Procedures Involving ALL and maintaining Commitment of all partners Harmonised, standardised Global A-CDM
  • 56. Isometric Scene of Pitstop (in progress)
  • 58. Likes and concerns of what you heard? Dislike Like
  • 59. What will be the changes?
  • 60. Is this rocket science?
  • 61. Nothing is impossible, the impossible just takes a bit longer