Flight OpsStream

Regulatory Impacts on Multiple AOC Operations

Moderator: Alex De Gunten, Business Development Officer, HEICOPanelists: Walid Al Rahmani, Director Policy, Regulations and Planning,

GCAA UAE Stephen Creamer, Director, Air Navigation Bureau, ICAO Tim Steeds, Director of Safety and Security, British Airways Luc Tytgat, Strategy and Safety Management Director, EASA

Thank You to Our Networking Break Sponsor:

An Outlook to the Future of Air Traffic Management (ATM) – Challenges & Opportunities

Moderator: Sergio Quito, Chief Operating Officer, GOL AirlinesPanelists: Stephen Creamer, Director, Air Navigation Bureau, ICAO Carey Fagan, Executive Director for International Affairs, Federal Aviation

Administration (FAA) Florian Guillermet, Executive Director Operations and Programme,

SESAR Joint Undertaking Rudy Kellar, Executive Vice President Service Delivery, Nav Canada Nithaar Zain, Head of International Affairs, Singapore Airlines Limited

Airport OperationsSession Conducted in Association with

Airports Council International (ACI)Moderator: Ian Witter, Head of Airside Regulation and Oversight, Heathrow Airport

Chair, World Safety and Technical Standing Committee, Airport Council International (ACI)

Panelists: Craig Bradbook, Vice President Aviation Services, Greater Toronto

Airports Authority Steven Yiu, General Manager Airfield, Airport Authority Hong Kong Rob Eagles, Head of ATM, IATA

IATA SFO – Airport Operations - Heathrow April 2017

Ian Witter – Head of Airside Regulation & Oversight

Airport Operations (APOC): Purpose

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LHR is impacted by a number of factors that have a negative affect on punctuality – especially during summer periods

European ATC French ATC strikes Pressure across

European networks Capacity limitations

within key sectors such Maastricht due to higher demand

Weather related impacts S16 impacted by

prolonged CB activity European weather

impacting arrivals and rotational departures

June 2016 worst on record

Increasing number of A380s in operation

Impact on punctuality: increased wake vortex, taxi, aROT turnaround times

26 in operation as of 2016, to increase to 34 by 2017/18

UK/European Airport passenger growth

Increased demand for Local London Airspace

LTN, STN, LCY growth up ~10%

LGW up ~5%

LHR

Airside Operations

NB: Q6 summer operations are more sensitive to above factors

Resilience - Strive for 5

Airspace congestion due to traffic growth in UK and EuropeEuropean ATC strikes and flow restrictions.

Target – 5% increase in punctuality to 82%

ThemesFlow itBalance itTurn itMove it

Time Based Separation - YESRECAT Vortex separationSID balancing – northbound/southbound bias - YESA-CDM and TOBT improvements - YESAMAN/DMANRapid Exit Taxiways - YES

eTBS exampleIllustrative: Not to scale

6 Nautical Miles

HEAVY MEDIUM

Is converted to time based separation

3.5 Nautical Miles

A343 A320

Is converted to time based separation

Current

eTBSexample

Dependent parallel approaches – Current operations

IPA - Benefits modelling focussed primarily on the use of an increased landing rate

12

Independent parallel approaches – Increase landing rate scenario

Dependent parallel approaches – Current operations

Independent parallel approaches – Maintain landing rate scenario

Space for additional departures

AD

AD

AD

AD

With TEAM

Additional arrivals enabled

With TEAM

Additional departures enabled

Illustration of benefits

Modelling approach | Modelled benefits | CBA | Sensitivities

• Simultaneous independent arrivals to both runways at Heathrow to enableduring Easterly and Westerly operations and in accordance with TEAM rulesutilising RNP AR 0.15 to departure runway/ILS to arrival runway.

• RNP AR approaches accommodated in current Heathrow airspace

• Automated monitoring and alerting system - no monitor controllers required.

• Monitor frequency to be selected by all inbound aircraft for issue of any necessary breakout instructions

SHT3NA20 LL

UAE10A20 LL

BAW423A09 LL

BAW38A31 LL

No gap required to allow lander on departure runway

27R

27L

RNP-AR a/c

IPA Ops

Independent Parallel Approach at Heathrow

Automated Monitoring & Alerting Concept

Independent Parallel Approach at Heathrow

Headlines eILS

eILS replaces the old ILS and to reduces the Dynamic Localiser

Sensitive Area (DLSA), which will increase the runway capability during

Low Visibility Procedures and reduce the A380 operational

constraints on the ground operations LocaliserGlidepath

New cabinAntennas replaced 32 Arrays ILS installed

• Foundations and sub-base• Earthworks• New pits and ducts• Working around services• Electrical works• Barriers and Bollards• Pavement and markings

New enhanced technology deployed

09L Glid09L Loc

09R Loc27L Loc

27R Loc

09R Glid 27L Glid

27R Glid1st

2nd 3rd

4th

eILS Benefit Specifics

• Allows Independent A380 operations on Alpha/Bravo south in LVPs

• No requirement for extra gaps to manoeuvre A380 from Alpha onto Bravo in LVPs

• Reduction in runway crossing times of the Southern Runway in LVPs (i.e. 10nm to 8nm)

• Reduction in A380-A380 spacing from 7nm to 6nm in LVPs (and potentially further)

• If 5nm spacing, every 3 pairs A380-A380 will save 1 movement in LVPs

• Ability to handle multiple A380s in Wide Area of the DLSA (currently only 1) and retain ILS usage,

as no DLSA

• 5nm spacing in LVPs and Increased resilience in LVPs

• Opens up Sierra 11 for departure to Code D aircraft in LVPs

• The benefit of the eILS in normal visibility condition is a small reduction the probability of go-

arounds behind A380s on 27L.

This equals an increase of 4-6 arrivals per hour during LVP’s*

Assumptions:• The flow rate under current ILS is 26 + 6 • The flow rate with eILS will be 30 + 6 (i.e. increase of +4)• Operational experience / additional benefits above the spacing benefit may allow

this rate to increase to 32 + 6 (i.e. increase of +6) but this is an stretch targetNote: The increase in arrival rate may limit TEAM during long periods of LVPs (2 hours +) as start up

delay would become an issue.

*The TEAM +6 remains

Benefits - eILS reduces DLSA, thus increase landing capabilityduring LPVs and reduces A380 operational constraints

Extended Runway centre line

Current DLSA for the A380 with existing aerial.Complicated shapes, different for each runway.

New eLSA including A380’s with new aerialAs per existing LSA shape

27R ILS aerial

Existing LSA shape with existing aerial for all aircraft (excluding the A380)

Current DLSA for the A380 with existing aerial.Complicated shapes, different for each runway.

Extended Runway centre line

27L ILS aerial

eDLSA 82m* Centreline to Clearance

eDLSA 82m* Centreline to Clearance

New DLSA for the A380 with existing aerial. Better for safety and (ROT)

New DLSA for the A380 with existing aerial. Better for safety and (ROT)

‹#›

Current Masterplan – Submitted to Airports Commission

Runway farther west

200 fewer homes

Fewer people affected by noise

New cargo area

New green space

Heathrow West Heathrow East

• 3 independent runways

• 740,000 ATMs

• 130 mppa

• Min connect times of 45-60 mins

• 3 million tonnes cargo pa

2016

2017

2019

2020

2021

2018

Government announcement

Government consultationon draft NPS

Heathrow Stage 1 consultation

Heathrow Stage 2 consultation

NPS ‘designated’ by Government

Heathrow submit DCO application

Government decision to grant DCO

Expansion Timeline2021

2022

2024

2025

2023

ACP formal consultation ?

ACP final submission ?

SoS ACP approval ?

New runway operational

A-CDM@YYZ Update | Confidential

The case for A-CDM@YYZCraig Bradbrook

Vice President, Aviation Services

Greater Toronto Airports Authority

IATA Safety & Flight Operations ConferenceSeoul, April 25, 2017

The YYZ Challenge

24

Managing Growth

andComplexity

Growth

25

2014 2015 2016 2017 2018 2019 2020 202135M

40M

45M

50M

55M

Passengers(Year)

400K

420K

440K

460K

480K

AircraftMovement

(Year)

57M(2021)

488K(2021)

419K(2016)

44.3M(2016)

Passengers Aircraft Movements (ATB)

+ 70K flights

+ 13M passengers

ComplexityInfrastructure• 2 Terminals

• built to different standards

• 128 aircraft stands• 60% Narrow body only

• % of Wide body increasing

• Gate assignment rules• Adjacent parked aircraft

• Terminal apron ‘Horseshoes’• Congestion

• Designed for an O/D operation• Connecting passengers > 30%

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Processes• Each terminal has three

segregated sectors • Domestic, Transborder and

International

• Aircraft gating restrictions

• ‘Swing gates’ within the terminal

• US pre-clearance

• Special baggage processes• US CBP, One Stop Security,

International-to-Domestic (ITD)

• TWOV limitations

Other factors• Winter operation and

aircraft deicing• Hold over times and taxi out

times

• Weather elsewhere

• Arrival OTP issues• Gating conflicts → hardstand

• Ground handler resources

• Winter sun destination operations• Delays accumulate

• Last flight arrives very late

• Restricted hours

• General Aviation

Executing the aviation operation in real time

27

Aspect Trend

Complexity of the operation

Customer expectations(airlines, passengers, stakeholders)

Scale of operation

Potential for something to go wrong

Potential impact of events

Potential reputational risk

Decision time / Response time

Solu

tion

(Video)

A-CDM: A win-win

28

Shorter taxi times

Reduced fuel burn

More efficient turn around

Reduced delays

Better crew management

Improved passenger experience

AIR

LIN

ES

Reduced workload, more predictable traffic

Reduced probability of errors

Better pre-departure sequence

Reduced taxiway congestion

AN

SP

Reduced environmental impact

Improved punctuality

Improved gate/stand management

More efficient deicing process

Reduced apron congestion

Optimization of capacity

AIR

PO

RT

Better planning and use of resources

Improved customer satisfaction

Increased productivity

Improved safety

SER

VIC

ES

29

Hong Kong Intrnational Airport Collaboration Between

Airports and Airlines on Process Transformation

25 April 2017

Mr. Steven Yiu

General Manager, Airfield

Airport Authority Hong Kong

HKIA Statistics

190destinations

2Terminals 50

countries

42 mainland

destinations

2runways

>100 airlines

HKIA StatisticsDaily movement

record

1,226 (6Feb2016)

2016 Annual movements

411,530

Daily average

1,200 movements

Monthly movement record

35,666 (Dec 2016)

Hourly movements

68

Case 1Airport Wide Vehicle Tracking System (GPS)

GPS installation completed with stable operation

All airside motorised vehicles (3500 no.) installed with vehicle tracking system

Vehicle location information for resource deployment

Speeding reduced by > 50%

Incident/ accident investigation (e.g. pilferage cases)

Future integration with ACDM to monitor aircraft turnaround

IoT – Big Data Analysis

• Stage 1: completed in 2013; Stage 2: Full scale will be launched in July 2017

• Real-time airport collaboration, i.e. TOBT and TSAT

• On-Time-Performance monitoring

• Aircraft towing and ramp service coordination platform

• Interface with T-CDM and Internet of Things (IoT) for better resources planning and management

Case 2Full Implementation of HKIA ACDM and Future Inter-airport ACDM Collaboration

(Not Implemented at HKIA)

35

• Four-month interval real time

- Performance of each flight under monitoring- Follow-up with individual pilot for improvement

• To increase runway capacity in the medium to long run

Case 3ROTA Data Sharing with Airlines

Fixed B777 /A320 Fuselage Mock up Mobile A330 Fuselage Mock up

• Fixed and mobile training facilities for aircraft loading bridge docking training and on-site qualification examinations

• Virtual Reality Trainings

Develop a customized system and train airport staff

i.e. ALB operation, Airside driving

Case 4Provision of Common Training Facilities & Standardized Trainings

Phase 1

Safety Cones for RHOs and CTOs

• Chocks, earthing cables and steps for LMOs

Phase 2 (to be implemented)

• Provision of Conveyor Belt Loaders, Lower Deck Loaders, Main DeckLoaders to RHOs to improve arrival baggage delivery KPIs

i.e. 20/40 min pledge of first/ last bags

Uphold Equipment Standard

Reduce Apron Traffic

Conveyor Belt LoaderLower Deck Loader

Passenger Step

Case 5Airide Equipment Pooling

• 7 x 24 IAC inter-department operations andcoordination

• Manned bya) Airport Control Centre Personnel,b) Home-based airlines representatives,c) Ramp Handling Operators,d) Line Maintenance Operators,e) Airport Security, etc.to facilitate seamless real-time operational flows,planning and emergency response and management

Case 6Multi-parties Collaboration – Integrated Airport Centre

Thank You

Airport OperationsSession Conducted in Association with

Airports Council International (ACI)Moderator: Ian Witter, Head of Airside Regulation and Oversight, Heathrow Airport

Chair, World Safety and Technical Standing Committee, Airport Council International (ACI)

Panelists: Craig Bradbook, Vice President Aviation Services, Greater Toronto

Airports Authority Steven Yiu, General Manager Airfield, Airport Authority Hong Kong Rob Eagles, Head of ATM, IATA

Thank You to Our Networking Break Sponsor:

Extracting the Value of Big Data in Aircraft Operations

One presentation, Five speakers!

Dave Jesse – Do we have Big Data? Jon Tree – Data to and from a modern aircraft Christopher Solan – An aviation Big Data platform Billy Nolen – What airlines want from Big Data Andy Sage – Merging data from many sources

Dave Jesse Flight Data Services CEO

Analyzes lots of data Hundreds of operators Thousands of aircraft Millions of flights

Big Data characteristics5 V’s of Big Data

VolumeAviation data

All world’s FDR data for a year

100PB100,000,000,000,000,000 Bytes

Volume

Lots of data – FDR data used over many years Example: B787 records 1,800 parameters

First 100 parameters relate to flying Remainder relating to engineering

Big Data characteristics5 V’s of Big Data

Volume Variety Velocity Veracity

Aviation data

Not that big Related sources Modest

Veracity

Normal instrumentation failures Occasional design errors

ILS frequency 109.?5 MHz

Big Data characteristics5 V’s of Big Data

Volume Variety Velocity Veracity Value

Aviation data

Not that big Related sources Modest Good; stable High?

Do we have Big Data?

Jon Tree Boeing Digital Aviation & Analytics / JeppesenDirector of Aviation and Regulatory Standards, Industry Relations

Flight operations efficiency solutions, crew, fleet, flight planning, EFB, information management and data analytics

Airline

• Flight Operations• Maintenance & Engineering• Data & Information Management• Crew and Fleet

Airspace• Airspace & Procedure Design• Traffic Flow Management• Enroute/Real-time Optimization• Trajectory Based Operations

Airport• Surface Movement• Arrival & Departure Optimization• Gate & Equipment Optimization• Capacity Constraints

ANSP• Infrastructure• Regulatory and Fees• NextGen, SESAR, CARATS, others

Airplane

Communications & ConnectivityData Management & EquipageIntegrated Design and Analytics

Boeing 5-A Model

Information Serving Operations Advancements in aircraft sensor data capture Converting data into information serving operations through

System Wide Information Management (SWIM) Providing interoperable solutions for Collaborative Decision

Making (CDM) and Predictive Risk Reduction (PRR) Using data and analytics for operational benefits – safety,

efficiency, capacity, and systemic improvements

The aircraft as a sensor Digital Flight Data Acquisition Unit (DFDAU) and Flight Data Recorder

(FDR) ACARS and Quick Access Recorder (QAR)

Aircraft Health Management (AHM) – Turn information into insight Decision support tools

Aircraft Condition Monitoring System (ACMS) Fuel performance monitoring Maintenance fault communication Improved custom alerting and analytics

The flight crew / aircraft central to efficiencies Precise 4D position and trajectory information - future vision of

4D Trajectory Based Operations (4DTBO) DataComm – data link services for ATM (i.e., CPDLC and DCL) Broadband and narrowband capabilities for information management EFB and the Aircraft Interface Device (AID) On-Board Navigation (Network) Server – EFB and Electronic Log Book Secure Server Router (777-X) Advanced ATM through Flight and Flow Information for a Collaborative

Environment (FF-ICE)

SWIM operational data consumption

SWIM supports network optimization through CDM

Historical Data

SWIM

Advanced Analytics

Internal Airline

Information

Predicted System state

Operational Decisions

Current and predicted state (airspace, airports)

Intent

Other ATM Actors

Data to and from a modern aircraft

Christopher Solan GE Aviation Senior Product Manager

Delivers a big data analysis platform fuel management precision-based navigation safety

Flight DataA walled garden

Legacy of privacy, privilege

Silos, firewalled Closed technology Proprietary formats

External Aviation Data

Data Integration

and Core Analytics

Customer Data

WX TerrainNavigation DB

Flight Data Flight Plans OOOI Times

Raw > Logical Parameters

Load Sheets

Advanced Analytics

Standard Measurements Custom Measurements

Standard Events Custom Events

Safety Profile

Fuel ProfileCustom Analytics Development

Ops Profile

Flight Analytics Hub

APIs Business Intelligence Connectors

Flight Analytics Channels

Analytics Explorer

Configurable Dashboards Mobile Apps

Direct Application Connection

Personal

PlatformOpening thewalled garden

Expand the audience

Dashboards Mobile apps Personalized

analytics

An aviation Big Data platform

Billy Nolen Airlines for America Senior Vice President,

Safety, Security and Operations

Leader of the Operations Division Air and Ground Safety Security Flight Operations Air Traffic Management Engineering and Maintenance Cargo Services

Billy Nolen – Airlines for America Early days at American Airline - lack of strong actionable data Success of CAST in the US

Aggregated data has contributed to accident reduction Desire to get to actionable intelligence for multiple data

streams Need tools to extract meaningful information. Big Data can contribute to operational performance and safety

What airlines want from Big Data

Andy Sage National Air Traffic Services Account Director,

Airlines and Airspace

Heads Information Business Translates data into real value

for airlines and airports

Big Data for Flight Ops: Airline A‘Are my pilots correct that we are being held down at lower flight levels?’

Analysed actual flown data versus Flight Plan

Evidence of no level cap for past 6 months

Resulted in change of flight planning policy

Associated fuel & environmental benefits.

Big Data for Flight Ops: Airline B‘Am I planning more fuel than I need on my network?’

Analysed actual flown data versus Flight Plan

Identified extra unnecessary track mileage planned

Enabled future changes to the flight planning system

Flight routing efficiency improvements

Potential reduction in fuel uplift

Big Data for Flight Ops: Airline C‘Is my flight time performance consistent with other operators?’

Actual flight time against scheduled block time Provides time allocated for ground movement

Analysed on-time arrival performance Assessed against other operators Uncover inaccurate block time scheduling

Reduce or increase future schedule times Improve network on-time performance

Chart showing complexity of data at the same time as how to derive

result

What has stopped us until now?Industry challenges to unlock the true potential of data:

Lack of transparency to high value data

Inability to benchmark due to data silos

Complex ownership and consolidation

Cost of access and storage

“We want to gather long term statistical data but cannot access it beyond 6 weeks as it is embedded within separate vendor platforms”

So what’s different now?Opportunities to provide the industry with:

Availability of data

Cloud hosting services

Ability to deliver solutions

Ability to process vast amounts of data

Real time operational insight

What other questions can we answer?Performance against other operators: On-time arrival performance

Average flight times and block time performance

Horizontal and vertical performance

Overall flight efficiency of a route

Throughout all phases of flight

“The beauty of Big Data is that you can see the answersbefore you know which questions to ask!”

Merging data from many sources

Big Data Discussion

Extracting the Value of “Big Data” in Aircraft Operations

Moderator: Dave Jesse, CEO and Founder, Flight Data ServicesPanelists: Billy Nolen, Senior Vice President Safety, Security and Operations, A4A Andrew Sage, Account Director (Airlines and Airspace Users) NATS UK Christopher Solan, Senior Product Manager, GE Aviation Digital

Solutions Jonathan Tree, Director of Aviation and Regulatory Standards,

International and Industry Relations, Boeing/Jeppesen

Summary

Probably: We have lots of data but not the volumes or

complexity of many Big Data systems We can adopt Big Data techniques for aviation Some systems working, more to come

Thank you to the Panel

Jon Tree Christopher Solan Billy Nolen Andy Sage

References Amazon Snowmobile photos from

https://aws.amazon.com/snowmobile/?nc2=h_m1 Jeppesen statue from http://www.grasshoppair.com/2015/02/portrait-

elrey-borge-jeppesen.html [copyright grasshoppair.com] Should be replaced by photo of Jon Tree

Billy Nolen photo from A4A website (high res download) Microphone photo

https://commons.wikimedia.org/wiki/File:Fouad_adan.png

IATA-Led Workshops

Flight Data Connect – Namsan V Insight into IATA ’s Operational Efficiency Tools –

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Conference DinnerSponsored by:

Location: Grand BallroomTime: 19:30

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