IV международный форум

28-30 ноября 2018, Москва

Renaissance Moscow Monarh Centre

ОРГАНИЗАТОР

ЦЕНТР СТРАТЕГИЧЕСКИХ РАЗРАБОТОК В ГРАЖДАНСКОЙ АВИАЦИИ (ЦСР ГА)

ПРИ УЧАСТИИ

ФЕДЕРАЛЬНЫХ ОРГАНОВ ВЛАСТИ

ПАРТНЕР ФОРУМА

АВИАЦИОННЫЙ IT ФОРУМ РОССИИ И СНГ - 2018

ГЕНЕРАЛЬНЫЙ СПОНСОР ФОРУМА

Putting Flight Data to work towards fuel savingsAviation IT Forum for Russia & CIS / Moscow 2018François Chazelle – Partner & CCO

BIG DATA SOLUTIONS FOR SAFETY AND EFFICIENCY OF AVIATION OPERATIONS

FUEL SAVINGS

5-6%

IN CLIMB PHASE

AIRPORTSAFETY & EFFICIENCY

FLIGHT DATA

WEATHER DATA

RADAR DATA

STRATEGIC COMMERCIAL PARTNERSHIPS

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Series A round

FUEL EFFICIENCY ENVIRONMENT

Flight Planning Taxi Take-Off Climb Cruise Descent Landing

is the only solution focusing on the climb phase.

Dashboards:

Confidential - Do not distribute

FMS – AIRCRAFT CENTRIC

60 MHz computations 4 Mb static RAM32 Mb program & Navigation Performance Databases

Generic OEM Performance Model Real Time Partial Weather

FMS:

Generic OEM Performance Model Real Time Partial Weather

OPTI FLIGHT – CONNECTED AIRCRAFT

30 GFlops computations Several Gbs of RAMUnlimited Terabytes of storage

Tail number specific Machine Learning performance models

Accurate 4D Weather Forecast

Real Time Flight Recommendations

FLIGHTOPTIMIZATION

Mainframe Computers:

TAIL NUMBER SPECIFIC PERFORMANCE MODELS

Historical QAR Data for each aircraft

MACHINE LEARNING PERFORMANCE MODEL

Confidential - Do not distribute

OPTIMIZATION OF EACH CLIMBReach the same point in ground distance at the same time with a more efficient trajectory

Fuel consumption Climb time

Ground distanceT° and wind gradients every 1000 ft

CLIMB PROFILE OPTIMISATIONFlight Plan

(Tail number, TOW, TOC, cruise Mach, …)

Confidential - Do not distribute

Confidential - Do not distribute

Fuel flow without OptiClimb

Flight with OptiClimb Flight without OptiClimb

Fuel flow with OptiClimb

Cruise Level

Crossover

FL120

M.76

IAS 300 KTS

IAS 241 KTS

During cockpit preparation SPD REST: 241 / FL120

TGT SPD: 300 / 0.76

Up to 3 OptiClimb speeds vs. 1 ECON Climb speed

ECOFLYING THE AIRCRAFT

Confidential - Do not distribute

DAY TO DAY IMPLEMENTATION

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Flight Plan(Tail numbers, Weights,

Temperature, Winds, Cost Index)

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Optimization(Tail numbers, Weights,

Temperature, Winds, Cost Index)

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Pilot Entryinto FMS / FCU

OptiClimb Climb Profiles

SAVING ANALYSIS - FLIGHT DETAILS

• Two similar flights (20/06/2015 and 23/06/2015)

LEG LEZL (Seville) - LFPO (Paris Orly)

Time 17h

Weight at FL100 64.700 kg

Weather ISA +4° and 10 kt headwind

ISO distance 251 km

ISO altitude FL380

ISO Mach 0.79

Comparison between 2 flights with and without OptiClimb

Confidential - Do not distribute

ALTITUDE

Time (s)

Confidential - Do not distribute

FUEL FLOW

Level off during climb, due to ATC

Time (s)

Fuel

Flo

w (

kg/s

)

Confidential - Do not distribute

OFP INTEGRATION

Confidential - Do not distribute

CREW BRIEFING INTEGRATION

Confidential - Do not distribute

LAUNCH CUSTOMER

« Thanks to OptiClimb, Transavia is nowequipped with the latest technology tothe benefit of its environmental policy.This system does not require anyadditional equipment. It is a quick andeasy way to minimize our ecologicalfootprint. »

Nathalie Stubler,President and CEO, Transavia France

Confidential - Do not distribute

THE SINGLE MOST EFFICIENT FUEL SAVING INITIATIVE

Reserve Fuel

Reduced Altitude Acceleration

Constant Descent

Idle Reverse

Engine out taxi in

48%

16,7%

15,2%

12,8%

5,6%

1,7%

DOUBLETHE SAVINGS

*Assumption for a medium haul fleet

Confidential - Do not distribute

OPTICLIMB SAVINGS

Confidential – Do not distribute

$52,920238 tons

CO2 /YEAR

$/ YEAR

Potential annual benefit across a fleet of

20 Boeing 737NGs

- 70kg average savings per climb - 4 flights /aircraft/ day- 75% adherence rate - average fuel cost of 0.70$ per kg

- 4,760 metric tons / Year of reduction in CO2 emissions

- $ 1,058,400 / Year of fuel savings

OPTI CLIMB SET UPIndividual Performance Models

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OFP link setup

Pilot briefing

Historical QAR Data

Machine Learning

Performance Model for each aircraft

OCC

Flight Plans

OptiClimb Schedules

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3

Confidential - Do not distribute

OPTI CLIMB SET UPIndividual Performance Models

1Historical QAR Data

Machine Learning

Performance Model for each aircraft

MACHINE LEARNING PERFORMANCE MODEL

Last 200 flights of each tail number for the whole fleet

CSV or raw QAR Data with dataframes

Around 20 parameters needed

Can be de-identified if required

Confidential - Do not distribute

OPTI CLIMB SET UP

OFP link setupOCC

Flight Plans

OptiClimb Schedules

2

Webex call with designated IT specialist from the OCC

Potential integration with OFP or EFB supplier solutions

Automate sending of OFPs to Safety Line

Push back OptiClimb Schedules into EFF or Briefing Package

Confidential - Do not distribute

OPTI CLIMB SET UP

Pilot briefing3

Webex call with Chief and/or Technical Pilots

Target is to accumulate up to 1000 flights over a 1-2 month period

Identify group of test Captains for the test phase

2 page instructions including a sample OptiClimb Schedule

Review of safety and operational aspects

Confidential - Do not distribute

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4 customers

28 test airlines worldwide

LCC & Legacy airlines

Total fleet of over 1500 aircraft

Aircraft types :

• A320 Family, A310, A330• 717, 737, 787, 777, 747• CRJ• Ejets

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OPTI CLIMB PRESENCE - 11/2018

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