How To Improve Your Aviation Efficiency

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Lee Kelly
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1 ATM Collaborative Research in Latin America CANSO Feb 13 The information contained in this document is GE proprietary information and is disclosed in confidence. It is the property of GE and shall not be used, disclosed to others or reproduced without the express written consent of GE, including, but without limitation, it is not to be used in the creation, manufacture, development, or derivation of any repairs, modifications, spare parts, designs, or configuration changes or to obtain FAA or any other government or regulatory approval to do so. If consent is given for reproduction in whole or in part, this notice and the notice set forth on each page of this document shall appear in any such reproduction in whole or in part. The information contained in this document may also be controlled by the U.S. export control laws. Unauthorized export or re-export is prohibited.

2 I find out what the world needs, then I proceed to invent it. -Thomas Edison, Founder, General Electric GE Aviation

3 If I had asked my customers what they wanted, they would have said A faster horse Henry Ford 3 GE Aviation

Surface and airspace congestion Efficiency = Deal with the

4 Collaborative Research in Brazil DECEA Request: ID bottlenecks & improvements Growing air traffic demand Surface and airspace congestion Efficiency = Deal with the growing demand Reduce operating costs Reduce environmental impact GE Aviation

5 ICAO forecasts.8% annual traffic growth in LatAm to 5 Number of departures / year expected to increase from 5M in 5 to 5M+ in 5 Source: Long-term Traffic and Aircraft Movement Forecasts, International Civil Aviation Organization, 5 GE Aviation

6 Flight costs Capacity <-> Demand Motivation Expanded Infrastructure New Technologies Per seat cost reduction Growth / Expansion Rationalization Cost Current technology & infrastructure limits 6 GE Aviation

7 Objectives Measure Analyze ID Improvements 7 GE Aviation

8 Collaboration leading to innovation Exchange of knowledge ANSPs Airports Exchange of ideas Operators 8 GE Aviation

File: BrazilDemoV1_baselinemetrics Sheet: Plan Baseline 6 6 DepartureDist 6 EnrouteDist 3 1 ArrivalDist 3 1 6 8 1 1 1 DepartureTime 8 6 6 EnrouteTime 3 1 1 1 16 18 ArrivalTime 3 1 15 5 3

9 File: BrazilDemoV1_baselinemetrics Sheet: Plan Baseline 6 6 DepartureDist 6 EnrouteDist 3 1 ArrivalDist DepartureTime EnrouteTime ArrivalTime DepartureFuel 6 6 EnrouteFuel 3 1 ArrivalFuel Measure, Analyze, Improve GE Efficiency Analysis Airline Data (FOQA, Netline) Visualization Metrics Playback Control Generate Scenario Modeling & SImulation ATC Weather Airline Ops Flow Control Airspace, Airport Data Surface Gates Airspace Sequencing

10 Model existing operations Airports Airways & routes Sector boundaries TMA, Enroute and area control modeled 1 September 1

11 Model existing operations SIDs, STARs & arrival procedures at all airports Including RNP AR arrivals at SDU Detailed airport model Runways, taxiways, gates and parking spots 11 September 1

12 Airspace analysis & efficiency model

13 Conclusion Innovation and technical advancement have been at the core of GE since its founding New technologies and processes needed to deal with increasing traffic levels in an environmentally and socially responsible manner GE Global Research collaborating with ANSPs and operators Evaluating existing operations Identifying promising new technologies and operations Both current and future traffic patterns

15 AIRPORT DATA Brazil collaborative research objectives System capacity Controller Workload Demand vs. Capacity Separation Statistics Fuel Costs Delay MEASURE OPERATIONS ANALYZE PERFORMANCE ID POSSIBLE IMPROVEMENTS RNP Arrival Management Flow Management Surface Management passenger traffic AIRSPACE DATA database AIRLINE DATA time Quantify both current operations and potential changes to identify areas for improved efficiency & capacity recoverable costs base cost

Brazil Airline Efficiency Development Technical Challenges & Proposed Solutions Airlines / ANSP Data Simulation Optimization Development GE

16 Brazil Airline Efficiency Development Technical Challenges & Proposed Solutions Airlines / ANSP Data Simulation Optimization Development GE AETHER Performance Metrics Measure Analyze Decision Support Airlines Controllers Airports Research leads to solutions Improve 16 September 1

AN AIRCRAFT TAXI SIMULATION MODEL FOR THE UNITED PARCEL SERVICE LOUISVILLE AIR PARK. W. Swain Ottman Angela C. Ford Gregory R.

Proceedings of the 1999 Winter Simulation Conference P. A. Farrington, H. B. Nembhard, D. T. Sturrock, and G. W. Evans, eds. AN AIRCRAFT TAXI SIMULATION MODEL FOR THE UNITED PARCEL SERVICE LOUISVILLE AIR