1 / 20

Impact of data accuracy on TFM initiatives

Impact of data accuracy on TFM initiatives. Fluctuation in demand leads to : Fewer compressions More revisions Unnecessary extensions Needless delay. LGA 10/16 Example. TMS actively managed program to deliver enough a/c Time Operation Start Time End Time AAR

nate
Download Presentation

Impact of data accuracy on TFM initiatives

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Impact of data accuracy on TFM initiatives • Fluctuation in demand leads to : • Fewer compressions • More revisions • Unnecessary extensions • Needless delay

  2. LGA 10/16 Example • TMS actively managed program to deliver enough a/c Time Operation Start Time End Time AAR 10:17 Original GDP 11:30 17:59 35 12:47 Compression 12:44 17:59 14:03 Extension 18:00 21:59 35 15:10 Revision 14:49 21:59 35/40/32/32/32/32/32/32 18:00 Extension 22:00 1:59 32 21:56 Rev/Ext 23:00 3:59 35 22:27 Rev 23:00 3:59 39 22:46 Compression 22:43 0:00 00:23 GDP CNX

  3. GDP Deliver Hour Rate Tower Cnt 1100 35 38 +3 1200 35 39 +4 1300 35 41*+6 1400 35 43 +8 1500 35,40 34 = 1600 32 37 +5 1700 32 25 -7 1800 32 40 +8 1900 32 34 +2 2000 32 36 +4 2100 32 27 -5 2200 32 34 +2 2300 39 36 -3 0000 39 34 -5 *includes double count for 3 go-arounds

  4. Prior to 1800 extension • Arrival demand “a little light for 1700 hour” • No action taken to increase so they could try to “get LGA out of their departure delays” • Program delivering at AAR for rest of program hours • Extension necessary

  5. 1800 Plan - extension until 0159 • Arrivals at or above AAR for next 4 hours • Departures still backed up

  6. Just 45 minutes after 1800 plan • 13 flights Departing Past EDT • 8 out of 37 flights in 1900Z hour or 22% of flights departing late

  7. Dark-greenie Flight List

  8. Late departures spread out - looks okay Large spike of late departures Revision and extension indicated Flights are drifting later in time

  9. 2231 Plan - revise at higher rate • Rate raised to 39 • Revision shifts flights later producing under delivery in 2200 hour • 15 flights departing past EDT – 10 out of 42 in 2300Z (~24%).

  10. GDP CNX at 0023 • Canceled prior to end time of 1800 extension • 2156 extension was unnecessary

  11. Backup

  12. Prior to 1800 extension • Arrival demand “a little light for 1700 hour” • No action taken to increase so they could try to “get LGA out of their departure delays” • Program delivering at AAR for rest of program hours • Extension necessary

  13. 1 hour after extension • Demand above AAR • Delivery fairly smooth • Compression not indicated

  14. After modeled Compression • Savings of 9 minutes on average delay • Spike in demand in 20z • No compression implemented

  15. 2 hours after extension • Compression is not indicated • Revision is indicated

  16. After Modeled Compression • Delay savings of 15 minutes • Increased demand in 22 & 23 hours • No compression this hour

  17. Delay savings by carrier if compression had been run hourly Jean, I don’t think the carrier stats are significant

  18. After modeled revision • Demand at or below AAR from 2200 on • Average delay 160 min • No revision was run at this time

  19. 4 hours after extension • Revision indicated • Extension also indicated

  20. After modeled compression • Delay savings of 11 minutes, average 136 • Increased demand in 2200 & 2300 hours • No compression was run

More Related