Incorporating Gate Variability in Airline Block Planning
•Download as PPTX, PDF•
1 like•920 views
Presentation at AGIFORS SSP May 21, 2013. Reviews variability of gate taxi-out time and how on-time performance improvements can be driven by incorporating taxi variability into block plans.
Recommended
Recommended
More Related Content
What's hot
What's hot (10)
Viewers also liked
Viewers also liked (20)
Similar to Incorporating Gate Variability in Airline Block Planning
Similar to Incorporating Gate Variability in Airline Block Planning (20)
More from Joshua Marks
More from Joshua Marks (19)
Recently uploaded
Recently uploaded (20)
Incorporating Gate Variability in Airline Block Planning
- 1. AGIFORS SSP 2013 Incorporating Gate Operations into Schedule Planning Joshua Marks, CEO +1 703 994 0000 Mobile josh@masflight.com W W W . M A S F L I G H T . C O M
- 2. We used masFlight’s analytics platform All 2012 flight operations for U.S. mainline carriers Gate Characteristics in Schedule Planning New technology makes it possible to incorporate gate variability into schedules Big data can highlight where: • Obstructions or distance drive significantly longer taxi-out times • Other gate factors drive variability that impacts on-time performance
- 3. Block planning is an art based on review of: Taxi-out time history Flight time history Taxi-in history One-time factors Big data enables a more scientific approach with: Departure and arrival gates Competitive dynamics Intra-seasonal weather Tail number differences 0 50 100 150 200 250 5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 155 165 175 185 195 205 215 225 235 CountofFlights Minutes After Gate Departure Taxi-Out, Runway Landing and Gate In Distribution Delta LGA-ATL 2012 Gate Out Landing Time Gate In Block Time Planning: From Art to Science Much more is possible today than just taxi and air time analysis Modal Taxi Out 23 min Modal Gate Arrival 2h 28m
- 4. 0 500 1000 1500 2000 2500 3000 3500 4000 5 15 25 35 45 55 65 75 85 Taxi-Out Time In Minutes United Mainline Taxi-Out from SFO Gates Calendar Year 2012 – All Flights 5 15 25 35 45 55 65 75 Taxi-Out Time in MInutes United Taxi-Out from SFO (2012) Domestic (Blue) vs. Int’l (Red) Domestic International Multiple Factors Affect Taxi-Out Variability Blocked ramp Tugs and tow bars Ground personnel Push-back distance Distance to runway Taxiway factors Construction ATC and pilot skills Taxi speed Concurrent runways Traffic management Weather Flights Flight Type Alone Doesn’t Reveal Underlying Drivers Parsing by flight or mission (domestic, international, fleet) doesn’t tell the full story Parsing operations by flight type doesn’t reveal the drivers
- 5. Gate Variability in Taxi Out Time is Significant United’s SFO Operation: 5 min difference in average taxi-out times by pier West International (Odd gates 91-99) 23.5 minutes East International (Even gates 90-100) 21.3 minutes West Base Domestic (Gates 72-75) 21.0 minutes East Base Domestic (Gates 68-71) 18.1 minutes Outer Domestic Pier (Gates 76-77 and 80, 82, 84, 88) 18.6 minutes Inner Domestic Pier (Gates 81, 83, 85, 87, 89) 20.7 minutes Data from 2012 All UA SFO Operations
- 6. Gate Assignments Matter! UA 760 SFO-JFK 10:45am Departure Gate 80* 19 min Gate 84 20 min Gate 81 22 min Gate 85 23 min At hubs, gate choices drive 5 min differences in taxi-out. Gate choice can determine an on-time arrival for 10% of flights. Gate 82 18 min Gate 83 23 min
- 7. Now consider taxi-out averages at the gate level UA 760 SFO-JFK 10:45am Departure (2012 departures) Airport teams think about operations… But from a passenger-centric perspective. joshrushing.com Many teams plan for consistency in gating, but operational demands shift assignments. Evidence supports that real improvements can result from collaboratively integrating gate allocation into block forecasts.
- 8. 54% 48% 36% 31% 21% LAX MIA ORD DFW JFK American Hubs 43% 42% 34% 33% 22% LGA DTW ATL MSP SLC Delta Hubs 62% 45% 35% 33% 27% 24% 12% SFO O… IAH IAD E… LAX DEN United Hubs 23% 13% 9% 9% BOS JFK LGB FLL JetBlue Focus Cities Significant Variance in Taxi Time by Gate Creates an Opportunity to Improve OTP We reviewed the difference in average taxi-out time at key hubs, measuring the spread between the fastest and slowest gates. 46% 31% 22% 21% 21% 20% 17% BWI LAX M… DAL PHL LAS PHX Southwest Focus Cities Narrow ramps, tight piers and intersections are key drivers of gate-level taxi out variability. Less significant variability observed for Alaska, Frontier, and Virgin America hubs
- 9. Variability + Delays = Opportunity Because behavioral change is needed, focus on hubs where gate adjustments can drive maximum OTP gains. AA-DFW AA-JFK AA-LAX AA-ORD AA-MIA AS-PDX AS-SEA B6-BOSB6-FLL B6-JFK B6-LGB DL-ATL DL-DTW DL-LGA DL-MSP DL-SLC UA-DEN UA-EWR UA-IAD UA-IAH UA-LAX UA-ORD UA-SFO US-CLT US-DCA US-PHL US-PHX WN-BWI WN-DAL WN-LAX WN-LAS WN-MDW WN-PHL WN-PHX FL-ATL F9-DEN NK-FLL VX-LAX VX-SFO 5.0% 7.0% 9.0% 11.0% 13.0% 15.0% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% CRITICALFLIGHTS(SAT+10TO+20) TAXI OUT VARIABILITY AMONG DEPARTURE GATES (Average taxi-out difference, fastest vs. slowest gates) 2012 Comparison: Variability of Departure Taxi-Out Time Among Gates vs. Percent of Critical Flights (Arrival 10-20 mins after scheduled time) Box 3: Block-gate coordination matters: High impact + High variability Box 1: Gates don’t matter (much) Box 2: General Scheduling Issues
- 10. Possible solutions: Taxi faster from the problem gates. Incentives, fuel and maintenance, etc. Allocate flights to gates during planning. Reduce airport discretion in managing flows. Both are viable – but both require cross-functional coordination in the airline
- 11. Food for Thought #1: Taxi Faster! Coordinating with flight operations to increase taxi-out speed when departing specific gates. Southwest does it! -23% -12% -7% -7% -4% -2% -1% 4% 19% 31% -40% -30% -20% -10% 0% 10% 20% 30% 40% Delta US Airways Alaska United Spirit American JetBlue Frontier Virgin America Southwest Relative Taxi Speed (Narrowbodies Only) at U.S. Stations (2012) Versus other airlines at each airport WN averages 31% faster at each airport they serve While Delta lags significantly behind You can change flight and ground behavior • AirTran pilots adopting Southwest practices? • Delta’s taxi-out improvement initiatives are focused on this • Surgical approach BWI-FLL 2009 2010 2011 2012 Average Taxi-Out 13.5 min 13.4 min 13.0 min 12.4 min
- 12. Food for Thought #2: Gate Arbitrage? If you are willing to restrict flights to groups of gates... Then can you shift block time from fast to slow gates? The Concept Divide airport gates into three buckets based on taxi-out times and variability Fastest third: Reduce block times for departures Middle third: No change for departures Slowest third: Increase block times Objective is to keep overall block times neutral and benefit from “fitting the curve” of taxi-out times
- 13. Food for Thought #2: Gate Arbitrage? Method: Restrict flight assignments to specific color boxes – and adjust block times for each color set accordingly. Gate 41 Increase Gate 43 Increase Gate 45 No Change Gate 47A No Change Gate 47B No Change Gate 49A No Change Gate 48A Subtract Gate 46A No Change Gate 42B No Change Gate 42A Increase Gate 40 Increase Gate 48B Subtract Gate 44 Subtract AA LAX T-4
- 14. Food for Thought #2: Gate Arbitrage? If you are willing to restrict flights to groups of gates... Then can you shift block time from fast to slow gates? What we found from applying this method Los Angeles (American) Denver (Frontier) San Francisco (United) 29,000 flights in sample set Low variance of taxi times across gates Shifting 1 minute from best gates to worst drove marginal (< 0.1%) change in on-time arrivals No material benefits. Without variability, no impact. 23,100 flights in sample set Moderate variance of taxi-out across gates Shifting 5 minutes from best gates to worst drove small shift (0.5%) in on-time arrivals Small but tangible gain, but may not be worth the effort. 36,500 flights in sample set High variance of taxi times across gates Same 0.5% gain from neutral block, but surgical block adds can drive 1% gain in OTP Adding block by gate set drives a material gain.
- 15. Food for Thought #2: Gate Arbitrage? If you are willing to restrict flights to groups of gates... Then can you shift block time from fast to slow gates? Conclusions If you have high variability of taxi-out times across gates at a hub, particularly within the same pier And if the number of flights where assigning gates will make a material difference in on-time performance Then assigning flights to specific gate sets and adjusting blocks can potentially drive OTP gains
- 16. Communication is Key How do you persuade… Airport teams to change gate assignment priorities? Flight operations to focus on taxi speed and routes? Management to embrace how big data visibility can address small issues that add up to big OTP changes? It takes focus to coordinate and prioritize at the cross-department level required.
- 17. Conclusions Big Data focuses gate performance Multiyear analysis can focus attention on specific gate problems Define controllable factors & parties Gate issues can be addressed but require cross-functional input Gate taxi variability is material in OTP Five-minute average differences in taxi time in the same pier Low-hanging fruit at key hubs Many critical flights + high gate variability = OTP opportunity Increasing taxi-out speed is one way… Encourage ground and pilot actions to speed push & taxi … block adjustment by gate is another Folding taxi-out time into gate allocation drives improvements Schedule planning should visualize the potential and seek buy-in across flight and airport operations