America West

1. America West Jared Musil Michal Lang Ryan Schwanz

2. Business Context

3. Background Low fare, full service airline based out of Phoenix, Arizona 90+ destinations across the US, Canada , Mexico, and, Central America Annual revenues of over $1 billion 77 aircraft fleet of Airbus A318, A319, A320, Boeing 737, & 757’s

4. Airline Efficiency • “One of the major factors cited for the success of discount (or no frills) airlines is the quick turnaround of their airplanes, which helps them achieve high airplane utilization.” • Measured as the time between an airplanes arrival and departure • “Long turnaround times decrease revenue-producing flying time while short turnaround times please customers and can increase airlines revenues”

5. Components of turnaround time Airlines have little control over passenger boarding times Passengers expect levels of service corresponding to the airline and level of service they pay for

6. Back-To-Front vs. Outside-In

7. Technical Features

8. Types of Interference Aisle Interference Occur when passengers stowing luggage in overhead bins block other passengers access Seat Interference Occur when passengers seated close to the aisle block other passengers seated in the same row

9. Case Work Outside-In passenger enplane/deplane simulation Effective for United but abandoned Board each customer individually by row and seat Claimed to cut total boarding time in half Half-row boarding Splits cabin into a starboard and port side

10. Methodology • Optimize • Implement • Simulate • Refine • Fine tune • Analyze

11. Optimization Model Partnered with Arizona State University industrial engineering department Objective: Minimize expected boarding interferences Assumption: Lower passenger interferences correlates to lower boarding times Questions: What is the optimal number of boarding groups?

12. Simulate Built using ProModel Nonlinear model Quadratic and Cubic terms in the objective function Engine: Mixed Integer Linear Programming Uses a heuristic approach (self learning) No guarantees that a global solution will be found

13. Refine & Constrain Implementation limits Several passengers traveling together Interference weights Some take longer than others Practical factors Gate agent processing speed

14. Analyze Seat interference match model predictions  Aisle interferences do not match predictions  Reverse pyramid interference gains eventually plateau Suggests alternate optimal or even superior solutions exist

15. 6.7 minutes → Fine-Tune Collected data to improve model using cameras Results

16. Implement Pilot program at LAX • Used reverse pyramid with six boarding groups • Validate and fine tune the results of the analysis Then system wide • Implemented in 80% of its airports in September 2003 • Las Vegas had a infrastructure constraint stemming from boarding passes

17. Conclusion Average savings: One gate attendant = 26% Two gate attendants = 39% Boarding times of 60 seconds or less were achieved with a 95% confidence interval An average decrease in departure delays of 21% was observed in the first three months after adopting the new boarding strategy America Wests largest hub decreased boarding time delays decreased by 60.1%

18. Additional Benefits Airline customers can easily understand when to queue up for boarding Simpler boarding process for airline agents Special seating for bulkhead seats now available

19. Questions? Thank You