Small Fleet Airline Maintenance Planning Optimization through Collaborative Predictive Modeling

Small fleet airlines have significant maintenance inefficiencies due to isolated operational data, leading to unproductive maintenance planning, increased costs, and frequent unscheduled events. The praxis proposes a predictive reliability model leveraging collaborative data inputs at the fleet-wide level by multiple airlines in order to advance maintenance interval (MI) accuracy and mean time between failures (MTBF) prediction. Using data from two airlines, a 45-aircraft airline, and a 250-aircraft airline, regression analysis was employed to compare a traditional single-airline data model with a fleet-wide collaborative model. The results indicate that fleet-wide models improved MI prediction accuracy by 8.53%, reduced unscheduled maintenance events by 8.58%, and reduced maintenance hours by 9.72% annually. The findings confirm the hypothesis that collaborative data sharing enhances airline maintenance planning efficiency and provides a solution for small fleet operators to achieve maintenance cost savings.

Author

• Perera Amaratunge, Anton

Language

• en

Date created

• 2025

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Engineering Management

Degree

• D.Engr.

Advisor

• Small, Stanley

Committee Member(s)

• Schlegelmilch, Barret
• Heine, Karen

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/tq57ns12k