Work Package 3

turnaround, fleet, crew & passengers

Our Challenge

The activities on an aircraft are planned and carried out by different stakeholders. Therefore, often data and operational goals are not disclosed and harmonized and single local decisions can have downstream impacts on optimization possibilities.

In case of a late arrival we want to optimize the effects and costs for the downstream flights. This use case offers a lot of optimization potential by using the partners’ systems, and we are able to generate an amount of solution parameters to support the holistic optimization in this project.

Our Vision and Mission

In this domain aspects of the turnaround at the airport and fleet planning are adressed in a combined manner. Planning and coordinating the aircraft related activities at an airport is important for minimizing the ground time and costs for an aircraft as well as the detection of network effects.

We want to show what is needed and possible in our domain by integrating such an amount of systems and different planning aspects.

our use cases and Cooperation

TU Dresden – Tournaround Manager GMAN 2.0
Goal: Determine stochastic Off-block times under inclusion of available resources and detection of the speeding-up potential by suitable measures

Diehl Aerospace in cooperation with TU Braunschweig – TurnaroundOptimizer
Goal: Precise detection of failure events in the cabin and efficient usage of resources to minimize delays in turnaround

Jeppesen – Taxioptimizer and Crew Manager 
Goal: Early detection of unexpected taxi times based on historical data; efficient crew planning

DLR – Airport Net Performance Display
Goal: Calculation of performance key indicators for airports in the network as additional information for local decisions

INFORM – Network-wide Cost Model
Goal: Early detection of network-wide (subsequent) costs and suitable measures to reduce these for rebooking, crew, fuel etc.

Fraunhofer-FKIE – De-Icing System
Goal: Determine available de-icing resources

Friedrich-Alexander-University Erlangen-Nurnberg (FAU) – Tail Assignment
Goal: Calculation of tail assigning under robustness, minimal delay