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On an airport, numerous activities are going on in parallel: aircrafts departing and landing, passengers checking in, luggage being loaded, … They depend on each other and there is only little tolerance for delays. Every delay will have consequences for the subsequent activity. On top of that there might arise additional disturbances such as lonely luggages or the need for de-icing (further slowing down the processes).

The person responsible for the management of all these activites is the airline operator. She has to collect all information needed in order to make the best decision.


Currently the data are spread across different systems and tools. Therefore, the collecting process is extensive and inefficient.
(At the same time decisions have to be made quickly as acceptable time slots are quite narrow.)


Opstimal wants to combine the different data sources within one data platform in order to
a) provide more quickly a better understanding of the current situation for the Airline Operator.
b) suggest the best options using a holistic optimizing algorithm that can be adapted to personal priorities.


In order to bring together the spread data of diverse subsystems these subsystems must be understood. This is what happens in work packages 1 to 3: withing the aviation domains flight plan & trajectory, maintenance and turnaround & crew the most important use cases are detected, data is collected and analysed.

In parallel, an algorithm is developed within work package 4 that holisticly optimizes the combined data of the subsystems.