Reducing operational impact of ATFM delay uncertainty

We use AI to reduce uncertainty and therefore improve airlines’ operations management throughout the day.


To resolve imbalances between demand and capacity the Network Manager imposes regulations, delaying flights on the ground. The length of the ground delay assigned to a regulated flight may change dynamically until departure. This variability in the delay stems from the mechanisms used by the Computer-Assisted Slot Allocation system (CASA) to manage the regulation slots.


The FADE AI module has been developed to reduce this uncertainty and therefore improves airlines’ operations management throughout the day. Trained on historical data, it is fully integrated in CASA and can predict the trend of the delay with an accuracy of 75 % FADE reduces the prediction error by up to 63% when compared to the model without FADE.