Skip to main content

Smart Turnaround, ETA Prediction and Passenger Flow Pilot

Jeppesen is working together with Boeing and SEA in this replication. The goal of the pilot is to improve aircraft turnaround processes at airports. As one of the key factors for increased operational efficiency is reduced down time of an aircraft, which means less time on ground, the replication pilot focuses on ETA (estimated time of arrival) prediction and airport turnaround.

Within the scope of the replication pilot it is planned to improve the prediction of the estimated time of arrivals at the airport Milano Malpensa by analyzing historical data and thus be able to more precisely predict when an aircraft will be landing. This is one step to improve turnaround planning and to optimize turnaround times.

Another step is to capture and analyze available turnaround data to create situational awareness for the turnaround process. Situational awareness and the availability of the essential data for the turnaround enables optimization and improvement of processes. Furthermore Big Data analysis of historical turnaround data is used to analyze historic turnaround processes and enable the prediction of future turnaround events.

During the replication pilot, outcomes and results of the initial pilot, “smart passenger flow” will be analyzed and applied.