Event Details

Data driven approaches for predicting air cargo turnaround times

Cargo airlines typically operate on a tight schedule to maximize flight hours and thereby aim to minimize the time spent on ground, which is also known as the turnaround time. The turnaround process comprises all operations to prepare the aircraft for its next flight. When the actual turnaround time deviates substantially from the time originally scheduled, the consequences can be severe; the departure of the aircraft may be delayed, and this delay can further propagate to an entire route of consecutive journeys with the same aircraft, resources will be used inefficiently, and operational costs can increase. Creating prediction models to forecast the aircraft turnaround time accurately can help to improve decision making, thus staying within the crew duty time limits as well as adhering to airport timeslots. In the case of passenger aircraft, the turnaround process is well studied in academic literature. However, despite its importance, air cargo turnarounds have thus far received much less attention. The aim of our research is therefore to develop a better understanding of cargo aircraft turnaround times and to explore the potential use of data driven approaches to predict the duration of future turnarounds.