Air Transport Ground Operations Management: Digital Twin Building Blocks for Real-Time Monitoring and Process Optimization

Transporting billions of passengers and millions of tons of cargo every year, the air transport industry has become a cornerstone of the global economy, with continued growth already forecasted for the coming years. However, the sector must address the complex logistical challenges posed by surging global demand and an increasingly challenging environment. This thesis specifically focuses on ground process operational efficiency, aiming to develop real-time monitoring and optimization strategies for both outbound baggage ground handling and air cargo ground operations. To achieve these objectives, the research draws on real-world data from two major European airport hubs and leverages the innovative technological framework of digital twins, alongside operations research and machine learning techniques.
This thesis first provides a thorough clarification of the digital twin concept before developing its core elements in the context of air transport ground processes. More specifically, it explores the real-world entities, virtual processes, and real-to-virtual connections of the digital twin to optimize the daily coordinated allocation of check-in desks and sorting piers for outbound flights, improve the coordination of cargo ground service vehicles during aircraft turnarounds, and enable real-time monitoring of air cargo ground operations and aircraft (un)loading progress. This is achieved through a combined scientific and practical framework that includes thorough literature reviews, as well as the development of novel mathematical models, original heuristics, and tailored parametrization protocols for existing solution methods.
Ultimately, while contributing substantially to the scientific literature, these developments provide efficient solutions to real-world challenges, expanding baggage handling system capacity, mitigating aircraft delays, and enabling rapid responses to operational disruptions. This thesis therefore provides the air transport industry with the necessary methodological tools to maintain operational efficiency and high service standards despite the rising global air passenger and cargo traffic. In addition, it bridges the gap between the digital twin conceptual framework and its practical application to critical air transport ground processes, fostering a deeper understanding of these complex operations and enhancing the industry’s decision-making capabilities.