COVID-19 arrived in the world suddenly and unexpectedly. It caused major disruptions at economical, operational and other levels. In the case of flight traffic, the operations were reduced to 10% of their original levels. The question after COVID-19 is how to restart the operations and how to keep the balance between safety and capacity. In this paper we present an analysis using simulation techniques for understanding the impact in a security area of an important airport in Latin America; the airport of Mexico City. The results allow to illustrate the potential congestion given by the implemented covid-19 restriction, even when the traffic recovers only by 25% of the pre-covid-19 traffic. The congestion can be mitigated by applying some layout changes (snake queue vs parallel queue) and when more capacity is added to the system (extra security line). The results will raise situational awareness for airport stakeholders when implementing the actions suggested by different international institutions like WHO, IATA or ICAO.
This research aims to find relevant evidence on whether there is a link between air capacity management (ACM) optimization and airline operations, also considering the airline business model perspective. The selected research strategy includes a case study based on Paris Charles de Gaulle Airport to measure the impact of ACM optimization variables on airline operations. For the analysis we use historical data which allows us to evaluate to what extent the new schedule obtained from the optimized scenario disrupts airline planned operations. The results of this study indicate that ACM optimization has a substantial impact on airline operations. Moreover, the airlines were categorized according to their business model, so that the results of this study revealed which category was the most affected. In detail, this study revealed that, on the one hand, Full-Service Cost Carriers (FSCCs) were the most impacted and the presented ACM optimization variables had a severe impact on slot allocation (approximately 50% of slots lost), fuel burn accounted as extra flight time in the airspace (approximately 12 min per aircraft) and disrupted operations (approximately between 31% and 39% of the preferred assigned runways were changed). On the other hand, the comparison shows that the implementation of an optimization model for managing the airport capacity, leads to a more balanced usage of runways and saves between 7% and 8% of taxi time (which decreases fuel emission).
Deze publicatie presenteert de resultaten van het Smartest Connected Cargo Airport Schiphol (SCCAS)-project: een tweejarig onderzoek naar logistieke innovaties die de concurrentiepositie van Schiphol op de luchtvrachtketen versterken. In dit project hebben KLM Cargo, Schiphol Nederland, Cargonaut, TU Delft en Hogeschool van Amsterdam samen met diverse partijen in de luchtvrachtketen nieuwe inzichten ontwikkeld om het afhandelingsproces op Schiphol te stroomlijnen en de productkwaliteit in temperatuurgevoelige ketens zoals bloemen en farma beter te beheersen.In Europa heeft Schiphol een sterke positie: het is de derde vrachtluchthaven na Frankfurt en Parijs. Door de beperking van het aantal beschikbare slots op Schiphol krijgen andere luchthavens zoals Brussel, Luik en Luxemburg de kans om extra lading aan te trekken. Het is daarom de ambitie van Schiphol zich te ontwikkelen tot de Europese voorkeursluchthaven voor logistiek hoogwaardige goederenstromen zoals e-commerce, farmaceutische producten en bloemen, en zich te onderscheiden door een efficiënt en betrouwbaar afhandelingsproces. Om die positie te bereiken zet Schiphol in op vier concrete innovatiedoelstellingen:- verbetering van transparantie in de keten door het delen van informatie;- inzicht in logistieke prestaties op basis van volledige en betrouwbare data over zendingen;- efficiënte en betrouwbare aan- en afvoer van luchtvrachtzendingen (landside pickup & delivery);- procesverbeteringen in de supply chains van temperatuurgevoelige producten.
