Efficient passenger flow is a crucial objective at both small and larger airports. One central part of this is the handling of checked luggage which is influenced by necessary security screening. Within this thesis, these processes are studied at San Luis Obispo County Regional Airport. The underlying problem of the airport is its outbound luggage system which was already suffering from delays prior to Covid-19. Delays were never measured and the bottleneck responsible for them was never identified. However, expected growth in passenger and flight volume necessitates to predict when customer dissatisfaction and extensive luggage delays are inevitable, given that the airport does not plan to change the baggage screening system in the near future.
In order to understand the dependencies within said system, process flowcharts for baggage-related activities are defined and translated into a simulation model. After model verification and validation, scenarios of expanding the flight schedule during different times of the day are tested while monitoring the number of bags failing to be loaded into the respective aircraft in time. Further scenarios of model adjustments are used to monitor how the number of missed bags changes while maintaining an expanded flight schedule. Model adjustments were made by changing single parameters such as the scan time or single resources each.
Simulation experiments have shown that the number of additional flights that can be added to the flight schedule of February 2020 depend on the time of the day. For instance, the current outbound luggage conveyor system’s capacity is sufficient to cover 1 additional early morning flight, and up to 3 afternoon flights. Experiments with model parameter adjustments led to identifying the luggage scanner as the bottleneck of the luggage system, whereas other tested parameter adjustments showed to have minimal impact on the number of missed bags. Since the model’s flight plan can be conveniently adjusted in the connected Excel database, the model could be used as a tactical decision tool for capacity analysis.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-3810 |
| Date | 01 March 2021 |
| Creators | Ott, Marian |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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