# Identification of Bottlenecks in Passenger Handling Processes Using Data-Driven Tools
## 2 Conceptual Framework and Design Principles of the Simulation Model
After completing check-in, the passenger proceeds to the security screening phase. For the sake of model simplicity, no additional walking time is simulated between check-in and security. Instead, each passenger is immediately assigned to one of four screening stations, based on a sequential distribution logic (i.e., rotating assignment to scanners 1 through 4, in order). This simplifies the allocation mechanism while ensuring balanced system usage. Each security scanner has its own queue, and passengers wait in line only at their assigned station. The service at the scanner is again modeled using an exponential distribution, capturing variability in inspection times due to different passenger profiles or the detection of additional screening needs. As with check-in, the FIFO rule applies within each scanner queue. Once the screening process is complete, the passenger is considered fully processed and exits the simulation, representing entry into the post-security departure zone. The model does not simulate subsequent phases such as boarding, retail interactions, or terminal  
Figure 2: Line chart illustrating the assignment of two service stations to passengers. waiting time, as the focus remains on the critical landslide stages where bottlenecks most commonly occur. This modular structure allows the simulation to reflect realistic process interactions, while remaining computationally efficient and interpretable. The flow logic for each processing block, including condition checks, time updates, and queue transfers, is implemented through Excel formulas and conditional logic, making the model fully traceable and adaptable for further experimentation. The method of assigning check-in desks is illustrated in more detail using a line chart in Figure 2. The model operates with two parallel check-in desks (referred to as Server no. 1 and Server no. 2) and assumes that all passengers arrive for service independently at time intervals T\({}_{1}\), T\({}_{2}\),..., T\({}_{n}\). If at least one station is available, passenger service begins immediately upon their arrival at the station. This is reflected in the timeline by an arrow from the arrival point to the corresponding idle server. However, if both stations are occupied at the moment of arrival, the passenger must wait in a queue until one of the service stations becomes available. Passengers in the queue are indicated by a red \"X\" on the diagram. In the simulation model, service durations for individual passengers are generated stochastically based on an exponential distribution. These values are added to the time of the start of service to determine the time at which the service ends. The model continuously compares the arrival time of the next passenger with the end times of both check-in desks. If one or both servers are free, the earliest available one is selected. If not, the simulation calculates the moment when the next server becomes free and schedules the waiting passenger accordingly. This mechanism replicates the logic of a FIFO queue with dynamic server assignment and enables the tracking of waiting times, queue lengths, and overall utilization of check-in resources under variable input conditions. It is fully implemented using Excel functions and time-based conditions, allowing for transparent simulation flow without the need for external programming.