In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for
material flow and accountability. The queuing model employed in our study is based on discrete-event simulation and
processes various types of cargo simultaneously. Onsite measurements are collected in an airport facility to validate the
queuing model. The overall performance of the aviation security cargo inspection system is computed, analyzed, and
optimized for the different system dynamics. Various performance measures are considered such as system capacity,
residual capacity, throughput, capacity utilization, subscribed capacity utilization, resources capacity utilization,
subscribed resources capacity utilization, and number of cargo pieces (or pallets) in the different queues. These metrics
are performance indicators of the system's ability to service current needs and response capacity to additional requests.
We studied and analyzed different scenarios by changing various model parameters such as number of pieces per pallet,
number of TSA inspectors and ATS personnel, number of forklifts, number of explosives trace detection (ETD) and
explosives detection system (EDS) inspection machines, inspection modality distribution, alarm rate, and cargo closeout
time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted
performance measures should reduce the overall cost and shipping delays associated with new inspection requirements.