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Simulation-framework for illicit-goods detection in large volume freight

: Kretschmann, Lutz; Münsterberg, Torsten

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Kersten, Wolfgang (Ed./Hrsg.) ; TU Hamburg-Harburg, Institut für Logistik und Unternehmensführung:
Digitalization in supply chain management and logistics : Smart and digital solutions for an industry 4.0 environment; Hamburg International Conference of Logistics 2017, Hamburg
Berlin: epubli, 2017 (Proceedings of the Hamburg International Conference of Logistics (HICL) 23)
ISBN: 978-3-7450-4328-0
ISBN: 3-7450-4328-6
Hamburg International Conference of Logistics (HICL) <11, 2017, Hamburg>
Conference Paper, Electronic Publication
Fraunhofer IML ()
Maritime security; illicit trade; detection architecture; discrete-event simulation

Innovative non-intrusive inspection technologies can help customs prevent illicit trade in large volume freight. Validation whether technologies fulfill their intended purpose ideally takes place under real conditions. However, constraints limit the number and type of experiments performed during such field trials. Against this background simulation offers the opportunity to evaluate improvements in detection of illicit-goods without interrupting activities on site. A discrete event simulation framework in the context of large volume freight is introduced in this paper. It provides the means to compare alternative detection architectures - combinations of different detection technologies – regarding their effectiveness in identifying illicit goods in containers while at the same time the flow of goods through security checkpoints can be analyzed. The framework is applied to an exemplary case study comparing a single device detection architecture with a two device system. Results highlight the somewhat counter intuitive logic that adding a second device to the detection architecture either reduces the overall false clear probability at the cost of a higher false alarm rate or vice versa. Further the impact that adding another layer of detection has on the flow of containers through the detection architecture and in particular on process time is discussed. Findings described here are only a first step towards building a comprehensive simulation-framework for illicit-goods detection in large volume freight. Nonetheless, they illustrate how modelling and simulation can help customs identify the optimal use of innovative detection technologies to increase overall security at EU-borders.