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  4. Direct handling between vessels and trucks: skipping storage of containers at seaport terminals
 
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Direct handling between vessels and trucks: skipping storage of containers at seaport terminals

Citation Link: https://doi.org/10.15480/882.16185
Publikationstyp
Conference Paper
Date Issued
2025-10-18
Sprache
English
Author(s)
Nellen, Nicole  orcid-logo
Maritime Logistik W-12  
Kastner, Marvin  orcid-logo
Maritime Logistik W-12  
Jahn, Carlos  orcid-logo
Maritime Logistik W-12  
TORE-DOI
10.15480/882.16185
TORE-URI
https://hdl.handle.net/11420/58911
Citation
21. ASIM-Fachtagung Simulation in Produktion und Logistik 2025
Contribution to Conference
21. ASIM-Fachtagung Simulation in Produktion und Logistik 2025  
Publisher DOI
10.25368/2025.239
Publisher
Technische Universität Dresden, Professur für Technische Logistik
ISBN of container
978-3-86780-806-4
Container yards are increasingly becoming bottlenecks at the terminals. To address this, new approaches are needed. One way to redesign processes at the terminal is the direct handling of containers on the seaside. This study employs a discrete-event simulation model to analyse the effects of delayed truck arrivals on quay crane productivity during direct handling between vessels and trucks. In this context, direct handling of containers refers to the loading and unloading of containers between vessels and trucks without intermediate storage in the container yard. A simulation model using Tecnomatix Plant Simulation replicates a terminal employing both conventional and direct handling, examining various truck delay scenarios. Results indicate that minor truck delays mildly affect quay crane productivity, whereas significant delays considerably diminish productivity, especially when a larger share of containers is handled directly. Although direct handling offers efficiency potential, delayed trucks pose significant planning challenges. Future research will aim to develop strategies to mitigate these impacts, such as flexible export container loading sequences.
Subjects
Simulation
Künstliche Intelligenz
Modellierung
Optimierung
Containerlager
Ereignissimulationsmodell
Artificial Intelligence,
Modelling
Optimisation
Container storage facility
event simulation model
DDC Class
388: Transportation
519: Applied Mathematics, Probabilities
658.5: Of Production
Lizenz
https://creativecommons.org/licenses/by/4.0/
Publication version
publishedVersion
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