SEAIMar 14, 2025

Towards a Digital Twin Modeling Method for Container Terminal Port

arXiv:2503.13511v14 citationsh-index: 2KES
Originality Synthesis-oriented
AI Analysis

This addresses inefficiencies in container terminal operations for managers and operators, but it is incremental as it applies an existing digital twin concept to a specific domain.

The paper tackled the problem of enhancing productivity and minimizing non-productive movements in container terminal yards by implementing a digital twin-based methodology, resulting in improved efficiency through simulation that reduced unproductive movements.

This paper introduces a novel strategy aimed at enhancing productivity and minimizing non-productive movements within container terminals, specifically focusing on container yards. It advocates for the implementation of a digital twin-based methodology to streamline the operations of stacking cranes (SCs) responsible for container handling. The proposed approach entails the creation of a virtual container yard that mirrors the physical yard within a digital twin system, facilitating real-time observation and validation. In addition, this article demonstrates the effectiveness of using a digital twin to reduce unproductive movements and improve productivity through simulation. It defines various operational strategies and takes into account different yard contexts, providing a comprehensive understanding of optimisation possibilities. By exploiting the capabilities of the digital twin, managers and operators are provided with crucial information on operational dynamics, enabling them to identify areas for improvement. This visualisation helps decision-makers to make informed choices about their stacking strategies, thereby improving the efficiency of overall container terminal operations. Overall, this paper present a digital twin solution in container terminal operations, offering a powerful tool for optimising productivity and minimising inefficiencies.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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