A Port Digital Twin Model for Operational Uncertainty Management
Abstract
Lacking information challenges the management of portoperational uncertainty in estimating the situation to support a decision onreactivity planning. This paper applies Digital Twin (DT) to model a replicatedvirtual port operation from a real-world port of Thailand. The proposed DTmodel offers a tool to accelerate generating data of the port operation withconfigurable uncertainty. The model is validated by using generated datafrom the DT model compared with the real-world data. The result shows thatthe DT model produces the same behaviour as the real-world system. Anoutcome of this paper is a DT model eligible to generate port operation datafor later application with machine learning to predict the port capacity underuncertainty to support reactivity planning.
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