Abstract
Physical Internet (PI) is a new concept to ensure global mobility of physical objects. Conventionally, logistics networks are closed and independent. Under the concept of PI, they are transformed into an open logistics network, providing an efficient way to relocate physical goods to a given place in a short period of time. A hyperconnected city logistics system is conceptualized as the final segment of a PI-network. It uses regional and city hubs as the final leg of last-mile delivery. Inventory at PI-hubs has to be managed efficiently so as to maximize the benefits of PI. This paper proposes a digital twin-based inbound synchronization framework to streamline the operations of a PI-hub in a hyperconnected city logistics system. Digital twins and Internet of Things technologies are proposed for data acquisition and virtualization of real conditions of physical objects, followed by machine learning-integrated models to optimize a joint order fulfillment and replenishment operation in the PI-hubs. Adopting the proposed framework can formulate a Total Inbound Synchronization at three levels: order synchronization, process synchronization and information synchronization. Simulation results show a significant reduction of traveling distance in PI-hubs if the interdependent order fulfillment and replenishment operations are considered as a joint operation. In addition, this paper provides practical implications for logistics service providers to manage information flows within a PI-network driven by digital twins.
Published Version
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