Towards Digital Twins of Multimodal Supply Chains

Abstract

Both modern multi- and intermodal supply chains pose a significant challenge to control and maintain while offering numerous optimization potential. Digital Twins have been proposed to improve supply chains. However, as of today, they are only used for certain parts of the entire supply chain. This paper presents an initial framework for a holistic Digital Supply Chain Twin (DSCT) capable of including an entire multimodal supply chain. Such a DSCT promises to enable several improvements all across the supply chain while also be capable of simulating and evaluate several different scenarios for the supply chain. Therefore, the DSCT will not only be able to optimize multi- and intermodal supply chains but also makes them potentially more robust by identifying possible issues early on. This paper discusses the major requirements that such a DSCT must fulfil to be useful and how several information technologies that matured in recent years or are about the mature are the key enablers to fulfil these requirements. Finally, a suggested high-level architecture for such a DSCT is presented as a first step towards the realization of a DSCT, as presented in this work

Digital Twins for Ports: Derived from Smart City and Supply Chain Twinning Experience

“…"A DSCT acts as a tool for decision-makers in logistics and supply chain management to holistically improve logistics performance along the whole customer order process through data-driven decision-making" [48]. "A digital twin gives analysts the possibility of experimenting with the SC's computer prototype to test what-if scenarios and quantify the effects of changes" [47].…”

“…Interaction, Simulation, Realtime planning, Visualization, Collaboration [46], [48], [47], [49] Built Environment "An integrated software solution to manage static and dynamic information of a built asset across its lifecycle phases. It usually provides a realistic digital representation of the physical asset, generated by enriching the geometric or graphical data with support from building automation systems (BAS), sensors, internet of things (IoT) components, and other feedback systems informing about the asset, its occupants, or its environment" [50].…”

“…In the context of supply chains, ports are often described as nodes in the transport chain of supply chains that connect organizational, logistics, and information networks to facilitate the seamless flow of goods [91]. The coordination of transport chains requires the synchronization and coupling of numerous consecutive transport and transshipment processes carried out by a multitude of actors such as freight forwarders, terminal operators, port authorities, shipping companies and railroad companies [48]. Ports and container terminals enable ports to add value to the cargo that passes through them, for example, ports can contribute to sourcing and pre-assembly activities [92].…”

“…For a complex supply chain such as the maritime chain with a complex hinterland transportation structure, a DSCT can have many advantages. The DSCT could, among other things, (1) predict delivery times using machine learning from previous transports of goods through the supply chain, (2) identify the limits and bottlenecks of the supply chain by simulating different scenarios and workloads of the existing transport network, and (3) determine the most cost-effective measures to save energy or money through better collaboration and by making the best use of existing resources [48].…”

Exploring the Potentials of Automation in Logistics and Supply Chain Management: Paving the Way for Autonomous Supply Chains

“…These new ways of exchanging and processing data also make the digital twin technology a promising one for the automation of informational processes. The authors of this article [16] outlined the necessity of digital twins in future supply chains and dove deeper into the conceptualization of a framework for a holistic digital supply chain twin of multimodal supply chains that seeks to include an entire multimodal supply chain and enables new simulation and evaluation opportunities. The intended approach would also enable early risk detection and mitigation in order to create more robust networks.…”