Digital Twin-Driven Smart Production, Logistics, and Supply Chains

Dear Colleagues,

Recently, the three main goals for smart operations have been outlined as (a) human-centric, (b) resilience, and (c) sustainability. To achieve these, digital twins (DTs) continue to attract significant attention as a core operational technology. The DT has emerged as one of the most representative technologies for smart operations across various industrial sectors, which involve production, logistics, and supply chains. The DT can be defined as an advanced virtual asset that represents a configuration of physical assets, reflects complex and heterogeneous functional units, and synchronizes static and dynamic information objects derived from the physical assets. Through vertical and horizontal integrations, the core technical functionalities of the DT include monitoring, control, simulation, visualization, diagnosis, and predictive analysis. Moreover, the ideal implementation and application of DTs is essential for the construction of cyber-physical systems in diverse industrial sectors.

Numerous studies on DTs have been proposed to elaborate on human-centric, resilience, and sustainable operation perspectives. These studies contain efficient models, frameworks, methods, and supportive algorithms. Although existing studies have facilitated the implementation and application of DTs, there are massive opportunities and necessities to improve and extend such research. In the areas of production, logistics, and supply chains with human-centric, resilience, and sustainability perspectives, studies on DTs must be improved to accomplish self-configuration and fulfil autonomous operation to industrial assets. In addition, there are difficulties of federations between DTs in multiple systems that include several stakeholders and necessities of the efficient processing, management, and synchronization of an enormous amount of heterogenous information elements.

For these reasons, this Special Issue aims to present novel models, frameworks, methods, and supportive algorithms related to DTs as the core operational technology in areas of production, logistics, and supply chains.

We invite papers that address, but which are not limited to, the following topics:

• Advanced and event-driven simulations using digital twins.
• Asset descriptions for the synchronization of digital twins.
• Conceptual models and architectural frameworks to support digital twins in production, logistics, and supply chains.
• The coordination of new emerging technologies for the implementation of digital twins.
• Data-driven modeling and simulation of digital twins.
• Digital twins for human–robot collaborations, ergonomic analyses, and human-centric operations.
• Digital twins for material handling devices (e.g., autonomous mobile robots, delivery drones, industrial robots, etc.)
• Digital twins for resilient operation control and business processes.
• Digital twins for sustainable operations in industrial systems (e.g., manufacturing systems, warehouses, distribution centers, etc.)
• Industrial applications the digital twins as real-world case studies.
• Information aggregation, fusion, and synchronization methods for digital twins.
• Supportive rules and algorithms for the implementation and application of digital twins.

Prof. Dr. Sang Do Noh
Dr. Kyu-Tae Park
Guest Editors

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• cyber-physical system (CPS)
• digital twin
• operational technology
• smart production
• smart logistics
• smart supply chain