Digital Twin-Assisted Intelligent Logistics and Warehouse Automation

Abstract

As the world has moved into the fourth industrial revolution, the logistics and warehouses have become more and more part of a digital ecosystem, where intelligent technologies are helping companies to reach unprecedented levels of operational efficiency, flexibility and sustainability. Digital Twin (DT) technology has become a game-changer as it enables virtual representations of physical logistics assets, warehouse structures and processes to be created in real-time. Digital Twins, when supported by Artificial Intelligence (AI), the Internet of Things (IoT), cloud computing, and big data analytics, enable predictive monitoring, autonomous decision making, dynamic resource allocation and ongoing process optimisation. This paper provides a thorough overview of Digital Twin-driven intelligent logistics and warehouse automation, discusses recent developments in technology, implementation models, and their industrial applications. The study covers the challenges of embedding IoT connected sensors, autonomous mobile robots, cyber-physical systems, edge-cloud computing, and machine learning algorithms to improve the productivity, inventory control, route optimization, and predictive maintenance of warehouses. Additionally, the paper examines weaknesses of traditional WMS and uncovers existing problems and gaps in the field of scalability, interoperability, cyber security and real-time synchronization. The survey presented in this work shows the importance of Digital Twin as a crucial enabling technology for new generation smart warehouses and for the intelligent supply chain in Industry 5.0, as well as the opportunities for future research in autonomous logistics operations in Industry 5.0.