Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/317829 
Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Journal of Intelligent Manufacturing [ISSN:] 1572-8145 [Volume:] 35 [Issue:] 8 [Publisher:] Springer US [Place:] New York, NY [Year:] 2023 [Pages:] 3815-3836
Verlag: 
Springer US, New York, NY
Zusammenfassung: 
The existing logistics practices frequently lack the ability to effectively handle disruptions. Recent research called for dynamic, digital-driven approaches that can help prioritise allocation of logistics resources to design more adaptive and sustainable logistics networks. The purpose of this study is to explore inter-dependencies between physical and digital assets to examine how cyber-physical systems could enable interoperability in logistics networks. The paper provides an overview of the existing literature on cyber-physical applications in logistics and proposes a conceptual model of a Cloud Material Handling System. The model allows leveraging the use of digital technologies to capture and process real-time information about a logistics network with the aim to dynamically allocate material handling resources and promote asset and infrastructure sharing. The model describes how cloud computing, machine learning and real-time information can be utilised to dynamically allocate material handling resources to product flows. The adoption of the proposed model can increase efficiency, resilience and sustainability of logistics practices. Finally, the paper offers several promising research avenues for extending this work.
Schlagwörter: 
Cyber-physical systems
Material handling systems
Resilience
Sustainability
Digital interoperability
Deep reinforcement learning
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