Affiliations: [a]
Department of Engineering and Architecture, University of Parma, Parma, Italy
| [b]
Centre of Competence Shopfloor & Vehicle Software, Mercedes-Benz AG, Sindelfingen, Germany
| [c] Faculty of Geomatics, Computer Science and Mathematics, University of Applied Sciences Stuttgart, Stuttgart, Germany
Abstract: RFID is used in logistics in the automotive industry to automate processes and optimise material flow. However, the data generated by RFID installations during operation offer more potential for further analyses to collect even more benefits from the technology. Therefore, in this paper, RFID data will be used to create a digital twin of the RFID-enabled material flow (DTRMF) in real-time and to programme various big data analyses. The architecture of the DTRMF must meet various qualitative requirements. Since the big data and digital twin architectures available in the literature either do not optimally fulfil all these requirements, or they are not described in enough detail to support real applications, this paper presents a new digital twin architecture for RFID-enabled material flow. This architecture consists of the data ingestion layer, data processing and analyses layer, data storage layer, visualisation layer, and the optional semantic layer. In addition, suitable technologies for the implementation of the architecture are described, and the feasibility of the architecture is demonstrated and verified by means of a case study.
Keywords: Digital twin, RFID, logistics, case study, automotive industry
