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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
