Architecture, application and implementation of a digital twin of the RFID-enabled material flow in real-time for automotive intralogistics

Abstract

RFID is used in logistics in the automotive industry to automate processes and optimize material flow. However, the data generated by RFID installations during operation offers more potential for further analyses in order to benefit even more from the technology. Therefore, in this paper the data will be used to generate a digital twin of the RFID-enabled material flow (DTRMF) in real-time and to program various big data analyses. The architecture of the DTRMF has to fulfill various qualitative requirements. Since the big data and digital twin architectures available in literature do not fulfill optimally all of these requirements or are not described in enough detail to be applicable, this paper presents a new digital twin architecture for the RFID-enabled material flow. This architecture consists of the data ingestion layer, data processing and analyses layer, data storage layer, visualization layer and the optional semantic layer. In addition, suitable technologies for the implementation of the architecture are described and the feasibility of the architecture was demonstrated and verified by means of a case study.