Abstract
Digital Twins have been in the focus of research in recent years, trying to achieve the vision of Industry 4.0. In the domain of industrial energy systems, they are applied to facilitate a flexible and optimized operation. With the help of Digital Twins, the industry can participate even stronger in the ongoing renewable energy transition. Current Digital Twin implementations are often application-specific solutions without general architectural concepts and their structures and namings differ, although the basic concepts are quite similar. For this reason, we analyzed concepts, architectures, and frameworks for Digital Twins in the literature to develop a technology-independent Generic Digital Twin Architecture (GDTA), which is aligned with the information technology layers of the Reference Architecture Model Industry 4.0 (RAMI4.0). This alignment facilitates a common naming and understanding of the proposed architectural structure. A proof-of-concept shows the application of Semantic Web technologies for instantiating the proposed GDTA for a use case of a Packed-Bed Thermal Energy Storage (PBTES).
Highlights
Digitalization is changing the way business is conducted within industrial value chains, facilitated by the rapid development of communication and information technology [1]
To provide some insights into the capability of our prototypical Digital Twin (DT) implementation, we show the procedure of loading a dynamic thermal model of the Packed-Bed Thermal Energy Storage (PBTES) into the DT, train the model with available data, and use the model for a time-series prediction of the outlet temperature of the PBTES
A novel Generic Digital Twin Architecture (GDTA) based on the 5D-DT concept is presented and evaluated based on a prototypical proof-of-concept implementation
Summary
Digitalization is changing the way business is conducted within industrial value chains, facilitated by the rapid development of communication and information technology [1]. This process is referred to as the fourth industrial revolution or Industry 4.0. The goal is a highly optimized and customized production, as well as enhanced automation and adaption capabilities [2]. To realize these visions of Industry 4.0, the Digital Twin (DT) is one of the most promising enabling technologies [3]. DTs are the key enabler for such applications, as their common functionality includes monitoring, diagnostic, prediction, and control [5]
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