The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems ☆

By T. Uhlemann, C. Schock, Christian Lehmann, S. Freiberger, R. Steinhilper. 2017

414 citations recorded by the source corpus.

Abstract The acquisition of data and the development of different options in production system and factory planning requires up to 2/3rds of the total needed time resources. The digitization of production systems offers the possibility of automated data acquisition. Nevertheless, approaches concerning fully automated data acquisition systems are not widely spread among SME (small and medium sized enterprises). On the one hand, this is caused by the heterogeneous databases, on the other hand by insufficient data processing systems. Furthermore, the advantages of The Digital Twin are not sufficiently known due to the lack of competence in SME concerning matters of Industry 4.0. In order to transfer knowledge about the benefits of digitalization, the development of demonstrating platforms is crucial. This paper introduces a learning factory based concept to demonstrate the potentials and advantages of real time data acquisition and subsequent simulation based data processing. Therefore, an existing learning factory will be upgraded regarding both, multi-modal data acquisition technologies as well as a locally independent optimization environment. Thereby the requirements of SME concerning flexible, easy to use, scalable and service oriented digitization applications are met. The approach is part of a concept for the realization of a Cyber Physical Production System (CPPS) in SME that ensures the development of an image of the production with the aid of a multi-modal data acquisition.

Subfields: Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/188ee5a7071ea95839d0a8ad27ee2db438098261

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In Industrial and Manufacturing Engineering

Citations in the corpus

Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop (2018, background): “The critical challenge of this twining is the real-time monitoring and synchronizing data (Uhlemann et al. 2017).”
A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications (2019, background): “Precisely, Uhlemann et al. [68], Uhlemann [69], while working on the realization of a Cyber Physical Production System, identiﬁed real time multi-modal data acquisition, and subsequent simulation-based data processing, as important factors allowing cyber-physical synchronization.”
A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line (2017, methodology): “A critical gap towards the twinning between the physical world and a virtual model is the real-time monitoring data synchronization for a digital twin in the design [39], which is realized by two major steps: 1) build the real-time communication between equipment through constructing both physical i”
Digital Twin for rotating machinery fault diagnosis in smart manufacturing (2018, methodology): “Multi-modal data acquisition is integrated into a Digital Twin model to realise the cyber-physical production system (Uhlemann et al. 2017).”
Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020, background): “For example, in [131], a practical example in the context of cyber physical production system is given.”
Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system (2019, background): “The ‘‘ twinning ’’ between the physical world and a virtual model is a real-time monitoring data synchronisation for the digital copy of one system (Uhlemann et al. 2017), which is realised by: (1) building the communication between equipment and system through industrial Ethernet; and (2)…”
Digital Twin in Industry: State-of-the-Art (2019, background): “In this way, it realized the effective production control in real time [43].”