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• W2722925682 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." @default.
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• W2722925682 date "2017-01-01" @default.
• W2722925682 modified "2023-10-05" @default.
• W2722925682 title "The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems" @default.
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• W2722925682 doi "https://doi.org/10.1016/j.promfg.2017.04.043" @default.
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