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Architecture for Knowledge Exploration of Industrial Data for Integration into Digital Services

: Weskamp, Jan Nicolas; Chowdhury, Arnab Ghosh; Pethig, Florian; Wisniewski, Lukasz


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Industrial Electronics Society -IES-:
IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020. Proceedings : Online Conference; Tampere, Finland, 10 - 12 June 2020
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-7281-6389-5
ISBN: 978-1-7281-6390-1
Conference on Industrial Cyberphysical Systems (ICPS) <2020, Online>
Conference Paper
Fraunhofer IOSB ()
industry 4.0; Asset Administration Shell; MetaData; OPC UA; Knowledge Exploration; big data platform

Gaining added value from industrial data is a challenging process. It is often unknown which data is available, in what form and what it means. In addition, the infrastructure to integrate the data into appropriate services is often missing. Another challenge is the heterogeneity of solutions, technologies and infrastructure on the shop floor. This paper presents a solution that integrates industrial data based on Industrie 4.0 technologies from the shop floor and provides it to a knowledge platform. The proposed solution is working as autonomous and automated as possible. The existing data and metadata are used to automatically configure and instantiate the components of the platform. Users and Services can interact with the platform to search for required data. To achieve this, components were developed to collect data from the production. Furthermore, there is a knowledge platform where the data is prepared, stored and searched. This platform interacts with a middleware and services so that the data arrives automatically at its desired destination. The solution was evaluated through an implementation, showing that the usage of meta data is enabling a fast and easy integration of data in the digital services for Industrie 4.0.