Issue |
MATEC Web Conf.
Volume 304, 2019
9th EASN International Conference on “Innovation in Aviation & Space”
|
|
---|---|---|
Article Number | 04006 | |
Number of page(s) | 8 | |
Section | Systems | |
DOI | https://doi.org/10.1051/matecconf/201930404006 | |
Published online | 17 December 2019 |
Linked Data Architecture for Assistance and Traceability in Smart Manufacturing
1Fraunhofer-Institute for Machine Tools and Forming Technology IWU,
Reichenhainer Straße 88,
09126 Chemnitz, Germany
* Corresponding author: e-mail: marko.friedemann@iwu.fraunhofer.de
** Corresponding author: e-mail: ken.wenzel@iwu.fraunhofer.de
*** Corresponding author: e-mail: adrian.singer@iwu.fraunhofer.de
Traceability systems and digital assistance solutions are becoming increasingly vital parts of modern manufacturing environments. They help tracking quality-related information throughout the production process and support workers and maintenance personnel to cope with the increasing complexity of manufacturing technologies. In order to support these use cases, the integration of information from different data sources is required to create the necessary insights into processes, equipment and production quality.
Common challenges for such integration scenarios are the various data formats, encodings and software interfaces that are involved in the acquisition, transmission, management and retrieval of relevant product and process data.
This paper proposes a Linked Data based system architecture for modular and decoupled assistance software. Its web-oriented approach allows to connect two usually disparate data sets: semantic descriptions of complex production systems on the one hand and high-volume and high-velocity production data on the other hand. The proposed concept is illustrated with a typical example from the manufacturing domain. The described End-of-Line quality assessment on forming machines is used for traceability and product monitoring.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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