Issue |
MATEC Web Conf.
Volume 161, 2018
13th International Scientific-Technical Conference on Electromechanics and Robotics “Zavalishin’s Readings” - 2018
|
|
---|---|---|
Article Number | 03027 | |
Number of page(s) | 6 | |
Section | Robotics and Automation | |
DOI | https://doi.org/10.1051/matecconf/201816103027 | |
Published online | 18 April 2018 |
Ontology-driven approach for describing industrial socio-cyberphysical systems’ components
1
SPIIRAS, 199178, 14th Line, St.Petersburg, Russia
2
ITMO University, 197101, 49 Kronverksky Pr., St. Petersburg, Russia
* Corresponding author: teslya@iias.spb.su
Nowadays, the concept of the industrial Internet of things is considered by researchers as the basis of Industry 4.0. Its use is aimed at creating a single information space that allows to unite all the components of production, starting from the processed raw materials to the interaction with suppliers and users of completed goods. Such a union will allow to change the established business processes of production to increase the customization of end products for the consumer and to reduce the costs for its producers. Each of the components is described using a digital twin, showing their main characteristics, important for production. The heterogeneity of these characteristics for each of the production levels makes it very difficult to exchange information between them. To solve the problem of interaction between individual components this paper proposes to use the ontological approach to model the components of industrial socio-cyberphysical systems. The paper considers four scenarios of interaction in the industrial Internet of things, based on which the upper-level ontology is formed, which describes the main components of industrial socio-cyberphysical systems and the connections between them.
© The Authors, published by EDP Sciences, 2018
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. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.