Reference Network and Localization Architecture for Smart Manufacturing Based on 5G
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and communication network for smart manufacturing that combines 5G with other existing technologies and focuses on high-mix, low-volume applications, particularly at small and medium-sized enterprises. The architecture is derived from a set of functional requirements, and we describe different views on this architecture to show how the requirements can be fulfilled. It connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many industrial use cases.
Details
Original language | English |
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Title of host publication | Advances in System-Integrated Intelligence - Proceedings of the 6th International Conference on System-Integrated Intelligence SysInt 2022, Genova, Italy |
Editors | Maurizio Valle, Dirk Lehmhus, Christian Gianoglio, Edoardo Ragusa, Lucia Seminara, Stefan Bosse, Ali Ibrahim, Klaus-Dieter Thoben |
Publisher | Springer Science and Business Media B.V. |
Pages | 470-479 |
Number of pages | 10 |
ISBN (electronic) | 978-3-031-16281-7 |
ISBN (print) | 978-3-031-16280-0 |
Publication status | Published - 2023 |
Peer-reviewed | Yes |
Publication series
Series | Lecture Notes in Networks and Systems |
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Volume | 546 LNNS |
ISSN | 2367-3370 |
Conference
Title | 6th International Conference on System-Integrated Intelligence, SysInt 2022 |
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Duration | 7 - 9 September 2022 |
City | Genova |
Country | Italy |
Keywords
ASJC Scopus subject areas
Keywords
- 5G, Adaptive manufacturing, Localization, M2M