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Abstract
Digital twin documents are expected to form a global network of digital twins, a “Digital Twin Web”, that allows the discovery and linking of digital twins with an approach similar to the World Wide Web. Digital twin documents can be used to describe various aspects of machines and their twins, such as physical properties, nameplate information, and communication interfaces. Digital twin is also one of the core concepts of the fourth industrial revolution, aiming to make factories more efficient through optimized control methods and seamless information flow, rendering them “smart factories”. In this paper, we investigate how to utilize digital twin documents in smart factory communication. We implemented a proof-of-concept simulation model of a smart factory that allowed simulating three different control methods: centralized client-server, decentralized client-server, and decentralized peer-to-peer. Digital twin documents were used to store the necessary information for these control methods. We used Twinbase, an open-source server software, to host the digital twin documents. Our analysis showed that decentralized peer-to-peer control was most suitable for a smart factory because it allowed implementing the most advanced cooperation between machines while still being scalable. The utilization of Twinbase allowed straightforward removal, addition, and modification of entities in the factory.
Original language | English |
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Article number | 225 |
Number of pages | 13 |
Journal | Machines |
Volume | 10 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 2022 |
MoE publication type | A1 Journal article-refereed |
Keywords
- architecture
- client-server
- digital twin
- machine-to-machine communication
- P2P
- peer-to-peer
- robot operating system
- ROS
- simulation
- smart factory
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Dive into the research topics of 'Using Digital Twin Documents to Control a Smart Factory : Simulation Approach with ROS, Gazebo, and Twinbase'. Together they form a unique fingerprint.Projects
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MACHINAIDE: MACHINAIDE - Knowledge based services for and optimization of machines
Tammi, K., Ala-Laurinaho, R., Autiosalo, J., Hietala, J., Salminen, P., Yang, C., Mattila, J., Tu, J. & Sahoo, S.
01/10/2019 → 30/04/2023
Project: Business Finland: Other research funding