A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations]
Background A production line is the basic unit of smart factories and smart manufacturing. However, owing to the development of the industrial Internet of Things, sensors, and other technologies, more data are being collected, leading to a data explosion, and the heterogeneous nature of multiple sou...
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F1000 Research Ltd
2024-06-01
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| Series: | Digital Twin |
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| Online Access: | https://digitaltwin1.org/articles/4-7/v1 |
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| author | Xuesong Mei Zhiyuan Li Zheng Sun Jun Xu Dawei Zhang |
| author_facet | Xuesong Mei Zhiyuan Li Zheng Sun Jun Xu Dawei Zhang |
| author_sort | Xuesong Mei |
| collection | DOAJ |
| description | Background A production line is the basic unit of smart factories and smart manufacturing. However, owing to the development of the industrial Internet of Things, sensors, and other technologies, more data are being collected, leading to a data explosion, and the heterogeneous nature of multiple sources makes it difficult to manage data in a unified manner. Methods A production line data collection, storage, and management system based on cloud-fog-edge computing collaboration and a digital twin was designed. Multi-source heterogeneous data were collected and transmitted based on the OPC UA, and an information model of the production line was established. Modules for data mapping, publishing, and receiving were developed to achieve unified data collection and transmission. The data storage and management platform was constructed by front-end and back-end separation technologies. Results The developed data collection and management system was verified for functionality and performance on a digital twin production line. Functional tests show that the system has the functions of data acquisition and transmission, device addition and viewing, device data querying and downloading, data and model visualization, and user rights setting. The average time for edge data collection and transmission is 183.6ms. The average response time of the cloud for fog requests is less than 1s. This shows that the system can satisfy the real-time requirements of a digital twin production line. Conclusions The proposed system is real-time and stable, providing support for big data and virtual-reality interaction in digital twins. |
| format | Article |
| id | doaj-art-7e7f6c7e34dc471a8da985cfdf9aa6d5 |
| institution | Kabale University |
| issn | 2752-5783 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | Digital Twin |
| spelling | doaj-art-7e7f6c7e34dc471a8da985cfdf9aa6d52024-12-13T01:00:38ZengF1000 Research LtdDigital Twin2752-57832024-06-01419196A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations]Xuesong Mei0Zhiyuan Li1https://orcid.org/0000-0003-3681-3284Zheng Sun2https://orcid.org/0000-0001-9299-5540Jun Xu3https://orcid.org/0000-0001-7255-9952Dawei Zhang4School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, ChinaSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, ChinaSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, ChinaSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, ChinaSchool of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, ChinaBackground A production line is the basic unit of smart factories and smart manufacturing. However, owing to the development of the industrial Internet of Things, sensors, and other technologies, more data are being collected, leading to a data explosion, and the heterogeneous nature of multiple sources makes it difficult to manage data in a unified manner. Methods A production line data collection, storage, and management system based on cloud-fog-edge computing collaboration and a digital twin was designed. Multi-source heterogeneous data were collected and transmitted based on the OPC UA, and an information model of the production line was established. Modules for data mapping, publishing, and receiving were developed to achieve unified data collection and transmission. The data storage and management platform was constructed by front-end and back-end separation technologies. Results The developed data collection and management system was verified for functionality and performance on a digital twin production line. Functional tests show that the system has the functions of data acquisition and transmission, device addition and viewing, device data querying and downloading, data and model visualization, and user rights setting. The average time for edge data collection and transmission is 183.6ms. The average response time of the cloud for fog requests is less than 1s. This shows that the system can satisfy the real-time requirements of a digital twin production line. Conclusions The proposed system is real-time and stable, providing support for big data and virtual-reality interaction in digital twins.https://digitaltwin1.org/articles/4-7/v1Digital twin; Cloud-fog-edge Computing collaboration; OPC UA; Data collection; Distributed storage; Data managementeng |
| spellingShingle | Xuesong Mei Zhiyuan Li Zheng Sun Jun Xu Dawei Zhang A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations] Digital Twin Digital twin; Cloud-fog-edge Computing collaboration; OPC UA; Data collection; Distributed storage; Data management eng |
| title | A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations] |
| title_full | A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations] |
| title_fullStr | A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations] |
| title_full_unstemmed | A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations] |
| title_short | A quick response data collection and management system for digital twin production line based on cloud-fog-edge computing collaboration [version 1; peer review: 2 approved, 1 approved with reservations] |
| title_sort | quick response data collection and management system for digital twin production line based on cloud fog edge computing collaboration version 1 peer review 2 approved 1 approved with reservations |
| topic | Digital twin; Cloud-fog-edge Computing collaboration; OPC UA; Data collection; Distributed storage; Data management eng |
| url | https://digitaltwin1.org/articles/4-7/v1 |
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