Large scale MTConnect data collection
Paper
Paper/Presentation Title | Large scale MTConnect data collection |
---|---|
Presentation Type | Paper |
Authors | Cui, Yesheng (Author), Kara, Sami (Author) and Chan, Ka C. (Author) |
Journal or Proceedings Title | Proceedings of the IEEE 2019 9th International Conference on Cybernetics and Intelligent Systems (CIS) Robotics, Automation and Mechatronics (RAM) |
Number of Pages | 6 |
Year | 2019 |
Place of Publication | Piscataway, United States |
ISBN | 9781728134581 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/CIS-RAM47153.2019.9095828 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/9095828 |
Conference/Event | 9th International Conference on Cybernetics and Intelligent Systems (CIS) and Robotics, Automation and Mechatronics (RAM) (CIS & RAM 2019) |
Event Details | Rank C C |
Event Details | 9th International Conference on Cybernetics and Intelligent Systems (CIS) and Robotics, Automation and Mechatronics (RAM) (CIS & RAM 2019) Parent IEEE International Conference on Cybernetics and Intelligent Systems Event Date 18 to end of 20 Nov 2019 Event Location Bangkok, Thailand |
Abstract | Data collection is the first stage of data lifecycle to drive manufacturing activities such as monitoring, prediction and optimization. Data collection at shop floor is more complex since it is affected by both the physical and cyber worlds. Two common issues are: difficult to collect data of various machines which support different interfaces and communication protocols, and hard to analyze inconsistent data. MTConnect provides a standard solution to collect consistent data from various machines and devices. The current MTConnect applications are based on a single computer which is not suitable to collect large-scale MTConnect data. Cloud computing technology can handle this issue easily such as Apache NiFi. In this paper, a NiFi based solution is proposed to address issues of large-scale MTConnect data collection, processing, and long-term storage. The proposed approach also provides a fault tolerant infrastructure for data provenance to ensure historical data integrity for the requirement of enterprise compliance. |
Keywords | MTConnect; NiFi; data collection |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
401407. Manufacturing management | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of New South Wales |
School of Management and Enterprise | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q5z63/large-scale-mtconnect-data-collection
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