Large scale MTConnect data collection

Paper


Cui, Yesheng, Kara, Sami and Chan, Ka C.. 2019. "Large scale MTConnect data collection." 9th International Conference on Cybernetics and Intelligent Systems (CIS) and Robotics, Automation and Mechatronics (RAM) (CIS & RAM 2019). Bangkok, Thailand 18 - 20 Nov 2019 Piscataway, United States. https://doi.org/10.1109/CIS-RAM47153.2019.9095828
Paper/Presentation Title

Large scale MTConnect data collection

Presentation TypePaper
AuthorsCui, Yesheng (Author), Kara, Sami (Author) and Chan, Ka C. (Author)
Journal or Proceedings TitleProceedings of the IEEE 2019 9th International Conference on Cybernetics and Intelligent Systems (CIS) Robotics, Automation and Mechatronics (RAM)
Number of Pages6
Year2019
Place of PublicationPiscataway, United States
ISBN9781728134581
Digital Object Identifier (DOI)https://doi.org/10.1109/CIS-RAM47153.2019.9095828
Web Address (URL) of Paperhttps://ieeexplore.ieee.org/document/9095828
Conference/Event9th 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.

KeywordsMTConnect; NiFi; data collection
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
401407. Manufacturing management
Public Notes

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Byline AffiliationsUniversity of New South Wales
School of Management and Enterprise
Institution of OriginUniversity of Southern Queensland
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