Large scale MTConnect data collection

被引:0
|
作者
Cui, Yesheng [1 ]
Kara, Sami [1 ]
Chan, Ka C. [2 ]
机构
[1] Univ New South Wales, Sch Mech & Mfg Engn, Sustainable Mfg & Life Cycle Engn Res Grp, Sydney, NSW, Australia
[2] Univ Southern Queensland, Fac Business Educ Law & Arts, Sch Management & Enterprise, Springfield, Australia
来源
PROCEEDINGS OF THE IEEE 2019 9TH INTERNATIONAL CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS (CIS) ROBOTICS, AUTOMATION AND MECHATRONICS (RAM) (CIS & RAM 2019) | 2019年
关键词
MTConnect; NiFi; data collection; large scale;
D O I
10.1109/cis-ram47153.2019.9095828
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:77 / 82
页数:6
相关论文
共 50 条
  • [21] Data Collection from Smart-city Sensors through large-scale Urban Vehicular Networks
    Khan, Muhammad Awais
    Sargento, Susana
    Luis, Miguel
    2017 IEEE 86TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2017,
  • [22] Large Displays and Tablets: Data Exploration and its Effects on Data Collection
    Gorkovenko, Katerina
    Lischke, Lars
    Wozniak, Pawel W.
    NORDICHI'18: PROCEEDINGS OF THE 10TH NORDIC CONFERENCE ON HUMAN-COMPUTER INTERACTION, 2018, : 664 - 675
  • [23] A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks
    Lei, Chunyang
    Bie, Hongxia
    Fang, Gengfa
    Gaura, Elena
    Brusey, James
    Zhang, Xuekun
    Dutkiewicz, Eryk
    SENSORS, 2016, 16 (07)
  • [24] Rechargeable UAV Trajectory Optimization for Real-Time Persistent Data Collection of Large-Scale Sensor Networks
    Wang, Rui
    Li, Deshi
    Meng, Kaitao
    2024 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS, ICC WORKSHOPS 2024, 2024, : 1481 - 1486
  • [25] TOWARDS DATA-DRIVEN SUSTAINABLE MACHINING - COMBINING MTCONNECT PRODUCTION DATA AND DISCRETE EVENT SIMULATION
    Bengtsson, N.
    Michaloski, J.
    Proctor, F.
    Shao, G.
    Venkatesh, S.
    PROCEEDINGS OF THE ASME INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE 2010, VOL 1, 2011, : 379 - 387
  • [26] Large Differences in Time Use for Three Data Collection Systems
    Nelly Kalfs
    Willem Saris
    Social Indicators Research, 1998, 44 : 267 - 290
  • [27] UAV Trajectory Optimization for Large-Scale and Low-Power Data Collection: An Attention-Reinforced Learning Scheme
    Zhu, Yuchen
    Yang, Bo
    Liu, Min
    Li, Zhongcheng
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (04) : 3009 - 3024
  • [28] Total Energy Cost Optimization for Data Collection With Boat-Assisted Drone: A Study on Large-Scale Marine Sensor
    Huang, Xianfei
    Wang, Gaocai
    IEEE ACCESS, 2023, 11 : 134473 - 134484
  • [29] Regional Density-aware Data Collection Using Unmanned Aerial Vehicle in Large-scale Wireless Sensor Networks
    Kim, Eui-Jik
    Choi, Hyo Hyun
    Kwon, Jung-Hyok
    SENSORS AND MATERIALS, 2018, 30 (08) : 1735 - 1742
  • [30] The Unanticipated Challenges Associated With Implementing an Observational Study Protocol in a Large-Scale Physical Activity and Global Positioning System Data Collection
    McCrorie, Paul
    Walker, David
    Ellaway, Anne
    JMIR RESEARCH PROTOCOLS, 2018, 7 (04):