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
  • [31] Use of interactive telephone technology for longitudinal data collection in a large trial
    Russell, Charlotte
    Howel, Denise
    Ward-Platt, Martin P.
    Ball, Helen L.
    CONTEMPORARY CLINICAL TRIALS, 2012, 33 (02) : 364 - 368
  • [32] Memory management for large scale data stream recorders
    Fu, Kun
    Zimmermann, Roger
    ENTERPRISE INFORMATION SYSTEMS VI, 2006, : 97 - +
  • [33] Face Retrieval on Large-Scale Video Data
    Herrmann, Christian
    Beyerer, Juergen
    2015 12TH CONFERENCE ON COMPUTER AND ROBOT VISION CRV 2015, 2015, : 192 - 199
  • [34] An Improved Method for Extracting Rat Cerebrospinal Fluid with Repeatable Large-Scale Collection
    Wang, Limei
    Yang, Wei
    Ran, Yanhong
    Song, Hui
    Yan, Xinxin
    Guo, Jianmin
    VETERINARY SCIENCES, 2025, 12 (01)
  • [35] A Scalable Two-Hop Multi-Sink Wireless Sensor Network for Data Collection in Large-Scale Smart Manufacturing Facilities
    Gao, Cong
    Wang, Zhongmin
    Chen, Yanping
    Tian, Zhenzhou
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2020, 36 (04) : 795 - 819
  • [36] Cost of organ procurement and transplantation network data collection for a large transplant center
    Roberts, JP
    Nikolai, B
    Tomlanovich, S
    AMERICAN JOURNAL OF TRANSPLANTATION, 2003, 3 (10) : 1316 - 1317
  • [37] Consent to data collection: privacy policies and data collection notices
    Piccolo, Daiane Marcela
    Affonso, Elaine Parra
    Sant'Ana, Ricardo Cesar Goncalves
    BIBLIOS-REVISTA DE BIBLIOTECOLOGIA Y CIENCIAS DE LA INFORMACION, 2023, (86): : 220 - 236
  • [38] Large Scale Hierarchical Classification Framework for Network Big Data
    Han, Weihong
    Huang, Zizhong
    Jia, Yan
    PROCEEDINGS OF THE 2015 4TH INTERNATIONAL CONFERENCE ON SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, 2016, 43 : 392 - 396
  • [39] A System for Large-Scale Visualization of Streaming Doppler Data
    Kristof, Peter
    Benes, Bedrich
    Song, Carol X.
    Zhao, Lan
    2013 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, 2013,
  • [40] REUSALBE SOFTWARE ARCHITECTURE PATTERNS FOR WEB BASED DATA COLLECTION SYSTEMS SUPPORTING LARGE-SCALE HUMAN SUBJECTS RESEARCH WITH SUBSTANIAL REPORTING REQUIREMENTS
    Brymer-Bashore, Jeffrey B.
    PSYCHOLOGY AND PSYCHIATRY, SOCIOLOGY AND HEALTHCARE, EDUCATION, VOL II, 2015, : 849 - 862