The Application and Design of Big Data in Operation and Maintenance of Industry 4.0

DOI

10.2991/mmebc-16.2016.373How to use a DOI?

Keywords

Industry 4.0; Operation and Maintenance; Big Data; Architecture Design; Cloud Computing

Abstract

Industry 4.0 system generates vast amounts of data in the Operation and Maintenance process. To explore the value of these data is the key to achieve the goals and values of Industry 4.0. This paper discusses the various application scenarios of Big Data for the Operation and Maintenance process of Industry 4.0, including the predictive maintenance of failures, production optimization, product innovation, supply chain optimization, performance monitoring, quality management and secure handling of information, and other aspects. To achieve the formation of industrial Big Data and its application, the paper designs three-tier architecture of the Big Data management platform including data acquisition, storage, analysis, processing and application service providing which integrates data from disparate systems. Through the effective analysis of these industrial data on the platform, it can achieve the relative business services provided to the users of the Industry 4.0 system. The architecture of the Big Data platform has guided the practice of the Operation and Maintenance in the cooperative enterprises and has significantly increased the efficiency of their Operation and Maintenance works

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiqing Cao
AU  - Shuhai Zhang
PY  - 2016/06
DA  - 2016/06
TI  - The Application and Design of Big Data in Operation and Maintenance of Industry 4.0
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 1845
EP  - 1850
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.373
DO  - 10.2991/mmebc-16.2016.373
ID  - Cao2016/06
ER  -