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/).
Cite this article
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 -