Big Data Analytics for Industrial Process Control

被引：0
|
作者：
Khan, Abdul Rauf [1 ]
Schioler, Henrik [1 ]
Kulahci, Murat [2 ,3 ]
Knudsen, Torben [1 ]
机构：
[1] Aalborg Univ, Dept Elect Syst, Aalborg, Denmark
[2] Tech Univ Denmark, Dept Appl Math & Comp Sci, Lyngby, Denmark
[3] Lulea Univ Technol, Lulea, Sweden
来源：
2017 22ND IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA) | 2017年
关键词：
Big data analytics for industrial process; Cloud Computing; Data Mining; Genetic Algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Today, in modern factories, each step in manufacturing produces a bulk of valuable as well as highly precise information. This provides a great opportunity for understanding the hidden statistical dependencies in the process. Systematic analysis and utilization of advanced analytical methods can lead towards more informed decisions. In this article we discuss some of the challenges related to big data analysis in manufacturing and relevant solutions to some of these challenges.
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页数：8
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