Data and knowledge mining with big data towards smart production

被引:169
|
作者
Cheng, Ying [1 ]
Chen, Ken [1 ]
Sun, Hemeng [1 ]
Zhang, Yongping [1 ]
Tao, Fei [1 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Big data; Data mining techniques (DMTs); Production management; Smart manufacturing; Statistical analysis; Knowledge discovery; NEURAL-NETWORK; DISPATCHING RULE; YIELD PREDICTION; EXTRACTION; SELECTION; DESIGN;
D O I
10.1016/j.jii.2017.08.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Driven by the innovative improvement of information and communication technologies (ICTs) and their applications into manufacturing industry, the big data era in manufacturing is correspondingly arising, and the developing data mining techniques (DMTs) pave the way for pursuing the aims of smart production with the real-time, dynamic, self-adaptive and precise control. However, lots of factors in the ever-changing environment of manufacturing industry, such as, various of complex production processes, larger scale and uncertainties, more complicated constrains, coupling of operational performance, and so on, make production management face with more and more big challenges. The dynamic inflow of a large number of raw data which is collected from the physical manufacturing sites or generated in various related information systems, caused the heavy information overload problems. Indeed, most of traditional DMTs are not yet sufficient to process such big data for smart production management. Therefore, this paper reviews the development of DMTs in the big data era, and makes discussion on the applications of DMTs in production management, by selecting and analyzing the relevant papers since 2010. In the meantime, we point out limitations and put forward some suggestions about the smartness and further applications of DMTs used in production management.
引用
收藏
页码:1 / 13
页数:13
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