Big data processing framework for manufacturing

被引:5
|
作者
Ye, Yinghao [1 ]
Wang, Meilin [1 ]
Yao, Shuhong [1 ]
Jiang, Jarvis N. [1 ]
Liu, Qing [1 ]
机构
[1] Guangdong Univ Technol, Sch Informat Engn, Guangzhou, Peoples R China
关键词
manufacturing; big data; data processing; random forest;
D O I
10.1016/j.procir.2019.04.109
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Data analysis of manufacturing plays a vital part in the intelligent manufacturing service of Product-Service Systems (PSS). In order to solve the problem that, manufacturing companies can't obtain valuable information from enterprise's big data through traditional data analysis methods, this paper put forward a data processing architecture framework and introduce the predictive algorithm (Random Forest). Finally, a real-time prediction of quality under this framework which uses the random forest algorithm is given to verify the usefulness of the architecture framework. (C) 2019 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 11th CIRP Conference on Industrial Product-Service Systems
引用
收藏
页码:661 / 664
页数:4
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