Big data analytics for intelligent manufacturing systems: A review

被引：186

作者：

Wang, Junliang ^{[1
,2
,3
]}

Xu, Chuqiao ^{[4
]}

Zhang, Jie ^{[1
,2
]}

Zhong, Ray ^{[5
]}

机构：

[1] Donghua Univ, Inst Artificial Intelligence, Shanghai, Peoples R China

[2] Donghua Univ, Shanghai Engn Res Ctr Ind Big Data & Intelligent, Shanghai, Peoples R China

[3] Beijing Chonglee Machinery Engn Co Ltd, Natl Synthet Fiber Engn Technol Res Ctr, Beijing, Peoples R China

[4] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China

[5] Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China

来源：

JOURNAL OF MANUFACTURING SYSTEMS | 2022年 / 62卷

关键词：

Big data analytics (BDA); Intelligent manufacturing; Artificial intelligence; Manufacturing systems; SUPPLY CHAIN MANAGEMENT; FAULT-DIAGNOSIS; PRODUCT DESIGN; CYCLE TIME; NETWORKS; DRIVEN; PREDICTION; NEUROSCIENCE; CHALLENGES; FRAMEWORK;

D O I：

10.1016/j.jmsy.2021.03.005

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

With the development of Internet of Things (IoT), 5 G, and cloud computing technologies, the amount of data from manufacturing systems has been increasing rapidly. With massive industrial data, achievements beyond expectations have been made in the product design, manufacturing, and maintain process. Big data analytics (BDA) have been a core technology to empower intelligent manufacturing systems. In order to fully report BDA for intelligent manufacturing systems, this paper provides a comprehensive review of associated topics such as the concept of big data, model driven and data driven methodologies. The framework, development, key technologies, and applications of BDA for intelligent manufacturing systems are discussed. The challenges and opportunities for future research are highlighted. Through this work, it is hoped to spark new ideas in the effort to realize the BDA for intelligent manufacturing systems.

引用

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页码：738 / 752

页数：15

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