Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

被引：193
作者：
Dai, Hong-Ning [1 ]
Wang, Hao [2 ]
Xu, Guangquan [3 ]
Wan, Jiafu [4 ]
Imran, Muhammad [5 ]
机构：
[1] Macau Univ Sci & Technol, Fac Informat Technol, Macau, Macao, Peoples R China
[2] Norwegian Univ Sci & Technol Aalesund, Fac Engn & Nat Sci, Gjovik, Norway
[3] Tianjin Univ, Coll Intelligence & Comp, Tianjin Key Lab Adv Networking, Tianjin, Peoples R China
[4] South China Univ Technol, Sch Mech & Automot Engn, Guangzhou, Guangdong, Peoples R China
[5] King Saud Univ, Coll Comp & Informat Sci, Riyadh, Saudi Arabia
来源：
ENTERPRISE INFORMATION SYSTEMS | 2020年 / 14卷 / 9-10期
基金：
中国国家自然科学基金; 美国国家科学基金会;
关键词：
Smart manufacturing; data analytics; data mining; internet of things; FRAMEWORK; MACHINE; SYSTEMS; ALGORITHM; NETWORKS; SECURITY; PRIVACY; DESIGN;
D O I：
10.1080/17517575.2019.1633689
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Data analytics in massive manufacturing data can extract huge business values while can also result in research challenges due to the heterogeneous data types, enormous volume and real-time velocity of manufacturing data. This paper provides an overview on big data analytics in manufacturing Internet of Things (MIoT). This paper first starts with a discussion on necessities and challenges of big data analytics in manufacturing data of MIoT. Then, the enabling technologies of big data analytics of manufacturing data are surveyed and discussed. Moreover, this paper also outlines the future directions in this promising area.
引用
收藏
页码：1279 / 1303
页数：25
相关论文
共 90 条
[1]   AN INTRODUCTION TO KERNEL AND NEAREST-NEIGHBOR NONPARAMETRIC REGRESSION [J].
ALTMAN, NS .
AMERICAN STATISTICIAN, 1992, 46 (03) :175-185
[2]  
[Anonymous], 2009, Artificial intelligence: A modern approach
[3]  
[Anonymous], 2002, PRINCIPAL COMPONENT
[4]  
[Anonymous], DATA VISUALIZATION T
[5]  
[Anonymous], 2010, P 1 ACM S CLOUD COMP
[6]  
[Anonymous], 2011, P 9 USENIX C FIL STR
[7]  
[Anonymous], 2016, INT J KNOWL ENG SOFT, DOI DOI 10.1504/IJKESDP.2016.075976
[8]  
[Anonymous], 2016, Research methods: the essential knowledge base
[9]  
[Anonymous], 2010, 9 USENIX S OP SYST D
[10]  
[Anonymous], 2010, P 5 EUR C COMP SYST
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