Data-driven smart manufacturing

被引：967

作者：

Tao, Fei ^{[1
]}

Qi, Qinglin ^{[1
]}

Liu, Ang ^{[2
]}

Kusiak, Andrew ^{[3
]}

机构：

[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China

[2] Univ New South Wales, Sch Mech & Mfg Engn, Sydney, NSW 2053, Australia

[3] Univ Iowa, Dept Mech & Ind Engn, Iowa City, IA USA

来源：

JOURNAL OF MANUFACTURING SYSTEMS | 2018年 / 48卷

基金：

中国国家自然科学基金;

关键词：

Big data; Smart manufacturing; Manufacturing data; Data lifecycle; BIG DATA; DATA-MANAGEMENT; ONLINE REVIEWS; CHALLENGES; ANALYTICS; DESIGN; IMPROVEMENT; GENERATION; FRAMEWORK; SELECTION;

D O I：

10.1016/j.jmsy.2018.01.006

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The advances in the internet technology, internet of things, cloud computing, big data, and artificial intelligence have profoundly impacted manufacturing. The volume of data collected in manufacturing is growing. Big data offers a tremendous opportunity in the transformation of today's manufacturing paradigm to smart manufacturing. Big data empowers companies to adopt data-driven strategies to become more competitive. In this paper, the role of big data in supporting smart manufacturing is discussed. A historical perspective to data lifecycle in manufacturing is overviewed. The big data perspective is supported by a conceptual framework proposed in the paper. Typical application scenarios of the proposed framework are outlined. (C) 2018 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

引用

页码：157 / 169

页数：13

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