Institutional Repository of Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
Industrial Big Data Analytics: Challenges, Methodologies, and Applications | |
Wang JP(王军平); JUNPING WANG | |
发表期刊 | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING |
2016-10 | |
期号 | 11页码:1101-1110 |
摘要 | While manufacturers have been generating highly distributed data from various systems, devices and applications, a number of challenges in both data management and data analysis require new approaches to support the big data era. These challenges for industrial big data analytics is real-time analysis and decision-making from massive heterogeneous data sources in manufacturing space. This survey presents new concepts, methodologies, and applications scenarios of industrial big data analytics, which can provide dramatic improvements in velocity and veracity problem solving. We focus on five important methodologies of industrial big data analytics: 1) Highly distributed industrial data ingestion: access and integrate to highly distributed data sources from from various systems, devices and applications; 2) Industrial big data repository: cope with sampling biases and heterogeneity, and store different data formats and structures; 3) Large-scale industrial data management: organizes massive heterogeneous data and share large-scale data; 4) Industrial data analytics: track data provenance, from data generation through data preparation; 5) Industrial data governance: ensures data trust, integrity and security. For each phase, we introduce to current research in industries and academia, and discusses challenges and potential solutions. We also examine the typical applications of industrial big data, including smart factory visibility, machine fleet, energy management, proactive maintenance, and just in time supply chain. These discussions aim to understand the value of industrial big data. Lastly, this survey is concluded with a discussion of open problems and future directions. |
关键词 | Industry 4.0 Cloud Robotics Industrial Big Data Predictive Manufacturing |
收录类别 | SCI |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/12346 |
专题 | 精密感知与控制研究中心_人工智能与机器学习 |
通讯作者 | JUNPING WANG |
作者单位 | Laboratory of Precision Sensing and Control Center, Institute of Automation, Chinese Academy |
推荐引用方式 GB/T 7714 | Wang JP,JUNPING WANG. Industrial Big Data Analytics: Challenges, Methodologies, and Applications[J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,2016(11):1101-1110. |
APA | Wang JP,&JUNPING WANG.(2016).Industrial Big Data Analytics: Challenges, Methodologies, and Applications.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING(11),1101-1110. |
MLA | Wang JP,et al."Industrial Big Data Analytics: Challenges, Methodologies, and Applications".IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING .11(2016):1101-1110. |
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