Industrial Big Data Analytics: Challenges, Methodologies, and Applications

CORC > 自动化研究所 > 中国科学院自动化研究所 > 精密感知与控制研究中心 > 人工智能与机器学习

	Industrial Big Data Analytics: Challenges, Methodologies, and Applications
	Wang JP(王军平); JUNPING WANG
刊名	IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
	2016-10
期号	11 页码:1101-1110
关键词	Industry 4.0 Cloud Robotics Industrial Big Data Predictive Manufacturing
英文摘要	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.
内容类型	期刊论文
源URL	[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.