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Industrial Big Data Analytics: Challenges, Methodologies, and Applications
Wang JP(王军平); JUNPING WANG
Source PublicationIEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
2016-10
Issue11Pages:1101-1110
AbstractWhile 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.
KeywordIndustry 4.0 Cloud Robotics Industrial Big Data Predictive Manufacturing
Indexed BySCI
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12346
Collection精密感知与控制研究中心_人工智能与机器学习
Corresponding AuthorJUNPING WANG
AffiliationLaboratory of Precision Sensing and Control Center, Institute of Automation, Chinese Academy
Recommended Citation
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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