Paper Info
Title
Industrial Big Data Analysis in Smart Factory: Current Status and Research Strategies.
Abstract
Under the background of cyber-physical systems and Industry 4.0, intelligent manufacturing has become an orientation and produced a revolutionary change. Compared with the traditional manufacturing environments, the intelligent manufacturing has the characteristics as highly correlated, deep integration, dynamic integration, and huge volume of data. Accordingly, it still faces various challenges. In this paper, we summarize and analyze the current research status in both domestic and aboard, including industrial big data collection, modeling of the intelligent product lines based on ontology, the predictive diagnosis based on industrial big data, group learning of product line equipment and the product line reconfiguration of intelligent manufacturing. Based on the research status and the problems, we propose the research strategies, including acquisition schemes of industrial big data under the environment of intelligent, ontology modeling and deduction method based intelligent product lines, predictive diagnostic methods on production lines based on deep neural network, deep learning among devices based on cloud supplements and 3-D selforganized reconfiguration mechanism based on the supplements of cloud. In our view, this paper will accelerate the implementation of smart factory.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2741105
IEEE ACCESS
Keywords
Field
DocType
Industrial big data,smart factory,data analysis,cyber-physical systems
Ontology (information science),Data science,Data modeling,Ontology,Deep integration,Computer science,Manufacturing engineering,Production line,Big data,Control reconfiguration,Cloud computing,Distributed computing
Journal
Volume
ISSN
Citations 
5
2169-3536
3
PageRank 
References 
Authors
0.40
25
2
Name
Order
Citations
PageRank
Xiaoya Xu130.40
Qingsong Hua2111.56