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Effective visualization methods for a manufacturing big data system
Journal of the Korean Data & Information Science Society 2017;28:1301-11
Published online November 30, 2017
© 2017 Korean Data & Information Science Society.

Kwan-Hee Yoo1

1Department of Computer Science. Chungbuk National University
Correspondence to: Kwan-Hee Yoo
Professor, Department of Computer Science, Chungbuk National University, Cheongju 286-44, Korea. E-mail:
Received November 3, 2017; Revised November 14, 2017; Accepted November 15, 2017.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Manufacturing big data systems have supported decision making that can improve preemptive manufacturing activities through collection, storage, management, and predictive analysis of related 4M data in pre-manufacturing processes. Effective visualization of data is crucial for efficient management and operation of data in these systems. This paper presents visualization techniques that can be used to effectively show data collection, analysis, and prediction results in the manufacturing big data systems. Through the visualization technique presented in this paper, we have confirmed that it was not only easy to identify the problems that occurred at the manufacturing site, but also it was very useful to reply to these problems.
Keywords : Big data, data analysis and prediction, data visualization, manufacturing big data systems