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http://dx.doi.org/10.7465/jkdi.2017.28.6.1301

Effective visualization methods for a manufacturing big data system  

Yoo, Kwan-Hee (Department of Computer Science, Chungbuk National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.6, 2017 , pp. 1301-1311 More about this Journal
Abstract
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;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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