Back to Search Start Over

iHPPPVis: Interactive Visual Analytics Approach for Production Performance Monitoring of Heavy-Plate Production Process

Authors :
Zhang, Tongkang
Ding, Jinliang
Zeng, Cheng
Guan, Kaifeng
Liu, Ye
Zhao, Chunhui
Chai, Tianyou
Source :
IEEE Transactions on Cybernetics; 2024, Vol. 54 Issue: 7 p3864-3877, 14p
Publication Year :
2024

Abstract

Efficient monitoring of production performance is crucial for ensuring safe operations and enhancing the economic benefits of the Iron and Steel Corporation. Although basic modeling algorithms and visualization diagrams are available in many scientific platforms and industrial applications, there is still a lack of customized research in production performance monitoring. Therefore, this article proposes an interactive visual analytics approach for monitoring the heavy-plate production process (iHPPPVis). Specifically, a multicategory aggregated monitoring framework is proposed to facilitate production performance monitoring under varying working conditions. In addition, A set of visualizations and interactions are designed to enhance analysts’ analysis, identification, and perception of the abnormal production performance in heavy-plate production data. Ultimately, the efficacy and practicality of iHPPPVis are demonstrated through multiple evaluations.

Details

Language :
English
ISSN :
21682267
Volume :
54
Issue :
7
Database :
Supplemental Index
Journal :
IEEE Transactions on Cybernetics
Publication Type :
Periodical
Accession number :
ejs66966317
Full Text :
https://doi.org/10.1109/TCYB.2024.3387129