生产(经济)
视觉分析
过程(计算)
计算机科学
分析
可视化
鉴定(生物学)
集合(抽象数据类型)
数据科学
风险分析(工程)
过程管理
数据挖掘
工程类
业务
宏观经济学
经济
程序设计语言
操作系统
生物
植物
作者
Tongkang Zhang,Jinliang Ding,Cheng Zeng,K.-L. Guan,Ye Liu,Chunhui Zhao,Tianyou Chai
标识
DOI:10.1109/tcyb.2024.3387129
摘要
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.
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