IHPPVis: Interactive Visual Analysis of Industrial data in Heavy Plate Production. Issue 2 (2020)

• Record Type: Journal Article
• Authors: Zhang, Tongkang; Ma, Yufei; Xu, Depeng; Liu, Changxin; Ding, Jinliang
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 12050
• Page End: 12055
• Publication Date: 2020
• Subjects: Industrial data -- Heavy plates production -- Visual analytics -- Quality-related fault; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.745
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper develops an interactive visualization system, called iHPPVis, to analyze and locate the cause of quality-related faults for the heavy plates production. A time distribution of the products under different operating conditions based on Marey's graph is presented and the process data for corresponding conditions to identify clusters and outliers is visualized, which utilizes the alternative dimension reduction algorithms. The crucial stage that leads to the abnormality of product quality is also diagnosed, and the data distribution of heterogeneous process variables in the crucial stage is exhibited. By integrating alternative algorithms with interactive visual analysis to achieve quality-related fault diagnosis, iHPPVis can facilitate the improvement of heavy plates quality. A case study is conducted to demonstrate its effectiveness and exhibit a pilot application of visual analytics for the heavy plates production.