Abstract | ||
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Modern machines continuously log status reports over long periods of time, which are valuable data to optimize working routines. Data visualization is a commonly used tool to gain insights into these data, mostly in retrospective (e.g., to determine causal dependencies between the faults of different machines). We present an approach to bring such visual analyses to the shop floor to support react... |
Year | DOI | Venue |
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2022 | 10.1109/MCG.2022.3157961 | IEEE Computer Graphics and Applications |
Keywords | DocType | Volume |
Data visualization,Monitoring,Task analysis,Manufacturing,Maintenance engineering,Time series analysis,Real-time systems | Journal | 42 |
Issue | ISSN | Citations |
2 | 0272-1716 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
---|---|---|---|
Michael Becher | 1 | 7 | 2.88 |
Dominik Herr | 2 | 0 | 0.34 |
Christoph Muller | 3 | 0 | 0.34 |
Kuno Kurzhals | 4 | 227 | 20.63 |
Guido Reina | 5 | 297 | 31.26 |
Lena Wagner | 6 | 0 | 0.34 |
Thomas Ertl | 7 | 4417 | 401.52 |
Daniel Weiskopf | 8 | 2988 | 204.30 |