Dataflow-based Visual Analysis for Fault Diagnosis and Predictive Maintenance in Manufacturing

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dc.contributor.authorWörner, M.en_US
dc.contributor.authorMetzger, M.en_US
dc.contributor.authorT.Ertl,en_US
dc.contributor.editorM. Pohl and H. Schumannen_US
dc.date.accessioned2014-01-27T16:03:39Z
dc.date.available2014-01-27T16:03:39Z
dc.date.issued2013en_US
dc.description.abstractPredictive machine maintenance, which monitors the current condition of a machine, can be much more efficient than maintaining it on a strict schedule or only as a reaction to actual breakdowns. Although sophisticated theoretical models exist, these are not always employed in practice, presumably in part due to their abstract nature. Introducing interactive visualization into the analysis process may facilitate the adoption of predictive maintenance. We apply a dataflow-based visual analytics approach to the analysis of diagnostic machine data on a real-world dataset and collect feedback from domain experts.en_US
dc.description.seriesinformationEuroVis Workshop on Visual Analyticsen_US
dc.identifier.isbn978-3-905674-55-2en_US
dc.identifier.urihttps://doi.org/10.2312/PE.EuroVAST.EuroVA13.055-059en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.8 [Computer Graphics]en_US
dc.subjectApplicationsen_US
dc.titleDataflow-based Visual Analysis for Fault Diagnosis and Predictive Maintenance in Manufacturingen_US
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