Visual Data Analysis of Production Quality Data for Aluminum Casting

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dc.contributor.authorJekic, Nikolina
dc.contributor.authorMutlu, Belgin
dc.contributor.authorSchreyer, Manuela
dc.contributor.authorNeubert, Steffen
dc.contributor.authorSchreck, Tobias
dc.date.accessioned2020-12-24T19:16:59Z
dc.date.available2020-12-24T19:16:59Z
dc.date.issued2021-01-05
dc.description.abstractToday’s manufacturing industry is shaped by the Industry 4.0 vision, which is to increase the number of individual goods produced while minimizing the production costs and time. To increase the production outcome and quality, users need to continuously monitor and adjust the entire process. While the recent advances in sensor technology can help users to collect, produce and exchange data, human beings are often overwhelmed by the amount of data being collected. Still, the human visual system is a powerful tool that can be used to decode and process large datasets. To make intelligent use of this ability, we have developed an interactive visual data analysis tool called ADAM that can support production data exploration in the aluminum industry. Furthermore, we demonstrate the effectiveness of our tool using real production data and present insights which could be gained from use of our tool by domain experts.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2021.179
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70791
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectInteractive Visual Analytics and Visualization for Decision Making
dc.subjectaluminum casting
dc.subjectproduction quality
dc.subjectvisual data analysis
dc.titleVisual Data Analysis of Production Quality Data for Aluminum Casting
prism.startingpage1487

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