Visual Data Analysis of Production Quality Data for Aluminum Casting

dc.contributor.author Jekic, Nikolina
dc.contributor.author Mutlu, Belgin
dc.contributor.author Schreyer, Manuela
dc.contributor.author Neubert, Steffen
dc.contributor.author Schreck, Tobias
dc.date.accessioned 2020-12-24T19:16:59Z
dc.date.available 2020-12-24T19:16:59Z
dc.date.issued 2021-01-05
dc.description.abstract Today’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.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2021.179
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/70791
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Interactive Visual Analytics and Visualization for Decision Making
dc.subject aluminum casting
dc.subject production quality
dc.subject visual data analysis
dc.title Visual Data Analysis of Production Quality Data for Aluminum Casting
prism.startingpage 1487
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