How to Discover Knowledge for Improving Availability in the Manufacturing Domain?

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dc.contributor.authorUtz, Fabian
dc.contributor.authorNeumann, Christian
dc.contributor.authorOmid, Tafreschi
dc.date.accessioned2017-12-28T02:04:05Z
dc.date.available2017-12-28T02:04:05Z
dc.date.issued2018-01-03
dc.description.abstractThis paper presents a specific process model for Knowledge Discovery in Databases (KDD) projects aiming at availability improvement in manufacturing. For this purpose, Overall Equipment Efficiency (OEE) is analyzed and used, since it is an approved approach to monitor and improve the degree of availability in manufacturing. To define the specific process model, we use the generic CRISPDM reference model and conduct a mapping for availability improvement. We prove the applicability of our model in the context of a specific KDD project in a large enterprise in the manufacturing industry.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2018.552
dc.identifier.isbn978-0-9981331-1-9
dc.identifier.urihttp://hdl.handle.net/10125/50441
dc.language.isoeng
dc.relation.ispartofProceedings of the 51st 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.subjectReports from the Field
dc.subjectCRISP-DM, Data Mining, Knowledge Discovery, Manufacturing, Overall Equipment Efficiency (OEE)
dc.titleHow to Discover Knowledge for Improving Availability in the Manufacturing Domain?
dc.typeConference Paper
dc.type.dcmiText

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