Mining Industrial Logs for System Level Insights
dc.contributor.author | Czora, Sebastian | |
dc.contributor.author | Dix, Marcel | |
dc.contributor.author | Fromm, Hansjörg | |
dc.contributor.author | Klöpper, Benjamin | |
dc.contributor.author | Schmitz, Björn | |
dc.contributor.editor | Mitschang, Bernhard | |
dc.contributor.editor | Nicklas, Daniela | |
dc.contributor.editor | Leymann, Frank | |
dc.contributor.editor | Schöning, Harald | |
dc.contributor.editor | Herschel, Melanie | |
dc.contributor.editor | Teubner, Jens | |
dc.contributor.editor | Härder, Theo | |
dc.contributor.editor | Kopp, Oliver | |
dc.contributor.editor | Wieland, Matthias | |
dc.date.accessioned | 2017-06-21T11:24:44Z | |
dc.date.available | 2017-06-21T11:24:44Z | |
dc.date.issued | 2017 | |
dc.description.abstract | Industrial systems are becoming more and more complex and expensive to operate. Companies are making considerable efforts to increase operational efficiency and eliminate unplanned downtime of their equipment. Condition monitoring has been applied to improve equipment availability and reliability. Most of the condition monitoring applications, however, focus on single components, not on entire systems. The objective of this research was to demonstrate that a combination of visual analytics and association rule mining can be successfully used in a condition monitoring context on system level. | en |
dc.identifier.isbn | 978-3-88579-660-2 | |
dc.identifier.pissn | 1617-5468 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-266 | |
dc.subject | condition monitoring | |
dc.subject | predictive maintenance | |
dc.subject | log file analysis | |
dc.subject | data mining | |
dc.title | Mining Industrial Logs for System Level Insights | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 64 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 57 | |
gi.conference.date | 6.-10. März 2017 | |
gi.conference.location | Stuttgart | |
gi.conference.sessiontitle | Workshop Big Data Management Systems in Business and Industrial Applications (BigBIA17) |
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