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Automating Industrial Event Stream Analytics: Methods, Models, and Tools

Zehnder, Philipp

Abstract (englisch):

Industrial event streams are an important cornerstone of Industrial Internet of Things (IIoT) applications. For instance, in the manufacturing domain, such streams are typically produced by distributed industrial assets at high frequency on the shop floor. To add business value and extract the full potential of the data (e.g. through predictive quality assessment or maintenance), industrial event stream analytics is an essential building block. One major challenge is the distribution of required technical and domain knowledge across several roles, which makes the realization of analytics projects time-consuming and error-prone. For instance, accessing industrial data sources requires a high level of technical skills due to a large heterogeneity of protocols and formats. To reduce the technical overhead of current approaches, several problems must be addressed. The goal is to enable so-called "citizen technologists" to evaluate event streams through a self-service approach. This requires new methods and models that cover the entire data analytics cycle.
In this thesis, the research question is answered, how citizen technologists can be facilitated to independently perform industrial event stream analytics. ... mehr


Volltext §
DOI: 10.5445/IR/1000144443
Veröffentlicht am 06.04.2022
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Hochschulschrift
Publikationsdatum 06.04.2022
Sprache Englisch
Identifikator KITopen-ID: 1000144443
Verlag Karlsruher Institut für Technologie (KIT)
Umfang xvi, 171 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Wirtschaftswissenschaften (WIWI)
Institut Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Prüfungsdatum 23.09.2021
Referent/Betreuer Sure-Vetter, York
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