Serving Bosch Production Data as Virtual KGs

Elem Güzel-Kalayci, Irlan Grangel Gonzalez, Felix Lösch, Guohui Xiao, Anees Ul-Mehdi, Evgeny Kharlamov, Diego Calvanese

Publikation: KonferenzbeitragPaper

Abstract

Analyses of manufacturing processes is vital for effective and efficient manufacturing. In complex industrial settings, such analyses should account for data that comes from many different and highly heterogeneous machines, and thus are affected by the data integration challenge. In this work, we show how this challenge can be addressed with semantics using Virtual Knowledge Graphs. For this purpose, we propose the SIB Framework, in which we semantically integrate Bosch manufacturing data. In this demo we we present SIB in action on 2 scenarios for the analysis of the Surface Mounting Process (SMT) pipeline.

Originalspracheenglisch
Seiten355-358
Seitenumfang4
PublikationsstatusVeröffentlicht - Jan 2021
Veranstaltung19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice: ISWC-Posters 2020 - Online, Virtual, Online
Dauer: 1 Nov 20206 Nov 2020
https://iswc2020.semanticweb.org/

Konferenz

Konferenz19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice
OrtVirtual, Online
Zeitraum1/11/206/11/20
Internetadresse

ASJC Scopus subject areas

  • !!Computer Science(all)

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