Serving Bosch Production Data as Virtual KGs

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

Research output: Contribution to conferencePaper

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.

Original languageEnglish
Pages355-358
Number of pages4
Publication statusPublished - Jan 2021
Event19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice: ISWC-Posters 2020 - Online, Virtual, Online
Duration: 1 Nov 20206 Nov 2020
https://iswc2020.semanticweb.org/

Conference

Conference19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice
CityVirtual, Online
Period1/11/206/11/20
Internet address

ASJC Scopus subject areas

  • Computer Science(all)

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