An important scenario here is monitoring of manufacturing processes, including e.g. analysing the quality of the man- ufactured products and predicting the ...
Data-driven methods like Machine Learning are used in analysis of manufacturing processes for a wide range of industries, including e.g. analysing the ...
Our approach relies on ontologies for discrete manufacturing monitoring that encapsulate domain and ML knowledge; it has several semantic modules for automation ...
Jun 24, 2021 · Teaching and research videos from the SIRIUS Centre for Research-based Innovation at the University of Oslo and its partners.
Baifan Zhou, Yulia Svetashova, Tim Pychynski, Evgeny Kharlamov: Semantic ML for Manufacturing Monitoring at Bosch. ISWC (Demos/Industry) 2020: 398.
... Machine Learning (ML), in monitoring of manufacturing processes. In this work, we propose ML pipelines for quality monitoring in Resistance Spot Welding.
Making manufacturing smarter with the help of AI, digital twins, and semantic technologies is my passion. I have been with Bosch Research since 2018.
[PDF] The Data Value Quest: A Holistic Semantic Approach at Bosch
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Mikut, Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding,. Journal of Intelligent Manufacturing (2022) 1–25.
We propose a system, called SemML, for ontology-enhanced ML pipeline development. It has several novel components and relies on ontologies and ontology ...
We propose a software system SemML that allows to reuse and generalise ML pipelines for conditions monitoring by relying on semantics.