Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding
Digitalisation trends of Industry 4.0 and Internet of Things led to an unprecedented growth of
manufacturing data. This opens new horizons for data-driven methods, such as Machine …
manufacturing data. This opens new horizons for data-driven methods, such as Machine …
[HTML][HTML] SemML: Facilitating development of ML models for condition monitoring with semantics
Monitoring of the state, performance, quality of operations and other parameters of
equipment and production processes, which is typically referred to as condition monitoring …
equipment and production processes, which is typically referred to as condition monitoring …
Ontology-enhanced machine learning: a Bosch use case of welding quality monitoring
In the automotive industry, welding is a critical process of automated manufacturing and its
quality monitoring is important. IoT technologies behind automated factories enable …
quality monitoring is important. IoT technologies behind automated factories enable …
Predicting quality of automated welding with machine learning and semantics: a Bosch case study
B Zhou, Y Svetashova, S Byeon, T Pychynski… - Proceedings of the 29th …, 2020 - dl.acm.org
Manufacturing of car bodies heavily relies on demanding welding processes of joining body
parts together that introduce thousands of joining welding spots in each car. Quality …
parts together that introduce thousands of joining welding spots in each car. Quality …
Scaling usability of ML analytics with knowledge graphs: exemplified with a Bosch welding case
Automated welding is heavily used in the automotive industry to produce car bodies by
connecting metal parts with welding spots. Modern welding solutions and manufacturing …
connecting metal parts with welding spots. Modern welding solutions and manufacturing …
Towards generalized welding ontology in line with ISO and knowledge graph construction
Towards Generalized Welding Ontology in Line with ISO and Knowledge Graph Construction |
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SemFE: Facilitating ML pipeline development with semantics
B Zhou, Y Svetashova, T Pychynski… - Proceedings of the 29th …, 2020 - dl.acm.org
Machine learning (ML) based data analysis has attracted an increasing attention in the
manufacturing industry, however, many challenges hamper their wide spread adoption. The …
manufacturing industry, however, many challenges hamper their wide spread adoption. The …
Towards ontology reshaping for KG generation with user-in-the-loop: applied to Bosch welding
Knowledge graphs (KG) are used in a wide range of applications. The automation of KG
generation is very desired due to the data volume and variety in industries. One important …
generation is very desired due to the data volume and variety in industries. One important …
Machine learning methods for product quality monitoring in electric resistance welding
B Zhou - 2021 - publikationen.bibliothek.kit.edu
Abstract Electric Resistance Welding (ERW) is a group of fully automated manufacturing
processes that join metal materials through heat, which is generated due to electric current …
processes that join metal materials through heat, which is generated due to electric current …
High-quality vector vortex arrays by holographic and geometric phase control
Cylindrical vector vortex (CVV) beams are topical forms of structured light, and have been
studied extensively as single beams, non-separable in two degrees of freedom: spatial …
studied extensively as single beams, non-separable in two degrees of freedom: spatial …