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 …

Monitoring of the state, performance, quality of operations and other parameters of
equipment and production processes, which is typically referred to as condition monitoring …

Traditional knowledge graph embedding (KGE) aims to map entities and relations into
continuous space vectors to provide high-quality data feature representation for downstream …

In the automotive industry, welding is a critical process of automated manufacturing and its
quality monitoring is important. IoT technologies behind automated factories enable …

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 …

Machine learning (ML) based data analysis has attracted an increasing attention in the
manufacturing industry, however, many challenges hamper their wide spread adoption. The …

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 …

Machine learning (ML) is gaining much attention for data analysis in manufacturing. Despite
the success, there is still a number of challenges in widening the scope of ML adoption. The …

Today, knowledge graphs (KGs) are growing by enrichment and refinement methods. The
enrichment and refinement can be gained using the correction and completion of the KG …

Knowledge Graphs (KG) are valuable information sources that store knowledge in a domain
(healthcare, finance, e-commerce, cyber-security.). Most industrial KGs are dynamic by …