Modular automation provides a challenge for traditional physics simulators, especially if they
are used as a simulator in the loop of a development or research project looking at behavior …

Modern manufacturing systems collect a huge amount of data which gives an opportunity to
apply various Machine Learning (ML) techniques. The focus of this paper is on the detection …

The recent advances in digitalization, improved connectivity and cloud based services are
making a huge revolution in manufacturing domain. In spite of the huge potential benefits in …

Industrial automation and control systems (IACS) are taking care of our most important
infrastructures, providing electricity and clean water, producing medicine and food, along …

This thesis investigates anomaly detection and classification in a simulated modular
manufacturing environment using Machine Learning algorithm Random Forest. This …

In the realm of manufacturing, ensuring optimal product quality is of utmost importance. This
emphasizes the necessity for efficient anomaly detection, which identifies deviations from …

In a manufacturing environment, the continuous operation of production lines is of most
importance to ensure optimal productivity and profitability. To maintain efficiency and safety …

Automated manufacturing environments often benefit greatly from the ability to detect
patterns that deviate from expected behavior. Anomaly Detection (AD) is vital in automated …

This white paper aims at briefly summarizing the datasets that are known to have been
created and used in the 3-year Europan research project InSecTT. By making this list public …