In this paper, we present a novel framework that combines large language...
The trend in industrial automation is towards networking, intelligence a...
The creation of a Digital Twin for existing manufacturing systems, so-ca...
Automation systems are increasingly being used in dynamic and various
op...
Systematic Literature Reviews aim at investigating current approaches to...
Many decision-making approaches rely on the exploration of solution spac...
Real-life industrial use cases for machine learning oftentimes involve
h...
Industrial transfer learning increases the adaptability of deep learning...
Developing consistently well performing visual recognition applications ...
In recent years, the use of lithium-ion batteries has greatly expanded i...
Shorter product life cycles and increasing individualization of producti...
Nowadays, formal methods are used in various areas for the verification ...
Deep learning promises performant anomaly detection on time-variant data...
Reconfiguration demand is increasing due to frequent requirement changes...
Anomalies represent deviations from the intended system operation and ca...
The early and robust detection of anomalies occurring in discrete
manufa...
In this article, the concepts of transfer and continual learning are
int...
Digital Twins have been described as beneficial in many areas, such as
v...