5 citations · 5 across the 3 of their papers we have counts for
4 papers
Dynamic Hybrid Modeling: Incremental Identification and Model Predictive Control
Adrian Caspari, Thomas Bierweiler, Sarah Fadda +5
Mathematical models are crucial for optimizing and controlling chemical processes, yet they often face significant limitations in terms of computational time, algorithm complexity,…
One-Class Domain Adaptation via Meta-Learning
Stephanie Holly, Thomas Bierweiler, Stefan von Dosky +3
The deployment of IoT (Internet of Things) sensor-based machine learning models in industrial systems for anomaly classification tasks poses significant challenges due to distribut…
Low-Power Vibration-Based Predictive Maintenance for Industry 4.0 using Neural Networks: A Survey
Alexandru Vasilache, Sven Nitzsche, Daniel Floegel +7
The advancements in smart sensors for Industry 4.0 offer ample opportunities for low-powered predictive maintenance and condition monitoring. However, traditional approaches in thi…
Towards Robust and Transferable IIoT Sensor based Anomaly Classification using Artificial Intelligence
Jana Kemnitz, Thomas Bierweiler, Herbert Grieb +2
The increasing deployment of low-cost industrial IoT (IIoT) sensor platforms on industrial assets enables great opportunities for anomaly classification in industrial plants. The p…