3 citations · 4 across the 5 of their papers we have counts for
5 papers · 1 filter
Federated Deep Clustering Networks for High-Dimensional and Heterogeneous Data
Morris Stallmann, Charalampos S. Kouzinopoulos, Marcin Pietrasik +1
Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized data scenario, this task is co…
Federated Learning for Distributed CNC Tool Wear Prediction
Afsana Khan, Morris Stallmann, Marcin Pietrasik +3
Tool wear prediction is an important task in CNC machining, where accurate monitoring of tool condition supports product quality and process reliability. Machine learning methods h…
Machine Learning for Pattern Detection in Printhead Nozzle Logging
Nikola Prianikov, Evelyne Janssen-van Dam, Marcin Pietrasik +1
Correct identification of failure mechanisms is essential for manufacturers to ensure the quality of their products. Certain failures of printheads developed by Canon Production Pr…
Deep Learning Methods for Detecting Thermal Runaway Events in Battery Production Lines
Athanasios Athanasopoulos, Matúš Mihalák, Marcin Pietrasik
One of the key safety considerations of battery manufacturing is thermal runaway, the uncontrolled increase in temperature which can lead to fires, explosions, and emissions of tox…
Predicting the Lifespan of Industrial Printheads with Survival Analysis
Dan Parii, Evelyne Janssen, Guangzhi Tang +2
Accurately predicting the lifespan of critical device components is essential for maintenance planning and production optimization, making it a topic of significant interest in bot…