Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis.
Today machines can learn und develop an ‚artificial intelligencene‘, meaning that those systems support and take (real time) decisions based on data from running operations. Thus, AI can be introduced into production. Typical approaches are Condition Monitoring, Predictive Maintenance, Image processing and diagnosis.
The 4. Conference on Machine Learning for Cyber Physical Systems and Industry 4.0 – ML4CPS – accesses the following topics; we are looking forward to welcome you the 23. – 24. October 2018 in Karlsruhe!
Main themes of the conference are:
Machine Learning Methods – Deep Learning
- Learning of automata and state-based systems
- Time series prediction
- Dimensionality reduction
- Clustering, classification
Data Stream Processing
- Real-time enabled algorithms
- Online learning
- Distributed learning
Applications in Machine Learning in Industry 4.0 and Cyber-physical systems
- (Self-) Diagnosis
- Predictive Maintenance
- Condition Monitoring
- Anomalieerkennung / Event-Detection
- Image processing in production
- Pattern recognition
The conference offers a forum to present new approaches to Machine Learning for Cyber Physical Systems, to discuss experiences and to develop visions. Therefore, the conference addresses researchers and users from different industry sectors such as production technology, automation, automotive and telecommunication.
Professor Dr.-Ing. habil. Jürgen Beyerer, Fraunhofer Institut IOSB
Professor Dr. rer. nat. Oliver Niggemann, Fraunhofer IOSB-INA