Machine Learning is currently the most widespread area of artificial intelligence being practically applied. It deals with the question of how data can be used to continually improve computer-based models or decisions (through learning). For example, in a production process this makes it possible to define ever more precisely the best possible time for the replacement of worn components in a machine (predictive maintenance).
The ML research group works on basic Machine Learning algorithms mainly in the area of industry 4.0 and medical engineering, but also in the area of chatbots.
The aim of the joint project is to support SMEs with the special machine learning software development lifecycle and the significant quality indicators which result from this. During the project appropriate instruments will be produced which will evaluate data quality related to representative coverage of the characterisation, as well as the quality of the KI models. This will ensure the product risk of the manufacturers' KI-based products and guarantee the customer quantified performance with regard to KI decisions.
The Industry 4.0 research project SensoGrind deals with the monitoring of the grinding process with regard to overheating and the resulting reduction in quality. The grinding processes are monitored using optical and electromagnetic sensors and machine learning techniques, and analysed in a cloud-based system. This enables intelligent planning of process conditions and ensures the highest possible level of productivity and quality.
In the Data Literacy and Data Science project, nine universities and universities of applied sciences in Baden-Württemberg are developing new training and qualification initiatives for the collection, evaluation and use of the large amounts of data which occur in companies. In doing so, a broad range of educational methodologies will be implemented: online and face-to-face elements complement each other. These professional development initiatives are specifically aimed at small and medium-sized enterprises (SMEs).
|Prof. Dr. Christoph Reich||Email application is started:Christoph.Reich(at)hs-furtwangen.de|
|Prof. Dr. Maja Temerinac-Ott||Email application is started:Temerinac-ott(at)hs-furtwangen.de|
|Matthias Lermer||Email application is started:Matthias.Lermer(at)hs-furtwangen.de|
|Daniel Schönle||Email application is started:Daniel.Schoenle(at)hs-furtwangen.de|
|Jan Stodt||Email application is started:Jan.Stodt(at)hs-furtwangen.de|