Artificial Intelligence in Automation

ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen

01.08.2018 bis 31.07.2021


The primary objective of the research project is to bring machine learning (ML) for intelligent technical systems (ITS) to the whole value chain. This requires the development and transfer of the latest ML innovations to the key areas of application in ITS in order to bring ML technologies into products and production chains, and conversely, to raise the awareness of regional companies how and when ML can be integrated into agile business models and production chains. Coupled with the focus on the current application fields: learning assistance systems, cognitive plug and work, cognitive optimization and quality management, predictive maintenance, as well as ML and 5G, the concept of 'ML as a service' for ITS is advanced. The project can build on technical digitization strategies excellently initiated by regional small and medium-sized enterprises (SMEs) and the proven excellence of the participating partners in the ML field to realize the step towards the use of digital data by ML technologies.

This project is promoted by:
Bundesministerium für Bildung und Forschung (BMBF)
Sponsors: Das Deutsche Zentrum für Luft- und Raumfahrt e.V. (DLR)
Funding Code: 01IS18041D
Funding Lines: KT 2020 - Softwareintensive eingebettete Systeme
Stakeholders / Contacts: Anton Pfeifer, M. Sc., Christoph-Alexander Holst, M. Sc.
Employees: Anton Pfeifer, M. Sc., Malte Schmidt, M. Sc.
Benedikt Eiteneuer, M. Sc., Nemanja Hranisavljevic, M. Sc., Prof. Dr. rer. nat. Oliver Niggemann
Dimensionality Reduction and Anomaly Detection for CPPS Data using Autoencoder
In: 20th IEEE International Conference on Industrial Technology Melbourne, Australien, Feb 2019, Feb 2019
Malte Schmidt, M. Sc., Prof. Dr.-Ing. Volker Lohweg
Interval-based Interpretable Decision Tree for Time Series Classification
In: Proceedings - 31. Workshop Computational Intelligence, Nov 2021
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