todo
IFE

Ml4Pro2 - Machine learning for production and its products

Duration
-
Participants

Through machine learning (ML), knowledge can be generated from data in order to generate added value at all levels of the company processes. Products such as mobile platforms, robots or vehicles use data to optimize their behavior.

However, production systems are also increasingly using it to react more flexibly to new market developments and customer needs and to produce products optimally using the available resources. The local use of ML procedures close to the origin of the data is particularly promising.

The aim of the project is to make ML available for intelligent products and production processes. For this purpose, the latest ML methods are to be integrated into products and production chains. It is also about raising the awareness of companies to use ML for agile business models. The main topics are hybrid learning processes, the integration of expert knowledge, the interpretability of data, learning on data streams and cognitive edge computing. The ML methods are considered cross-application based on three industrial use cases: condition monitoring, process optimization and improvement of product quality. Results and procedures are made available to other companies on an ML platform. This platform includes, for example, reference implementations, methods for data preprocessing and data visualization as well as application knowledge about typical processes when using the ML methods.

Project partners

Project request

Privacy policy

Yes, I have read the Privacy Policy note and I consent that the data provided by me, including the contact data, for the processing of the inquiry and in case of questions are electronically collected and stored. My data will only be used strictly for my request and will not be passed without my consent. This consent can be revoked any time with effect for the future.'

(3 Buchstaben)

Other active projects

Duration
-
iFE: EMC-optimal input and output filters using 3D simulation The IDEALER project uses results from the preliminary project Ide3AL. In the preliminary project, it was basically...
Head
Duration
-
Electromobility is an important building block for reducing CO2 and achieving climate targets. A prerequisite for the widespread use of electric vehicles is a demand-oriented...
Head
Participants
Duration
-
The energy turnaround is one of the greatest challenges for the manufacturing industry in Germany. Global political events make the reduction of energy consumption at all levels...
Head