Bachelor-/ Master Thesis: »Production meets Federated Learning«

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 32,000 employees work with an annual research budget of 3.4 billion euros.

At the Fraunhofer IPT in Aachen, we work with more than 530 employees every day to make the production of the future more digital, more flexible and more sustainable. In the department »High performance cutting«, we deal with high-quality requirements in the metal cutting industry, especially in highly regulated sectors such as aerospace.
Within the scope of your thesis, you will investigate federated learning for decentralized AI model training for quality assurance of machining processes within the project »FL.IN.NRW«. A custom dataset composed of machine internal signals and external sensor signals was acquired and your task is to generate AI pipelines to predict final workpiece quality according to ISO DIN 1101 in a centralized, individual and federated learning scenario.

Here you partly work on your tasks on-site in our institute/ machine park.

What you will do

• State of the art: quality prediction in metal cutting applications
• Data acquisition: machine internal signals, force sensors, microscopy data and laser data
• Hands-on development of pre-processing, training, local and global evaluation pipelines
• Evaluation of centralized, individual and federated learning scenarios for quality prediction applications

What you bring to the table

• You are studying production engineering, mechanical engineering, or a comparable subject
• Initial Programming (python) and Machine Learning (pytorch, and scikit-learn) experience is required
• A high degree of initiative, independence, and motivation
• Good language skills in German or English

What you can expect

• Ideal conditions for practical experience alongside your studies
• Professional supervision and collaboration in a dedicated team
• A state-of-the-art machine park equipped with edge cloud systems and 5G infrastructure
• Flexible working to combine study and job in the best possible way

Interested? Apply online now. We look forward to getting to know you!

https://jobs.fraunhofer.de/job-invite/79483/

For any further information on this position please contact:
Gustavo Laydner de Melo Rosa Eng. Mec.
Research assistant, »High performance cutting«
Phone: +49 241 8904-256