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

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

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

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

Fraunhofer Institute for Production Technology IPT

www.ipt.fraunhofer.de

Requisition Number: 79483 Application Deadline:

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