Bachelor-/ Master Thesis: »Tool Wear meets Federated Learning«
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. As part of your thesis, you will investigate federated learning for decentralized AI model training for tool wear detection and measurement in milling processes within the »FL4AI« project. A custom dataset has been acquired, consisting of microscopic tool wear images and CNC-integrated camera videos. Your task will be to generate AI pipelines to detect and measure flank wear according to ISO DIN 8688-2 in centralized, individual, and federated learning scenarios.
Here you partly work on your tasks on-site in our institute/ machine park.
What you will do
What you bring to the table
What you can expect
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
Requisition Number: 80591 Application Deadline:
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