Bachelor-/ Master Thesis: »Bayesian Optimization for Optimizing Laser Processes«

  • Abschlussarbeit
  • Aachen

Webseite Fraunhofer-Institut für Produktionstechnologie IPT

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 30,800 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 “Production Quality”, we focus on data-driven optimization of production processes with the help of machine learning and artificial intelligence.

Laser processes enable highly precise and flexible material processing and are therefore crucial for innovative fields of technology such as semiconductor manufacturing and microsystems engineering and medical technology. The optimization of laser processes is becoming increasingly important, but also more complex, due to rising demands on performance, precision, quality, and sustainability. Bayesian optimization (BO) – a special machine learning approach – represents a promising alternative to classic methods of process optimization due to its adaptive decision making and data efficiency. In this thesis, a BO algorithm for the optimization of laser processes is to be developed, applied, and tested as part of a feasibility study. The aim is to determine the industrial maturity of BO and investigate how this can be increased in the future regarding its establishment in production engineering practice.

What you will do

  • Literature research on Bayesian optimization in laser machining processes
  • Process and requirements analysis in close cooperation with laser processing experts
  • Development and implementation of a BO algorithm for the efficient identification of optimal process parameters for laser machining processes
  • Conducting experiments on synthetic optimization problems
  • Verification and validation of the algorithm on a real process
  • Documenting the results and writing up the scientific work

What you bring to the table

  • You study mechanical engineering, automation technology, computer science, mathematics or a comparable subject
  • You are interested in the use of artificial intelligence in production technology
  • You are optimally already familiar with the theory and approaches of machine learning and would like to specialize in this field
  • Advanced programming skills in Python and related libraries (pandas, numpy, PyTorch) preferable
  • A high level of motivation, willingness to learn and independence
  • Good language skills in German and/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/75788/

For any further information on this position please contact:
Lars Leyendecker M.Sc.
Group manager »Production Quality«
Phone: +49 241 8904-314

Um dich für diesen Job zu bewerben, besuche bitte jobs.fraunhofer.de.