Student for thesis: AI-supported quality monitoring in metal arc welding

Life is always about becoming... In life it is about going on a journey to become the best version of our future self. As we discover new things, we face challenges, master them and grow beyond us.

Apply to Mercedes-Benz and find the area where you can develop your talents individually. You will be supported by visionary colleagues who share your pioneering spirit. Joining us means becoming part of a global team whose goal is to build the most desirable cars in the world. Together for excellence.

Number: MER0003VHT In the Team Design Engineering, Forming and Joining Technology Axis we design the manufacturing technologies that will shape the production of coming vehicle generations. Our focus is on modern track and arc welding processes for chassis and structural components – with the aim of continuously increasing quality, efficiency and flexibility in production. In close cooperation with the production areas, we develop new technologies from the first idea to the robust series application and thus advance measurable progress in production. Driven by the enormous potential of artificial intelligence, we are currently developing a new approach to data-based monitoring of metal-protection gas welding. With the help of machine learning methods, process signals are to be analyzed in such a way that the state of the welding seam can be reliably assessed immediately after the welding process – completely based on the detected data. Investigations under laboratory conditions have already shown that the approach works technically and has a high development potential. In the final work, this approach is now to be tested under real series conditions and validated by real welding. These challenges come to you: Integration into MSG welding and the basics of machine learning

Analysis and processing of real process data as a basis for the further steps

Training and comparison of different ML models for data-based quality determination

quantification of the effects of typical process variations on model quality and validation of models under standard conditions

Development of concepts for increasing model erosion

Interpretation and documentation of your results and derivation of concrete recommendations for serial use

The activity can begin from February 2026. The final topics will be discussed with the university, you and us.

Course in Computer Science, Mechanical Engineering, Industrial Engineering, Data Science or a comparable degree programme

Secure knowledge of German and English in word and writing

Safe handling of MS Office and Python (or comparable)

Commitment and team skills

Communication

Self-employed

Fun on data science and application in practice

Additional information: We are looking forward to your online application with CV, lettering, certificates, current enrollment certificate, giving the semester and proof of the regular study period. Please do not forget to mark your documents as ''relevant for this application' in the online form and to observe the maximum file size of 5 MB. Further information on the setting criteria can be found here. Disabled and equalized applicants are welcome! The severely disabled representative (SBV-Untertuerkheim@mercedes-benz.com) is happy to support you in the application process. HR Services will be happy to help you with questions about the application process. You can reach us by email via myhrservice@mercedes-benz.com or by phone at 0711/17-99000 (Mo-Fr 10-12am & 13-15am).

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