Frisch promoviert

Using AI to achieve the optimal vehicle chassis

Using AI, Tobias Lehrer has developed methods that can assess, more quickly than before, how the development process for vehicle chassis components can be optimised.

1. You’ve completed your PhD – what does that mean for you personally?

A PhD involves a wide range of challenges. I’m grateful for the opportunity to have grown both professionally and personally through these tasks.

2. What is your thesis about?

The development of components for vehicle chassis is a complex and time-consuming process. Throughout the entire development phase, it is essential to ensure that the designed components can subsequently be manufactured reliably. Simulation techniques provide valuable mechanical assessments for this purpose, but are often associated with long computation times and thus delay the development process.
This is precisely where my research comes in: using artificial intelligence, I am developing methods that automate these assessments and deliver them in a significantly shorter time. This provides developers with faster feedback and enables them to make informed decisions as early as the initial stages of product development.

3. What was a highlight or a special experience in connection with your PhD?

Many worthwhile scientific discoveries come at the end of an arduous journey. It’s a real highlight when, at the end of such a journey, your own idea actually works.

4. What are your plans for your future career?

I have already put these plans into action. Artificial intelligence has long since become part of everyday life – including in engineering, where innovative software solutions make existing development processes significantly more efficient. In my day-to-day work, I collaborate with clients to develop bespoke applications that intelligently combine artificial intelligence with traditional engineering. The result: shorter product development cycles and higher-quality products.

5. What advice can you give to future PhD students?

As every PhD is as individual as the person behind it, there’s no one-size-fits-all formula – the important thing is to savour your successes, see the low points through, and form as realistic a picture as possible of what a PhD entails from the outset. In any case, a thirst for research and technical curiosity are helpful

6. Why did you choose OTH Regensburg for your PhD?

Good supervision is a key prerequisite for a successful PhD. I got to know Prof. Marcus Wagner whilst I was still an undergraduate at OTH Regensburg. Even back then, I was confident that our collaboration would be successful – and that confidence was confirmed.

 

LINKS

Tobias Lehrer on ResearchGate.net

Tobias Lehrer wearing his doctoral cap after his thesis defence. Photo: Katharina Eichenseer
Tobias Lehrer wearing his doctoral cap after his thesis defence. Photo: Katharina Eichenseer

Tobias Lehrer (7 September 1994, Nuremberg)

Profile

    • Field of study

      Mechanical Engineering

    • PhD subject

      Artificial Intelligence in Engineering

    • PhD period

      April 2020 – June 2026

    • University / Faculty

      OTH Regensburg/Mechanical Engineering

    • Partner institution / Faculty

      Technical University of Munich

    • Industry partner

      Scale GmbH, BMW AG

Field of study

PhD subject

PhD period

University / Faculty

Partner institution / Faculty

Industry partner

Mechanical Engineering

Artificial Intelligence in Engineering

April 2020 – June 2026

OTH Regensburg/Mechanical Engineering

Technical University of Munich

Scale GmbH, BMW AG

    • Supervisor, OTH Regensburg

      Prof. Dr.-Ing. Marcus Wagner, supervisor and examiner

    • Supervisor, TU Munich

      Prof. Dr.-Ing. habil. Fabian Duddeck, PhD, Supervisor and External Examiner

    • Title of the doctoral thesis

      Data-driven Modelling of Early-Stage Manufacturability Assessments of Deep Drawing Processes

    • Funding

      Public funding through the “Central Innovation Programme for SMEs (ZIM)” funding scheme

Supervisor, OTH Regensburg

Supervisor, TU Munich

Title of the doctoral thesis

Funding

Prof. Dr.-Ing. Marcus Wagner, supervisor and examiner

Prof. Dr.-Ing. habil. Fabian Duddeck, PhD, Supervisor and External Examiner

Data-driven Modelling of Early-Stage Manufacturability Assessments of Deep Drawing Processes

Public funding through the “Central Innovation Programme for SMEs (ZIM)” funding scheme