Marcel Auer, M.Sc.

Marcel Auer, M.Sc.

  • Fritz-Haber-Weg 1, Geb. 30.33, R.110
    76131 Karlsruhe

Research

Engineering based on information models

Digital twins are virtual representations of physical systems and processes. They offer in-depth insights into their real counterparts through simulations, real-time data acquisition, and asset-specific documentation. This technology opens up new perspectives for industry, particularly in minimizing risks and costs while increasing efficiency.

Together with my colleagues in the IDEAS research group, I am investigating the areas of application of digital twins and their added value in industrial use. My focus is on using standardized information models (e.g. Asset Administration Shell, AAS) in the engineering process of large industrial plants. Particularly in regulated industrial sectors (pharmaceuticals, process industry, etc.), new plants and plant modifications can be planned in detail in advance with the help of digital twins and checked concerning the requirements set. This can significantly reduce the time required for certification processes and commissioning.

CV

01.12.2023 - today: Research assistant in the professorship of Secure Interconnected Automation Technology at the Institute of Control Systems (IRS)

  • with Prof. Dr.-Ing. Mike Barth of the Karlsruhe Institute of Technology

01.03.2023 - 30.11.2023: Development engineer at OPVengineering GmbH

  • Software development for automation of test benches for the development of e-drives

2022: M.Sc. Electrical Engineering and Information Technology at KIT

  • Field of Specialization: Sensor Systems
  • Master's thesis at Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) on the topic "Investigation on the Measurement Accuracy of a Laser-Induced Damage Threshold Testbed in the Short-Wave Infrared"

2017-2019: Student Researcher at the Institut für Technik der Informationsverarbeitung (ITIV)

  • Similarity assessment of driving situations using time-elastic methods for pattern recognition in time series
  • Consideration and evaluation of different methods for predictive maintenance applications in the automotive context

2018: B.Sc. Electrical Engineering and Information Technology at KIT

  • Bachelor thesis at ITIV on the topic "Conception and evaluation of methods of pattern recognition in time series of dynamic systems in the automotive context"