Roman Möhle, M.Sc. studied Industrial Engineering at the TU Dortmund University of Technology. He is a research associate at IPS in the Smart Quality department. His focus is on the integration of machine learning and image processing systems in production systems as well as the quality field of technical cleanliness.

• Use of machine learning and AI in production systems.
• Technical cleanliness in production systems
• Development of intelligent image processing systems in a production context

• Supervision of project and final theses
• Realization of lecture series(es) of the IPS
• Execution of exercises to the lectures of the IPS

• Creation of data analysis and integration of intelligent AI models in production.
• Analysis and improvement of the technical cleanliness of production systems

• Panusch T., Möhle R., Zwinkau R., Deuse J. (2021) Reduction of Human Effort in Technical Cleanliness Inspection Through Advanced Image Processing Approaches. In: Trzcielinski S., Mrugalska B., Karwowski W., Rossi E., Di Nicolantonio M. (eds) Advances in Manufacturing, Production Management and Process Control. AHFE 2021. Lecture Notes in Networks and Systems, vol 274. Springer, Cham. doi.org/10.1007/978-3-030-80462-6_14
• Zwinkau, Ronny; Möhle, Roman; Frentrup, Simon; Deuse, Jochen (2019): Automatic particle classification through deep learning approaches for increasing productivity in the technical cleanliness laboratory, International Conference on Applied Automatic particle classification through deep learning approaches for increasing productivity in the technical cleanliness laboratory. In: Isabel L. Nunes (Hg.): Advances in Human Factors and Systems Interaction. Proceedings of the AHFE 2019 International Conference on Human Factors and Systems Interaction. Washington D.C., USA, 24.-28.07.2019: Springer.
• Zwinkau, Ronny; Frentrup, Simon; Möhle, Roman; Deuse, Jochen (2018): Metall/Nichtmetall- Klassifikation von Partikeln mit Deep Learning. In: Journal für Oberflächentechnik (JOT) (10), 50-57.