Robin Ströbel, M.Sc.

  • 76131 Karlsruhe
    Kaiserstraße 12

Ströbel Robin, M.Sc.

Area of Research:

  • Software-defined Manufacturing and digital Twins
  • Industrie 4.0

General Tasks:


  • SDM4FZI: Software-defined Manufacturing in der Fahrzeug- und Zulieferindustrie
  • SDMflex : Flexible SDM through Continuously Self-Learning Quality-Aware Digital Twins

Curriculum Vitae:

since 04/2022

Research Associate at the Institute of Production Science (wbk) at Karlsruhe Institute of Technology (KIT)


Study of mechanical engineering (M.Sc.) at Karlsruhe Institute of Technology (KIT)


Exchange semester at Jiaotong-Universität Shanghai (SJTU)


Study of mechanical engineering (B.Sc.) at Karlsruhe Institute of Technology (KIT)


Framework for Holistic Online Optimization of Milling Machine Conditions to Enhance Machine Efficiency and Sustainability
Bott, A.; Anderlik, S.; Ströbel, R.; Fleischer, J.; Worthmann, A.
2024. Machines, 12 (3), Art.-Nr.: 153. doi:10.3390/machines12030153
Interoperable system for automated extraction and identification of machine control data in brownfield production
Gönnheimer, P.; Ströbel, R.; Dörflinger, R.; Mattes, M.; Fleischer, J.
2023. Manufacturing Letters, 35, 915 – 925. doi:10.1016/j.mfglet.2023.08.010
Training and validation dataset 2 of milling processes for time series prediction
Ströbel, R.; Mau, M.; Deucker, S.; Fleischer, J.
2023, September 15. doi:10.35097/1738
Software-Defined Manufacturing for the Entire Life Cycle at Different Levels of Production
Behrendt, S.; Martin, M.; Puchta, A.; Ströbel, R.; Fisel, J.; May, M.; Gönnheimer, P.; Fleischer, J.; Lanza, G.
2023. Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains : Stuttgart Conference on Automotive Production (SCAP2022). Ed.: N. Kiefl, 25–34, Springer International Publishing. doi:10.1007/978-3-031-27933-1_3
Generalizability of an Identification Approach for Machine Control Signals in Brownfield Production Environments
Gönnheimer, P.; Ströbel, R.; Dörflinger, R.; Mattes, M.; Alexander, P.; Wuest, T.; Fleischer, J.
2023. Procedia CIRP, 120, 649 – 654. doi:10.1016/j.procir.2023.09.053
A Model-Driven Digital Twin for Manufacturing Process Adaptation
Spaney, P.; Becker, S.; Ströbel, R.; Fleischer, J.; Zenhari, S.; Möhring, H.-C.; Splettstößer, A.-K.; Wortmann, A.
2023. 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), Västerås, 1st-6th October 2023, 465 – 469, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MODELS-C59198.2023.00081
Potential of systematically generated training datasets on the accuracy and generalization of AI-based approaches for the automated identification of machine control signals
Gönnheimer, P.; Ströbel, R.; Roßkopf, A.; Dörflinger, R.; Walter, I.; Becker, J.; Fleischer, J.
2023. 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering CIRP ICME ‘22, Italy. Hrsg.: R. Teti, D. D’Addona, 145 – 150, Elsevier. doi:10.1016/j.procir.2023.06.026
Software-Defined Workpiece Positioning for Resource-Optimized Machine Tool Utilization
Ströbel, R.; Probst, Y.; Hutt, L.; Fleischer, J.
2023. Journal of Machine Engineering, 23 (1), 71–84. doi:10.36897/jme/161660