Jan Mertes, M.Sc.

Wissenschaftlicher Mitarbeiter

Kontakt

Telefon: +49 631 205 4306

Telefax: +49 631 205 3304

E-Mail: jan.mertes(at)rptu.de


Adresse

Erwin-Schrödinger-Straße
67663 Kaiserslautern

Gebäude 57
Raum 226

Details

  • seit April 2021 Wissenschaftlicher Mitarbeiter am FBK
  • Forschungsschwerpunkt: Digitale Technologien für Produktionssysteme

 

Veröffentlichungen

Journals

J. Mertes, C. Schellenberger, L. Yi, M. Schmitz, M. Glatt, M. Klar, B. Ravani, H.D. Schotten, J.C. Aurich: Experimental evaluation of 5G performance based on a digital twin of a machine tool. CIRP Journal of Manufacturing Science and Technology 55 (2024): S. 141-152. 10.1016/j.cirpj.2024.09.012

L.Yi, P.Ruediger-Flore, A. Karnoub, J. Mertes, M. Glatt, J.C. Aurich: Is it possible to develop a digital twin for noise monitoring in manufacturing? Digital Twin (2024). 10.12688/digitaltwin.17931.1 

L. Yi, J. Mertes, M. Klar, S. Ghansiyal, C. Fei, M. Glatt, J.C. Aurich: A new gradient infill design method for material extrusion using density-based topology optimization and G-code extension. Manufacturing Letters 37 (2023): S.21-25. 10.1016/j.mfglet.2023.06.003

P. Ruediger-Flore, M. Klar, M. Hussong, J. Mertes, L. Yi, M. Glatt, P. Kölsch, J. C. Aurich: Neural Radiance Fields in der Fabrikplanung - Untersuchung von Neural Radiance Fields zur Modellrekonstruktion in der Fabrikplanung. WT Werkstattstechnik  113/6 (2023) S.219-223 10.37544/1436-4980-2023-06-11

J. Mertes, D. Lindenschmitt, M. Amirrezai, N. Tashakor, M. Glatt, C. Schellenberger, S.M. Shah, A. Karnoub, C. Hobelsberger, L. Yi, S. Götz, J.C. Aurich, H.D. Schotten: Evaluation of 5G-capable framework for highly mobile, scalable human-machine interfaces in cyber-physical production systems. Journal of Manufacturing Systems 64 (2022): S. 578-593.

J. Mertes, M. Klar, D. Lindenschmitt, M. Glatt, H. D. Schotten, J. C. Aurich: Adaptive Informationsdarstellung in der industriellen Produktion: Konzeption eines 5G-fähigen AR-Systems. ZWF - Zeitschrift für wirtschaftlichen Fabrikbetrieb 116/11 (2021): S.757-761.

Conferences

A. Mukherjee, J. Mertes, M. Glatt, J.C. Aurich: Voice User Interface based control for Industrial machine tools. Procedia CIRP 121 - Proceedings of the 11th CIRP Global Web Conference (2024): S. 121-126. 10.1016/j.procir.2023.09.238

M. Glatt, P. Kölsch, M. Wagner, J. Mertes, J.C. Aurich: Framework for synergetic integration of heterogenous Digital Twins in Manufacturing Systems.Procedia CIRP 120 - Proceedings of the 56th CIRP International Conference on Manufacturing Systems (2023): S. 798-803. 10.1016/j.procir.2023.09.078

J. Mertes, M. Glatt, C. Schellenberger, P. M. Simon, L. Yi, H. D. Schotten, J. C. Aurich: Implementation and Evaluation of 5G-enabled sensors for Machine Tools. Procedia CIRP 120 - Proceedings of the 56th CIRP Conference on Manufacturing Systems (2023): S. 45-50. 10.1016/j.procir.2023.08.009

M. Glatt, P. Kölsch, M. Wagner, J. Mertes, J. C. Aurich: Framework for synergetic integration of heterogenous Digital Twins in Manufacturing Systems. Procedia CIRP 120 - Proceedings of the 56th CIRP Conference on Manufacturing Systems  (2023): S. 798-803. 10.1016/j.procir.2023.09.078

J. Mertes, M. Glatt, L. Yi, M. Klar, B. Ravani ,J.C. Aurich: Modeling and Implementation of a 5G-Enabled Digital Twin of a Machine Tool Based on Physics Simulation. Proceedings of the 3rd Conference on Physical Modeling for Virtual Manufacturing Systems and Processes. IRTG 2023. Springer (2023): S.90–110. 10.1007/978-3-031-35779-4_6 

M. Klar, J. Mertes, M. Glatt, B. Ravani, J. C. Aurich: A Holistic Framework for Factory Planning Using Reinforcement Learning. Proceedings of the 3rd Conference on Physical Modeling for Virtual Manufacturing Systems and Processes. IRTG 2023. Springer (2023). S. 129–148. 10.1007/978-3-031-35779-4_8.

 Mertes, M. Glatt, C. Schellenberger, M. Klar, H.D. Schotten, J.C. Aurich: Development of a 5G-enabled Digital Twin of a Machine Tool. Procedia CIRP 107 (2022): S. 173-178.

C.Siedler, J.Mertes, Li Yi, M.Glatt, C.Schellenberger, H.D.Schotten, J.C.Aurich: 5G as an enabler for cloud-based machine tool control. Procedia CIRP 104 - Proceedings of the 54th CIRP Conference on Manufacturing Systems (2021):S.235–240