Publikationen

Bekemeier, S.; Caldeira Rêgo, C. R.; Mai, H. L.; Saikia, U.; Waseda, O.; Apel, M.; Arendt, F.; Aschemann, A.; Bayerlein, B.; Courant, R.; Dziwis, G.; Fuchs, F.; Giese, U.; Junghanns, K.; Kamal, M.; Koschmieder, L.; Leineweber, S.; Luger, M.; Lukas, M.; Maas, J.; Mertens, J.; Mieller, B.; Overmeyer, L.; Pirch, N.; Reimann, J.; Schröck, S.; Schulze, P.; Schuster, J.; Seidel, A.; Shchyglo, O.; Sierka, M.; Silze, F.; Stier, S.; Tegeler, M.; Unger, J.; Weber, M.; Hickel, T.; Schaarschmidt, J. (2025): Advancing Digital Transformation in Material Science: The Role of Workflows Within the MaterialDigital Initiative,  Advanced Engineering Materials published by Wiley-VCH GmbH
DOI: 10.1002/adem.202402149

Aschemann, A.; Hagen, P.; Albers, S.; Rofallski, R.; Schwabe, S.; Dagher, M.; Lukas, M.; Leineweber, S.; Klie, B.; Schneider, P.; Bossemeyer, H.; Hinz, L.; Kastner, M.; Reitz, B.; Reithmeier, E.; Luhmann, T.; Wackerbarth, H.; Overmeyer, L.; Giese,U. (2024): Smart Rubber Extrusion Line Combining Multiple Sensor Techniques for AI-Based Process Control,  Advanced Engineering Materials Journal
DOI: 10.1002/adem.202401316

Lukas, M.; Leineweber, S.; Reitz, B.; Overmeyer, L. (2024): Real-time temperature control in rubber extrusion lines: a neural network approach,  The International Journal of Advanced Manufacturing Technology
DOI: 10.1007/s00170-024-14061-1

Lukas, M.; Leineweber, S.; Reitz, B.; Overmeyer, L.; Aschemann, A.; Klie, B.; Giese, U. (2024): Minimizing Temperature Deviations in Rubber Mixing Process using Artificial Neural Networks,  Rubber Chemistry and Technology (2024)
DOI: 10.5254/rct.24.00003

Lukas, M.; Leineweber, S.; Reitz, B.; Overmeyer, L.; Aschemann, A.; Klie, B.; Giese, U. (2023): Data Mining-Enabled Temperature Control for Sustainable Production in Rubber Extrusion Lines: An Artificial Neural Network-Based Approach,  WGP 2023: Production at the Leading Edge of Technology pp 539–549
DOI: 10.1007/978-3-031-47394-4_52

Lukas, M.; Leineweber, S.; Reitz, B.; Overmeyer, L.; Aschemann, A.; Klie, B.; Giese, U. (2023): Minimizing Temperature Deviations in Rubber Extrusion Lines using Artificial Neural Network based Process Control,  Presented at the 204th Technical Meeting Rubber Division, ACS International Elastomer Conference in Cleveland, Ohio

Lukas, M.; Leineweber, S.; Overmeyer L. (2023): Künstliche Intelligenz und Data-Mining in der Kautschukextrusion,  phi – Produktionstechnik Hannover informiert, Newsletter Nr. 39
DOI: 10.48811/phi-23-006