Optimizing Learning Pathways for Digital Twin Education in Manufacturing Systems
Rechkemmer, D.; Korth, M.; Behrendt, S.; May, M. C.; Benfer, M.; Lanza, G.
2026. Advancing Learning Factories: Enabling Future-Ready Skills – Proceedings of the 15th Conference on Learning Factories 2025, Volume 1. Ed.: L. Louw, I. de Kock, K. von Leipzig, 62–69, Springer Nature Switzerland. doi:10.1007/978-3-031-98880-6_8

Conference on Circular Production Systems and Technologies (CCPT) 2026 - Book of Abstracts
Grauberger, P.; Zanger, F.; Lanza, G. (Hrsg.)
2026

Semantic 3D product modelling for automated inspection in remanufacturing processes
Kaiser, J.-P.; Koch, D.; Stamer, F.; Peeters, J.; Lanza, G.
2026. Journal of Remanufacturing, 16 (1), Artikel-Nr.: 1. doi:10.1007/s13243-025-00157-8

Datenbasierte Erstellung und Überprüfung von Modellen zur Produkt- und Prozesskonfiguration. Dissertation
Frey, A. M.
2026, Februar 11. Shaker Verlag. doi:10.5445/IR/1000190408

Uncertainty-Aware Prognostics of Ball Bearings Using Physics-Based Simulation and Conditional Normalizing Flows
Bott, A.; Liu, B.; Nuding, L.; Wachsmuth, J.; Puchta, A.; Jürgen, F.
2026. IEEE Access, 14 (1), 1. doi:10.1109/ACCESS.2026.3661174

Pre-Filtered Numerical Integration for Machine Tool Vibration Measurements
Heimberger, F.; Oexle, F.; Puchta, A.; Fleischer, J.
2026. doi:10.5445/IR/1000190302

Rotational moulding for small diameter continuous fibre reinforced thermoplastics structures
Schaible, P.; Ehret, J.; Schabel, S.; Fleischer, J.
2026. Composites and Advanced Materials, 35. doi:10.1177/26349833261420239

Investigation of the formation and reduction of hydrogen porosity during laser welding of additively manufactured AlSi10Mg parts
Kramer, S.; Lubkowitz, V.; Haas, M.; Michel, J.; Spurk, C.; Olowinsky, A.; Faria, G. A.; Jarwitz, M.; Graf, T.; Schulze, V.; Zanger, F.
2026. The International Journal of Advanced Manufacturing Technology. doi:10.1007/s00170-025-17198-9

Ressourceneffiziente Kreislaufsysteme am KIT (REKS@KIT): Herausforderungen – Forschungsbedarfe – Empfehlungen
Albiez, M.; Dehn, F.; Eiche, E.; Grauberger, P.; Hilgers, C.; Holtmann, D.; Hoose, C.; Kaster, A.-K.; Kirchlechner, C.; Meier, M.; Rabe, K.; Matthiesen, S.; Schultmann, F.; Schulze, V.; Selzer, M.; Stapf, D.; Stemmermann, P.; Stutz, H.-H.; Ummenhofer, T.; Volk, R.; Wilcke, W.
2026. (C. Hilgers & V. Schulze, Hrsg.), Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000189474

Modeling Process–Microstructure Relations in PBF-LB/M Laser Treatment using Gaussian Process Surrogates and Bayesian Optimization
Groenewold, J.; Mai, D.; Stamer, F.; Lanza, G.
2026. doi:10.5445/IR/1000189041