Gräßler I, Ovtcharova J, Dattner M, et al. Begriffe Der Strategischen Produktplanung Und -Entwicklung. Produkt Und Hybride Leistung.; 2023.

Uhe B, Kuball C-M, Merklein M, Meschut G. Approach for a sustainable process chain in manufacturing of fasteners for mechanical joining. In: Materials Research Proceedings; 2023. doi:10.21741/9781644902417-49

Trienens D, Schöppner V, Bunse R. Determination of Correlations between Melt Quality and the Screw Performance Index in the Extrusion Process. Polymers 2023. Published online 2023. doi:https://doi.org/10.3390/polym15163427

Schöppner V, Kleinschmidt D. Improvement of a method for the correction of wall slip effects within the rheological measurements of filled rubber compounds. SPE Polymers. Published online 2023:1-17.

Gräßler I, Hieb M, Roesmann D, Unverzagt M. Creating Synthetic Training Data for Machine Vision Quality Gates. In: Lohweg V, ed. Springer Vieweg; 2023:95-106. doi:10.1007/978-3-662-66769-9_7 

Butzhammer L, Kappe F, Meschut G, Hausotte T. Dynamic conformity assessment for joining force monitoring using Bayes filters. In: Materials Research Proceedings. Materials Research Forum LLC; 2023. doi:10.21741/9781644902417-48

Gräßler I, Hieb M. Creating Synthetic Datasets for Deep Learning used in Machine Vision. In: CIRP ; 2023.

Gräßler I, Hesse P. CONSIDERING ENGINEERING ACTIVITIES AND PRODUCT CHARACTERISTICS TO ACHIEVE MATERIAL CIRCULARITY BY DESIGN. In: Proceedings of the Design Society. Vol 3. Cambridge University Press (CUP); 2023:1077-1086. doi:10.1017/pds.2023.108

Gräßler I, Roesmann D, Unverzagt M, Pottebaum J. Virtual Test Scenarios for Human-Centered Design with Virtual Measurement Systems. In: Poster. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany; 2023:416-417. doi:10.5162/smsi2023/p70

Gräßler I, Hieb M, Roesmann D, Unverzagt M, Pottebaum J. Virtual learning environment for teaching the handling of collaborative robots. In: SSRN Electronic Journal. Elsevier BV; 2023. doi:10.2139/ssrn.4471596

Gräßler I, Hieb M. Cloud-Computing für die Verwendung synthetischer Trainingsdaten für Machine Vision Quality Gates. In: Automation 2023. Vol 2419. VDI-Berichte. VDI Verlag ; 2023:765-776. doi:10.51202/9783181024195-765

Brüning F, Kleinschmidt D, Petzke J. Wall Slip-Free Viscosity Determination of Filled Rubber Compounds Using Steady-State Shear Measurements. Polymers. Published online 2023:1-23. doi:https://doi.org/10.3390/polym15224406

Schöppner V, Austermeier L, Brüning F, Oldemeier JP, Brandt O. Recycling-Ansatz für mehrkomponentige Kunststoffprodukte durch thermische Verbundtrennung. EXTRUSION. 2023;(8/2023):56-59.

Schöppner V, Arndt T. Anvil-free ultrasonic welding for welding situations with one sided access. In: 76th Annual Assembly of the International Institute of Welding (IIW). ; 2023.

Brüning F, Kleinschmidt D, Petzke J. Elastomerrecycling mittels Mikrowellenstrahlung. Kunststoffland NRW Report. 2023;(03/2023):28-29.

Moritzer E, Kartelmeyer S, Kringe R, Jaroschek C. Conformal Cooling at Low Cost. Plastics Insights. 2023;(8/2023):44-48.

Gräßler I, Hieb M. Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. In: Lectures. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany; 2023:253-524. doi:10.5162/smsi2023/d7.4

Gräßler I, Preuß D, Brandt L, Mohr M. Efficient Formalisation of Technical Requirements for Generative Engineering. In: Proceedings of the Design Society. ; 2023:1595-1604. doi:10.1017/pds.2023.160

Wituschek S, Kappe F, Meschut G, Lechner M. Combination of versatile self-piercing riveting processes. In: Materials Research Proceedings. Materials Research Forum LLC; 2023. doi:10.21741/9781644902417-16

Chalicheemalapalli Jayasankar D. Advances In RTM Manufacturing Of Metal-FRP Hybrids By Self-Sealing And In-Mold Cleaning Techniques.; 2023.