Bodden E, Pottebaum J, Fockel M, Gräßler I. Evaluating Security Through Isolation and Defense in Depth. IEEE Security &; Privacy. 2024;22(1):69-72. doi:10.1109/msec.2023.3336028

Pottebaum J, Ebel M, Gräßler I. Uncovering Impact of Innovation: Continuous Stakeholder Engagement through Scenario-based Systems Engineering. In: Penkert B, Hellingrath B, Rode M, et al., eds. Proceedings of the 21st ISCRAM Conference (ISCRAM 2024). ISCRAM; 2024. doi:10.5281/ZENODO.11298332

Gräßler I, Wiechel D, Özcan D, Taplick P. Tailored metrics for assessing the quality of MBSE models. In: Proceedings of the Design Society. Vol 4. Cambridge University Press (CUP); 2024:2545-2554. doi:10.1017/pds.2024.257

Gräßler I, Wiechel D, Koch A-S, Sturm T, Markfelder T. Methodology for Certification-Compliant Effect-Chain Modeling. Systems. 2023;11(3). doi:10.3390/systems11030154

Gräßler I, Preuß D. Automatisierte Abhängigkeitsanalyse von Anforderungen zur Wirkkettenmodellierung. In: Hölzle K, Kreimeyer M, Roth D, Maier T, Riedel O, eds. Stuttgarter Symposium Für Produktentwicklung SSP 2023. Fraunhofer IAO; 2023.

Gräßler I, Wiechel D. Customized impact analyses for technical engineering changes. In: 2023 18th Annual System of Systems Engineering Conference (SoSe). IEEE; 2023. doi:10.1109/sose59841.2023.10178484

Gräßler I, Mozgova I, Pottebaum J, Ott M, Jung P, Hesse P. Handling of uncertainties in the design of sustainable Additive Manufacturing products by merging Design-for-X and Scenario-Technique. In: Teti R, ed. Procedia CIRP ICME. Elsevier; 2023.

Weller J, Roesmann D, Eggert S, von Enzberg S, Gräßler I, Dumitrescu R. Identification and prediction of standard times in machining for precision steel tubes through the usage of data analytics. In: Procedia CIRP. Vol 119. Elsevier BV; 2023:514-520. doi:10.1016/j.procir.2023.01.011

Gräßler I, Tusek AM, Özcan D. Entwicklung zukunftsfähiger Geschäftsmodelle in der Automatisierungstechnik anhand von Megatrends. In: VDI Wissensforum GmbH, ed. Automation 2023. Vol 2419. Transformation by Automation. VDI Verlag; 2023:863-874. doi:10.51202/9783181024195-863

Gräßler I, Özcan D, Preuß D. KI-basierte Extrahierung von Anforderungen aus Regularien für die Automobilentwicklung. In: Krause D, Paetzold-Byhain K, Wartzack S, eds. Design fox X - Beiträge zum 34. DfX-Symposium. Vol 34. ; 2023:163-172. doi:10.35199/dfx2023.17

Gräßler I, Bodden E, Wiechel D, Pottebaum J. Defense-in-Depth als neues Paradigma der sicherheitsgerechten Produktentwicklung: interdisziplinäre, bedrohungsbewusste und lösungsorientierte Security. Konstruktion. 2023;75(11-12):60-65. doi:10.37544/0720-5953-2023-11-12-60

Gräßler I, Steffen E, Maier GW, Roesmann D. Introduction—The Digital Twin of Humans. In: Gräßler I, Maier GW, Steffen E, Roesmann D, eds. The Digital Twin of Humans. Springer International Publishing; 2023:3-10. doi:10.1007/978-3-031-26104-6_1

Gräßler I, Maier GW, Steffen E, Roesmann D, eds. The Digital Twin of Humans. Springer International Publishing; 2023. doi:10.1007/978-3-031-26104-6

Roesmann D, Gräßler I. Integration of Human Factors for Assembly Systems of the Future. In: The Digital Twin of Humans. Springer International Publishing; 2023:187–203. doi:10.1007/978-3-031-26104-6_9

Gräßler I, Koch A-S, Tusek AM. POTENTIALS AND GOALS OF MODELS IN STRATEGIC PRODUCT PLANNING AND INNOVATION MANAGEMENT. In: Proceedings of the Design Society. Vol 3. Cambridge University Press (CUP); 2023:2915-2924. doi:10.1017/pds.2023.292

Hesse P, Gräßler I. Interdependency study of design guidelines. In: Horwath I, Schweizer S, eds. Climate Protection, Resource Efficiency, and Sustainable Engineering: Transdisciplinary Approaches to Design and Manufacturing Technology. 1. transcript; 2023:128-138.

Hesse P, Gräßler I. Sustainable product life cycle. In: Horwath I, Schweizer S, eds. Climate Protection, Resource Efficiency, and Sustainable Engineering: Transdisciplinary Approaches to Design and Manufacturing Technology. 1. transcript; 2023:89-98.

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

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 

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