- Titel
- Automated Adaptation of Digital Twins for Production Line Design by Adapting Existing Models Through LLM-Guided Expert Interviews
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-996961
- Übersetzter Titel (DE)
- Automatisierte Anpassung digitaler Zwillinge für die Produktionslinienplanung durch Anpassung bestehender Modelle mittels LLM-geführter Experteninterviews
- Konferenz
- 21. ASIM-Fachtagung Simulation in Produktion und Logistik. Dresden, Germany, 24. bis 26. September 2025
- Quellenangabe
- Simulation in Produktion und Logistik 2025
Herausgeber: Sebastian Rank
Herausgeber: Mathias Kühn
Herausgeber: Thorsten Schmidt
Erscheinungsort: Dresden
Verlag: Technische Universität Dresden, Professur für Technische Logistik
Erscheinungsjahr: 2025
ISBN: 978-3-86780-806-4 - Erstveröffentlichung
- 2025
- DOI
- https://doi.org/10.25368/2025.247
- Abstract (EN)
- The design of new production lines is a costly process, considering multiple variants must be compared. Simulations are indispensable to evaluate different production concepts. However, they require detailed models. A digital twin, which can be used not only in the design phase but also in operation, offers potential here. The creation of such a twin is often complex, as it requires a complex modelling phase. This paper presents a framework to automate the creation of digital twins for production line design by adapting existing models through Large Language Model-guided expert interactions. New production lines often are similar to existing ones, for which digital twins can be generated by process mining. The adaptation of these models is then carried out by a domain expert using a Large Language Model that allows to make changes to the digital twin without greater modelling knowledge. The framework is evaluated using a case study from the “IoTFactory” at our university. The results show that it is suitable for reducing the effort needed to create digital twins for production line design by adapting existing models.
- Freie Schlagwörter (DE)
- Simulation, Künstliche Intelligenz, Modellierung, Optimierung, Produktionslinie, Konstruktionsphase
- Freie Schlagwörter (EN)
- Simulation, Artificial Intelligence, Modelling, Optimisation, Production line, design phase
- Klassifikation (DDC)
- 620
- Klassifikation (RVK)
- ZM 9500
- Publizierende Institution
- Technische Universität Dresden, Dresden
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-996961
- Veröffentlichungsdatum Qucosa
- 18.10.2025
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY-SA 4.0