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Ahmeti, Engjëll ; Herold, Maximilian ; Koller, Jan ; Döpper, Frank:
Using Stable Diffusion Based Augmentation for Visual Wear Classification in Remanufacturing.
In: Kohl, Holger ; Seliger, Günther ; Dietrich, Franz ; Campana, Giampaolo
(Hrsg.):
Safe and Sustainable Value Creation by Design. -
Cham
: Springer
,
2026
. - S. 160-168
ISBN 978-3-032-21154-5
DOI: https://doi.org/10.1007/978-3-032-21154-5_18
Abstract
The increasing demand for raw materials and shorter product cycles have driven the advancement of the circular economy, with the European Union focusing on reducing raw material consumption and ensuring the circularity of products and components. Remanufacturing, a key element of circular economy, faces challenges in assessing the condition of products and components, a process traditionally carried out manually, requiring expert knowledge. This paper aims to address the lack of diverse datasets by generating synthetic datasets to enable AI-supported visual inspections in remanufacturing. Specifically, this paper focuses on generating realistic wear patterns, in the example of corrosion effects, with starter motors as the reference product. The research explores different diffusion models, emphasizing globally generated corrosion patterns. The outcomes include the creation of a synthetic dataset, the development of an accurate wear classification model, and a validated framework for integrating AI-based inspections in remanufacturing operations. This approach aims to improve efficiency and quality in remanufacturing processes, contributing to a circular economy.
Weitere Angaben
| Publikationsform: | Aufsatz in einem Buch |
|---|---|
| Begutachteter Beitrag: | Ja |
| Institutionen der Universität: | Fakultäten > Fakultät für Ingenieurwissenschaften > Lehrstuhl Umweltgerechte Produktionstechnik > Lehrstuhl Umweltgerechte Produktionstechnik - Univ.-Prof. Dr.-Ing. Frank Döpper |
| Titel an der UBT entstanden: | Nein |
| Themengebiete aus DDC: | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften |
| Eingestellt am: | 12 Mai 2026 05:55 |
| Letzte Änderung: | 12 Mai 2026 05:55 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/97019 |