KIT | KIT-Bibliothek | Impressum | Datenschutz

Stakeholder-Based Deterministic and Probabilistic Quality Control Using Gaussian Mixtures for Circular Factories

Darijani, Ali ORCID iD icon 1,2,3; Moser, Gabriel ORCID iD icon 4; Vlajic, Kristian ORCID iD icon 4; Nasrollah, Zahra Sadat Hajseyed 1,2,3; Hoffmann, Luisa ORCID iD icon 5; Khabou, Mehdi 6; Düser, Tobias 4; Albers, Albert 4; Dietrich, Stefan ORCID iD icon 6; Heizmann, Michael 5; Beyerer, Jürgen 1,2,3
1 Fakultät für Informatik – Lehrstuhl IES Beyerer: Interaktive Echtzeitsysteme (Lehrstuhl IES Beyerer: Interaktive Echtzeitsysteme), Karlsruher Institut für Technologie (KIT)
2 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)
3 Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung (IOSB)
4 Institut für Produktentwicklung (IPEK), Karlsruher Institut für Technologie (KIT)
5 Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie (KIT)
6 Institut für Angewandte Materialien – Werkstoffkunde (IAM-WK), Karlsruher Institut für Technologie (KIT)

Abstract:

Quality Control (QC) in Circular Factorys (CFs) is fundamentally more challenging due to the uncertainty of the incoming prod-
ucts to be reprocessed, compared to linear factories, which have tight tolerances on the input raw materials and parts. One must have an expressive model to manage the multimodality of circular factories. QC and the decision-making process that it entails can be understood as a mapping from system requirements and variation space to discrete decisions, which can be formulated either deterministically or probabilistically. Ideally, the model must also be able to handle the deterministic and probabilistic cases seamlessly. Gaussian Mixture Models (GMMs) and their universal approximation property are considered suitable for the circular factory context. GMM can also address deterministic cases by approximating the Dirac delta as a limiting case. We present a stakeholder-oriented QC framework in which stakeholder requirements, product generations, and alternative solutions for new product generations are represented probabilistically over quality-relevant variation spaces. Two complementary decision perspectives are considered. ... mehr


Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Institut für Industrielle Informationstechnik (IIIT)
Institut für Produktentwicklung (IPEK)
Fakultät für Informatik – Lehrstuhl IES Beyerer: Interaktive Echtzeitsysteme (Lehrstuhl IES Beyerer: Interaktive Echtzeitsysteme)
Institut für Angewandte Materialien – Werkstoffkunde (IAM-WK)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2026
Sprache Englisch
Identifikator KITopen-ID: 1000198415
Erschienen in Conference on Circular Production Systems and Technologies (CCPT 2026)
Veranstaltung Conference on Circular Production Systems and Technologies (CCPT 2026), Karlsruhe, Deutschland, 08.06.2026 – 10.06.2026
Verlag Springer
Bemerkung zur Veröffentlichung Accepted to "2026 Conference on Circular Production Systems and Technologies (CCPT)"
Schlagwörter Quality Control, Probabilistic Representation, Gaussian, Mixture, Circular Factory
KIT – Die Universität in der Helmholtz-Gemeinschaft
KITopen Landing Page