Schimanek, RobertDietrich, FranzKemmerling, Luis2024-02-142024-02-142024-01-14https://depositonce.tu-berlin.de/handle/11303/20749https://doi.org/10.14279/depositonce-19547Modern industries face complexity with diverse products and shorter lifecycles, shifting towards circular economy principles for value preservation and profitability. Artificial Intelligence (AI), specifically Machine Learning and Deep Learning, is considered for efficient product identification and evaluation in reverse logistics and prior to remanufacturing. However, the industrial viability of AI in this context remains to be determined. This research explores potential applications, challenges, technologies, and implementation aspects through expert interviews. The gained insights clarify the effectiveness of AI in product management within reverse logistics across diverse sectors. This data is referenced by "Cameraless and worker-centred AI inspection prior to assembly and disassembly", 2024, Annals of the CIRIPen600 Technik, Medizin, angewandte Wissenschaften::620 Ingenieurwissenschaften::620 Ingenieurwissenschaften und zugeordnete Tätigkeiteninspectionmachine learningcircular economyartificial intelligencesustainable manufacturingmaschinelles LernenKreislaufwirtschaftkünstliche Intelligenznachhaltige FertigungTextual Data