AI-enhanced Identification, Inspection and Sorting for Reverse Logistics in Remanufacturing

In a circular economy for remanufacturing, after each life cycle used products are returned to a remanufacturer for identification, inspection, sorting and reprocessing. Shortcomings and requirements of the remanufacturing market are identified through expert interviews and process analysis. A concept is proposed to enable an improved identification and a more objective inspection by enhancing the working environment and processes of sorting stations. Digitization and machine learning are applied on business data, using machine vision as well as sensor and actor skills of the worker. With an experimental case study on visual object recognition a positive impact on identification and thus sorting could be demonstrated.