AI-enhanced Identification, Inspection and Sorting for Reverse Logistics in Remanufacturing
| Autor: | Katharina Schweitzer, Clemens Briese, Hannah Lickert, Franz Dietrich, Jörg Krüger, Pinar Bilge, Marian Schlüter |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Computer science Machine vision Circular economy Cognitive neuroscience of visual object recognition Sorting 02 engineering and technology Reverse logistics 010501 environmental sciences 01 natural sciences Manufacturing engineering Identification (information) 020901 industrial engineering & automation General Earth and Planetary Sciences Remanufacturing Digitization 0105 earth and related environmental sciences General Environmental Science |
| Zdroj: | Procedia CIRP. 98:300-305 |
| ISSN: | 2212-8271 |
| DOI: | 10.1016/j.procir.2021.01.107 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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