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Fostering collaboration between reuse, repair and recycling centers for electric and electronic equipment

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dc.contributor.author Sterkens, Wouter
dc.contributor.author Bracquené, Ellen
dc.contributor.author Goedemé, Toon
dc.contributor.author Dewulf, Wim
dc.contributor.author Peeters, Jef R.
dc.date.accessioned 2021-06-15T12:16:42Z
dc.date.available 2021-06-15T12:16:42Z
dc.date.issued 2021
dc.identifier.uri http://hdl.handle.net/10344/10190
dc.description non-peer-reviewed en_US
dc.description.abstract When an electronic device fails, treatment procedures and objectives can differ significantly depending on the actor who receives the device. For example, repair facilities generally focus on product reuse and rely on the expertise of employees to select models suitable for repair and subsequent reselling in second-hand stores, while recycling businesses generally focus on bulk processing to recycle raw materials. Even though devices destined for recycling might still qualify for repair or contain valuable/reusable components, there is no method to identify those models quickly in a cost-efficient manner. In addition, tools are lacking that facilitate the registration and retrieval of information on the repairability of specific models or the value of its spare parts. Therefore, an interactive web application has been developed in close collaboration with one of Europe’s largest networks of reuse and repair centers. The developed application can be used when performing triage to determine whether to repair or recycle a specific model. A photograph of the device label is uploaded to an online model identification pipeline. The latter recognizes text on the image with deep learning techniques and compares the text with a database to identify the model, allowing for model-specific information and previous repair experiences to be displayed to the user. Thereafter, novel triage and repair information can be registered and stored for later use. In the presented research, the triage and registration procedure is tested at two repair facilities on 97 washing machines. Learnings from the co-development as well as improvements made throughout the experiment on to the interactive interfaces and forms of the application are presented in this article. en_US
dc.language.iso eng en_US
dc.relation.ispartofseries 4th PLATE 2021 Virtual Conference, 26-28 May 2021;
dc.subject electric and electronic equipment en_US
dc.subject reuse en_US
dc.subject repair and recycling en_US
dc.subject computer vision en_US
dc.subject deep learning object character recognition en_US
dc.subject product identification en_US
dc.title Fostering collaboration between reuse, repair and recycling centers for electric and electronic equipment en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.identifier.doi 10.31880/10344/10190
dc.contributor.sponsor Smart-re en_US
dc.contributor.sponsor Vlaanderen Circulair en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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