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Details

Autor(en) / Beteiligte
Titel
Automatic high-speed smartphone disassembly system
Ist Teil von
  • Journal of cleaner production, 2024-01, Vol.434, p.139928, Article 139928
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2024
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Given the increased amount of waste and the high concentration of valuable metals in smartphones, the need for the material recycling of smartphones is increasing. However, developing an automatic high-speed disassembly system faces three difficulties: detaching the batteries secured with adhesive, the differences in the internal structures of smartphones with respect to manufacturers and types, and the need for preferential breakage that disables the screws without damaging the battery. In the present study using experiments and simulations, these difficulties were overcome by freezing the smartphones to disable the battery adhesive, performing internal structure analysis using X-ray scanning and deep learning, and ensuring preferential breakage by disabling the screws by press cutting and then simultaneously striking the top and bottom of the smartphone. In the end, a fully automatic high-speed disassembly system was developed. Currently, the system's throughput is approximately 600 units per hour, with a disassembly success rate of 88.3 % on average, as experimentally validated using 1213 smartphones of various types and manufacturers. The disassembly success rate varied widely with the smartphone manufacturer. Thus, in combination with the current sensing technology that enables automatic determination of the manufacturer, recycling plant operational strategies can be designed. For example, when the smartphones of 15 designated manufacturers were processed, 97 % of them were processed, and roughly 90 % of the processed smartphones were successfully disassembled. [Display omitted] •A high-speed automatic smartphone disassembly system was developed.•Batteries secured with adhesive were removed by first freezing the smartphones.•The positions of battery/screws were detected by X-ray scanning and deep learning.•Preferential mechanical breakage method with minimal battery damage was developed.•Throughput was 10 smartphones/min., and the disassembly success ratio was 88.3%.
Sprache
Englisch
Identifikatoren
ISSN: 0959-6526
eISSN: 1879-1786
DOI: 10.1016/j.jclepro.2023.139928
Titel-ID: cdi_crossref_primary_10_1016_j_jclepro_2023_139928

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