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Refurbishment and remanufacturing planning model for pre-owned consumer electronics.

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Title: Refurbishment and remanufacturing planning model for pre-owned consumer electronics.
Authors: Schepler, Xavier1 (AUTHOR) xavier.schepler@gmail.com, Absi, Nabil2 (AUTHOR), Jeanjean, Antoine3 (AUTHOR) antoine.jeanjean@recommerce.com
Source: International Journal of Production Research. Apr2024, Vol. 62 Issue 7, p2499-2521. 23p.
Subjects: Remanufacturing, Household electronics, Heuristic programming, Production planning, Smartwatches, Reverse logistics
Geographic Terms: Europe
Abstract: In this paper, we are interested in modelling and solving a flow and resource planning problem related to the trade-in, treatment and resale of pre-owned consumer electronic products. This problem is motivated and inspired by the flows and the processes of the company Recommerce Group, which mainly handles traded-in used smartphones in Europe, but also used tablets, smartwatches, game consoles, laptops, etc. Collected products must be directed to refurbishment centres. After having been recorded, cleaned, tested and reset, they may be refurbished, or remanufactured by a subcontractor. They may also remain in their initial state. Finally, they are sold on diversified channels. This problem can be generalised to other refurbishment and remanufacturing activities of used consumer electronic products. We first formulate the problem as a mixed-integer linear program and show its NP-hardness. In order to solve large size real-life instances, mixed-integer programming based heuristic approaches are proposed. Extensive computational experiments on realistic instances are conducted to show the advantages and the limits of the proposed approaches. Several managerial insights are investigated and analysed. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Refurbishment and remanufacturing planning model for pre-owned consumer electronics.
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  Data: <searchLink fieldCode="DE" term="%22Remanufacturing%22">Remanufacturing</searchLink><br /><searchLink fieldCode="DE" term="%22Household+electronics%22">Household electronics</searchLink><br /><searchLink fieldCode="DE" term="%22Heuristic+programming%22">Heuristic programming</searchLink><br /><searchLink fieldCode="DE" term="%22Production+planning%22">Production planning</searchLink><br /><searchLink fieldCode="DE" term="%22Smartwatches%22">Smartwatches</searchLink><br /><searchLink fieldCode="DE" term="%22Reverse+logistics%22">Reverse logistics</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Europe%22">Europe</searchLink>
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  Data: In this paper, we are interested in modelling and solving a flow and resource planning problem related to the trade-in, treatment and resale of pre-owned consumer electronic products. This problem is motivated and inspired by the flows and the processes of the company Recommerce Group, which mainly handles traded-in used smartphones in Europe, but also used tablets, smartwatches, game consoles, laptops, etc. Collected products must be directed to refurbishment centres. After having been recorded, cleaned, tested and reset, they may be refurbished, or remanufactured by a subcontractor. They may also remain in their initial state. Finally, they are sold on diversified channels. This problem can be generalised to other refurbishment and remanufacturing activities of used consumer electronic products. We first formulate the problem as a mixed-integer linear program and show its NP-hardness. In order to solve large size real-life instances, mixed-integer programming based heuristic approaches are proposed. Extensive computational experiments on realistic instances are conducted to show the advantages and the limits of the proposed approaches. Several managerial insights are investigated and analysed. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2023.2218942
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      – Code: eng
        Text: English
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        PageCount: 23
        StartPage: 2499
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      – SubjectFull: Remanufacturing
        Type: general
      – SubjectFull: Household electronics
        Type: general
      – SubjectFull: Heuristic programming
        Type: general
      – SubjectFull: Production planning
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      – SubjectFull: Smartwatches
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      – SubjectFull: Reverse logistics
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      – SubjectFull: Europe
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            NameFull: Schepler, Xavier
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            NameFull: Absi, Nabil
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            NameFull: Jeanjean, Antoine
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            – D: 01
              M: 04
              Text: Apr2024
              Type: published
              Y: 2024
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