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Enhancing end-of-life product recyclability through modular design and social engineering optimiser.

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Title: Enhancing end-of-life product recyclability through modular design and social engineering optimiser.
Authors: Tian, Guangdong1 (AUTHOR), Sheng, Haowen1 (AUTHOR), Zhang, Lele2 (AUTHOR) zll1291@163.com, Zhang, Honghao3 (AUTHOR), Fathollahi-Fard, Amir M.4 (AUTHOR), Zhang, Xuesong5 (AUTHOR), Feng, Yixiong6 (AUTHOR)
Source: International Journal of Production Research. Jul2026, Vol. 64 Issue 13, p5338-5356. 19p.
Subjects: Modular design, Multi-objective optimization, Optimization algorithms, Waste recycling, Sustainability, Sustainable development, Sustainable design
Abstract: Amidst the thriving landscape of manufacturing, the vision of sustainability in Industry 5.0 is becoming increasingly significant. The implementation of recycling represents a crucial step in the pursuit of sustainability, particularly in light of the mounting challenge posed by the proliferation of end-of-life (EOL) products. Addressing this challenge, we propose a novel Design for Modular Recyclability (DFMR) approach aimed at facilitating the recycling of EOL products. Our study develops a multi-objective optimisation model with a focus on maximising green recyclability and independence while minimising aggregation. We introduce an innovative Social Engineering Optimiser (SEO) to simulate behavioural patterns in complex environments, aiding in identifying and implementing effective strategies for optimal or near-optimal results in diverse scenarios. The practical effectiveness of the proposed models and algorithms is demonstrated by applying them to a real-life case study in an internal combustion engine, followed by performance comparisons with existing well-established multi-objective optimisation algorithms. The findings of our study demonstrate the efficacy of the proposed DFMR model, offering a novel approach for decision-makers to undertake EOL product recovery. This contributes to the further exploration of complex and promising paths towards sustainable manufacturing and green production that are more in line with Industry 5.0. [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: Enhancing end-of-life product recyclability through modular design and social engineering optimiser.
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  Data: <searchLink fieldCode="AR" term="%22Tian%2C+Guangdong%22">Tian, Guangdong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sheng%2C+Haowen%22">Sheng, Haowen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Lele%22">Zhang, Lele</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> zll1291@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Honghao%22">Zhang, Honghao</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fathollahi-Fard%2C+Amir+M%2E%22">Fathollahi-Fard, Amir M.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xuesong%22">Zhang, Xuesong</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Feng%2C+Yixiong%22">Feng, Yixiong</searchLink><relatesTo>6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Jul2026, Vol. 64 Issue 13, p5338-5356. 19p.
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  Data: <searchLink fieldCode="DE" term="%22Modular+design%22">Modular design</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Waste+recycling%22">Waste recycling</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainability%22">Sustainability</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+development%22">Sustainable development</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+design%22">Sustainable design</searchLink>
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  Data: Amidst the thriving landscape of manufacturing, the vision of sustainability in Industry 5.0 is becoming increasingly significant. The implementation of recycling represents a crucial step in the pursuit of sustainability, particularly in light of the mounting challenge posed by the proliferation of end-of-life (EOL) products. Addressing this challenge, we propose a novel Design for Modular Recyclability (DFMR) approach aimed at facilitating the recycling of EOL products. Our study develops a multi-objective optimisation model with a focus on maximising green recyclability and independence while minimising aggregation. We introduce an innovative Social Engineering Optimiser (SEO) to simulate behavioural patterns in complex environments, aiding in identifying and implementing effective strategies for optimal or near-optimal results in diverse scenarios. The practical effectiveness of the proposed models and algorithms is demonstrated by applying them to a real-life case study in an internal combustion engine, followed by performance comparisons with existing well-established multi-objective optimisation algorithms. The findings of our study demonstrate the efficacy of the proposed DFMR model, offering a novel approach for decision-makers to undertake EOL product recovery. This contributes to the further exploration of complex and promising paths towards sustainable manufacturing and green production that are more in line with Industry 5.0. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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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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      – Type: doi
        Value: 10.1080/00207543.2024.2424970
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      – Code: eng
        Text: English
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        PageCount: 19
        StartPage: 5338
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      – SubjectFull: Modular design
        Type: general
      – SubjectFull: Multi-objective optimization
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Waste recycling
        Type: general
      – SubjectFull: Sustainability
        Type: general
      – SubjectFull: Sustainable development
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      – SubjectFull: Sustainable design
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      – TitleFull: Enhancing end-of-life product recyclability through modular design and social engineering optimiser.
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            NameFull: Tian, Guangdong
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            NameFull: Sheng, Haowen
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            NameFull: Zhang, Lele
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            NameFull: Zhang, Honghao
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            NameFull: Fathollahi-Fard, Amir M.
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            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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