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Applying data mining technique to disassembly sequence planning: a method to assess effective disassembly time of industrial products

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  • Marco Marconi
  • Michele Germani
  • Marco Mandolini
  • Claudio Favi

Abstract

Design for end-of-life and design for disassembly are enabling design strategies for the implementation of business models based on the circular economy paradigm. The paper presents a method for calculating the effective disassembly sequence and time for industrial products. Five steps support designers in defining liaisons and related properties and precedence among components with the aim to calculate the best disassembly sequence and time. The effective disassembly time is computed considering the actual conditions of a product and its components (e.g. deformation, rust and wear) using corrective factors. This aspect represents the main contribution to the state of the art in the field of design for disassembly. The corrective factors are derived from a specific data mining process, based on the observation of real de-manufacturing activities. The proposed approach has been used for calculating the disassembly times of target components in a washing machine and in a coffee machine. The case studies highlight the method reliability of both: definition of time-effective disassembly sequences and assessment of effective disassembly times. In particular, a comparison of experimental tests shows a maximum deviation of −6% for the electric motor of the washing machine and −3% for the water pump of the coffee machine.

Suggested Citation

  • Marco Marconi & Michele Germani & Marco Mandolini & Claudio Favi, 2019. "Applying data mining technique to disassembly sequence planning: a method to assess effective disassembly time of industrial products," International Journal of Production Research, Taylor & Francis Journals, vol. 57(2), pages 599-623, January.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:599-623
    DOI: 10.1080/00207543.2018.1472404
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    Cited by:

    1. Simone Franzò & Andrea Urbinati & Davide Chiaroni & Vittorio Chiesa, 2021. "Unravelling the design process of business models from linear to circular: An empirical investigation," Business Strategy and the Environment, Wiley Blackwell, vol. 30(6), pages 2758-2772, September.
    2. Nancy M. P. Bocken & Ilka Weissbrod & Maria Antikainen, 2021. "Business Model Experimentation for the Circular Economy: Definition and Approaches," Circular Economy and Sustainability, Springer, vol. 1(1), pages 49-81, June.
    3. Abbate, Stefano & Centobelli, Piera & Cerchione, Roberto, 2023. "From Fast to Slow: An Exploratory Analysis of Circular Business Models in the Italian Apparel Industry," International Journal of Production Economics, Elsevier, vol. 260(C).
    4. Md. Abdul Moktadir & Anil Kumar & Syed Mithun Ali & Sanjoy Kumar Paul & Razia Sultana & Jafar Rezaei, 2020. "Critical success factors for a circular economy: Implications for business strategy and the environment," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3611-3635, December.
    5. Andrea Urbinati & Davide Chiaroni & Giovanni Toletti, 2019. "Managing the Introduction of Circular Products: Evidence from the Beverage Industry," Sustainability, MDPI, vol. 11(13), pages 1-12, July.
    6. Piera Centobelli & Roberto Cerchione & Davide Chiaroni & Pasquale Del Vecchio & Andrea Urbinati, 2020. "Designing business models in circular economy: A systematic literature review and research agenda," Business Strategy and the Environment, Wiley Blackwell, vol. 29(4), pages 1734-1749, May.
    7. Gianmarco Bressanelli & Federico Adrodegari & Daniela C. A. Pigosso & Vinit Parida, 2022. "Towards the Smart Circular Economy Paradigm: A Definition, Conceptualization, and Research Agenda," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
    8. Roxana Lavinia Pacurariu & Sorin Daniel Vatca & Elena Simina Lakatos & Laura Bacali & Mircea Vlad, 2021. "A Critical Review of EU Key Indicators for the Transition to the Circular Economy," IJERPH, MDPI, vol. 18(16), pages 1-19, August.
    9. Özden Tozanlı & Elif Kongar & Surendra M. Gupta, 2020. "Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain," Sustainability, MDPI, vol. 12(13), pages 1-33, July.
    10. Naiara Uriarte-Gallastegi & Beñat Landeta-Manzano & German Arana-Landín & Iker Laskurain-Iturbe, 2022. "How Do Technologies Based on Cyber–Physical Systems Affect the Environmental Performance of Products? A Comparative Study of Manufacturers’ and Customers’ Perspectives," Sustainability, MDPI, vol. 14(20), pages 1-26, October.

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