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Design for Product Embedded Disassembly

  • Chapter
Evolutionary Computation in Practice

Part of the book series: Studies in Computational Intelligence ((SCI,volume 88))

This chapter discusses an application of multi-objective genetic algorithm for designing products with a built-in disassembly means that can be triggered by the removal of one or a few fasteners at the end of the product lives. Given component geometries, the method simultaneously determines the spatial configuration of components, locators and fasteners, and the end-of-life (EOL) treatments of components and subassemblies, such that the product can be disassembled for the maxim profit and minimum environmental impact through recycling and reuse via domino-like “self-disassembly” process. A multi-objective genetic algorithm is utilized to search for Pareto optimal designs in terms of 1) satisfaction of the distance specification among components, 2) efficient use of locators on components, 3) profit of EOL scenario, and 4) environmental impact of EOL scenario. The method is applied to a simplified model of the Power Mac G4 cube® for demonstration.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Michigan, 48109-2125, Ann Arbor, MI, USA

    Shingo Takeuchi & Kazuhiro Saitou

Authors
  1. Shingo Takeuchi
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  2. Kazuhiro Saitou
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Editor information

Editors and Affiliations

  1. Memorial University of Newfoundland, NLA1B 3X5, St John’s, Canada

    Tina Yu

  2. VGO Associates, 36 Low Street, 01951, Newbury, MA, USA

    Lawrence Davis

  3. Buyukdere Cad. Ozsezen Is Merkezi, 122 C Blok Kat 8, Esentepe, Istanbul, Turkey

    Cem Baydar

  4. Cranfield University, MK43 0AL, Cranfield, Bedford, UK

    Rajkumar Roy

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© 2008 Springer-Verlag Berlin Heidelberg

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Takeuchi, S., Saitou, K. (2008). Design for Product Embedded Disassembly. In: Yu, T., Davis, L., Baydar, C., Roy, R. (eds) Evolutionary Computation in Practice. Studies in Computational Intelligence, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75771-9_2

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  • DOI: https://doi.org/10.1007/978-3-540-75771-9_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75770-2

  • Online ISBN: 978-3-540-75771-9

  • eBook Packages: EngineeringEngineering (R0)

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