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    Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm

    188548_68538_Paper_Multi_Objective_F.pdf (382.3Kb)
    Access Status
    Open access
    Authors
    Geetha, K.
    Ravindran, D.
    Siva Kumar, M.
    Islam, Mohammad Nazrul
    Date
    2012
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Geetha, K. and Ravindran, D. and Siva Kumar, M. and Islam, M.N. 2012. Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm. International Journal of Advanced Manufacturing Technology. 67 (9-12): pp. 2439-2457.
    Source Title
    International Journal of Advanced Manufacturing Technology
    DOI
    10.1007/s00170-012-4662-6
    ISSN
    0268-3768
    Remarks

    The original publication is available at www.springerlink.com

    NOTICE: This is the author’s version of a work in which changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication.

    URI
    http://hdl.handle.net/20.500.11937/32856
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology.

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