Robust design is a methodology for improving the quality of a product or process by minimizing the effect of variations in the inputs without eliminating the causes of those variations. In robust design, the putative best design is obtained by solving a multi-criteria optimization problem, trading off the nominal performance against the minimization of the variation of the performance measure. Because some existing methods combine the two criteria with a weighted sum or another fixed aggregation strategy, which are known to miss Pareto points, they may fail to obtain a desired design. To overcome this inadequacy, a more comprehensive preference aggregation method is implemented here into robust design. Three examples -- one simple mathematical example, one multi-criteria structure design example, and one automotive example -- are presented to illustrate the effectiveness of the proposed method.


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    Title :

    Improving Robust Design with Preference Aggregation Methods


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE 2004 World Congress & Exhibition ; 2004



    Publication date :

    2004-03-08




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English


    Keywords :


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