Early in the engineering design cycle, it is difficult to quantify product reliability or compliance to performance targets due to insufficient data or information for modeling the uncertainties. Design decisions are therefore, based on fuzzy information that is vague, imprecise qualitative, linguistic or incomplete. The uncertain information is usually available as intervals with lower and upper limits. In this work, the possibility theory is used to assess design reliability with incomplete information. The possibility theory can be viewed as a variant of fuzzy set theory. A possibility-based design optimization method is proposed where all design constraints are expressed possibilistically. It is shown that the method gives a conservative solution compared with all conventional reliability-based designs obtained with different probability distributions. A general possibility-based design optimization method is also presented which handles a combination of random and possibilistic design variables. Numerical examples demonstrate the application of possibility theory in design.


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    Title :

    A Design Optimization Method Using Possibility Theory


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE 2005 World Congress & Exhibition ; 2005



    Publication date :

    2005-04-11




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    A Design Optimization Method Using Possibility Theory

    Mourelatos, Z. P. / Zhou, J. / Kloess, A. et al. | British Library Conference Proceedings | 2005


    A design optimization method using possibility theory

    Mourelatos,Z.P. / Zhou,J. / Kloess,A. et al. | Automotive engineering | 2005