• DocumentCode
    538157
  • Title

    Product robust design based on evolutionary algorithm

  • Author

    Ming, Zhou ; Chengqi, Xue

  • Author_Institution
    Coll. of Mech. Eng., Southeast Univ., Nanjing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    17-19 Nov. 2010
  • Firstpage
    273
  • Lastpage
    277
  • Abstract
    The product robust design which based on evolutionary algorithm could improve the general degree of the products greatly, achieve maximum product function, and meet the diverse needs of users. The product characteristic matrix and the product´s binary tree structure gene are formed by semantic analysis and hierarchical cluster analysis. Through crossover and mutated of the robust factor, robust population and using population, using evolutionary operator such as similarity, correlation, fitness equation to get the global optimal product design solution, which can ensure that product has no sensitivity and small fluctuations while being used in different environment, facing different user with different usage, and then the product could achieve strong robustness. The example of the high-heeled shoes shows that this method has better adaptability and innovativeness in product design.
  • Keywords
    evolutionary computation; footwear; matrix algebra; product design; trees (mathematics); evolutionary algorithm; hierarchical cluster analysis; high-heeled shoes; maximum product function; product binary tree structure gene; product characteristic matrix; product robust design; semantic analysis; Footwear; Robustness; evolutionary algorithm; product robust design; robust factor; using factor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Aided Industrial Design & Conceptual Design (CAIDCD), 2010 IEEE 11th International Conference on
  • Conference_Location
    Yiwu
  • Print_ISBN
    978-1-4244-7973-3
  • Type

    conf

  • DOI
    10.1109/CAIDCD.2010.5681355
  • Filename
    5681355