• DocumentCode
    480476
  • Title

    Study on Modelling of the Product Design Knowledge Based on Functional Feature Partition

  • Author

    Baotong, Li ; Jun, Hong ; Zhihui, Qiu ; Yubao, Chen

  • Author_Institution
    State Key Lab. for Manuf. Syst. Eng., Xi´´an Jiaotong Univ., Xi´´an
  • Volume
    5
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    1102
  • Lastpage
    1105
  • Abstract
    A product design methodology based on functional feature partition is proposed to remedy the existing deficiency in modelling of the design knowledge for complex products. In this approach, a partitioning is firstly performed by mapping the functions to structures layer by layer. Based on this partition, a united product decomposing structure for standard products, optimal products and series products is developed to package the basic design knowledge of the corresponding functional structure. Then, the integrated knowledge model based on object-oriented method and hybrid inference method is constructed, in this model, knowledge can be organized at hierarchical classification and expressed with different forms. Finally, a case study on an automobile movement system is given to illustrate the effectiveness of this method.
  • Keywords
    inference mechanisms; object-oriented methods; pattern classification; product design; product development; functional feature partition; hierarchical classification; hybrid inference method; object-oriented method; optimal product; product design knowledge modelling; series product; standard product; united product decomposing structure developement; Computer science; Expert systems; Laboratories; Mutual coupling; Object oriented modeling; Packaging; Product design; Product development; Software engineering; Standards development; functional feature partition; knowledge inference; knowledge model; knowledge unit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.191
  • Filename
    4723099