• DocumentCode
    2966401
  • Title

    A product platform optimization method based on QFD

  • Author

    Luo, X.G. ; Tang, J.F. ; Kwong, C.K.

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2009
  • fDate
    8-11 Dec. 2009
  • Firstpage
    1317
  • Lastpage
    1321
  • Abstract
    Quality function deployment (QFD) is a popular approach to design products that satisfy customer needs. To minimize the total quality loss caused by commonality when establishing a product platform and better satisfy customer requirements, this paper presents a five-step QFD-based methodology to determine the optimal values for platform engineering characteristics (ECs) and non-platform ECs of the products within a product family. First, the optimal values of ECs for each individual product within a family are determined. Then, the platform ECs are identified according to the calculated sensitivity indices of the ECs, and the values of each platform EC are clustered. A mathematical model is developed to simultaneously optimize the values of the platform and the non-platform ECs. Finally, the ECs that the worst overall customer satisfaction loss can be avoided are selected as platform ECs. A case study is used to demonstrate the methodology.
  • Keywords
    customer satisfaction; minimisation; product design; quality function deployment; customer needs satisfaction; mathematical model; platform engineering characteristics; product design; product platform optimization method; quality function deployment; total quality loss minimisation; Costs; Customer satisfaction; Design engineering; Design methodology; Manufacturing; Mathematical model; Optimization methods; Process design; Product design; Quality function deployment; customer requirements; optimization; product platform; quality function deployment (QFD);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-4869-2
  • Electronic_ISBN
    978-1-4244-4870-8
  • Type

    conf

  • DOI
    10.1109/IEEM.2009.5373023
  • Filename
    5373023