Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    An intelligent fuzzy regression approach for affective product design that captures nonlinearity and fuzziness

    172078_47746_Camera-ready version .pdf (745.0Kb)
    Access Status
    Open access
    Authors
    Chan, Kit Yan
    Kwong, C.
    Dillon, Tharam
    Fung, K.
    Date
    2011
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Chan, K.Y. and Kwong, C.K. and Dillon, T.S. and Fung, K.Y. 2011. An intelligent fuzzy regression approach for affective product design that captures nonlinearity and fuzziness. Journal of Engineering Design. 22 (8): pp. 523-542.
    Source Title
    Journal of Engineering Design
    DOI
    10.1080/09544820903550924
    ISSN
    14661837
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/24671
    Collection
    • Curtin Research Publications
    Abstract

    Affective product design aims at incorporating customers’ affective needs into design variables of a new product so as to optimise customers’ affective satisfaction. Faced with fierce competition in marketplaces, companies try to determine the settings in order to maximise customers’ affective satisfaction with products. To achieve this, a set of customer survey data is required in order to develop a model which relates customers’ affective responses to the design variables of a new product. Customer survey data are usually fuzzy since human feeling is usually fuzzy, and the relationship between customers’ affective responses and design variables is usually nonlinear. However, previous research on modelling the relationship between affective response and design variables has not addressed the development of explicit models involving either nonlinearity or fuzziness. In this paper, an intelligent fuzzy regression approach is proposed to generate models which represent this nonlinear and fuzzy relationship between affective responses and design variables. In order to do this, we extend the existing work on fuzzy regression by first utilising an evolutionary algorithm to construct branches of a tree representing structures of a model where the nonlinearity of the model can be addressed. The fuzzy regression algorithm is then used to determine the fuzzy coefficients of the model. The models thus developed are explicit, and consist of fuzzy, nonlinear terms which relate affective responses to design variables. A case study of affective product design of mobile phones is used to illustrate the proposed method.

    Related items

    Showing items related by title, author, creator and subject.

    • Varying Spread Fuzzy Regression for Affective Quality Estimation
      Chan, Kit Yan; Engelke, U. (2017)
      Design of preferred products requires affective quality information which relates to human emotional satisfaction. However, it is expensive and time consuming to conduct a full survey to investigate affective qualities ...
    • A stepwise based fuzzy regression procedure for developing customer preference models in new product development
      Chan, Kit Yan; Lam, H.K.; Dillon, T.; Ling, S. (2015)
      Fuzzy regression methods have commonly been used to develop consumer preferences models which correlate the engineering characteristics with consumer preferences regarding a new product; the consumer preference models ...
    • A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design
      Kwong, C.; Fung, K.; Jiang, H.; Chan, Kit Yan; Siu, K. (2013)
      Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.