A Nonlinear Fuzzy Regression for Developing Manufacturing Process Models

  • Kit Yan Chan
  • C. K. Kwong
  • Tharam S. Dillon
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 403)


It is well recognized that manufacturing concerns need to be considered in product design stage such that quality of manufactured products can be improved and their production cost can be reduced. To address these concerns, one common method is to develop manufacturing process models that relate the quality requirements of a new product to the variables of manufacturing processes. Based on the models, proper settings of process parameters and the predicted quality of new products can be obtained in the product design stage.


Genetic Programming Multivariate Adaptive Regression Spline Fuzzy Parameter Fuzzy Regression Fuzzy Linear Regression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Berlin Heidelberg 2012

Authors and Affiliations

  • Kit Yan Chan
    • 1
  • C. K. Kwong
    • 2
  • Tharam S. Dillon
    • 1
  1. 1.Digital Ecosystems and BusinessCurtin University of TechnologyPerthAustralia
  2. 2.Department of Industrial and SystemsThe Hong Kong Polytechnic UniversityKowloonHong Kong SAR

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