An Enhanced Fuzzy AHP Method with Extent Analysis for Determining Importance of Customer Requirements

Part of the Studies in Computational Intelligence book series (SCI, volume 403)

Introduction

This chapter discusses the implementation of the enhanced fuzzy Analytic Hierarchy Process (AHP), which is the improved version of the fuzzy AHP discussed in Chapter 3 for the determination of importance of customer requirements. Similar to the latter, the enhanced fuzzy AHP converts the linguistic assessment of customer requirements to triangular fuzzy numbers, which are used to build the pairwise comparison matrix of AHP. Then the enhanced fuzzy AHP uses the extent analysis method and the principles of comparison of fuzzy numbers to derive weight vectors. This improves the hitherto imprecise ranking of importance weights of customer requirements inherited from the previous works which used the conventional AHP and the fuzzy AHP discussed in Chapter 3. The enhanced fuzzy AHP with extent analysis refers to the "extent" to which an object satisfies a goal and where "satisfied extent" is defined by means of triangular fuzzy numbers. The weight vectors of the fuzzy AHP can be calculated using extent analysis and the principles of comparison of fuzzy numbers. Compared to eigenvectors which are used to calculate weight vectors in the conventional AHP, the enhanced fuzzy AHP is simple and easy to implement for the purpose of prioritizing customer satisfaction of quality function deployment (QFD). A case study of a hair dryer design is used to illustrate the effectiveness of the enhanced fuzzy AHP.

Keywords

Fuzzy Number Customer Satisfaction Customer Requirement Triangular Fuzzy Number Quality Function Deployment 
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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