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Journal cover: International Journal of Quality & Reliability Management

International Journal of Quality & Reliability Management

ISSN: 0265-671X
Incorporates: International Journal of Quality Science

Online from: 1984

Subject Area: Managing Quality

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Ranking of customer requirements using the fuzzy centroid-based method


Document Information:
Title:Ranking of customer requirements using the fuzzy centroid-based method
Author(s):Esmaeil Mehdizadeh, (Department of Industrial Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran)
Citation:Esmaeil Mehdizadeh, (2010) "Ranking of customer requirements using the fuzzy centroid-based method", International Journal of Quality & Reliability Management, Vol. 27 Iss: 2, pp.201 - 216
Keywords:Customer services management, Mathematical modelling, Quality function deployment
Article type:Research paper
DOI:10.1108/02656711011014311 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – The aim of this paper is to present a fuzzy centroid-based method to ranking customer requirements with competition consideration. The proposed method not only focuses on normal fuzzy numbers, but also considers non-normal fuzzy numbers to capture the true customer requirements.

Design/methodology/approach – This paper proposes a new customer requirements ranking method using QFD that not only focuses on the voice of the customer, but also considers the competitive environment. The method uses fuzzy mathematics instead of crisp numbers; this is known as the fuzzy centroid-based method.

Findings – A numerical example demonstrates that if the fuzzy numbers are non-normal, previous ranking methods were shown to be incorrect and to have led to some misapplications. To avoid possible further misapplications or spread in the future, the correct centroid formula used for fuzzy numbers is derived and their simplified expressions for non-normal fuzzy numbers are given.

Originality/value – Various methods have been developed to rate and rank customer needs; however, few methods consider the competitive environment. In addition, in real applications, fuzzy mathematics are usually more appropriate than crisp models. Many previous methods are misleading and have led to some misapplications if the fuzzy numbers are non-normal. The paper contributes to theory and practice by explaining the reasons for using the fuzzy centroid-based method.



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