Fuzzy group decision-making to multiple preference formats in quality function deployment

In a competitive and global business environment, it is certainly a distinct advantage to capture the genuine and major customer's requirements effectively. To take advantage of this, the unique way is to analyze customer's requirements systematically and to transform them into the appropriate product features properly. Quality function deployment (QFD) is a well-known planning methodology for translating customer needs (CNs) into relevant design requirements (DRs). The intent of applying QFD is to consolidate the customers' preferences to the various phases of the product development cycle for a new product, or a new version of an existing product. However, it is more difficult to assess the performance of this process with accurate quantitative evaluation due to its uncertain nature. Moreover, people tend to give information about their personal preferences in many different ways, numerically or linguistically, depending on their background and value systems. In this study, a new fuzzy group decision-making approach is presented to fuse multiple preference styles to respond CNs in product development with QFD in a better way. The approach is illustrated with a numerical example concerning the development of the hatch door of a car.

[1]  Randy R. Bruegman Exceeding Customer Expectations , 2002 .

[2]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[3]  William G. Ferrell,et al.  A methodology for selection problems with multiple, conflicting objectives and both qualitative and quantitative criteria , 2003 .

[4]  C. Hwang,et al.  Group Decision Making Under Multiple Criteria: Methods and Applications , 1986 .

[5]  Da Ruan,et al.  Fuzzy group decision making for selection among computer integrated manufacturing systems , 2003, Comput. Ind..

[6]  C. K. Kwong,et al.  A fuzzy AHP approach to the determination of importance weights of customer requirements in quality function deployment , 2002, J. Intell. Manuf..

[7]  Etienne E. Kerre,et al.  Reasonable properties for the ordering of fuzzy quantities (II) , 2001, Fuzzy Sets Syst..

[8]  Susan Carlson Skalak House of Quality , 2002 .

[9]  J. Kacprzyk Group decision making with a fuzzy linguistic majority , 1986 .

[10]  José L. Verdegay,et al.  On aggregation operations of linguistic labels , 1993, Int. J. Intell. Syst..

[11]  G. Bortolan,et al.  A review of some methods for ranking fuzzy subsets , 1985 .

[12]  Lotfi A. Zadeh,et al.  A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[13]  R. Yager Families of OWA operators , 1993 .

[14]  M. Amparo Vila,et al.  On a canonical representation of fuzzy numbers , 1998, Fuzzy Sets Syst..

[15]  Da Ruan,et al.  Determining the importance weights for the design requirements in the house of quality using the fuzzy analytic network approach , 2004 .

[16]  Marc Roubens,et al.  Ranking and defuzzification methods based on area compensation , 1996, Fuzzy Sets Syst..

[17]  Elim Liu,et al.  A structural component-based approach for designing product family , 2005, Comput. Ind..

[18]  House of quality: A fuzzy logic-based requirements analysis , 1999, Eur. J. Oper. Res..

[19]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[20]  Hefin Rowlands,et al.  Methods and techniques to help quality function deployment (QFD) , 2000 .

[21]  Abbie Griffin,et al.  The Voice of the Customer , 1993 .

[22]  Adrian Ashurst Exceeding customer expectations in care homes , 2008 .

[23]  Ming-Lu Wu,et al.  Quality function deployment: A literature review , 2002, Eur. J. Oper. Res..

[24]  Etienne E. Kerre,et al.  Reasonable properties for the ordering of fuzzy quantities (II) , 2001, Fuzzy Sets Syst..

[25]  Francisco Herrera,et al.  Multiperson decision-making based on multiplicative preference relations , 2001, Eur. J. Oper. Res..

[26]  Francisco Herrera,et al.  Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations , 1998, Fuzzy Sets Syst..

[27]  Cor P.M. Govers,et al.  QFD not just a tool but a way of quality management , 2001 .

[28]  J. Kacprzyk,et al.  Fuzzy regression analysis , 1992 .

[29]  Don Gunther,et al.  Quality Function Deployment - How to Make QFD Work for You , 2000 .

[30]  Richard Y. K. Fung,et al.  Fuzzy regression-based mathematical programming model for quality function deployment , 2004 .

[31]  Zeshui Xu,et al.  A method based on linguistic aggregation operators for group decision making with linguistic preference relations , 2004, Inf. Sci..

[32]  Soung Hie Kim,et al.  Using analytic network process and goal programming for interdependent information system project selection , 2000, Comput. Oper. Res..

[33]  Ying-Ming Wang,et al.  A minimax disparity approach for obtaining OWA operator weights , 2005, Inf. Sci..

[34]  Thomas F. Wallace Customer-Driven Strategy: Winning Through Operational Excellence , 1992 .

[35]  R. Yager Quantifier guided aggregation using OWA operators , 1996, Int. J. Intell. Syst..

[36]  Francisco Herrera,et al.  Applicability of the fuzzy operators in the design of fuzzy logic controllers , 1997, Fuzzy Sets Syst..

[37]  Yoji Akao,et al.  Quality Function Deployment : Integrating Customer Requirements into Product Design , 1990 .

[38]  Shing I. Chang,et al.  An integrated group decision-making approach to quality function deployment , 1999 .

[39]  J. Kacprzyk,et al.  Group decision making and consensus under fuzzy preferences and fuzzy majority , 1992 .

[40]  Francisco Herrera,et al.  Theory and Methodology Choice functions and mechanisms for linguistic preference relations , 2000 .

[41]  Gülçin Büyüközkan,et al.  A new approach based on soft computing to accelerate the selection of new product ideas , 2004, Comput. Ind..

[42]  Francisco Herrera,et al.  A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach , 1995, Inf. Sci..

[43]  Francisco Herrera,et al.  Combining Numerical and Linguistic Information in Group Decision Making , 1998, Inf. Sci..