An extension to possibilistic linear programming
Fuzzy Sets and Systems
A computerized quality function deployment approach for retail services
Computers and Industrial Engineering
Computers and Industrial Engineering
Fuzzy logic and optimization models for implementing QFD
Proceedings of the 23rd international conference on on Computers and industrial engineering
Fuzzy efficiency measures in data envelopment analysis
Fuzzy Sets and Systems
A review and classification of fuzzy mathematical programs
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Quality function deployment: a comprehensive literature review
International Journal of Data Analysis Techniques and Strategies
An evidential reasoning based approach for quality function deployment under uncertainty
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Fuzzy approaches to quality function deployment for new product design
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
A fuzzy integrated methodology for evaluating conceptual bridge design
Expert Systems with Applications: An International Journal
Towards a QFD-based expert system: A novel extension to fuzzy QFD methodology using rough set theory
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Telecommunications Policy
Engineering Applications of Artificial Intelligence
A systematic decision-making approach for the optimal product-service system planning
Expert Systems with Applications: An International Journal
Computers & Mathematics with Applications
Managing logistics customer service under uncertainty: An integrative fuzzy Kano framework
Information Sciences: an International Journal
A fuzzy nonlinear model for quality function deployment considering Kano's concept
Mathematical and Computer Modelling: An International Journal
Computers and Industrial Engineering
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Quality function deployment (QFD) is the product development process to maximize customer satisfaction. The engineering design characteristics related to product performance are specified for this purpose. For dealing with the fuzzy nature in the product design processes, fuzzy approaches are applied to represent the relationships between customer requirements (CRs) and engineering design requirements (DRs) as well as among the DRs. A new measure for evaluating the fuzzy normalized relationships is derived. A fuzzy model is formulated to determine the fulfillment level of each DR for maximizing the customer satisfaction under the resource limitation and the considerations of technical difficulty and market competition. The producing ranges of fulfillment level of each DR and those of customer satisfaction can provide the QFD team with more information. An example is used to illustrate the model.