Computers and Industrial Engineering
Fuzzy logic and optimization models for implementing QFD
Proceedings of the 23rd international conference on on Computers and industrial engineering
A new approach to quality function deployment planning with financial consideration
Computers and Operations Research
Computers and Industrial Engineering
Expectations and Rankings of Website Quality Features: Results of Two Studies on User Perceptions
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 7 - Volume 7
Quality function deployment implementation based on Fuzzy Kano model: An application in PLM system
Computers and Industrial Engineering
A fuzzy model for exploiting quality function deployment
Mathematical and Computer Modelling: An International Journal
An approach for manufacturing strategy development based on fuzzy-QFD
Computers and Industrial Engineering
A systematic decision-making approach for the optimal product-service system planning
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
An integrated linguistic-based group decision-making approach for quality function deployment
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
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Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product development, determining the fulfillment levels of design requirements (DRs) is crucial during QFD optimization. However, in real world applications, the values of DRs are often discrete instead of continuous. To the best of our knowledge, there is no mixed integer linear programming (MILP) model in which the discrete DRs values are considered. Therefore, in this paper, a new QFD optimization approach combining MILP model and Kano model is suggested to acquire the optimized solution from a limited number of alternative DRs, the values of which can be discrete. The proposed model can be used not only to optimize the product development but also in other applications of QFD such as quality management, planning, design, engineering and decision-making, on the condition that DR values are discrete. Additionally, the problem of lack of solutions in integer and linear programming in the QFD optimization is overcome. Finally, the model is illustrated through an example.