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Quality function deployment(QFD) is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements(CRs) is really a very essential starting point in the implementation of QFD, since it largely affects the target setting value of design requirements. This paper aims to propose a novel method to deal with the relative importance ratings(RIRs) of CRs problem considering customers’ diversified requirements and unknown information on customers’ weights, which is an indispensable process for determining the final importance ratings of CRs. First, a new concept of customer’s assessment structure is proposed according to the basic idea of grey relational analysis(GRA), and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers’ personalized and diversified requirements. Furthermore, an immune particle swarm optimization(IPSO) algorithm is designed to solve the model, and the weight vector of customers is obtained.Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method’s potential application in determining the RIRs of CRs.
Rating the final importance of customer requirements (CRs) is really a very essential starting point in the implementation of QFD, since it principally affects the target setting value of design requirements. This paper aims to propose a novel method to deal with the relative stress ratings (RIRs) of CRs problem considering customers ’diversified requirements and unknown information on customers’ weights, which is an indispensable process for determining the final resilience of CRs . First, a new concept of customer’s assessment structure is proposed according to the basic idea of gray relational analysis (GRA), and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers’ personalized and diversified requirements Furthermore, an immune particle swarm optimization (IPSO) algorithm is designed to Fix the model, and the weight vector of customers is obtained. Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method’s potential application in determining the RIRs of CRs.