Quantification and integration of an improved Kano model into QFD based on multi-population adaptive genetic algorithm

摘要

In an effort to address the inherent deficiencies of traditional Kano model and quality function deployment (QFD), this paper proposes an improved Kano model named as importance-frequency Kano (IF-Kano) model and integrates IF-Kano model into QFD. Considering the interaction between frequencies and importance weights of customer requirements (CRs), the IF-Kano model adopts the logical Kano classification criteria to categorize CRs. Then, both qualitative and quantitative results derived from IF-Kano model are integrated into QFD with a nonlinear programming model. The model aims to determine appropriate Kano categories of CRs and target values of engineering characteristics (ECs) with a view to achieving an optimal design solution under the best balance between enterprise satisfaction and customer satisfaction (CS). To solve the presented model, a multi-population adaptive genetic algorithm (MPAGA) is designed. Finally, an example of a home elevator design is given to demonstrate the feasibility and effectiveness of the developed approach and algorithm.