کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7541799 | 1489052 | 2017 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quantification and integration of an improved Kano model into QFD based on multi-population adaptive genetic algorithm
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
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 non-linear 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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 114, December 2017, Pages 183-194
Journal: Computers & Industrial Engineering - Volume 114, December 2017, Pages 183-194
نویسندگان
Lina He, Wenyan Song, Zhenyong Wu, Zhitao Xu, Maokuan Zheng, Xinguo Ming,