Modelling customer satisfaction for product development using genetic programming

被引:35
作者
Chan, KitYan [1 ]
Kwong, C. K. [1 ]
Wong, T. C. [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Kowloon, Hong Kong, Peoples R China
关键词
genetic programming; interaction terms; higher-order terms; customer satisfaction; design attributes; QUALITY FUNCTION DEPLOYMENT; ENGINEERING CHARACTERISTICS; FUNCTIONAL-RELATIONSHIPS; DESIGN; SYSTEM; IDENTIFICATION;
D O I
10.1080/09544820902911374
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Product development involves several processes in which product planning is the first one. Several tasks normally are required to be conducted in the product-planning process and one of them is to determine settings of design attributes for products. Facing with fierce competition in marketplaces, companies try to determine the settings such that the best customer satisfaction of products could be obtained. To achieve this, models that relate customer satisfaction to design attributes need to be developed first. Previous research has adopted various modelling techniques to develop the models, but those models are not able to address interaction terms or higher-order terms in relating customer satisfaction to design attributes, or they are the black-box type models. In this paper, a method based on genetic programming (GP) is presented to generate models for relating customer satisfaction to design attributes. The GP is first used to construct branches of a tree representing structures of a model where interaction terms and higher-order terms can be addressed. Then an orthogonal least-squares algorithm is used to determine the coefficients of the model. The models thus developed are explicit and consist of interaction terms and higher-order terms in relating customer satisfaction to design attributes. A case study of a digital camera design is used to illustrate the proposed method.
引用
收藏
页码:55 / 68
页数:14
相关论文
共 32 条
[1]  
[Anonymous], MATH COMPUTERS SIMUL
[2]  
[Anonymous], 1994, Genetic programming II: Automatic discovery of reusable programs, DOI DOI 10.5555/183460
[3]  
[Anonymous], EXPT TECHNIQUES
[4]  
[Anonymous], J OPERATIONS MANAGEM
[5]  
[Anonymous], 2003, Genetic programming IV: routine human-competitive machine intelligence
[6]   IDENTIFICATION OF NON-LINEAR OUTPUT-AFFINE SYSTEMS USING AN ORTHOGONAL LEAST-SQUARES ALGORITHM [J].
BILLINGS, SA ;
KORENBERG, MJ ;
CHEN, S .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1988, 19 (08) :1559-1568
[7]   An investigation into affective design using sorting technique and Kohonen self-organising map [J].
Chen, CH ;
Khoo, LP ;
Yan, W .
ADVANCES IN ENGINEERING SOFTWARE, 2006, 37 (05) :334-349
[8]   ORTHOGONAL LEAST-SQUARES METHODS AND THEIR APPLICATION TO NON-LINEAR SYSTEM-IDENTIFICATION [J].
CHEN, S ;
BILLINGS, SA ;
LUO, W .
INTERNATIONAL JOURNAL OF CONTROL, 1989, 50 (05) :1873-1896
[9]   Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD [J].
Chen, Y ;
Fung, RYK ;
Yang, J .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2005, 43 (17) :3583-3604
[10]   Fuzzy regression-based mathematical programming model for quality function deployment [J].
Chen, Y ;
Tang, J ;
Fung, RYK ;
Ren, Z .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2004, 42 (05) :1009-1027