DocumentCode
2634271
Title
Using genetic programming for developing relationship between engineering characteristics and customer requirements in new products
Author
Chan, K.Y. ; Dillon, T.S. ; Kwong, C.K. ; Ling, S.H.
Author_Institution
Digital Ecosyst. & Bus. Intell. Inst., Curtin Univ. of Technol., Perth, WA, Australia
fYear
2011
fDate
21-23 June 2011
Firstpage
526
Lastpage
531
Abstract
In product planning, development of models of relationship between engineering characteristics and customer requirements in new products is an important process in quality function deployment (QFD), which is a widely used customer driven approach. In this paper, a methodology based on genetic programming (GP) is presented to generate a reliable model that can be used to predict the customer requirements from the engineering characteristics. The proposed GP based method, which has the capability to carry out simultaneous optimization of model relationship structures and parameters, is used to automatically generate accurate nonlinear models relating the two requirements. A case study of the digital camera design shows that the proposed GP based method produce a more accurate and interpretable models than the other commonly used methods, which ignore nonlinear terms in the model development.
Keywords
customer services; genetic algorithms; product development; production planning; quality function deployment; reliability; GP based method; QFD; accurate nonlinear models; customer driven approach; customer requirements; digital camera design; engineering characteristics; genetic programming; interpretable models; model development; model relationship structures; new products; nonlinear terms; product development; product planning; quality function deployment; reliable model; simultaneous optimization; Biological system modeling; Computational modeling; Data models; Genetic programming; Mathematical model; Planning; Quality function deployment;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
Conference_Location
Beijing
ISSN
pending
Print_ISBN
978-1-4244-8754-7
Electronic_ISBN
pending
Type
conf
DOI
10.1109/ICIEA.2011.5975642
Filename
5975642
Link To Document