DocumentCode :
3496994
Title :
Product Platform Planning: an approach using Genetic Algorithm
Author :
Song, Haitao ; Zhang, Ying ; Song, Yunli ; Wang, Zikai ; Zhen, Lu
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai
fYear :
2008
fDate :
6-8 April 2008
Firstpage :
1621
Lastpage :
1625
Abstract :
In order to meet the variable planning problem in mass customization, this paper presents a method of genetic algorithm to satisfy a set of customer requirements. Unlike former methods for platform planning that designers have to determine product platform variables and individual variables beforehand, this new method focuses on improving the commonality of the product family within the diverse customer needs, and then determines the individual variables and their variation range, as well as the common variables of product platform and their optimal values. A simulation experiment of electric motor designing is reported to illustrate the potential and the feasibility of this method.
Keywords :
customer satisfaction; genetic algorithms; planning; product design; customer requirements satisfaction; diverse customer needs; electric motor designing; genetic algorithm; mass customization; product platform planning; variable planning problem; Consumer electronics; Costs; Electric motors; Genetic algorithms; Mass customization; Mathematical model; Meeting planning; Process planning; Product design; Robustness; Genetic algorithm; Mass customization; Product platform planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-1685-1
Electronic_ISBN :
978-1-4244-1686-8
Type :
conf
DOI :
10.1109/ICNSC.2008.4525480
Filename :
4525480
Link To Document :
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