DocumentCode :
538157
Title :
Product robust design based on evolutionary algorithm
Author :
Ming, Zhou ; Chengqi, Xue
Author_Institution :
Coll. of Mech. Eng., Southeast Univ., Nanjing, China
Volume :
1
fYear :
2010
fDate :
17-19 Nov. 2010
Firstpage :
273
Lastpage :
277
Abstract :
The product robust design which based on evolutionary algorithm could improve the general degree of the products greatly, achieve maximum product function, and meet the diverse needs of users. The product characteristic matrix and the product´s binary tree structure gene are formed by semantic analysis and hierarchical cluster analysis. Through crossover and mutated of the robust factor, robust population and using population, using evolutionary operator such as similarity, correlation, fitness equation to get the global optimal product design solution, which can ensure that product has no sensitivity and small fluctuations while being used in different environment, facing different user with different usage, and then the product could achieve strong robustness. The example of the high-heeled shoes shows that this method has better adaptability and innovativeness in product design.
Keywords :
evolutionary computation; footwear; matrix algebra; product design; trees (mathematics); evolutionary algorithm; hierarchical cluster analysis; high-heeled shoes; maximum product function; product binary tree structure gene; product characteristic matrix; product robust design; semantic analysis; Footwear; Robustness; evolutionary algorithm; product robust design; robust factor; using factor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Industrial Design & Conceptual Design (CAIDCD), 2010 IEEE 11th International Conference on
Conference_Location :
Yiwu
Print_ISBN :
978-1-4244-7973-3
Type :
conf
DOI :
10.1109/CAIDCD.2010.5681355
Filename :
5681355
Link To Document :
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