Application of Genetic Algorithm in the Study of Semantic Modeling Design of CNC Machine Tools

被引：3

作者：

Lan, Tu ^{[1
]}

Tang, Shengju ^{[1
]}

Chen, Bo ^{[1
]}

Guo, Deke ^{[2
]}

机构：

[1] Southwest Petr Univ, Mechatron Engn Coll, Chengdu, Si Chuan, Peoples R China

[2] Southwest branch Co Oil & Gas Field Petro China, Light Hydrocarbon Plant Gas Field Northwest Si, Jiangyou, Si Chuan, Peoples R China

来源：

ADVANCED MANUFACTURING TECHNOLOGY, PTS 1-4 | 2012年 / 472-475卷

关键词：

genetic algorithms; CNC machine tools; kansei engineering; modeling design;

D O I：

10.4028/www.scientific.net/AMR.472-475.2235

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Because of the outstanding advantages of genetic algorithms in solving optimization problems of engineering design, in this paper, using genetic algorithm combined with Kansei Engineering as a optimal design method for product's semantics modeling design, and using real-coded way to characterize shape characteristics of CNC machine tools, comprehensive accounted of user's semantic needs and color Mido, then, established the fitness function, combined with the key components to complete the design. By case analysis shows that the method is feasible, and lays a foundation for intelligent design of CNC machine tools.

引用

页码：2235 / +

页数：2