Optimization of machining process using evolutionary algorithms

被引：0

作者：

Cukor, G ^{[1
]}

Kuljanic, E ^{[1
]}

Barisic, B ^{[1
]}

机构：

[1] Univ Rijeka, Dept Prod Engn, Fac Engn, Rijeka, Croatia

来源：

AMST '05: ADVANCED MANUFACTURING SYSTEMS AND TECHNOLOGY, PROCEEDINGS | 2005年 / 486期

关键词：

cutting; optimization; evolutionary algorithms;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Advanced manufacturing requires a powerful tool for reliable modeling and solving the complex machining optimization problems. This paper proposes a non-conventional approach using evolutionary algorithms inspired by Darwinian findings about the evolution of the biological species and the survival of the fittest organisms (i.e. natural selection). It is illustrated with an experiment of longitudinal hard turning. Genetic programming (GP) is used to develop the models of both the surface roughness and the tool life considering the cutting speed, the feed and the depth of cut as predetermined cutting parameters. Finally, genetic algorithm (GA) is applied for their optimization.

引用

页码：135 / 142

页数：8

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