Application of Genetic Algorithm in Cutting Parameter Optimization

Li Feng Zhu; Yan Zhang

doi:10.4028/www.scientific.net/AMR.1082.138

Paper Titles

Using of the Principle of Autogenous Crushing in the Production of Caustic Magnesia
p.112

A Study of Picosecond-Laser Drilling Technique in Ceramics
p.117

Welding of Aluminum to DP600 Steel Plates by Refill Friction Stir Spot Welding Process (Refill FSSW): Preliminary Results
p.123

The Effect of Laser Processing Area on Nested-Circle Drilling Method
p.133

Application of Genetic Algorithm in Cutting Parameter Optimization
p.138

A Mechanistic Model for End Milling Cutting Forces in Brittle Porous Material
p.143

Evolution of Microstructure in Semi-Solid of Al-2wt%Si-0.5wt%Mg and Al-4wt%Si-05wt% Alloys during Isothermal Holding
p.152

Study on the Heat Treatment Process by Using Residual Heat after Forging of Steel 40MnB
p.169

Influence of Aging Treatment on Microstructure and Properties of GH2132
p.173

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1082Application of Genetic Algorithm in Cutting...

Application of Genetic Algorithm in Cutting Parameter Optimization

Abstract:

Process parameters optimization is an important problem in numerical control machining, through the analysis of various factors affecting the cutting effect in cutting process, a mathematical model of cutting parameter optimization in NC machining is established and the constraint conditions are also determined in the paper. The article puts forward using genetic algorithm to realize the optimization of mathematical model, and the optimization analysis results are verified in practical processing. The experimental results show that the optimized cutting parameters can satisfy machining requests and improve the cutting efficiency.

You might also be interested in these eBooks

Advanced Materials and Engineering Materials IV

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 1082)

Pages:

138-142

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1082.138

Citation:

Cite this paper

Online since:

December 2014

Authors:

Li Feng Zhu*, Yan Zhang

Keywords:

Genetic Algorithm (GA), NC Machining, Optimization, Process Parameters

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Xueguang Li, Shuren Zhang , Huiwei Wang, Jun Wang . Research& Experiment on Optimization of Cutting Elements Based on NC Machining[C] . 2010 3rdInternational Conference on Advanced Computer Theory and Engineering, 2010: V3-179~V3-183.

DOI: 10.1109/icacte.2010.5579665

Google Scholar

[2] Xueguang Li, Huiwei Wang, Shuren Zhang. Optimization Research of Cutting Parameters Based on Orthogonal Experiment Method[J]. MACHINE TOOL&HYDRAULICS, 2011, 39(8): 17-19.

Google Scholar

[3] Sofianopoulou, S. Formation of manufacturing cells in group technology using a genetic algorithm approach. International Journal of Industrial and Systems Engineering, 2010, 5(2): 212-225.

DOI: 10.1504/ijise.2010.030748

Google Scholar

[4] Kia, R. , Khaksar-Haghani, F., Javadian, N. Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm[J]. Journal of Manufacturing Systems, 2014, 33(1): 218-232.

DOI: 10.1016/j.jmsy.2013.12.005

Google Scholar

[5] Yu, Xianyu, Rao, Zhiyong, Zhu, Hui. The hybrid genetic algorithm of single-machine materials manufacturing process with periodic maintenance[J]. Applied Mechanics and Materials, 2012, 142(3): 16-19.

DOI: 10.4028/www.scientific.net/amm.142.16

Google Scholar

[6] Sharda, Bikram , Banerjee, Amarnath. Robust manufacturing system design using multi objective genetic algorithms, Petri nets and Bayesian uncertainty representation[J]. Journal of Manufacturing Systems, 2013, 32(2): 315-324.

DOI: 10.1016/j.jmsy.2013.01.001

Google Scholar