Methods of optimization of milling parameters based on genetic algorithm

Chengqiang Zhang; Jie Chen

doi:10.1109/ICEMI.2009.5274851

Methods of optimization of milling parameters based on genetic algorithm

Chengqiang Zhang, Jie Chen

School of Mechanical and Power Engineering

Nanjing Tech University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

In this paper, the genetic algorithm is used to optimize the milling parameters in the milling process so that the tool life can be enhanced and processing costs can be reduced. LABVIEW is used as software development platform to program, monitor the tool wear and determine the tool life. Through the method of orthogonal experiment to design experiment and then the measured data is dealt with by MATLAB, and a mathematical formula is established between milling parameters and tool life. Using mathematical formula and production cost process as a mathematical model. At last, dealing with the mathematical model through the application of genetic algorithms, the most optimized milling parameters is obtained. Experiment proves the practicality of the genetic algorithm in the optimization of milling parameters.

Original language	English
Title of host publication	ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments
Pages	1382-1385
Number of pages	4
DOIs	https://doi.org/10.1109/ICEMI.2009.5274851
State	Published - 2009
Event	9th International Conference on Electronic Measurement and Instruments, ICEMI 2009 - Beijing, China Duration: 16 Aug 2009 → 19 Aug 2009

Publication series

Name	ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments

Conference

Conference	9th International Conference on Electronic Measurement and Instruments, ICEMI 2009
Country/Territory	China
City	Beijing
Period	16/08/09 → 19/08/09

Keywords

Genetic algorithm
LABVIEW
Orthogonal experiment

Access to Document

10.1109/ICEMI.2009.5274851

Cite this

Zhang, C., & Chen, J. (2009). Methods of optimization of milling parameters based on genetic algorithm. In ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments (pp. 1382-1385). Article 5274851 (ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments). https://doi.org/10.1109/ICEMI.2009.5274851

@inproceedings{b13420b652244554b2e8064ede328846,

title = "Methods of optimization of milling parameters based on genetic algorithm",

abstract = "In this paper, the genetic algorithm is used to optimize the milling parameters in the milling process so that the tool life can be enhanced and processing costs can be reduced. LABVIEW is used as software development platform to program, monitor the tool wear and determine the tool life. Through the method of orthogonal experiment to design experiment and then the measured data is dealt with by MATLAB, and a mathematical formula is established between milling parameters and tool life. Using mathematical formula and production cost process as a mathematical model. At last, dealing with the mathematical model through the application of genetic algorithms, the most optimized milling parameters is obtained. Experiment proves the practicality of the genetic algorithm in the optimization of milling parameters.",

keywords = "Genetic algorithm, LABVIEW, Orthogonal experiment",

author = "Chengqiang Zhang and Jie Chen",

year = "2009",

doi = "10.1109/ICEMI.2009.5274851",

language = "英语",

isbn = "9781424438624",

series = "ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments",

pages = "1382--1385",

booktitle = "ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments",

note = "9th International Conference on Electronic Measurement and Instruments, ICEMI 2009 ; Conference date: 16-08-2009 Through 19-08-2009",

}

Zhang, C & Chen, J 2009, Methods of optimization of milling parameters based on genetic algorithm. in ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments., 5274851, ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments, pp. 1382-1385, 9th International Conference on Electronic Measurement and Instruments, ICEMI 2009, Beijing, China, 16/08/09. https://doi.org/10.1109/ICEMI.2009.5274851

Methods of optimization of milling parameters based on genetic algorithm. / Zhang, Chengqiang; Chen, Jie.
ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments. 2009. p. 1382-1385 5274851 (ICEMI 2009 - Proceedings of 9th International Conference on Electronic Measurement and Instruments).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhang, Chengqiang

AU - Chen, Jie

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N2 - In this paper, the genetic algorithm is used to optimize the milling parameters in the milling process so that the tool life can be enhanced and processing costs can be reduced. LABVIEW is used as software development platform to program, monitor the tool wear and determine the tool life. Through the method of orthogonal experiment to design experiment and then the measured data is dealt with by MATLAB, and a mathematical formula is established between milling parameters and tool life. Using mathematical formula and production cost process as a mathematical model. At last, dealing with the mathematical model through the application of genetic algorithms, the most optimized milling parameters is obtained. Experiment proves the practicality of the genetic algorithm in the optimization of milling parameters.

AB - In this paper, the genetic algorithm is used to optimize the milling parameters in the milling process so that the tool life can be enhanced and processing costs can be reduced. LABVIEW is used as software development platform to program, monitor the tool wear and determine the tool life. Through the method of orthogonal experiment to design experiment and then the measured data is dealt with by MATLAB, and a mathematical formula is established between milling parameters and tool life. Using mathematical formula and production cost process as a mathematical model. At last, dealing with the mathematical model through the application of genetic algorithms, the most optimized milling parameters is obtained. Experiment proves the practicality of the genetic algorithm in the optimization of milling parameters.

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KW - Orthogonal experiment

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T2 - 9th International Conference on Electronic Measurement and Instruments, ICEMI 2009

Y2 - 16 August 2009 through 19 August 2009

ER -

Methods of optimization of milling parameters based on genetic algorithm

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