• DocumentCode
    1568357
  • Title

    Methods of optimization of milling parameters based on genetic algorithm

  • Author

    Zhang, Chengqiang ; Chen, Jie

  • Author_Institution
    Sch. of Mech. & Power Eng., Nanjing Univ. of Technol., Nanjing, China
  • fYear
    2009
  • 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
    mechanical engineering computing; milling; optimisation; tools; wear; LABVIEW; MATLAB; genetic algorithm; milling parameters; optimization; production cost process; tool life; tool wear; Computerized monitoring; Cost function; Data acquisition; Genetic algorithms; Instruments; Mathematical model; Milling; Optimization methods; Power measurement; Production; LABVIEW; genetic algorithm; orthogonal experiment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3863-1
  • Electronic_ISBN
    978-1-4244-3864-8
  • Type

    conf

  • DOI
    10.1109/ICEMI.2009.5274851
  • Filename
    5274851