A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms

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MILFELNER, Matjaž ;ČUŠ, Franci .
A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 50, n.10, p. 446-461, july 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/a-system-for-monitoring-and-optimizing-the-milling-process-with-genetic-algorithms/>. Date accessed: 09 apr. 2020. 
doi:http://dx.doi.org/.
Milfelner, M., & Čuš, F.
(2004).
A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms.
Strojniški vestnik - Journal of Mechanical Engineering, 50(10), 446-461.
doi:http://dx.doi.org/
@article{.,
	author = {Matjaž  Milfelner and Franci  Čuš},
	title = {A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {50},
	number = {10},
	year = {2004},
	keywords = {optimization; cutting forces; cutting parameters; ball-end mill; genetic algorithms; },
	abstract = {This paper presents a system for monitoring and optimizing the ball-end milling process. The system combines different methods and technologies, like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the appropriate hardware and software support. The system for monitoring and optimizing the ball-end milling process combines the process monitoring system of the ball-end milling process and the optimization model. The monitoring system is designed for monitoring and collecting the variables of the milling process by means of sensors and the transformation of those data into numerical values, which are the starting point for the optimization of the ball-end milling process. The optimization model is used for the optimization of the milling parameters with genetic algorithms. The optimization is based on the analytical cutting-force model and the tool-wear model. The developed methods can be used for the cutting-force estimation and the optimization of the cutting parameters. The integration of the proposed system will lead to a reduction in the production costs and production time, flexibility in machining-parameter selection, and an improvement in product quality.},
	issn = {0039-2480},	pages = {446-461},	doi = {},
	url = {https://www.sv-jme.eu/article/a-system-for-monitoring-and-optimizing-the-milling-process-with-genetic-algorithms/}
}
Milfelner, M.,Čuš, F.
2004 July 50. A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 50:10
%A Milfelner, Matjaž 
%A Čuš, Franci 
%D 2004
%T A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms
%B 2004
%9 optimization; cutting forces; cutting parameters; ball-end mill; genetic algorithms; 
%! A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms
%K optimization; cutting forces; cutting parameters; ball-end mill; genetic algorithms; 
%X This paper presents a system for monitoring and optimizing the ball-end milling process. The system combines different methods and technologies, like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the appropriate hardware and software support. The system for monitoring and optimizing the ball-end milling process combines the process monitoring system of the ball-end milling process and the optimization model. The monitoring system is designed for monitoring and collecting the variables of the milling process by means of sensors and the transformation of those data into numerical values, which are the starting point for the optimization of the ball-end milling process. The optimization model is used for the optimization of the milling parameters with genetic algorithms. The optimization is based on the analytical cutting-force model and the tool-wear model. The developed methods can be used for the cutting-force estimation and the optimization of the cutting parameters. The integration of the proposed system will lead to a reduction in the production costs and production time, flexibility in machining-parameter selection, and an improvement in product quality.
%U https://www.sv-jme.eu/article/a-system-for-monitoring-and-optimizing-the-milling-process-with-genetic-algorithms/
%0 Journal Article
%R 
%& 446
%P 16
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 50
%N 10
%@ 0039-2480
%8 2017-07-07
%7 2017-07-07
Milfelner, Matjaž, & Franci  Čuš.
"A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms." Strojniški vestnik - Journal of Mechanical Engineering [Online], 50.10 (2004): 446-461. Web.  09 Apr. 2020
TY  - JOUR
AU  - Milfelner, Matjaž 
AU  - Čuš, Franci 
PY  - 2004
TI  - A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - optimization; cutting forces; cutting parameters; ball-end mill; genetic algorithms; 
N2  - This paper presents a system for monitoring and optimizing the ball-end milling process. The system combines different methods and technologies, like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the appropriate hardware and software support. The system for monitoring and optimizing the ball-end milling process combines the process monitoring system of the ball-end milling process and the optimization model. The monitoring system is designed for monitoring and collecting the variables of the milling process by means of sensors and the transformation of those data into numerical values, which are the starting point for the optimization of the ball-end milling process. The optimization model is used for the optimization of the milling parameters with genetic algorithms. The optimization is based on the analytical cutting-force model and the tool-wear model. The developed methods can be used for the cutting-force estimation and the optimization of the cutting parameters. The integration of the proposed system will lead to a reduction in the production costs and production time, flexibility in machining-parameter selection, and an improvement in product quality.
UR  - https://www.sv-jme.eu/article/a-system-for-monitoring-and-optimizing-the-milling-process-with-genetic-algorithms/
@article{{}{.},
	author = {Milfelner, M., Čuš, F.},
	title = {A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {50},
	number = {10},
	year = {2004},
	doi = {},
	url = {https://www.sv-jme.eu/article/a-system-for-monitoring-and-optimizing-the-milling-process-with-genetic-algorithms/}
}
TY  - JOUR
AU  - Milfelner, Matjaž 
AU  - Čuš, Franci 
PY  - 2017/07/07
TI  - A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 50, No 10 (2004): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - optimization, cutting forces, cutting parameters, ball-end mill, genetic algorithms, 
N2  - This paper presents a system for monitoring and optimizing the ball-end milling process. The system combines different methods and technologies, like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the appropriate hardware and software support. The system for monitoring and optimizing the ball-end milling process combines the process monitoring system of the ball-end milling process and the optimization model. The monitoring system is designed for monitoring and collecting the variables of the milling process by means of sensors and the transformation of those data into numerical values, which are the starting point for the optimization of the ball-end milling process. The optimization model is used for the optimization of the milling parameters with genetic algorithms. The optimization is based on the analytical cutting-force model and the tool-wear model. The developed methods can be used for the cutting-force estimation and the optimization of the cutting parameters. The integration of the proposed system will lead to a reduction in the production costs and production time, flexibility in machining-parameter selection, and an improvement in product quality.
UR  - https://www.sv-jme.eu/article/a-system-for-monitoring-and-optimizing-the-milling-process-with-genetic-algorithms/
Milfelner, Matjaž, AND Čuš, Franci.
"A System for Monitoring and Optimizing the Milling Process with Genetic Algorithms" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 50 Number 10 (07 July 2017)

Authors

Affiliations

  • University of Maribor, Faculty of Mechanical Engineering, Slovenia
  • University of Maribor, Faculty of Mechanical Engineering, Slovenia

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 50(2004)10, 446-461

This paper presents a system for monitoring and optimizing the ball-end milling process. The system combines different methods and technologies, like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the appropriate hardware and software support. The system for monitoring and optimizing the ball-end milling process combines the process monitoring system of the ball-end milling process and the optimization model. The monitoring system is designed for monitoring and collecting the variables of the milling process by means of sensors and the transformation of those data into numerical values, which are the starting point for the optimization of the ball-end milling process. The optimization model is used for the optimization of the milling parameters with genetic algorithms. The optimization is based on the analytical cutting-force model and the tool-wear model. The developed methods can be used for the cutting-force estimation and the optimization of the cutting parameters. The integration of the proposed system will lead to a reduction in the production costs and production time, flexibility in machining-parameter selection, and an improvement in product quality.

optimization; cutting forces; cutting parameters; ball-end mill; genetic algorithms;