Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology

1306 Ogledov
1395 Prenosov
Izvoz citacije: ABNT
SURESH, Periyakgounder ;VENKATESAN, Rajamanickam ;SEKAR, Tamilperruvalathan ;ELANGO, Natarajan ;SATHIYAMOORTHY, Varatharajan .
Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 60, n.10, p. 656-664, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/optimization-of-intervening-variables-in-microedm-of-ss-316l-using-a-genetic-algorithm-and-response-surface-methodology/>. Date accessed: 29 sep. 2021. 
doi:http://dx.doi.org/10.5545/sv-jme.2014.1665.
Suresh, P., Venkatesan, R., Sekar, T., Elango, N., & Sathiyamoorthy, V.
(2014).
Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology.
Strojniški vestnik - Journal of Mechanical Engineering, 60(10), 656-664.
doi:http://dx.doi.org/10.5545/sv-jme.2014.1665
@article{sv-jmesv-jme.2014.1665,
	author = {Periyakgounder  Suresh and Rajamanickam  Venkatesan and Tamilperruvalathan  Sekar and Natarajan  Elango and Varatharajan  Sathiyamoorthy},
	title = {Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {60},
	number = {10},
	year = {2014},
	keywords = {microEDM; response surface methodology; genetic algorithm; stainless steel 316L; Taguchi Method},
	abstract = {This research paper attempts to investigate the optimum values of the major intervening parameters in micro-Electric Discharge Machining (microEDM) of Stainless Steel (SS) 316L. Experiments are conducted using a 400 micrometre brass electrode. The discharge current, pulseon time and pulse-off time with three levels are selected as significant intervening parameters. The Taguchi method is initially applied to determine the optimum process parameters and the number of experiments required to model the responses. The response-surface methodology (RSM) is applied to correlate between intervening parameters, and the selected objectives to maximize the material removal rate (MRR) and to minimize the tool wear rate (TWR) in the machining of SS 316 L. The mathematical model obtained from RSM is used as a fitness function to multi-objective optimization using a genetic algorithm (GA). The results reveal that the resulting optimal intervening parameters improve the chosen objectives significantly. The confirmation results prove that the better developed mathematical model yields deviate within 5% of the experiment.},
	issn = {0039-2480},	pages = {656-664},	doi = {10.5545/sv-jme.2014.1665},
	url = {https://www.sv-jme.eu/sl/article/optimization-of-intervening-variables-in-microedm-of-ss-316l-using-a-genetic-algorithm-and-response-surface-methodology/}
}
Suresh, P.,Venkatesan, R.,Sekar, T.,Elango, N.,Sathiyamoorthy, V.
2014 June 60. Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 60:10
%A Suresh, Periyakgounder 
%A Venkatesan, Rajamanickam 
%A Sekar, Tamilperruvalathan 
%A Elango, Natarajan 
%A Sathiyamoorthy, Varatharajan 
%D 2014
%T Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology
%B 2014
%9 microEDM; response surface methodology; genetic algorithm; stainless steel 316L; Taguchi Method
%! Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology
%K microEDM; response surface methodology; genetic algorithm; stainless steel 316L; Taguchi Method
%X This research paper attempts to investigate the optimum values of the major intervening parameters in micro-Electric Discharge Machining (microEDM) of Stainless Steel (SS) 316L. Experiments are conducted using a 400 micrometre brass electrode. The discharge current, pulseon time and pulse-off time with three levels are selected as significant intervening parameters. The Taguchi method is initially applied to determine the optimum process parameters and the number of experiments required to model the responses. The response-surface methodology (RSM) is applied to correlate between intervening parameters, and the selected objectives to maximize the material removal rate (MRR) and to minimize the tool wear rate (TWR) in the machining of SS 316 L. The mathematical model obtained from RSM is used as a fitness function to multi-objective optimization using a genetic algorithm (GA). The results reveal that the resulting optimal intervening parameters improve the chosen objectives significantly. The confirmation results prove that the better developed mathematical model yields deviate within 5% of the experiment.
%U https://www.sv-jme.eu/sl/article/optimization-of-intervening-variables-in-microedm-of-ss-316l-using-a-genetic-algorithm-and-response-surface-methodology/
%0 Journal Article
%R 10.5545/sv-jme.2014.1665
%& 656
%P 9
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 60
%N 10
%@ 0039-2480
%8 2018-06-28
%7 2018-06-28
Suresh, Periyakgounder, Rajamanickam  Venkatesan, Tamilperruvalathan  Sekar, Natarajan  Elango, & Varatharajan  Sathiyamoorthy.
"Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology." Strojniški vestnik - Journal of Mechanical Engineering [Online], 60.10 (2014): 656-664. Web.  29 Sep. 2021
TY  - JOUR
AU  - Suresh, Periyakgounder 
AU  - Venkatesan, Rajamanickam 
AU  - Sekar, Tamilperruvalathan 
AU  - Elango, Natarajan 
AU  - Sathiyamoorthy, Varatharajan 
PY  - 2014
TI  - Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2014.1665
KW  - microEDM; response surface methodology; genetic algorithm; stainless steel 316L; Taguchi Method
N2  - This research paper attempts to investigate the optimum values of the major intervening parameters in micro-Electric Discharge Machining (microEDM) of Stainless Steel (SS) 316L. Experiments are conducted using a 400 micrometre brass electrode. The discharge current, pulseon time and pulse-off time with three levels are selected as significant intervening parameters. The Taguchi method is initially applied to determine the optimum process parameters and the number of experiments required to model the responses. The response-surface methodology (RSM) is applied to correlate between intervening parameters, and the selected objectives to maximize the material removal rate (MRR) and to minimize the tool wear rate (TWR) in the machining of SS 316 L. The mathematical model obtained from RSM is used as a fitness function to multi-objective optimization using a genetic algorithm (GA). The results reveal that the resulting optimal intervening parameters improve the chosen objectives significantly. The confirmation results prove that the better developed mathematical model yields deviate within 5% of the experiment.
UR  - https://www.sv-jme.eu/sl/article/optimization-of-intervening-variables-in-microedm-of-ss-316l-using-a-genetic-algorithm-and-response-surface-methodology/
@article{{sv-jme}{sv-jme.2014.1665},
	author = {Suresh, P., Venkatesan, R., Sekar, T., Elango, N., Sathiyamoorthy, V.},
	title = {Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {60},
	number = {10},
	year = {2014},
	doi = {10.5545/sv-jme.2014.1665},
	url = {https://www.sv-jme.eu/sl/article/optimization-of-intervening-variables-in-microedm-of-ss-316l-using-a-genetic-algorithm-and-response-surface-methodology/}
}
TY  - JOUR
AU  - Suresh, Periyakgounder 
AU  - Venkatesan, Rajamanickam 
AU  - Sekar, Tamilperruvalathan 
AU  - Elango, Natarajan 
AU  - Sathiyamoorthy, Varatharajan 
PY  - 2018/06/28
TI  - Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 60, No 10 (2014): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2014.1665
KW  - microEDM, response surface methodology, genetic algorithm, stainless steel 316L, Taguchi Method
N2  - This research paper attempts to investigate the optimum values of the major intervening parameters in micro-Electric Discharge Machining (microEDM) of Stainless Steel (SS) 316L. Experiments are conducted using a 400 micrometre brass electrode. The discharge current, pulseon time and pulse-off time with three levels are selected as significant intervening parameters. The Taguchi method is initially applied to determine the optimum process parameters and the number of experiments required to model the responses. The response-surface methodology (RSM) is applied to correlate between intervening parameters, and the selected objectives to maximize the material removal rate (MRR) and to minimize the tool wear rate (TWR) in the machining of SS 316 L. The mathematical model obtained from RSM is used as a fitness function to multi-objective optimization using a genetic algorithm (GA). The results reveal that the resulting optimal intervening parameters improve the chosen objectives significantly. The confirmation results prove that the better developed mathematical model yields deviate within 5% of the experiment.
UR  - https://www.sv-jme.eu/sl/article/optimization-of-intervening-variables-in-microedm-of-ss-316l-using-a-genetic-algorithm-and-response-surface-methodology/
Suresh, Periyakgounder, Venkatesan, Rajamanickam, Sekar, Tamilperruvalathan, Elango, Natarajan, AND Sathiyamoorthy, Varatharajan.
"Optimization of Intervening Variables in MicroEDM of SS 316L using a Genetic Algorithm and Response-Surface Methodology" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 60 Number 10 (28 June 2018)

Avtorji

Inštitucije

  • Sona College of Technology, Department of Mechanical Engineering, Tamil Nadu, India 1
  • Government College of Engineering, Department of Mechanical Engineering, India 2
  • Kolej University Linton, School of Mechanical Engineering, Malaysia 3
  • Mahendra Engineering College, Department of Mechanical Engineering, India 4

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)10, 656-664

https://doi.org/10.5545/sv-jme.2014.1665

This research paper attempts to investigate the optimum values of the major intervening parameters in micro-Electric Discharge Machining (microEDM) of Stainless Steel (SS) 316L. Experiments are conducted using a 400 micrometre brass electrode. The discharge current, pulseon time and pulse-off time with three levels are selected as significant intervening parameters. The Taguchi method is initially applied to determine the optimum process parameters and the number of experiments required to model the responses. The response-surface methodology (RSM) is applied to correlate between intervening parameters, and the selected objectives to maximize the material removal rate (MRR) and to minimize the tool wear rate (TWR) in the machining of SS 316 L. The mathematical model obtained from RSM is used as a fitness function to multi-objective optimization using a genetic algorithm (GA). The results reveal that the resulting optimal intervening parameters improve the chosen objectives significantly. The confirmation results prove that the better developed mathematical model yields deviate within 5% of the experiment.

microEDM; response surface methodology; genetic algorithm; stainless steel 316L; Taguchi Method