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: 19 nov. 2024. 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. 19 Nov. 2024
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)
Strojniški vestnik - Journal of Mechanical Engineering 60(2014)10, 656-664
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
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.