Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy

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Izvoz citacije: ABNT
ÇOLAK, Oğuz .
Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 60, n.10, p. 675-681, june 2018. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/sl/article/optimization-of-machining-performance-in-high-pressure-assisted-turning-of-ti6al4v-alloy/>. Date accessed: 04 dec. 2021. 
doi:http://dx.doi.org/10.5545/sv-jme.2013.1079.
Çolak, O.
(2014).
Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy.
Strojniški vestnik - Journal of Mechanical Engineering, 60(10), 675-681.
doi:http://dx.doi.org/10.5545/sv-jme.2013.1079
@article{sv-jmesv-jme.2013.1079,
	author = {Oğuz  Çolak},
	title = {Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {60},
	number = {10},
	year = {2014},
	keywords = {High pressure cooling, Optimization, Tool life},
	abstract = {In this study, a genetic algorithm has been employed to determine optimum cutting parameters in the turning of Ti6Al4V alloy under conventional and high pressure cooling conditions. Three machining performance measures, i.e. surface roughness, material removal rate and cutting power, are considered as optimization criteria. First, with multi-regression analysis of experimental responses, empirical equations are defined and, by using these equations, objective functions are constructed for each pressure level, based on a hybrid model. Objective functions are maximized by means of a genetic algorithm and optimum machining parameters are determined. Moreover, tool wear tests are carried out at a cutting condition that is close to the optimum machining parameters. Optimization results show that optimum cutting parameters and their responses, particularly in P = 6 and 150 bar cooling conditions, are quite similar, but tool life is significantly different. Maximum tool life is achieved in the highest pressure level (P = 300 bar).},
	issn = {0039-2480},	pages = {675-681},	doi = {10.5545/sv-jme.2013.1079},
	url = {https://www.sv-jme.eu/sl/article/optimization-of-machining-performance-in-high-pressure-assisted-turning-of-ti6al4v-alloy/}
}
Çolak, O.
2014 June 60. Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 60:10
%A Çolak, Oğuz 
%D 2014
%T Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy
%B 2014
%9 High pressure cooling, Optimization, Tool life
%! Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy
%K High pressure cooling, Optimization, Tool life
%X In this study, a genetic algorithm has been employed to determine optimum cutting parameters in the turning of Ti6Al4V alloy under conventional and high pressure cooling conditions. Three machining performance measures, i.e. surface roughness, material removal rate and cutting power, are considered as optimization criteria. First, with multi-regression analysis of experimental responses, empirical equations are defined and, by using these equations, objective functions are constructed for each pressure level, based on a hybrid model. Objective functions are maximized by means of a genetic algorithm and optimum machining parameters are determined. Moreover, tool wear tests are carried out at a cutting condition that is close to the optimum machining parameters. Optimization results show that optimum cutting parameters and their responses, particularly in P = 6 and 150 bar cooling conditions, are quite similar, but tool life is significantly different. Maximum tool life is achieved in the highest pressure level (P = 300 bar).
%U https://www.sv-jme.eu/sl/article/optimization-of-machining-performance-in-high-pressure-assisted-turning-of-ti6al4v-alloy/
%0 Journal Article
%R 10.5545/sv-jme.2013.1079
%& 675
%P 7
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 60
%N 10
%@ 0039-2480
%8 2018-06-28
%7 2018-06-28
Çolak, Oğuz.
"Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy." Strojniški vestnik - Journal of Mechanical Engineering [Online], 60.10 (2014): 675-681. Web.  04 Dec. 2021
TY  - JOUR
AU  - Çolak, Oğuz 
PY  - 2014
TI  - Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2013.1079
KW  - High pressure cooling, Optimization, Tool life
N2  - In this study, a genetic algorithm has been employed to determine optimum cutting parameters in the turning of Ti6Al4V alloy under conventional and high pressure cooling conditions. Three machining performance measures, i.e. surface roughness, material removal rate and cutting power, are considered as optimization criteria. First, with multi-regression analysis of experimental responses, empirical equations are defined and, by using these equations, objective functions are constructed for each pressure level, based on a hybrid model. Objective functions are maximized by means of a genetic algorithm and optimum machining parameters are determined. Moreover, tool wear tests are carried out at a cutting condition that is close to the optimum machining parameters. Optimization results show that optimum cutting parameters and their responses, particularly in P = 6 and 150 bar cooling conditions, are quite similar, but tool life is significantly different. Maximum tool life is achieved in the highest pressure level (P = 300 bar).
UR  - https://www.sv-jme.eu/sl/article/optimization-of-machining-performance-in-high-pressure-assisted-turning-of-ti6al4v-alloy/
@article{{sv-jme}{sv-jme.2013.1079},
	author = {Çolak, O.},
	title = {Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {60},
	number = {10},
	year = {2014},
	doi = {10.5545/sv-jme.2013.1079},
	url = {https://www.sv-jme.eu/sl/article/optimization-of-machining-performance-in-high-pressure-assisted-turning-of-ti6al4v-alloy/}
}
TY  - JOUR
AU  - Çolak, Oğuz 
PY  - 2018/06/28
TI  - Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 60, No 10 (2014): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2013.1079
KW  - High pressure cooling, Optimization, Tool life
N2  - In this study, a genetic algorithm has been employed to determine optimum cutting parameters in the turning of Ti6Al4V alloy under conventional and high pressure cooling conditions. Three machining performance measures, i.e. surface roughness, material removal rate and cutting power, are considered as optimization criteria. First, with multi-regression analysis of experimental responses, empirical equations are defined and, by using these equations, objective functions are constructed for each pressure level, based on a hybrid model. Objective functions are maximized by means of a genetic algorithm and optimum machining parameters are determined. Moreover, tool wear tests are carried out at a cutting condition that is close to the optimum machining parameters. Optimization results show that optimum cutting parameters and their responses, particularly in P = 6 and 150 bar cooling conditions, are quite similar, but tool life is significantly different. Maximum tool life is achieved in the highest pressure level (P = 300 bar).
UR  - https://www.sv-jme.eu/sl/article/optimization-of-machining-performance-in-high-pressure-assisted-turning-of-ti6al4v-alloy/
Çolak, Oğuz"Optimization of Machining Performance in High-Pressure Assisted Turning of Ti6Al4V Alloy" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 60 Number 10 (28 June 2018)

Avtorji

Inštitucije

  • Süleyman Demirel University, CAD/CAM Research and Application Center, Turkey 1

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 60(2014)10, 675-681

https://doi.org/10.5545/sv-jme.2013.1079

In this study, a genetic algorithm has been employed to determine optimum cutting parameters in the turning of Ti6Al4V alloy under conventional and high pressure cooling conditions. Three machining performance measures, i.e. surface roughness, material removal rate and cutting power, are considered as optimization criteria. First, with multi-regression analysis of experimental responses, empirical equations are defined and, by using these equations, objective functions are constructed for each pressure level, based on a hybrid model. Objective functions are maximized by means of a genetic algorithm and optimum machining parameters are determined. Moreover, tool wear tests are carried out at a cutting condition that is close to the optimum machining parameters. Optimization results show that optimum cutting parameters and their responses, particularly in P = 6 and 150 bar cooling conditions, are quite similar, but tool life is significantly different. Maximum tool life is achieved in the highest pressure level (P = 300 bar).

High pressure cooling, Optimization, Tool life