Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation

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LE, Minh-Thai ;LE VAN, An ;NGUYEN, Trung-Thanh .
Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 69, n.3-4, p. 155-168, february 2023. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/impacts-of-burnishing-variables-on-the-quality-indicators-in-a-single-diamond-burnishing-operation/>. Date accessed: 21 jul. 2024. 
doi:http://dx.doi.org/10.5545/sv-jme.2022.303.
Le, M., Le Van, A., & Nguyen, T.
(2023).
Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation.
Strojniški vestnik - Journal of Mechanical Engineering, 69(3-4), 155-168.
doi:http://dx.doi.org/10.5545/sv-jme.2022.303
@article{sv-jmesv-jme.2022.303,
	author = {Minh-Thai  Le and An  Le Van and Trung-Thanh  Nguyen},
	title = {Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {69},
	number = {3-4},
	year = {2023},
	keywords = {Single diamond burnishing; Average roughness; Vickers hardness; Bayesian regularization; NSGA-G; },
	abstract = {Diamond burnishing is an effective solution to finish a surface. The purpose of the current work is to optimize parameter inputs, including the spindle speed (S), depth of penetration (D), feed rate (f), and diameter of tool-tip (DT) for improving the Vickers hardness (VH) and decreasing the average roughness (Ra) of a new diamond burnishing process. A set of burnishing experiments is executed under a new cooling lubrication system comprising the minimum quantity lubrication and double vortex tubes. The Bayesian regularized feed-forward neural network (BRFFNN) models of the performances are proposed in terms of the inputs. The criteria importance through the inter-criteria correlation (CRITIC) method and non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) are applied to compute the weights of responses and find optimality. The optimal outcomes of the S, D, f, and DT were 370 rpm, 0.10 mm, 0.04 mm/rev, and 8 mm, respectively. The improvements in the Ra and VH were 40.7 % and 7.6 %, respectively, as compared to the original parameters. An effective approach combining the BRFFNN, CRITIC, and NSGA-G can be widely utilized to deal with complicated optimization problems. The optimizing results can be employed to enhance the surface properties of the burnished surface.},
	issn = {0039-2480},	pages = {155-168},	doi = {10.5545/sv-jme.2022.303},
	url = {https://www.sv-jme.eu/article/impacts-of-burnishing-variables-on-the-quality-indicators-in-a-single-diamond-burnishing-operation/}
}
Le, M.,Le Van, A.,Nguyen, T.
2023 February 69. Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 69:3-4
%A Le, Minh-Thai 
%A Le Van, An 
%A Nguyen, Trung-Thanh 
%D 2023
%T Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation
%B 2023
%9 Single diamond burnishing; Average roughness; Vickers hardness; Bayesian regularization; NSGA-G; 
%! Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation
%K Single diamond burnishing; Average roughness; Vickers hardness; Bayesian regularization; NSGA-G; 
%X Diamond burnishing is an effective solution to finish a surface. The purpose of the current work is to optimize parameter inputs, including the spindle speed (S), depth of penetration (D), feed rate (f), and diameter of tool-tip (DT) for improving the Vickers hardness (VH) and decreasing the average roughness (Ra) of a new diamond burnishing process. A set of burnishing experiments is executed under a new cooling lubrication system comprising the minimum quantity lubrication and double vortex tubes. The Bayesian regularized feed-forward neural network (BRFFNN) models of the performances are proposed in terms of the inputs. The criteria importance through the inter-criteria correlation (CRITIC) method and non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) are applied to compute the weights of responses and find optimality. The optimal outcomes of the S, D, f, and DT were 370 rpm, 0.10 mm, 0.04 mm/rev, and 8 mm, respectively. The improvements in the Ra and VH were 40.7 % and 7.6 %, respectively, as compared to the original parameters. An effective approach combining the BRFFNN, CRITIC, and NSGA-G can be widely utilized to deal with complicated optimization problems. The optimizing results can be employed to enhance the surface properties of the burnished surface.
%U https://www.sv-jme.eu/article/impacts-of-burnishing-variables-on-the-quality-indicators-in-a-single-diamond-burnishing-operation/
%0 Journal Article
%R 10.5545/sv-jme.2022.303
%& 155
%P 14
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 69
%N 3-4
%@ 0039-2480
%8 2023-02-22
%7 2023-02-22
Le, Minh-Thai, An  Le Van, & Trung-Thanh  Nguyen.
"Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation." Strojniški vestnik - Journal of Mechanical Engineering [Online], 69.3-4 (2023): 155-168. Web.  21 Jul. 2024
TY  - JOUR
AU  - Le, Minh-Thai 
AU  - Le Van, An 
AU  - Nguyen, Trung-Thanh 
PY  - 2023
TI  - Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2022.303
KW  - Single diamond burnishing; Average roughness; Vickers hardness; Bayesian regularization; NSGA-G; 
N2  - Diamond burnishing is an effective solution to finish a surface. The purpose of the current work is to optimize parameter inputs, including the spindle speed (S), depth of penetration (D), feed rate (f), and diameter of tool-tip (DT) for improving the Vickers hardness (VH) and decreasing the average roughness (Ra) of a new diamond burnishing process. A set of burnishing experiments is executed under a new cooling lubrication system comprising the minimum quantity lubrication and double vortex tubes. The Bayesian regularized feed-forward neural network (BRFFNN) models of the performances are proposed in terms of the inputs. The criteria importance through the inter-criteria correlation (CRITIC) method and non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) are applied to compute the weights of responses and find optimality. The optimal outcomes of the S, D, f, and DT were 370 rpm, 0.10 mm, 0.04 mm/rev, and 8 mm, respectively. The improvements in the Ra and VH were 40.7 % and 7.6 %, respectively, as compared to the original parameters. An effective approach combining the BRFFNN, CRITIC, and NSGA-G can be widely utilized to deal with complicated optimization problems. The optimizing results can be employed to enhance the surface properties of the burnished surface.
UR  - https://www.sv-jme.eu/article/impacts-of-burnishing-variables-on-the-quality-indicators-in-a-single-diamond-burnishing-operation/
@article{{sv-jme}{sv-jme.2022.303},
	author = {Le, M., Le Van, A., Nguyen, T.},
	title = {Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {69},
	number = {3-4},
	year = {2023},
	doi = {10.5545/sv-jme.2022.303},
	url = {https://www.sv-jme.eu/article/impacts-of-burnishing-variables-on-the-quality-indicators-in-a-single-diamond-burnishing-operation/}
}
TY  - JOUR
AU  - Le, Minh-Thai 
AU  - Le Van, An 
AU  - Nguyen, Trung-Thanh 
PY  - 2023/02/22
TI  - Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 69, No 3-4 (2023): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2022.303
KW  - Single diamond burnishing, Average roughness, Vickers hardness, Bayesian regularization, NSGA-G, 
N2  - Diamond burnishing is an effective solution to finish a surface. The purpose of the current work is to optimize parameter inputs, including the spindle speed (S), depth of penetration (D), feed rate (f), and diameter of tool-tip (DT) for improving the Vickers hardness (VH) and decreasing the average roughness (Ra) of a new diamond burnishing process. A set of burnishing experiments is executed under a new cooling lubrication system comprising the minimum quantity lubrication and double vortex tubes. The Bayesian regularized feed-forward neural network (BRFFNN) models of the performances are proposed in terms of the inputs. The criteria importance through the inter-criteria correlation (CRITIC) method and non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) are applied to compute the weights of responses and find optimality. The optimal outcomes of the S, D, f, and DT were 370 rpm, 0.10 mm, 0.04 mm/rev, and 8 mm, respectively. The improvements in the Ra and VH were 40.7 % and 7.6 %, respectively, as compared to the original parameters. An effective approach combining the BRFFNN, CRITIC, and NSGA-G can be widely utilized to deal with complicated optimization problems. The optimizing results can be employed to enhance the surface properties of the burnished surface.
UR  - https://www.sv-jme.eu/article/impacts-of-burnishing-variables-on-the-quality-indicators-in-a-single-diamond-burnishing-operation/
Le, Minh-Thai, Le Van, An, AND Nguyen, Trung-Thanh.
"Impacts of Burnishing Variables on the Quality Indicators in a Single Diamond Burnishing Operation" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 69 Number 3-4 (22 February 2023)

Authors

Affiliations

  • Le Quy Don Technical University, Faculty of Special Equipment, Vietnam 1
  • Nguyen Tat Thanh University, Faculty of Engineering and Technology, Viet Nam 2

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 69(2023)3-4, 155-168
© The Authors 2023. CC BY 4.0 Int.

https://doi.org/10.5545/sv-jme.2022.303

Diamond burnishing is an effective solution to finish a surface. The purpose of the current work is to optimize parameter inputs, including the spindle speed (S), depth of penetration (D), feed rate (f), and diameter of tool-tip (DT) for improving the Vickers hardness (VH) and decreasing the average roughness (Ra) of a new diamond burnishing process. A set of burnishing experiments is executed under a new cooling lubrication system comprising the minimum quantity lubrication and double vortex tubes. The Bayesian regularized feed-forward neural network (BRFFNN) models of the performances are proposed in terms of the inputs. The criteria importance through the inter-criteria correlation (CRITIC) method and non-dominated sorting genetic algorithm based on the grid partitioning (NSGA-G) are applied to compute the weights of responses and find optimality. The optimal outcomes of the S, D, f, and DT were 370 rpm, 0.10 mm, 0.04 mm/rev, and 8 mm, respectively. The improvements in the Ra and VH were 40.7 % and 7.6 %, respectively, as compared to the original parameters. An effective approach combining the BRFFNN, CRITIC, and NSGA-G can be widely utilized to deal with complicated optimization problems. The optimizing results can be employed to enhance the surface properties of the burnished surface.

Single diamond burnishing; Average roughness; Vickers hardness; Bayesian regularization; NSGA-G;