ALMEIDA, Fabrício Alves de;GOMES, Guilherme Ferreira;DE PAULA, Vinícius Renó;CORRÊA, João Éderson;DE PAIVA, Anderson Paulo;GOMES, José Henrique de Freitas;TURRIONI, João Batista. A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 64, n.3, p. 147-156, june 2018. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/a-weighted-mean-square-error-approach-to-robust-optimization-of-the-surface-roughness-in-aisi-12l14-free-machining-steel-turning-process/>. Date accessed: 01 sep. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2017.4901.
Almeida, F., Gomes, G., De Paula, V., Corrêa, J., de Paiva, A., Gomes, J., & Turrioni, J. (2018). A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process. Strojniški vestnik - Journal of Mechanical Engineering, 64(3), 147-156. doi:http://dx.doi.org/10.5545/sv-jme.2017.4901
@article{sv-jmesv-jme.2017.4901, author = {Fabrício Alves de Almeida and Guilherme Ferreira Gomes and Vinícius Renó De Paula and João Éderson Corrêa and Anderson Paulo de Paiva and José Henrique de Freitas Gomes and João Batista Turrioni}, title = {A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {64}, number = {3}, year = {2018}, keywords = {robust parameter optimization; mean square error; 12L14 free machining steel turning; response surface methodology}, abstract = {The objective of this work is to determine an optimal setup for the 12L14 free-machining steel-turning process that will be able to neutralize the influence of tool wear in the workpiece’s mean roughness Ra. Aiming this, equations for the mean and variance of the roughness were modelled using the response surface methodology. A crossed array with three input variables of the turning process (cutting speed, feed and depth of cut) and a noise variable (use of new and wear tools) is applied to the methodology. Subsequently, these same responses were optimized using the mean square error, which allows the response mean value to approach a predetermined target value by cancelling variations thereof through a weighted objective. Confirmation experiments were conducted to prove the suitability of the method and excellent results were obtained.}, issn = {0039-2480}, pages = {147-156}, doi = {10.5545/sv-jme.2017.4901}, url = {https://www.sv-jme.eu/article/a-weighted-mean-square-error-approach-to-robust-optimization-of-the-surface-roughness-in-aisi-12l14-free-machining-steel-turning-process/} }
Almeida, F.,Gomes, G.,De Paula, V.,Corrêa, J.,de Paiva, A.,Gomes, J.,Turrioni, J. 2018 June 64. A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 64:3
%A Almeida, Fabrício Alves de %A Gomes, Guilherme Ferreira %A De Paula, Vinícius Renó %A Corrêa, João Éderson %A de Paiva, Anderson Paulo %A Gomes, José Henrique de Freitas %A Turrioni, João Batista %D 2018 %T A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process %B 2018 %9 robust parameter optimization; mean square error; 12L14 free machining steel turning; response surface methodology %! A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process %K robust parameter optimization; mean square error; 12L14 free machining steel turning; response surface methodology %X The objective of this work is to determine an optimal setup for the 12L14 free-machining steel-turning process that will be able to neutralize the influence of tool wear in the workpiece’s mean roughness Ra. Aiming this, equations for the mean and variance of the roughness were modelled using the response surface methodology. A crossed array with three input variables of the turning process (cutting speed, feed and depth of cut) and a noise variable (use of new and wear tools) is applied to the methodology. Subsequently, these same responses were optimized using the mean square error, which allows the response mean value to approach a predetermined target value by cancelling variations thereof through a weighted objective. Confirmation experiments were conducted to prove the suitability of the method and excellent results were obtained. %U https://www.sv-jme.eu/article/a-weighted-mean-square-error-approach-to-robust-optimization-of-the-surface-roughness-in-aisi-12l14-free-machining-steel-turning-process/ %0 Journal Article %R 10.5545/sv-jme.2017.4901 %& 147 %P 10 %J Strojniški vestnik - Journal of Mechanical Engineering %V 64 %N 3 %@ 0039-2480 %8 2018-06-26 %7 2018-06-26
Almeida, Fabrício, Guilherme Ferreira Gomes, Vinícius Renó De Paula, João Éderson Corrêa, Anderson Paulo de Paiva, José Henrique de Freitas Gomes, & João Batista Turrioni. "A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process." Strojniški vestnik - Journal of Mechanical Engineering [Online], 64.3 (2018): 147-156. Web. 01 Sep. 2024
TY - JOUR AU - Almeida, Fabrício Alves de AU - Gomes, Guilherme Ferreira AU - De Paula, Vinícius Renó AU - Corrêa, João Éderson AU - de Paiva, Anderson Paulo AU - Gomes, José Henrique de Freitas AU - Turrioni, João Batista PY - 2018 TI - A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2017.4901 KW - robust parameter optimization; mean square error; 12L14 free machining steel turning; response surface methodology N2 - The objective of this work is to determine an optimal setup for the 12L14 free-machining steel-turning process that will be able to neutralize the influence of tool wear in the workpiece’s mean roughness Ra. Aiming this, equations for the mean and variance of the roughness were modelled using the response surface methodology. A crossed array with three input variables of the turning process (cutting speed, feed and depth of cut) and a noise variable (use of new and wear tools) is applied to the methodology. Subsequently, these same responses were optimized using the mean square error, which allows the response mean value to approach a predetermined target value by cancelling variations thereof through a weighted objective. Confirmation experiments were conducted to prove the suitability of the method and excellent results were obtained. UR - https://www.sv-jme.eu/article/a-weighted-mean-square-error-approach-to-robust-optimization-of-the-surface-roughness-in-aisi-12l14-free-machining-steel-turning-process/
@article{{sv-jme}{sv-jme.2017.4901}, author = {Almeida, F., Gomes, G., De Paula, V., Corrêa, J., de Paiva, A., Gomes, J., Turrioni, J.}, title = {A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {64}, number = {3}, year = {2018}, doi = {10.5545/sv-jme.2017.4901}, url = {https://www.sv-jme.eu/article/a-weighted-mean-square-error-approach-to-robust-optimization-of-the-surface-roughness-in-aisi-12l14-free-machining-steel-turning-process/} }
TY - JOUR AU - Almeida, Fabrício Alves de AU - Gomes, Guilherme Ferreira AU - De Paula, Vinícius Renó AU - Corrêa, João Éderson AU - de Paiva, Anderson Paulo AU - Gomes, José Henrique de Freitas AU - Turrioni, João Batista PY - 2018/06/26 TI - A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 64, No 3 (2018): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2017.4901 KW - robust parameter optimization, mean square error, 12L14 free machining steel turning, response surface methodology N2 - The objective of this work is to determine an optimal setup for the 12L14 free-machining steel-turning process that will be able to neutralize the influence of tool wear in the workpiece’s mean roughness Ra. Aiming this, equations for the mean and variance of the roughness were modelled using the response surface methodology. A crossed array with three input variables of the turning process (cutting speed, feed and depth of cut) and a noise variable (use of new and wear tools) is applied to the methodology. Subsequently, these same responses were optimized using the mean square error, which allows the response mean value to approach a predetermined target value by cancelling variations thereof through a weighted objective. Confirmation experiments were conducted to prove the suitability of the method and excellent results were obtained. UR - https://www.sv-jme.eu/article/a-weighted-mean-square-error-approach-to-robust-optimization-of-the-surface-roughness-in-aisi-12l14-free-machining-steel-turning-process/
Almeida, Fabrício, Gomes, Guilherme, De Paula, Vinícius, Corrêa, João, de Paiva, Anderson, Gomes, José Henrique, AND Turrioni, João. "A Weighted Mean Square Error Approach to the Robust Optimization of the Surface Roughness in an AISI 12L14 Free-Machining Steel-Turning Process" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 64 Number 3 (26 June 2018)
Strojniški vestnik - Journal of Mechanical Engineering 64(2018)3, 147-156
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
The objective of this work is to determine an optimal setup for the 12L14 free-machining steel-turning process that will be able to neutralize the influence of tool wear in the workpiece’s mean roughness Ra. Aiming this, equations for the mean and variance of the roughness were modelled using the response surface methodology. A crossed array with three input variables of the turning process (cutting speed, feed and depth of cut) and a noise variable (use of new and wear tools) is applied to the methodology. Subsequently, these same responses were optimized using the mean square error, which allows the response mean value to approach a predetermined target value by cancelling variations thereof through a weighted objective. Confirmation experiments were conducted to prove the suitability of the method and excellent results were obtained.