Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades

1309 Views
790 Downloads
Export citation: ABNT
SOORI, Mohsen ;ASMAEL, Mohammed .
Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 67, n.5, p. 235-244, july 2021. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/virtual-minimization-of-residual-stress-and-deflection-error-in-five-axis-milling-of-turbine-blades/>. Date accessed: 01 mar. 2024. 
doi:http://dx.doi.org/10.5545/sv-jme.2021.7113.
Soori, M., & Asmael, M.
(2021).
Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades.
Strojniški vestnik - Journal of Mechanical Engineering, 67(5), 235-244.
doi:http://dx.doi.org/10.5545/sv-jme.2021.7113
@article{sv-jmesv-jme.2021.7113,
	author = {Mohsen  Soori and Mohammed  Asmael},
	title = {Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {67},
	number = {5},
	year = {2021},
	keywords = {virtual machining, residual stress, deflection error, parameter optimization, turbine blade},
	abstract = {To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.},
	issn = {0039-2480},	pages = {235-244},	doi = {10.5545/sv-jme.2021.7113},
	url = {https://www.sv-jme.eu/article/virtual-minimization-of-residual-stress-and-deflection-error-in-five-axis-milling-of-turbine-blades/}
}
Soori, M.,Asmael, M.
2021 July 67. Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 67:5
%A Soori, Mohsen 
%A Asmael, Mohammed 
%D 2021
%T Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades
%B 2021
%9 virtual machining, residual stress, deflection error, parameter optimization, turbine blade
%! Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades
%K virtual machining, residual stress, deflection error, parameter optimization, turbine blade
%X To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.
%U https://www.sv-jme.eu/article/virtual-minimization-of-residual-stress-and-deflection-error-in-five-axis-milling-of-turbine-blades/
%0 Journal Article
%R 10.5545/sv-jme.2021.7113
%& 235
%P 10
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 67
%N 5
%@ 0039-2480
%8 2021-07-08
%7 2021-07-08
Soori, Mohsen, & Mohammed  Asmael.
"Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades." Strojniški vestnik - Journal of Mechanical Engineering [Online], 67.5 (2021): 235-244. Web.  01 Mar. 2024
TY  - JOUR
AU  - Soori, Mohsen 
AU  - Asmael, Mohammed 
PY  - 2021
TI  - Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2021.7113
KW  - virtual machining, residual stress, deflection error, parameter optimization, turbine blade
N2  - To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.
UR  - https://www.sv-jme.eu/article/virtual-minimization-of-residual-stress-and-deflection-error-in-five-axis-milling-of-turbine-blades/
@article{{sv-jme}{sv-jme.2021.7113},
	author = {Soori, M., Asmael, M.},
	title = {Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {67},
	number = {5},
	year = {2021},
	doi = {10.5545/sv-jme.2021.7113},
	url = {https://www.sv-jme.eu/article/virtual-minimization-of-residual-stress-and-deflection-error-in-five-axis-milling-of-turbine-blades/}
}
TY  - JOUR
AU  - Soori, Mohsen 
AU  - Asmael, Mohammed 
PY  - 2021/07/08
TI  - Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 67, No 5 (2021): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 10.5545/sv-jme.2021.7113
KW  - virtual machining, residual stress, deflection error, parameter optimization, turbine blade
N2  - To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.
UR  - https://www.sv-jme.eu/article/virtual-minimization-of-residual-stress-and-deflection-error-in-five-axis-milling-of-turbine-blades/
Soori, Mohsen, AND Asmael, Mohammed.
"Virtual Minimization of Residual Stress and Deflection Error in the Five-Axis Milling of Turbine Blades" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 67 Number 5 (08 July 2021)

Authors

Affiliations

  • Eastern Mediterranean University, Department of Mechanical Engineering, Turkey 1

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 67(2021)5, 235-244
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.

https://doi.org/10.5545/sv-jme.2021.7113

To simulate and analyse the real machined parts in virtual environments, virtual machining systems are applied to the production processes. Due to friction, chip forming, and the heat produced in the cutting zone, parts produced using machining operation have residual stress effects. The machining force and machining temperature can cause the deflection error in the machined turbine blades, which should be minimized to increase the accuracy of machined blades. To minimize the residual stress and deflection error of machined parts, optimized machining parameters can be obtained. In the present research work, the application of a virtual machining system is presented to predict and minimize the residual stress and deflection error in a five-axis milling operations of turbine blades. In order to predict the residual stress and deflection error in machined turbine blades, finite element analysis is implemented. Moreover, to minimize the residual stress and deflection error in machined turbine blades, optimized parameters of machining operations are obtained by using a genetic algorithm. To validate the research work, experimentally determining residual stress by using a X-ray diffraction method from the machined turbine blades is compared with the finite element results obtained from the virtual machining system. Also, in order to obtain the deflection error, the machined blades are measured by using the CMM machines. Thus, the accuracy and reliability of machined turbine blades can be increased by analysing and minimizing the residual stress and deflection error in virtual environments.

virtual machining, residual stress, deflection error, parameter optimization, turbine blade