A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process

1271 Views
790 Downloads
Export citation: ABNT
ŽUPERL, Uroš ;ČUŠ, Franci ;KIKER, Edo ;MILFELNER, Matjaž .
A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process. 
Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 51, n.9, p. 542-559, august 2017. 
ISSN 0039-2480.
Available at: <https://www.sv-jme.eu/article/a-combined-system-for-off-line-optimization-and-adaptive-adjustment-of-the-cutting-parameters-during-a-ball-end-milling-process/>. Date accessed: 02 oct. 2022. 
doi:http://dx.doi.org/.
Župerl, U., Čuš, F., Kiker, E., & Milfelner, M.
(2005).
A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process.
Strojniški vestnik - Journal of Mechanical Engineering, 51(9), 542-559.
doi:http://dx.doi.org/
@article{.,
	author = {Uroš  Župerl and Franci  Čuš and Edo  Kiker and Matjaž  Milfelner},
	title = {A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {51},
	number = {9},
	year = {2005},
	keywords = {machining; force control; adaptive control systems; optimization; ball-end mill; },
	abstract = {This paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modelling and adaptively controlling the process of ball-end milling. An overall procedure for the hybrid modelling of the cutting process (ANfis-system) used for working out the CNC milling simulator has been prepared. On the basis of the hybrid process modelling, off-line optimization and feedforward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of the cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining the constant roughness of the surface being milled by digital adaptation of the cutting parameters. In this way it compensates for all the disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. The basic control principle is based on a control scheme (UNKS) consisting of two neural identificators of the process dynamics and the primary controller. The CNC milling simulator tests the system stability and tunes the control-scheme parameters. The approach was successfully applied to a Heller CNC milling machine. Experiments have confirmed the efficiency of the adaptive control system, which was reflected in improved surface quality and decreased tool wear.},
	issn = {0039-2480},	pages = {542-559},	doi = {},
	url = {https://www.sv-jme.eu/article/a-combined-system-for-off-line-optimization-and-adaptive-adjustment-of-the-cutting-parameters-during-a-ball-end-milling-process/}
}
Župerl, U.,Čuš, F.,Kiker, E.,Milfelner, M.
2005 August 51. A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 51:9
%A Župerl, Uroš 
%A Čuš, Franci 
%A Kiker, Edo 
%A Milfelner, Matjaž 
%D 2005
%T A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process
%B 2005
%9 machining; force control; adaptive control systems; optimization; ball-end mill; 
%! A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process
%K machining; force control; adaptive control systems; optimization; ball-end mill; 
%X This paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modelling and adaptively controlling the process of ball-end milling. An overall procedure for the hybrid modelling of the cutting process (ANfis-system) used for working out the CNC milling simulator has been prepared. On the basis of the hybrid process modelling, off-line optimization and feedforward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of the cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining the constant roughness of the surface being milled by digital adaptation of the cutting parameters. In this way it compensates for all the disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. The basic control principle is based on a control scheme (UNKS) consisting of two neural identificators of the process dynamics and the primary controller. The CNC milling simulator tests the system stability and tunes the control-scheme parameters. The approach was successfully applied to a Heller CNC milling machine. Experiments have confirmed the efficiency of the adaptive control system, which was reflected in improved surface quality and decreased tool wear.
%U https://www.sv-jme.eu/article/a-combined-system-for-off-line-optimization-and-adaptive-adjustment-of-the-cutting-parameters-during-a-ball-end-milling-process/
%0 Journal Article
%R 
%& 542
%P 18
%J Strojniški vestnik - Journal of Mechanical Engineering
%V 51
%N 9
%@ 0039-2480
%8 2017-08-18
%7 2017-08-18
Župerl, Uroš, Franci  Čuš, Edo  Kiker, & Matjaž  Milfelner.
"A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process." Strojniški vestnik - Journal of Mechanical Engineering [Online], 51.9 (2005): 542-559. Web.  02 Oct. 2022
TY  - JOUR
AU  - Župerl, Uroš 
AU  - Čuš, Franci 
AU  - Kiker, Edo 
AU  - Milfelner, Matjaž 
PY  - 2005
TI  - A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process
JF  - Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - machining; force control; adaptive control systems; optimization; ball-end mill; 
N2  - This paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modelling and adaptively controlling the process of ball-end milling. An overall procedure for the hybrid modelling of the cutting process (ANfis-system) used for working out the CNC milling simulator has been prepared. On the basis of the hybrid process modelling, off-line optimization and feedforward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of the cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining the constant roughness of the surface being milled by digital adaptation of the cutting parameters. In this way it compensates for all the disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. The basic control principle is based on a control scheme (UNKS) consisting of two neural identificators of the process dynamics and the primary controller. The CNC milling simulator tests the system stability and tunes the control-scheme parameters. The approach was successfully applied to a Heller CNC milling machine. Experiments have confirmed the efficiency of the adaptive control system, which was reflected in improved surface quality and decreased tool wear.
UR  - https://www.sv-jme.eu/article/a-combined-system-for-off-line-optimization-and-adaptive-adjustment-of-the-cutting-parameters-during-a-ball-end-milling-process/
@article{{}{.},
	author = {Župerl, U., Čuš, F., Kiker, E., Milfelner, M.},
	title = {A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process},
	journal = {Strojniški vestnik - Journal of Mechanical Engineering},
	volume = {51},
	number = {9},
	year = {2005},
	doi = {},
	url = {https://www.sv-jme.eu/article/a-combined-system-for-off-line-optimization-and-adaptive-adjustment-of-the-cutting-parameters-during-a-ball-end-milling-process/}
}
TY  - JOUR
AU  - Župerl, Uroš 
AU  - Čuš, Franci 
AU  - Kiker, Edo 
AU  - Milfelner, Matjaž 
PY  - 2017/08/18
TI  - A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process
JF  - Strojniški vestnik - Journal of Mechanical Engineering; Vol 51, No 9 (2005): Strojniški vestnik - Journal of Mechanical Engineering
DO  - 
KW  - machining, force control, adaptive control systems, optimization, ball-end mill, 
N2  - This paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modelling and adaptively controlling the process of ball-end milling. An overall procedure for the hybrid modelling of the cutting process (ANfis-system) used for working out the CNC milling simulator has been prepared. On the basis of the hybrid process modelling, off-line optimization and feedforward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of the cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining the constant roughness of the surface being milled by digital adaptation of the cutting parameters. In this way it compensates for all the disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. The basic control principle is based on a control scheme (UNKS) consisting of two neural identificators of the process dynamics and the primary controller. The CNC milling simulator tests the system stability and tunes the control-scheme parameters. The approach was successfully applied to a Heller CNC milling machine. Experiments have confirmed the efficiency of the adaptive control system, which was reflected in improved surface quality and decreased tool wear.
UR  - https://www.sv-jme.eu/article/a-combined-system-for-off-line-optimization-and-adaptive-adjustment-of-the-cutting-parameters-during-a-ball-end-milling-process/
Župerl, Uroš, Čuš, Franci, Kiker, Edo, AND Milfelner, Matjaž.
"A Combined System for Off-Line Optimization and Adaptive Adjustment of the Cutting Parameters During a Ball-End Milling Process" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 51 Number 9 (18 August 2017)

Authors

Affiliations

  • University of Maribor, Faculty of Mechanical Engineering, Slovenia
  • University of Maribor, Faculty of Mechanical Engineering, Slovenia
  • University of Maribor, Faculty of Mechanical Engineering, Slovenia
  • University of Maribor, Faculty of Mechanical Engineering, Slovenia

Paper's information

Strojniški vestnik - Journal of Mechanical Engineering 51(2005)9, 542-559
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.

This paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy in modelling and adaptively controlling the process of ball-end milling. An overall procedure for the hybrid modelling of the cutting process (ANfis-system) used for working out the CNC milling simulator has been prepared. On the basis of the hybrid process modelling, off-line optimization and feedforward neural control scheme (UNKS) the combined system for off-line optimization and adaptive adjustment of the cutting parameters is built. This is an adaptive control system controlling the cutting force and maintaining the constant roughness of the surface being milled by digital adaptation of the cutting parameters. In this way it compensates for all the disturbances during the cutting process: tool wear, non-homogeneity of the workpiece material, vibrations, chatter etc. The basic control principle is based on a control scheme (UNKS) consisting of two neural identificators of the process dynamics and the primary controller. The CNC milling simulator tests the system stability and tunes the control-scheme parameters. The approach was successfully applied to a Heller CNC milling machine. Experiments have confirmed the efficiency of the adaptive control system, which was reflected in improved surface quality and decreased tool wear.

machining; force control; adaptive control systems; optimization; ball-end mill;