Authors :
N. G. A. Zebaze; Ju. L. Tchigirinsky
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/hak7ejyc
Scribd :
https://tinyurl.com/3nccz6r4
DOI :
https://doi.org/10.5281/zenodo.14613865
Abstract :
The surface roughness obtained by
optimizing the cutting parameters when turning on a
CNC machine tool is used to control the quality of
machining processes. The objective is to simulate a
CNC program designed for this process. The
machining parameters, including cutting speed (Vc),
feed rate (f), and depth of cut (ap), are carefully
calibrated to achieve a minimum surface roughness
(Ra). Analysis of variance (ANOVA) was used to
determine the dependence of surface roughness. This
analysis allows the effect of each parameter on surface
roughness to be estimated. The results of this analysis
are then used to construct a mathematical model that
establishes a correlation between cutting parameters
and surface roughness.
Keywords :
Roughness (Ra), CNC Turning, Machining Process, Initial Parameters, Numerical Modeling.
References :
- A. V. Sakharov, D. Rudoy, A.N. Altybaev, M. Petkovich, N. Miletic, Selection of machine tool equipment when implementing modular technology // E3S Web of Conferences, 2024, V. 583. DOI: https://doi.org/10.1051/e3sconf/202458305011
- B. Bazrov. M. Determining demands of parts production techniques // Science intensive technologies in mechanical engineering. 2023. №. 5. pp. 3-7. DOI: https://doi.org/10.30987/2223-4608-2023-3-7
- K. Zhuang, Z. Shi, Y. Sun, Z. Gao, L. Wang. Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process. Symmetry. 2021; 13(8):1438. DOI: https://doi.org/10.3390/sym13081438
- Suslov A. G., Shalygin M. G. Control of nanogeometry of parts by the method of surface hardening // Science intensive technologies in mechanical engineering. 2021. no. 11. pp. 38-41. DOI: https://doi.org/10.30987/2223-4608-2021-11-38-41
- Z. N. Muxiddinov. "A study on the influence of cutting parameters on surface roughness and visualization through contour plots and 3d surface profiles," technical science and innovation: Vol. 2024: Iss. 1, Article 14. DOI: https://doi.org/10.59048/2181-0400
- A. G. Suslov. Technological support of the parameters of the surface layer state of the parts (in Russian) / A.G. Suslov. Moscow: Mechanical Engineering, 1987. 207 p.
- Y. N. Polyanchikov, D. V. Krainev, P. A. Norchenko and al. Improvement of roughness parameters at machining by cutting with advance plastic deformation // Bulletin of Saratov State Technical University. 2010. №1. p. 67-71.
- Y. L. Chigirinsky. Stochastic modeling in mechanical engineering: A textbook / Y. L. Chigirinsky, N. V. Chigirinskaya. Yu. M. Bykov. - Volgograd: VolgGTU, 2002. - 68 p.
- P. Marimuthu, K. Chandrasekaran. Experimental study of stainless-steel optimal tuning of machining parameters using Taguchi and neural network, Engineering and Applied Sciences. 2011. P. 6. №10. P.1819-6608.
The surface roughness obtained by
optimizing the cutting parameters when turning on a
CNC machine tool is used to control the quality of
machining processes. The objective is to simulate a
CNC program designed for this process. The
machining parameters, including cutting speed (Vc),
feed rate (f), and depth of cut (ap), are carefully
calibrated to achieve a minimum surface roughness
(Ra). Analysis of variance (ANOVA) was used to
determine the dependence of surface roughness. This
analysis allows the effect of each parameter on surface
roughness to be estimated. The results of this analysis
are then used to construct a mathematical model that
establishes a correlation between cutting parameters
and surface roughness.
Keywords :
Roughness (Ra), CNC Turning, Machining Process, Initial Parameters, Numerical Modeling.