Cutting parameters optimization for surface roughness during dry hard turning of EN 31 bearing steel using CBN insert

2020 ◽  
Vol 26 ◽  
pp. 1119-1125
Author(s):  
M.S. Karthik ◽  
V.R. Raju ◽  
K. Niranjan Reddy ◽  
N. Balashanmugam ◽  
M.R. Sankar
2015 ◽  
Vol 809-810 ◽  
pp. 195-200
Author(s):  
Constatin Rotariu ◽  
Sevasti Mitsi ◽  
Dragos Paraschiv ◽  
Octavian Lupescu ◽  
Sergiu Lungu ◽  
...  

In this paper we analyze the influence of cutting parameters on the surface quality, surface roughness respectively, processed by turning when heat treated bearing steel, also called hard turning, and processing by turning of bearing steel without heat treatment. We set parameters of the cutting regime influencing the achievement of roughness surfaces which must be within the predetermined requirements if bearing rings exceeding 500 mm in diameter. This analysis will be done by statistical methods using the software Minitab 14.


2014 ◽  
Vol 602-605 ◽  
pp. 144-147
Author(s):  
Jun Min Xiao ◽  
Jin Xie

Based on experiments of ball-end cutters milling for 2A70 aluminum alloy, the prediction model of surface roughness for 2A70 aluminum alloy is established by using of regression analysis method of least square. Aiming at the actual milling problem in the enterprise the cutting parameters are optimized by using of optimization tool-box of MATLAB software, in the process of solving optimized parameters the machining efficiency is set as the objective function and surface roughness prediction model is set as the constraint condition. The optimized cutting parameters can greatly improve the machining efficiency in the premise of ensuring the quality of machined surface, and it provides the important theory evidence and case reference for NC machining enterprises to reduce production costs.


2012 ◽  
Vol 628 ◽  
pp. 144-149
Author(s):  
Wei Wei Liu ◽  
Yuan Yu ◽  
Feng Li ◽  
Chang Feng Yao ◽  
Bin Liu

The orthogonal experiment is processed for high-speed milling superalloy GH4169 with TiAlN coated carbide inserts. The surface roughness prediction model based on cutting parameters is established by using the least-squares regression method. And the effect of cutting parameters on surface roughness is studied. According to the prediction model of surface roughness, a model of cutting parameters optimization by using genetic algorithm based on annealing penalty function is established for maximum material removal rate under specified surface roughness values. Obtain the optimal parameter combination when the surface roughness Ra≤0.2µm, and the experimental validation is done. These results provide the basis for improving processing efficiency of processing GH4169 and choosing parameters under specified constraint conditions.


2017 ◽  
Vol 64 (3) ◽  
pp. 347-357
Author(s):  
Krzysztof Żak

Abstract In this paper, the basic cutting characteristics such as cutting forces, cutting power and its distribution, specific cutting energies were determined taking into account variable tool corner radius ranging from 400 to 1200 µm and constant cutting parameters typical for hard turning of a hardened 41Cr4 alloy steel of 55±1 HRC hardness. Finish turning operations were performed using chamfered CBN tools. Moreover, selected roughness profiles produced for different tool corner radius were compared and appropriate surface roughness parameters were measured. The measured values of Ra and Rz roughness parameters are compared with their theoretical values and relevant material distribution curves and bearing parameters are presented.


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