Optimization of Cutting Parameters and Nanoparticle Concentration in Hard Milling for Surface Roughness of JIS SKD61 Steel Using Linear Regression and Taguchi Method

2020 ◽  
pp. 628-635
Author(s):  
Thanh-Dat Phan ◽  
The-Vinh Do ◽  
Thanh-Long Pham ◽  
Huong-Lam Duong
Keyword(s):  
Surface Roughness ◽  
Linear Regression ◽  
Taguchi Method ◽  
Cutting Parameters ◽  
Nanoparticle Concentration ◽  
Hard Milling ◽  
Optimization Of Cutting Parameters

Prediction of Surface Roughness and Optimization of Cutting Parameters in CNC Turning of Rotational Features

2020 ◽  
Vol 38 (8A) ◽  
pp. 1143-1153
Author(s):  
Yousif K. Shounia ◽  
Tahseen F. Abbas ◽  
Raed R. Shwaish
Keyword(s):  
Surface Roughness ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Non Linear ◽  
Optimization Of Cutting Parameters

This research presents a model for prediction surface roughness in terms of process parameters in turning aluminum alloy 1200. The geometry to be machined has four rotational features: straight, taper, convex and concave, while a design of experiments was created through the Taguchi L25 orthogonal array experiments in minitab17 three factors with five Levels depth of cut (0.04, 0.06, 0.08, 0.10 and 0.12) mm, spindle speed (1200, 1400, 1600, 1800 and 2000) r.p.m and feed rate (60, 70, 80, 90 and 100) mm/min. A multiple non-linear regression model has been used which is a set of statistical extrapolation processes to estimate the relationships input variables and output which the surface roughness which prediction outside the range of the data. According to the non-linear regression model, the optimum surface roughness can be obtained at 1800 rpm of spindle speed, feed-rate of 80 mm/min and depth of cut 0.04 mm then the best surface roughness comes out to be 0.04 μm at tapper feature at depth of cut 0.01 mm and same spindle speed and feed rate pervious which gives the error of 3.23% at evolution equation.

The Optimization of Cutting Parameters for Surface Roughness in High Speed Milling Based on Taguchi Method

2012 ◽  
Vol 723 ◽  
pp. 196-201 ◽  
Author(s):  
Peng Nan Li ◽  
Ming Chen ◽  
Xiao Jian Kang ◽  
Li Na Zhang ◽  
Ming Zhou
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
High Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
High Speed Milling ◽  
Aisi 1045 Steel ◽  
Optimization Of Cutting Parameters ◽  
1045 Steel ◽  
Optimal Cutting Parameters

In this study AISI 1045 steel of different hardness are used in high speed milling. According to Taguchi method, cutting parameters (milling speed, milling depth, feed per tooth) and workpiece hardness for the influence of high speed milling of the surface roughness are optimized. Through this study, not only the optimal cutting parameters of the minimum surface roughness is obtained, but also the main cutting parameters that effect performance in high speed milling is analysed. Researching results can be provided to guide establishment of the high speed milling process.

Taguchi Approach for the Optimization of Cutting Parameters in Finish Turning of Medical Stainless Steel

2015 ◽  
Vol 809-810 ◽  
pp. 153-158
Author(s):  
Miroslav Radovanović ◽  
Laurentiu Slatineanu ◽  
Predrag Janković ◽  
Dušan Petković ◽  
Miloš Madić
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Taguchi Method ◽  
Orthogonal Array ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Finish Turning ◽  
Cutting Parameter ◽  
Optimization Of Cutting Parameters ◽  
Coated Carbide

Optimization of cutting parameters in finish turning of medical stainless steel 316LVM with coated carbide tools using Taguchi method is proposed in this paper. Four cutting parameters namely, insert radius, depth of cut, feed and cutting speed are optimized with considerations of surface roughness as performance characteristic. The effects of cutting parameters on the surface roughness were experimentally investigated. Experimentation was conducted as per Taguchi's orthogonal array. Four cutting parameters with three levels are arranged in L27 orthogonal array. The orthogonal array, measured values of surface roughness, signal-to-noise ratios and analysis of variance are employed to study the surface roughness. Based on the analysis, the optimal cutting parameter settings were determined. Through the confirmation test with optimal cutting parameter settings the effectiveness of the optimization approach are validated. The obtained results have shown that Taguchi method is suitable for optimizing the cutting parameter levels with the minimum number of experiments.

Optimization of cutting parameters for surface roughness in ball end milling of aluminium epoxy using Taguchi method

2019 ◽  
Author(s):  
H. Radhwan ◽  
S. Sharif ◽  
Z. Shayfull ◽  
M. A. Suhaimi ◽  
M. T. Mohd Khushairi ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
End Milling ◽  
Cutting Parameters ◽  
Ball End Milling ◽  
Optimization Of Cutting Parameters

Surface Roughness and Topography Analysis in Precision Milling of 3J33 Maraging Steel

2016 ◽  
Vol 874 ◽  
pp. 497-502 ◽  
Author(s):  
Yang Yao ◽  
Hong Tao Zhu ◽  
Chuan Zhen Huang ◽  
Dian Cong Zhang ◽  
Jun Wang ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Surface Topography ◽  
Maraging Steel ◽  
Surface Finish ◽  
Cutting Parameters ◽  
Tool Geometry ◽  
Milling Parameters ◽  
Optimization Of Cutting Parameters

In precision milling, the quality of surface finish is an important requirement for workpiece machined. Thus, optimization of cutting parameters is important for controlling the surface quality. In this study, the Taguchi method is used to find the effects of milling parameters on surface roughness in precision milling of 3J33 maraging steel. A model, which is based on the milling parameters and tool geometry, is also proposed in order to predict the surface topography. The experimental results show that milling speed has significant effect on the surface roughness among the milling parameters. Besides, tool geometry and material deformation play important roles in the surface topography.

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