Cutting Force Modeling in Precision Turning 3J33 Alloy for Tool with Nose Radius

2009 ◽  
Vol 69-70 ◽  
pp. 167-171
Author(s):  
Yuan Sheng Zhai ◽  
Yu Wang ◽  
Ying Chun Liang
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Parameters ◽  
Multiple Correlation Coefficient ◽  
Depth Of Cut ◽  
Ratio Test ◽  
Nose Radius ◽  
Precision Turning ◽  
Force Modeling

Based on experimental results, a predictive model with certain constraints of cutting parameters (feed rate and depth of cut) and nose radius for cutting forces is solved in precision turning 3J33 alloy. The proposed model is adequate with F-ratio test and multiple correlation coefficient of it. Regression analysis shows that depth of cut and feed rate influence the principal cutting force significantly. The goal of this study is to predict cutting forces under certain constraints of cutting parameters and nose radius.

Surface Roughness Prediction Based on Cutting Parameters and Nose Radius in Precision Turning

2007 ◽  
Vol 329 ◽  
pp. 539-544 ◽  
Author(s):  
Ying Chun Liang ◽  
Yuan Sheng Zhai ◽  
H.X. Wang ◽  
Qing Shun Bai ◽  
Y. Zhao
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Ratio Test ◽  
Nose Radius ◽  
Precision Turning ◽  
Proposed Model ◽  
Roughness Prediction ◽  
Optimal Cutting Parameters

In precision turning, the quality of surface finish is an important requirement for machined workpiece. Thus, the choice of optimal cutting parameters is very important for controlling the required surface quality. The focus of the present study is to find a correlation between surface roughness and cutting parameters (feed rate, depth of cut) and nose radius in turning 3J33 maraging steel, and to derive mathematical models for the predicted surface roughness based on both of cutting parameters and nose radius. The experimental design is carried out using the quadratic rotary combination design. The regression analysis shows feed rate and nose radius influence surface roughness significantly. With F-ratio test the proposed model is adequate. The method could be useful in predicting roughness parameters as a function of cutting parameters and nose radius.

scholarly journals Validation and optimization of cutting parameters for Ti-6Al-4V turning operation using DEFORM 3D simulations and Taguchi method

2021 ◽  
Vol 8 ◽  
pp. 5
Author(s):  
Japheth Oirere Obiko ◽  
Fredrick Madaraka Mwema ◽  
Michael Oluwatosin Bodunrin
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Optimization Of Cutting Parameters ◽  
The Relationship

In this study, we show that optimising cutting forces as a machining response gave the most favourable conditions for turning of Ti-6Al-4V alloy. Using a combination of computational methods involving DEFORM simulations, Taguchi Design of Experiment (DOE) and analysis of variance (ANOVA), it was possible to minimise typical machining response such as the cutting force, cutting power and chip-tool interface temperature. The turning parameters that were varied in this study include cutting speed, depth of cut and feed rate. The optimum turning parameter combinations that would minimise the machining responses were established by using the “smaller the better” criterion and selecting the highest value of Signal to Noise Ratio. Confirmatory simulation revealed that using cutting speed of 120 m/min, 0.25 mm depth of cut and 0.1 mm/rev feed rate, the lowest cutting force of 88.21 N and chip-tool interface temperature of 387.24 °C can be obtained. Regression analysis indicated that the highest correlation coefficient of 0.97 was obtained between cutting forces and the turning parameters. The relationship between cutting forces and the turning parameters was linear since first-order regression model was sufficient.

Modeling and Analysis of Cutting Forces in Hard Turning T250 Steel Using CBN Tools

2010 ◽  
Vol 154-155 ◽  
pp. 694-700
Author(s):  
Yue Ding ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
Hao Yang
Keyword(s):  
Cutting Force ◽  
Analysis Of Variance ◽  
Feed Rate ◽  
Cutting Forces ◽  
Hard Turning ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Modeling And Analysis ◽  
Feed Force

The objective of this paper is to study the cutting forces in hard turning T250 steel with CBN tools. Experiments based on the Box-Behnken design were conducted to develop the cutting forces models by response surface methodology (RSM). Significance tests of the model are performed by the analysis of variance (ANOVA). It is also discussed the effects of cutting parameters (cutting speed, feed rate and depth of cut) on the cutting force components. The results show that the models can fit experimental data via analysis of variance. The most important cutting parameter is depth of cut, followed by feed rate, while the effect of cutting speed can be neglected. Compared to cutting force and feed force, thrust force is the largest. In addition, the cutting forces generated by the uncoated tool are smaller than by the coated one due to tool wear.

Cutting Temperature and Cutting Forces Investigation Based on the Taguchi Design Method when High-Speed Milling of Titanium Matrix Composites with PCD Tool

2016 ◽  
Vol 836-837 ◽  
pp. 168-174 ◽  
Author(s):  
Ying Fei Ge ◽  
Hai Xiang Huan ◽  
Jiu Hua Xu
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Forces ◽  
High Speed ◽  
Volume Fraction ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
High Speed Milling ◽  
Radial Depth

High-speed milling tests were performed on vol. (5%-8%) TiCp/TC4 composite in the speed range of 50-250 m/min using PCD tools to nvestigate the cutting temperature and the cutting forces. The results showed that radial depth of cut and cutting speed were the two significant influences that affected the cutting forces based on the Taguchi prediction. Increasing radial depth of cut and feed rate will increase the cutting force while increasing cutting speed will decrease the cutting force. Cutting force increased less than 5% when the reinforcement volume fraction in the composites increased from 0% to 8%. Radial depth of cut was the only significant influence factor on the cutting temperature. Cutting temperature increased with the increasing radial depth of cut, feed rate or cutting speed. The cutting temperature for the titanium composites was 40-90 °C higher than that for the TC4 matrix. However, the cutting temperature decreased by 4% when the reinforcement's volume fraction increased from 5% to 8%.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

Predictive Modeling and Optimization of Cutting Forces Through RSM and Taguchi Techniques in the Turning of ASTM B574 (Hastelloy C-22)

2018 ◽  
pp. 398-417
Author(s):  
İsmail Kırbaş ◽  
Musa Peker ◽  
Gültekin Basmacı ◽  
Mustafa Ay
Keyword(s):  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Orthogonal Experimental Design ◽  
Depth Of Cut ◽  
Effective Parameters ◽  
Factors Affecting ◽  
The Impact

In this chapter, the impact of cutting parameters (depth of cut, cutting speed, feed, flow, rake angle, lead angle) on cutting forces in the turning process with regard to ASTM B574 (Hastelloy C-22) material has been investigated. Variance analysis has been applied in order to determine the factors affecting the cutting forces. The optimization of the parameters affecting the surface roughness has been obtained using response surface methodology (RSM) based on the Taguchi orthogonal experimental design. The accuracy of the developed models required for the estimation of the force values (Fx, Fy, Fz) is quite successful. In this study, where the R2 value has been used as the criterion/measure, accuracy values of 93.35%, 95.03%, and 95.09% have been achieved for Fx, Fy, and Fz, respectively. As a result of the ANOVA analysis, the most effective parameters for Fx at a 95% confidence interval are depth of cut, feed rate, flow, and rake angle. The most effective parameter for Fy is depth of cut, while the most effective parameters for Fz are depth of cut, feed rate, and flow, respectively.

Influence of the Cutting Parameters on the Cutting Forces of Carbon Steel

2002 ◽  
Author(s):  
Zulay Cassier ◽  
Patricia Mun˜oz-Escanola ◽  
Rolda´n Sa´nchez
Keyword(s):  
Carbon Steel ◽  
Cutting Forces ◽  
Low Cost ◽  
Cutting Parameters ◽  
Carbon Steels ◽  
Machining Process ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 1045 ◽  
Alloy Steels

Plain carbon steels and alloy steels have a great application in the manufacturing process especially due to their characteristic of high machinability and low cost. The machining of these materials, the study of the cutting forces, and the power required for the cutting process is one of the most important parameters to be evaluated. The relationship between this parameter and the other cutting variables process is crucial for the optimization of the machining process. The results of this research are empirical expressions, obtained from the cutting parameters (tool nose radius, feed rate and depth of cut) and the influence of these parameters on the cutting forces for each carbon steel studied (AISI 1020, AISI 1045 and AISI 4340), as well as a general expression which includes the mechanical properties of these carbon steels. These results enable the user to predict cutting forces when using a turning process.

A Study of Relation between Roundness and Cutting Force in CNC Turning Process

2015 ◽  
Vol 799-800 ◽  
pp. 366-371 ◽  
Author(s):  
Deuanphan Chanthana ◽  
Somkiat Tangjitsitcharoen
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Turning Process ◽  
Nose Radius ◽  
Cnc Turning ◽  
Cnc Turning Process ◽  
Tool Nose Radius

The roundness is one of the most important criteria to accept the mechanical parts in the CNC turning process. The relations of the roundness, the cutting conditions and the cutting forces in CNC turning is hence studied in this research. The dynamometer is installed on the turret of the CNC turning machine to measure the in-process cutting force signals. The cutting parameters are investigated to analyze the effects of them on the roundness which are the cutting speed, the feed rate, the depth of cut, the tool nose radius and the rake angle. The experimentally obtained results showed that the better roundness is obtained with an increase in cutting speed, tool nose radius and rake angle. The relation between the cutting parameters and the roundness can be explained by the in-process cutting forces. It is understood that the roundness can be monitored by using the in-process cutting forces.

scholarly journals Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6

2018 ◽  
Vol 14 (1) ◽  
pp. 67-76
Author(s):  
Mohanned Mohammed H. AL-Khafaji
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Thickness Ratio ◽  
Depth Of Cut ◽  
Feed Force ◽  
Machining Force ◽  
Force Components

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).

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