Investigation on Effect of Machining Parameters of End Milling on Surface Finish and Temperature Using Taguchi Technique

2016 ◽  
Vol 16 (4) ◽  
pp. 255-261
Author(s):  
Tamiloli N ◽  
Venkatesan J
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
End Milling ◽  
Cutting Temperature ◽  
Cutting Parameters ◽  
Milling Process ◽  
Machining Parameters ◽  
Cutting Zone ◽  
Machining Optimization ◽  
Quality Surface

AbstractMachining of alloy materials at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality. Thus, developing a model for estimating the cutting parameters and optimizing this model to minimize the surface roughness and cutting temperatures becomes utmost important to avoid any damage to the quality surface. This paper presents the development of new models and optimizing these models of machining parameters to minimize the surface roughness and cutting temperature in end milling process by Taguchi method with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and cutting temperature. Due to the complexity of this machining optimization problem, a single objective Taguchi method has been applied to resolve the problem, and the results have been analyzed.

EFFECT OF CUTTING PARAMETERS ON CUTTING ZONE IN CRYOGENIC HIGH SPEED MILLING OF INCONEL 718 ALLOY

2015 ◽  
Vol 77 (27) ◽  
Author(s):  
A. H. Musfirah ◽  
J. A. Ghani ◽  
C. H. Che Haron ◽  
M. S. Kasim
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
End Milling ◽  
Cutting Temperature ◽  
Cryogenic Cooling ◽  
Cutting Condition ◽  
Dry Machining ◽  
Part Quality ◽  
Cutting Zone ◽  
Coated Carbide

In tribology phenomenon, surface roughness has become one of the most important factors that contributed to the evaluation of part quality during machining operation. In order to understand the behavior of cryogenic cooling assistance in machining Inconel 718, this paper aims to provide better understanding of tribological characterization of liquid nitrogen near the cutting zone of this material in ball end milling process. Experiments were performed using a multi-layer TiAlN/AlCrN-coated carbide inserts under cryogenic and dry cutting condition. A transient milling simulation model using Third Wave Advantedge has been done in order to gain in-depth understanding of the thermomechanical aspects of machining and their influence on resulted part quality. The cryogenic results of the cutting temperature, cutting forces and surface roughness of the ball nose cutting tool have been compared with those of dry machining. Finally, experimental results proved that cryogenic implementation can  decrease the amount of heat transferred to the tool up to almost 70% and improve the surface roughness to a maximum of 31% when compared with dry machining. Furthermore, the microstructure of machined workpiece revealed that cryogenic cooling also can reduce a plastic deformation at the cutting surface as compared with the dry machining. 

Effect of Tool Wear on Surface Qualities in Milling of TC4

2016 ◽  
Vol 836-837 ◽  
pp. 132-138 ◽  
Author(s):  
Shu Cai Yang ◽  
Xiao Yang Cui ◽  
Yu Hua Zhang ◽  
Zhi Wei Wang
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Tool Wear ◽  
Surface Quality ◽  
End Milling ◽  
Great Influence ◽  
Chip Morphology ◽  
Milling Process ◽  
Serrated Chip ◽  
Quality Surface

Tool wear is easy occurred in titanium alloy milling process which will affect the surface quality. Surface roughness and surface morphology as an important index to describe and evaluate the surface quality has a great influence on service performance. Therefore, the study on the effect of tool wear on surface qualities is important to improve the surface integrity of titanium alloy parts. Cutting radius of ball-end milling cutter is solved to analyze the effect of tool wear on the cutting radius. The tool wear and the surface qualities of TC4 are achieved through wear experiment. And then the influence law of tool wear on surface qualities and chip morphology are analyzed. The results show that surface roughness value decrease firstly and then increases and that chip morphology with flank wear increase from the unit chip to the serrated chip.

Cutting Parameters Optimization of Mild Steel via AIS Heuristics Algorithm

2015 ◽  
Vol 761 ◽  
pp. 132-136
Author(s):  
Adnan Jameel Abbas ◽  
Mohammad Minhat ◽  
Md Nizam Abd Rahman
Keyword(s):  
Surface Roughness ◽  
Mild Steel ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Temperature ◽  
Cutting Parameters ◽  
Optimum Cutting ◽  
Cutting Velocity ◽  
Cutting Zone ◽  
The Ideal

. The minimum cost and high productivity of the recent industrial renaissance are its main challengers. Selecting the optimum cutting parameters play a significant role in achieving these aims. Heat generated in the cutting zone area is an important factor affecting workpiece and cutting tool properties. The surface finish quality specifies product success and integrity. In this paper, the temperature generated in the cutting zone (shear zone and chip-tool interface zone) and workpiece surface roughness is optimized using an artificial immune system (AIS) intelligent algorithm. A mild steel type (S45C) workpiece and a tungsten insert cutting tool type (SPG 422) is subjected to dry CNC turning operation are used in experiments. Optimum cutting parameters (cutting velocity, depth of cut, and feed rate) calculated by the (AIS) algorithm are used to obtain the simulated and ideal cutting temperature and surface roughness. An infrared camera type (Flir E60) is used for temperature measurement, and a portable surface roughness device is used for roughness measurement. Experimental results show that the ideal cutting temperature (110°C) and surface roughness (0.49 μm) occur at (0.3 mm) cut depth, (0.06 mm) feed rate, and (60 m/min) cutting velocity. The AIS accuracy rates in finding the ideal cutting temperature and surface roughness are (91.70 %) and (90.37 %) respectively. Analysis shows that the predicted results are close to the experimental ones, indicating that this intelligent system can be used to estimate cutting temperature and surface roughness during the turning operation of mild steel.

End-Milling Machinability of Inconel 718

1996 ◽  
Vol 210 (1) ◽  
pp. 11-23 ◽  
Author(s):  
M Alauddin ◽  
M A El Baradie ◽  
M S J Hashmi
Keyword(s):  
Surface Roughness ◽  
Tool Life ◽  
Inconel 718 ◽  
End Milling ◽  
Milling Process ◽  
Machining Parameters ◽  
Life Tests ◽  
Life Values ◽  
Published Research ◽  
Carbide Inserts

Most published research works on machining Inconel 718 have been mainly concerned with turning, while the milling process has received little attention due to the complexity of the process. In this paper a series of end-milling experiments of Inconel 718 has been carried out in order to: (a) optimize cutting variables, (b) investigate tool life values and relationships and (c) investigate surface roughness. The machining parameters have been optimized by measuring cutting forces. Tool life tests have been carried out using carbide inserts and the surface roughness has been analysed.

scholarly journals Machinability Investigation in Dry Turning of Ti–6al–4v With a Novel Tib2-based Cermet Tool Using Response Surface Methodology

2020 ◽  
Author(s):  
Yikun Yuan ◽  
Wenbin Ji ◽  
Shijie Dai ◽  
Huibo Zhang
Keyword(s):  
Surface Roughness ◽  
Cutting Temperature ◽  
Cutting Parameters ◽  
Machining Parameters ◽  
Processing Efficiency ◽  
Machined Surface ◽  
Dry Turning ◽  
Diffusion Wear ◽  
Cutting Length ◽  
Machined Surface Roughness

Abstract To ensure accuracy and improve the processing efficiency of Ti–6Al–4V alloys, dry turning experiment of Ti–6Al–4V was carried out using a novel TiB2-based cermet tool. The tool was reinforced by nanoscale VC additive and exhibited excellent hardness and fracture toughness.Response Surface Methodology (RSM) was used in the experiment to verify andevaluatethe cutting performance ofTiB2-based cermet tool.The cutting forces and machined surface roughness (Ra) were selected as the optimization objective. An analysis of variance (ANOVA) was used to find out the effective machining parameters on response factorsand demonstrate correctness of the models. It was found that theeffective factor on surface roughness was feed rate, while cutting depth significantly affected cutting forces.And the confirmation experiments showedthat the predicted values were in good agreement with experimental values. Based on the optimized cutting parameters, the tool life was measured and tool wear mechanismwasinvestigated. When the vc, apandfwere 100 mm/min, 0.16 mm, 0.1 mm/rev respectively for Ra optimization, the cutting length and tool lifecould reach to 3233 m and 29.4 min, respectively, due to the excellentwear resistance and stability of TiB2-based cermet tool at high cutting temperature. In this case, the main wear mechanism was adhesive wear and diffusion wear.

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.

Monitoring of Surface Roughness Based on Cutting Force and Cutting Temperature in Ball-End Milling Process by Utilizing Response Surface Analysis

2015 ◽  
Vol 799-800 ◽  
pp. 324-328
Author(s):  
Panrawee Yaisuk ◽  
Somkiat Tangjitsitcharoen
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Response Surface ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Temperature ◽  
Milling Process ◽  
Depth Of Cut ◽  
Tool Diameter ◽  
End Milling Process

The surface roughness is monitored using the cutting force and the cutting temperature in the ball-end milling process by utilizing the response surface analysis with the Box-Behnken design. The optimum cutting condition is obtained referring to the minimum surface roughness, which is the spindle speed, the feed rate, the depth of cut, and the tool diameter. The models of cutting force ratio and the cutting temperature are proposed and developed based on the experimental results. It is understood that the surface roughness is improved with an increase in spindle speed, feed rate and depth of cut. The cutting temperature decreases with an increase in tool diameter. The model verification has showed that the experimentally obtained surface roughness model is reliable and accurate to estimate the surface roughness.

Surface Roughness Optimization in End Milling Using the Multi Objective Genetic Algorithm Approach

2012 ◽  
Vol 576 ◽  
pp. 103-106 ◽  
Author(s):  
Muataz H.F. Al Hazza ◽  
Erry Yulian Triblas Adesta ◽  
Muhammad Riza ◽  
M.Y. Suprianto
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
End Milling ◽  
Cutting Speed ◽  
Root Mean Square Roughness ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Machining Optimization

In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness is important for it is economical and mechanical issues. This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and minimum Root-mean-square roughness (Rq). The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed.

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