Investigation of Dry Cutting and Applications of Cutting Fluid in Ball-End Milling Process

2011 ◽  
Vol 291-294 ◽  
pp. 3013-3023 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Channarong Rungruang
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
End Milling ◽  
Cutting Parameters ◽  
Milling Process ◽  
Cutting Fluid ◽  
Cutting Condition ◽  
Dry Cutting ◽  
Ball End Milling ◽  
End Milling Process

In order to realize the environmental hazard, this paper presents the investigation of the machinability of ball-end milling process with the dry cutting, the wet cutting, and the mist cutting for aluminum. The relations of the surface roughness, the cutting force, and the cutting parameters are examined based on the experimental results by using the Response Surface Analysis with the Box-Behnken design. The in-process cutting force is monitored to analyze the relations of the surface roughness and the cutting parameters. The proper cutting condition can be determined easily referring to the minimum use of cutting fluid, and the minimum surface roughness and cutting force of the surface plot. The effectiveness of the obtained surface roughness and cutting force models have been proved by utilizing the analysis of variance at 95% confident level.

Surface Roughness Prediction in Ball-End Milling Process for Aluminum by Using Air Blow Cutting

2011 ◽  
Vol 418-420 ◽  
pp. 1428-1434 ◽  
Author(s):  
Keerati Karunasawat ◽  
Somkiat Tangjitsitcharoen
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
End Milling ◽  
Cutting Speed ◽  
Milling Process ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Ball End Milling ◽  
Tool Diameter ◽  
End Milling Process

The objective of this research is to develop the surface roughness and cutting force models by using the air blow cutting of the aluminum in the ball-end milling process. The air blow cutting proposed in order to reduce the use of the cutting fluid. The surface roughness and cuttting force models are proposed in the exponential forms which consist of the cutting speed, the feed rate, the depth of cut, the tool diameter, and the air blow pressure. The coefficients of the surface roughness and cutting force models are calculated by utilizing the multiple regression with the least squared method at 95% significant level. The effects of cutting parameters on the cutting force are investigated and measured to analyze the relation between the surface roughness and the cutting conditions. The experimentally obtained results showed that the cutting force has the same trend with the surface roughness. The surface plots are constructed to determine the optimum cutting condition referring to the minimum surface roughness.

Intelligent Monitoring and Prediction of Surface Roughness in Ball-End Milling Process

2011 ◽  
Vol 121-126 ◽  
pp. 2059-2063 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Angsumalin Senjuntichai
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Prediction Accuracy ◽  
End Milling ◽  
Milling Process ◽  
Ball End Milling ◽  
Roughness Model ◽  
Force Ratio ◽  
Tool Diameter ◽  
End Milling Process

In order to realize the intelligent machines, the practical model is proposed to predict the in-process surface roughness during the ball-end milling process by utilizing the cutting force ratio. The ratio of cutting force is proposed to be generalized and non-scaled to estimate the surface roughness regardless of the cutting conditions. The proposed in-process surface roughness model is developed based on the experimentally obtained data by employing the exponential function with five factors of the spindle speed, the feed rate, the tool diameter, the depth of cut, and the cutting force ratio. The prediction accuracy and the prediction interval of the in-process surface roughness model at 95% confident level are calculated and proposed to predict the distribution of individually predicted points in which the in-process predicted surface roughness will fall. All those parameters have their own characteristics to the arithmetic surface roughness and the surface roughness. It is proved by the cutting tests that the proposed and developed in-process surface roughness model can be used to predict the in-process surface roughness by utilizing the cutting force ratio with the highly acceptable prediction accuracy.

Optimization of Process Parameters for Cutting Force for Aluminium 7010 in CNC End Milling Process

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
M. Kishanth ◽  
P. Rajkamal ◽  
D. Karthikeyan ◽  
K. Anand
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Optimization Of Process Parameters ◽  
Cnc End Milling ◽  
End Milling Process

In this paper CNC end milling process have been optimized in cutting force and surface roughness based on the three process parameters (i.e.) speed, feed rate and depth of cut. Since the end milling process is used for abrading the wear caused is very high, in order to reduce the wear caused by high cutting force and to decrease the surface roughness, the optimization is much needed for this process. Especially for materials like aluminium 7010, this kind of study is important for further improvement in machining process and also it will improve the stability of the machine.

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.

A Mechanistic Cutting Force Model for 3D Ball-end Milling

2000 ◽  
Vol 123 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Hsi-Yung Feng ◽  
Ning Su
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Chip Thickness ◽  
Milling Process ◽  
Force Model ◽  
Cutting Force Model ◽  
Ball End Milling ◽  
End Milling Process ◽  
Force Relationship

This paper presents an improved mechanistic cutting force model for the ball-end milling process. The objective is to accurately model the cutting forces for nonhorizontal and cross-feed cutter movements in 3D finishing ball-end milling. Main features of the model include: (1) a robust cut geometry identification method to establish the complicated engaged area on the cutter; (2) a generalized algorithm to determine the undeformed chip thickness for each engaged cutting edge element; and (3) a comprehensive empirical chip-force relationship to characterize nonhorizontal cutting mechanics. Experimental results have shown that the present model gives excellent predictions of cutting forces in 3D ball-end milling.

Optimization and Prediction of Cutting Force and Surface Roughness in End Milling Process of AISI 304 Stainless Steel

2015 ◽  
Vol 813-814 ◽  
pp. 362-367 ◽  
Author(s):  
Darshan A. Patel ◽  
Jitendra M. Mistry ◽  
Vrushit P. Kapatel ◽  
Dhaval R. Joshi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
End Milling ◽  
Milling Process ◽  
304 Stainless Steel ◽  
Depth Of Cut ◽  
Aisi 304 Stainless Steel ◽  
Aisi 304 ◽  
End Milling Process

The end milling process is most commonly used where the large amount material can be removed to produce almost final shape of component. The present work deals with the experimental study and optimization the machining parameter of AISI 304 stainless steel. The effects of spindle speed, feed rate and depth of cut have been studied on the cutting force and surface roughness using Taguchi’s 27 orthogonal arrays. Regression analyses were used to develop the model of response parameters. The analysis of the result shows, the surface roughness and the cutting force is increased with feed rate and depth of cut but decreased with increased the cutting speed. The ANOVA indicate the feed rate was the most dominate parameter on surface roughness and cutting force than speed and depth of cut.

Monitoring and Prediction of Surface Roughness in Ball End Milling with Air Blow Application

2012 ◽  
Vol 538-541 ◽  
pp. 1332-1337 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Suthas Ratanakuakangwan
Keyword(s):  
Surface Roughness ◽  
Regression Analysis ◽  
Cutting Force ◽  
Multiple Regression Analysis ◽  
Prediction Accuracy ◽  
Prediction Interval ◽  
End Milling ◽  
Cutting Condition ◽  
Ball End Milling ◽  
Roughness Model

This paper presents the additional work of the previous research in order to investigate the relations of the cutting conditions and the various air blow applications which affect the surface roughness. The suitable cutting condition is determined for the aluminum (Al6063) with the ball end milling by utilizing the response surface analysis referring to the minimum surface roughness. The cutting force is monitored during the cutting to analyze the surface roughness. The dynamometer is employed and installed on the table of 5-axis CNC maching center to measure the in-process cutting force. The models of surface roughness and cutting force are calculated by using the multiple regression analysis with the least squared method at 95% significant level. The experimentally obtained results showed that the surface roughness can be well explained by the in-process cutting force. The prediction accuracy and the prediction interval have been presented to verify the obtained surface roughness model at 95% confident level.

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