Selection of Minimum Quantity Lubrication (MQL) Parameters in Milling of Ti-6Al-4V

2012 ◽  
Vol 426 ◽  
pp. 139-142 ◽  
Author(s):  
Zhi Qiang Liu ◽  
X.J. Cai ◽  
Ming Chen ◽  
Qing Long An

Different parameters of Minimum Quantity Lubrication (MQL) system, including air pressure, oil quantity, nozzle position, might have different influences on the cutting force and the cutting temperature. This paper presents an experiment of end-milling titanium alloy with MQL system. The objective of the experiment is to investigate the influences of MQL parameters in milling of Ti-6Al-4V. The results of experiment show that there are different effects on the cutting force and the cutting temperature with different MQL parameters, which will help to select different parameters in the end-milling process of Ti-6Al-4V.

Author(s):  
Dae Hoon Kim ◽  
Pil-Ho Lee ◽  
Jung Sub Kim ◽  
Hyungpil Moon ◽  
Sang Won Lee

This paper investigates the characteristics of micro end-milling process of titanium alloy (Ti-6AL-4V) using nanofluid minimum quantity lubrication (MQL). A series of micro end-milling experiments are conducted in the meso-scale machine tool system, and milling forces, burr formations, surface roughness, and tool wear are observed and analyzed according to varying feed per tooth and lubrication conditions. The experimental results show that MQL and nanofluid MQL with nanodiamond particles can be effective to reduce milling forces, burrs and surface roughness during micro end-milling of titanium alloy. In particular, it is demonstrated that smaller size of nanodiamond particles — 35 nm — can be more effective to decrease burrs and surface roughness in the case of nanofluid MQL micro end-milling.


2015 ◽  
Vol 799-800 ◽  
pp. 324-328
Author(s):  
Panrawee Yaisuk ◽  
Somkiat Tangjitsitcharoen

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.


Author(s):  
Jung Sub Kim ◽  
Jin Woo Kim ◽  
Young Chang Kim ◽  
Sang Won Lee

This research experimentally investigates the characteristics of micro end-milling process of titanium alloy using nanofluid minimum quantity lubrication (MQL) with chilly CO2 gas. In the nanofluid MQL, hexagonal boron nitride (hBN) particles having a lamellar structure are used. They have high aspect ratio and enable sliding against other particles, which can provide better lubricity. In addition, the chilly CO2 gas enhances a cooling effect during the micro end-milling process. A series of micro end-milling experiments are conducted in the meso-scale machine tool system, and milling force, coefficient of friction, surface roughness and tool wear are observed and analyzed according to varying lubrication and cooling conditions. The results show that the nanofluid MQL with chilly gas can be effective for reducing milling forces, coefficient of friction, tool wear and improving surface quality.


2020 ◽  
Author(s):  
A. Singh ◽  
I. Shivakoti ◽  
Z. Mustafa ◽  
R. Phipon ◽  
A. Sharma

2011 ◽  
Vol 121-126 ◽  
pp. 2059-2063 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Angsumalin Senjuntichai

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.


Author(s):  
Xia Ji ◽  
Steven Y Liang

This article presents a sensitivity analysis of residual stress based on the verified residual stress prediction model. The machining-induced residual stress is developed as a function of cutting parameters, tool geometry, material properties, and lubrication conditions. Based on the residual stress predictive model, the main effects of the cutting force, cutting temperature, and residual stress are quantitatively analyzed through the cosine amplitude method. The parametric study is carried out to investigate the effects of minimum quantity lubrication parameters, cutting parameters, and tool geometry on the cutting performances. Results manifest that the cutting force and residual stress are more sensitive to the heat transfer coefficient and the depth of cut, while the cutting temperature is more sensitive to the cutting speed. Large maximum compressive residual stress is obtained under a lower flow rate of minimum quantity lubrication, small depth of cut, and the proper air–oil mixture ratio. This research can support the controlling and optimization of residual stress in industrial engineering by strategically adjusting the application parameters of minimum quantity lubrication.


Author(s):  
Xuewei Zhang ◽  
Tianbiao Yu ◽  
Wanshan Wang

An accurate prediction of cutting forces in the micro end milling, which is affected by many factors, is the basis for increasing the machining productivity and selecting optimal cutting parameters. This paper develops a dynamic cutting force model in the micro end milling taking into account tool vibrations and run-out. The influence of tool run-out is integrated with the trochoidal trajectory of tooth and the size effect of cutting edge radius into the static undeformed chip thickness. Meanwhile, the real-time tool vibrations are obtained from differential motion equations with the measured modal parameters, in which the process damping effect is superposed as feedback on the undeformed chip thickness. The proposed dynamic cutting force model has been experimentally validated in the micro end milling process of the Al6061 workpiece. The tool run-out parameters and cutting forces coefficients can be identified on the basis of the measured cutting forces. Compared with the traditional model without tool vibrations and run-out, the predicted and measured cutting forces in the micro end milling process show closer agreement when considering tool vibrations and run-out.


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