Analysis of Force Shape Characteristics and Detection of Depth-of-Cut Variations in End Milling

2004 ◽  
Vol 127 (3) ◽  
pp. 454-462 ◽  
Author(s):  
Liuqing Yang ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Cutting Forces ◽  
Analytical Approach ◽  
End Milling ◽  
Milling Process ◽  
Depth Of Cut ◽  
End Mill ◽  
Shape Characteristics ◽  
Cutting Experiments ◽  
End Milling Process ◽  
Degree Of Overlap

This paper proposes an analytical approach to detect depth-of-cut variations based on the cutting-force shape characteristics in end milling. Cutting forces of a single-flute end mill are analyzed and classified into three types according to their shape characteristics. Cutting forces of a multiple-flute end mill are then classified by considering both the cutting types of the corresponding single-flute end mill and the degree of overlap of successive flutes in the cut. Force indices are extracted from the cutting forces and depth-of-cut variations are detected based on the changes of the force shape characteristics via the force indices in an end-milling process. The detection methodology is validated through cutting experiments.

Analysis of Force Shape Characteristics and Detection of Depth-of-Cut Variations in End Milling

Manufacturing ◽  
2003 ◽  
Author(s):  
Liuqing Yang ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Cutting Forces ◽  
Analytical Approach ◽  
End Milling ◽  
Milling Process ◽  
Depth Of Cut ◽  
End Mill ◽  
Shape Characteristics ◽  
Cutting Experiments ◽  
End Milling Process ◽  
Degree Of Overlap

This paper proposes an analytical approach to detect depth-of-cut variations based upon the cutting force shape characteristics in end milling. Cutting forces of a single-flute end mill are analyzed and classified into three types according to their shape characteristics. Cutting forces of a multiple-flute end mill are then classified by considering both the cutting types of the corresponding single-flute end mill and the degree of overlap of successive flutes in the cut. Force indices are extracted from the cutting forces and depth-of-cut variations are detected based upon the changes of the force shape characteristics via the force indices in an end-milling process. The detection methodology is validated through cutting experiments.

Dynamic cutting force prediction for micro end milling considering tool vibrations and run-out

2018 ◽  
Vol 233 (7) ◽  
pp. 2248-2261 ◽  
Author(s):  
Xuewei Zhang ◽  
Tianbiao Yu ◽  
Wanshan Wang
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Chip Thickness ◽  
Milling Process ◽  
Force Model ◽  
Dynamic Cutting Force ◽  
Micro End Milling ◽  
Tool Vibrations ◽  
End Milling Process

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.

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.

Modeling & Analysis of End Milling Process Parameters Using Artificial Neural Networks

2014 ◽  
Vol 592-594 ◽  
pp. 2733-2737 ◽  
Author(s):  
G. Harinath Gowd ◽  
K. Divya Theja ◽  
Peyyala Rayudu ◽  
M. Venugopal Goud ◽  
M .Subba Roa
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Artificial Neural ◽  
End Milling Process

For modeling and optimizing the process parameters of manufacturing problems in the present days, numerical and Artificial Neural Networks (ANN) methods are widely using. In manufacturing environments, main focus is given to the finding of Optimum machining parameters. Therefore the present research is aimed at finding the optimal process parameters for End milling process. The End milling process is a widely used machining process because it is used for the rough and finish machining of many features such as slots, pockets, peripheries and faces of components. The present work involves the estimation of optimal values of the process variables like, speed, feed and depth of cut, whereas the metal removal rate (MRR) and tool wear resistance were taken as the output .Experimental design is planned using DOE. Optimum machining parameters for End milling process were found out using ANN and compared to the experimental results. The obtained results provβed the ability of ANN method for End milling process modeling and optimization.

Machining Characteristics of AlN-hBN Composites in End-Milling and Precision Lapping Processes

2008 ◽  
Vol 368-372 ◽  
pp. 947-950
Author(s):  
Si Young Beck ◽  
Bong Cheol Shin ◽  
Myeong Woo Cho ◽  
Eun Sang Lee ◽  
Dong Sam Park ◽  
...  
Keyword(s):  
Material Properties ◽  
End Milling ◽  
Milling Process ◽  
Cutting Conditions ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Micro Cracks ◽  
Experimental Works ◽  
Machining Characteristics ◽  
End Milling Process

In this study, the machining characteristics of developed AlN-hBN composites were investigated in the end-milling and precision lapping processes. To achieve the objectives, material properties of the developed AlN-hBN composites were evaluated according to the variation of hBN contents. And, required experimental works were performed to investigate the machining characteristics of the composites. First, the machiniability of the composite was evaluated in the end-milling process under various cutting conditions, such as spindle speed, feederate, and depth of cut variations. Also, generated micro cracks caused by the cutting process were investigated via SEM photographs. Next, precision lapping experiments were performed under various conditions, and the results were estimated.

Predicting Surface Roughness in End Milling Using an Innovative Technique From EC (Evolutionary Computation)

Manufacturing ◽  
2002 ◽  
Author(s):  
Hazim El-Mounayri ◽  
Zakir Dugla ◽  
Haiyan Deng
Keyword(s):  
Surface Roughness ◽  
Evolutionary Computation ◽  
End Milling ◽  
Milling Process ◽  
Depth Of Cut ◽  
Feed Speed ◽  
A New Technique ◽  
Experimental Values ◽  
Cutting Experiments ◽  
Good Agreement

A new technique from EC (Evolutionary Computation), PSO (Particle Swarm Optimization), is implemented to model the end milling process and predict the resulting surface roughness. Data collected from cutting experiments is used for model calibration and validation. The inputs to the model consist of Feed, Speed and Depth of cut while the output from the model is surface roughness. The model is validated through a comparison of the experimental values with their predicted counterparts. A good agreement is found. The proved technique opens the door for a new, simple and efficient approach that could be applied to the calibration of other empirical models of machining.

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.

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