On-Line Identification of End Milling Process Parameters

1989 ◽  
Vol 111 (4) ◽  
pp. 322-330 ◽  
Author(s):  
B. K. Fussell ◽  
K. Srinivasan

A method for on-line identification of process parameters relating the feedrate to the machining force in end milling operations is described here. Such on-line identification of changing process parameters is necessary for parameter adaptive force feedback control systems which use feedrate manipulation to maintain a specified cutting force in the presence of varying machining conditions. A simple model form for the complex process mechanics is preferred for the adaptive control application and is proposed here. Accurate low order models for the end milling process are obtained by using the measured feed drive velocity and the machining force as the input and output signals, respectively, and by choosing a sampling interval equal to the tooth delay period. An identification scheme based on the recursive minimization of the sum of the squares of the modeling error is used here, with special emphasis on techniques to keep the estimation scheme alert while avoiding oscillatory parameter estimates. The effectiveness of the proposed process model and estimation scheme under open loop conditions is confirmed by simulation and experimental tests involving changes in the axial and radial depths of cut and in the feedrate. The parameter estimates generated are accurate and responsive to the changing cutting conditions and are steady and accurate under constant cutting conditions because of the simplicity of the proposed model. The estimation scheme described here accommodates the effects of cutter runout, tilt, and interrupted cutting by the multiple flutes more readily and with less detriment to parameter estimates than other schemes reported in the literature. The effectiveness of the estimation scheme under closed loop conditions is also verified by simulation.

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

Author(s):  
M. Kishanth ◽  
P. Rajkamal ◽  
D. Karthikeyan ◽  
K. Anand

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.


2014 ◽  
Vol 592-594 ◽  
pp. 2733-2737 ◽  
Author(s):  
G. Harinath Gowd ◽  
K. Divya Theja ◽  
Peyyala Rayudu ◽  
M. Venugopal Goud ◽  
M .Subba Roa

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.


2008 ◽  
Vol 368-372 ◽  
pp. 947-950
Author(s):  
Si Young Beck ◽  
Bong Cheol Shin ◽  
Myeong Woo Cho ◽  
Eun Sang Lee ◽  
Dong Sam Park ◽  
...  

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.


2011 ◽  
Vol 325 ◽  
pp. 594-599 ◽  
Author(s):  
Hiroo Shizuka ◽  
Koichi Okuda ◽  
Masayuki Nunobiki ◽  
Yasuhito Inada

The effects of cutting conditions on the surface roughness in a micro-end-milling process of a mold material are described in this paper. Micro-end-milling operations were performed under different cutting conditions such as feed rate and depth of cut, in order to investigate the factors that had the greatest influence on the finished surface during micro-end-milling. It was revealed that the surface roughness begins to deteriorate when the radial depth of the cut exceeds the tool radius. In addition, it was found that this phenomenon is peculiar to micro-end-milling processes.


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