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.

A Comprehensive Study on Surface Roughness in Machining of AISI D2 Hardened Steel

2012 ◽  
Vol 576 ◽  
pp. 60-63 ◽  
Author(s):  
N.A.H. Jasni ◽  
Mohd Amri Lajis
Keyword(s):  
Surface Roughness ◽  
High Speed ◽  
End Milling ◽  
Cutting Speed ◽  
Hardened Steel ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Radial Depth ◽  
Aisi D2 ◽  
Coated Carbide

Hard milling of hardened steel has wide application in mould and die industries. However, milling induced surface finish has received little attention. An experimental investigation is conducted to comprehensively characterize the surface roughness of AISI D2 hardened steel (58-62 HRC) in end milling operation using TiAlN/AlCrN multilayer coated carbide. Surface roughness (Ra) was examined at different cutting speed (v) and radial depth of cut (dr) while the measurement was taken in feed speed, Vf and cutting speed, Vc directions. The experimental results show that the milled surface is anisotropic in nature. Surface roughness values in feed speed direction do not appear to correspond to any definite pattern in relation to cutting speed, while it increases with radial depth-of-cut within the range 0.13-0.24 µm. In cutting speed direction, surface roughness value decreases in the high speed range, while it increases in the high radial depth of cut. Radial depth of cut is the most influencing parameter in surface roughness followed by cutting speed.

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.

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.

Study on Surface Roughness in Micro End Milling of Mold Material

2011 ◽  
Vol 325 ◽  
pp. 594-599 ◽  
Author(s):  
Hiroo Shizuka ◽  
Koichi Okuda ◽  
Masayuki Nunobiki ◽  
Yasuhito Inada
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Milling Process ◽  
Cutting Conditions ◽  
Mold Material ◽  
Depth Of Cut ◽  
Milling Operations ◽  
Radial Depth ◽  
Micro End Milling ◽  
End Milling Process

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.

scholarly journals Investigation on Effect of Material Hardness in High Speed CNC End Milling Process

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
N. V. Dhandapani ◽  
V. S. Thangarasu ◽  
G. Sureshkannan
Keyword(s):  
Surface Roughness ◽  
High Speed ◽  
Cutting Tool ◽  
End Milling ◽  
Removal Rate ◽  
Milling Process ◽  
Depth Of Cut ◽  
Study Results ◽  
Cnc End Milling ◽  
End Milling Process

This research paper analyzes the effects of material properties on surface roughness, material removal rate, and tool wear on high speed CNC end milling process with various ferrous and nonferrous materials. The challenge of material specific decision on the process parameters of spindle speed, feed rate, depth of cut, coolant flow rate, cutting tool material, and type of coating for the cutting tool for required quality and quantity of production is addressed. Generally, decision made by the operator on floor is based on suggested values of the tool manufacturer or by trial and error method. This paper describes effect of various parameters on the surface roughness characteristics of the precision machining part. The prediction method suggested is based on various experimental analysis of parameters in different compositions of input conditions which would benefit the industry on standardization of high speed CNC end milling processes. The results show a basis for selection of parameters to get better results of surface roughness values as predicted by the case study results.

Study on the Machined Surface Geometry Generated by Multi-Axis Ball End Milling Process

2013 ◽  
Vol 770 ◽  
pp. 370-375
Author(s):  
Xiao Xiao Chen ◽  
Jun Zhao ◽  
Yong Wang Dong ◽  
Shuai Liu ◽  
Jia Bang Zhao
Keyword(s):  
Surface Roughness ◽  
End Milling ◽  
Cutting Parameters ◽  
Peak Height ◽  
Milling Process ◽  
Depth Of Cut ◽  
Small Range ◽  
Surface Geometry ◽  
Machined Surface ◽  
Two Parameters

This paper investigated the surface generated by single factor experiment under multi-axis finish milling condition, and the effects of cutting parameters on surface textures, 2D and 3D surface topographies and surface roughness characteristics were analyzed. Surface features evaluation indicators of Ra, Rq, Rt, surface heights histogram, maximum valley depth and maximum peak height corresponding to various cutting parameters were presented and discussed. The machining marks are closely related with tool orientation angles. The orderly distributions of concave and convex patterns on the machined surface are produced by the special cutting orientation of the cutting edges. The feed per tooth, spindle speed, tilt angle, and lead angle apparently affect surface roughness, while depth of cut and radial width of cut have no obvious effects on the surface roughness when the two parameters values vary in a small range.

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.

scholarly journals Prediction of Surface Roughness in End Milling Process Using Intelligent Systems: A Comparative Study

2011 ◽  
Vol 2011 ◽  
pp. 1-18 ◽  
Author(s):  
Abdel Badie Sharkawy
Keyword(s):  
Surface Roughness ◽  
Prediction Accuracy ◽  
End Milling ◽  
Milling Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Validation Data ◽  
Genetic Tuning ◽  
Inference Systems ◽  
End Milling Process

A study is presented to model surface roughness in end milling process. Three types of intelligent networks have been considered. They are (i) radial basis function neural networks (RBFNs), (ii) adaptive neurofuzzy inference systems (ANFISs), and (iii) genetically evolved fuzzy inference systems (G-FISs). The machining parameters, namely, the spindle speed, feed rate, and depth of cut have been used as inputs to model the workpiece surface roughness. The goal is to get the best prediction accuracy. The procedure is illustrated using experimental data of end milling 6061 aluminum alloy. The three networks have been trained using experimental training data. After training, they have been examined using another set of data, that is, validation data. Results are compared with previously published results. It is concluded that ANFIS networks may suffer the local minima problem, and genetic tuning of fuzzy networks cannot insureperfectoptimality unless suitable parameter setting (population size, number of generations etc.) and tuning range for the FIS, parameters are used which can be hardly satisfied. It is shown that the RBFN model has the best performance (prediction accuracy) in this particular case.

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.

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