International Journal of Current Engineering and Technology E-ISSN 2277 – 4106, P-ISSN 2347 – 5161

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Research Article

To Determine the Effect of Machining Parameters for Surface Finish

using turning of Aluminium 6063
Sunil Kumar* and Deepak Gupta

Department of Mechanical Engineering, Galaxy Global Group of Institutions, Ambala, Haryana, India

Accepted 04 Aug 2016, Available online 05 Aug 2016, Vol.6, No.4 (Aug 2016)

Abstract

The basic operation required for the preparation of various components in various manufacturing industries is
turning and surface finish is very essential for the quality point of view. The surface finish of the components is an
essential demand of the customer using components. Therefore to optimization of the surface finish is primary
requirement so that the cost and the overall production will not be compromised. Thus in the research work the
surface finish at various machining parameters is optimized. The rotation speed, feed rate and the depth of cut are
considered as primary parameters affecting the surface finish. Some other factors affecting the surface finish are tool
material, tool type and cutting fluids etc. The parameter influence most are cutting speed, depth of cut , feed,
geometry of cutting tool like principle cutting edge angle ,rake angle, nose radius etc. For the optimization the
surface finish it is very necessary to decide the controlling parameters. In the process of turning operation the
different values of cutting parameters, cutting speed (165, 220,275,330), feed rate (.2, 0.3, 0.4, 0.5 mm/rev), depth of
cut (.5, 1, 1.5, 2 mm) are selected. It is concluded that surface finish is highly influenced by speed than feed rate than
depth of cut. Surface finish decreases with increase of speed. Surface finish is minimum at Minimum revolving speed.
Surface finish is minimum at minimum depth of cut.

Keywords: Taguchi Design, Ra Orthogonal Array, Turning, cutting speed, feed, Ra, Surface Finish.

Introduction Literature Review

1 Initiallythe lathe machine was invented by the two- Pradeep L. Menezes , Kishore , Satish V. Kailas et al.
person. Lathe machine was designed by the Egypt in (2006) carried out study of Influence of surface texture
about 1300 BC. Initially, there are only two things that on coefficient of friction and transfer layer formation
are achieved in this lathe machine tool. The first thing during sliding of pure magnesium pin on 080 M40
is the turning of the wood piece manually with the help (EN8) steel plate The conclusions based on the
of a rope; and the second cutting of shapes in the wood experimental results is that The amplitude of stick–slip
by use of a sharp cutting tool., But there have been motion predominately depends on plowing component
some modifications and improvements with time over of friction.
the first invented two-person lathe machine, and also In 2007, N.R. Dhar, M.T. Ahmed, S. Islam et al.
most importantly the production of the rotary motion. carried an Experimental investigation on effect of
Surface finish, also known as surface texture, is the minimum quantity lubrication in machining Aisi 1040
characteristics of a surface. It has three components: steel. They concluded that, the cutting performance of
lay, surface roughness, and waviness. Many factors MQL machining is better than that of dry machining.
contribute to the surface finish in manufacturing. In Rishu Gupta and Ashutosh Diwedi etal concluded that
forming processes, such as molding or metal forming, the analysis of the experimental observations
surface finish of the die determines the surface finish of highlights that MRR in CNC turning process is greatly
the work piece. In machining the interaction of the influenced by depth of cut followed by cutting speed. It
cutting edges and the microstructure of the material is observed that the feed is most significantly
being cut both contribute to the final surface finish. In influences the Ra followed by nose radius.
general, the cost of manufacturing a surface increases Dhruv H. GajjarandPROF. Jayesh V. Desai et al
as the surface finish improves. concluded that MRR decrease with increase of pulse off
time, while surface roughness reduces. During off time
*Corresponding author Sunil Kumar is a M.Tech Scholar and removed material flushed away. More the off time
Deepak Gupta is working as Assistant Professor better the flushing. Servo voltage has little effect on SR
1348| International Journal of Current Engineering and Technology, Vol.6, No.4 (Aug 2016)
Sunil Kumar et al To Determine the Effect of Machining Parameters for Surface Finish using turning of Aluminium 6063

and KERF width but it has more effect over MRR. 27. Then results of all experiment will give 100
Surface roughness reduces with increase of servo accurate results. In comparison to above method the
voltage. Taguchi orthogonal array make list of nine
Rajmohan T. et al have studied on optimization of experiments in a particular order which cover all
machining parameters in electrical discharge factors. Those nine experiments will give 99.96%
machining of 304 stainless steel. From this study, it is
accurate result.
found that different combination of EDM process
parameters is required to achieve higher MRR for 304 By using this method number of experiments
stainless steel. reduced to 16 instead of 27 with almost same accuracy.
P Vamsi Krishna,D N Rao, and R R Srikant (1984)
carried out study on Predictive modelling of surface Surface finish measurement
roughness and tool wear in solid lubricant assisted
turning of AISI 1040 steel. Results indicate that content The first step of analysis is to filter the raw data to
of solid lubricant in SAE oil and type of solid lubricant remove very high frequency data since it can often be
affect surface roughness and tool wear. attributed to vibrations or debris on the surface. Next,
the data is separated into roughness, waviness and
Methodology
form. This can be accomplished using reference lines,
The Taguchi method is a well-known technique that envelope methods, digital filters, fractals or other
provides a systematic and efficient methodology for techniques.
process optimization and this is a powerful tool for the
design of high quality systems. Taguchi approach to Material used
design of experiments in easy to adopt and apply for
users with limited knowledge of statistics, hence Aluminium Alloy (Aluminium 6063). AA 6063 is
gained wide popularity in the engineering and
Aluminium Alloy, having elements in the
scientific community. This is an engineering
methodology for obtaining product and process concentrations Al (97.5 %), Cr (0.1 %), Cu (0.1 %) and
condition, which are minimally sensitive to the various Fe(0.35%)
causes of variation, and which produce high-quality
products with low development and manufacturing Cutting tool used
costs. Signal to noise ratio and orthogonal array are
two major tools used in robust design.
The Cutting tool is high speed steel (tip only.) A tool
The S/N ratio characteristics can be divided into three bit is a non-rotary cutting tool used in lathes. Such
categories when the characteristic is continuous cutters are also often referred to by the set-phrase
name of single-point cutting tool as distinguished. The
1. Nominal is the best cutting edge is ground to suit a particular machining
2. Smaller the better operation and may be re-sharpened or reshaped as
3. Larger is better characteristics. needed. The ground tool bit is held rigidly by a tool
holder while it is cutting.
For the maximum material removal rate, the solution is
Larger is better and S/N ratio is determined according
to the following equation: Results and Analysis

S.N Speed Feed D.O.C Surface Finish

S/N = -10 *log(Σ(1/Y2)/n) 1. 165 0.2 0.5 2.2
2. 165 0.3 1 5.1
Where, S/N = Signal to Noise Ratio, 3. 165 0.4 1.5 2.71
4. 165 0.5 2 2.52
n = No. of Measurements, y = Measured Value
5. 220 0.2 1 1.66
6. 220 0.3 0.5 3.33
The influence of each control factor can be more clearly 7. 220 0.4 2 2.95
presented with response graphs. Optimal cutting 8. 220 0.5 1.5 3.31
conditions of control factors can be very easily 9. 275 0.2 1.5 5.32
determined from S/N response graphs, too. Parameters 10. 275 0.3 2 3.15
11. 275 0.4 0.5 2.49
design is the key step in Taguchi method to achieve
12. 275 0.5 1 4.14
reliable results without increasing the experimental 13. 330 0.2 2 4.55
costs. 14. 330 0.3 1.5 2.52
If there is an experiment having 3 factors which 15. 330 0.4 1 2.86
have three values, then total number of experiment is 16. 330 0.5 0.5 4.05
1349| International Journal of Current Engineering and Technology, Vol.6, No.4 (Aug 2016)
Sunil Kumar et al To Determine the Effect of Machining Parameters for Surface Finish using turning of Aluminium 6063

Table 2 Response Table for Signal to Noise Ratio

Level Speed Feed D.O.C

1 -9.422 -9.732 -9.343
2 -8.661 -10.649 -10.005
3 -11.187 -8.777 -10.401
4 -10.616 -10.728 -10.138
Delta 2.526 1.952 1.058
Rank 1 2 3

Conclusions

From all the above experiments, observations and

calculations, following conclusions has

 It is concluded that surface finish is highly

influenced by speed than feed rate than depth of
cut.
 Surface finish decreases with increase of speed.
 Surface finish decreases with increase of feed rate.
 Surface finish decreases with increase of depth of
cut.
 Surface finish is maximum at speed 220 rpm.
 Surface finish is maximum at feed rate 0.4
mm/min
Fig. 1 Effect of Process Parameters on Surface Finish  Surface finish is maxim at depth of cut 0.5 mm.
(S/N Data and Means)
Table 3 Optimal combination for Surface Finish
The surface finish of the material 6063 is initially
Physical Optimal Combination
increases as the speed of the job increases from 165
Speed Feed Rate Depth of Cut
rpm to 220 rpm. The surface finish shows a decreasing Requirements
(RPM) (mm/min) (mm)
trend as the speed increases from 220 rpm to 275 rpm. 220 0.4 0.5
Min. Surface Finish
And the surface finish increases as the speed increases Level-2 Level-3 Level-1
from 275 rpm to 330 rpm. The overall behavior may be
predicted as increasing. The trend is opposite in of the References
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is initially decreases as the feed rate of the job 2014), Optimization of Process Parameters Influencing
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Volume 2, Issue 4
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ArjunBiloria & Rupinder Singh (Oct -2014), Optimizing the
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Insert Nose Radius for Turning Operation on CNC Turning
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