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STUDY ON TENSILE STRENGTH ON ARTIFICIALLY AGED AL-MG-SI ALLOY USING TAGUCHI’S TECHNIQUE

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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 10, Issue 01, January 2019, pp. 1312-1320, Article ID: IJMET_10_01_133
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=01
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication
Scopus Indexed
STUDY ON TENSILE STRENGTH ON
ARTIFICIALLY AGED AL-MG-SI ALLOY USING
TAGUCHI’S TECHNIQUE
Gowri Shankar M.C
Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology,
Manipal Academy of Higher Education, Manipal, Karnataka, India.
Y.M Shivaprakash*
Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology,
Manipal Academy of Higher Education, Manipal, Karnataka, India.
Jayashree P.K
Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology,
Manipal Academy of Higher Education, Manipal, Karnataka, India.
Gurumurthy B.M
Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology,
Manipal Academy of Higher Education, Manipal, Karnataka, India.
Sathyashankara Sharma
Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology,
Manipal Academy of Higher Education, Manipal, Karnataka, India.
*Corresponding Author
ABSTRACT
Al-Mg-Si alloy is most preferred material by scientists and engineers for seeking wide
range of industrial applications as its strength can be easily enhanced by cold working,
grain size refining, precipitation hardening and dispersion hardening. Demand for the
use of Al-Mg-Si alloy is growing rapidly because it has unique combination of properties,
which make it as one of the most versatile engineering materials. In the present study,
attempt has been made for systematic investigation on to know the implication of age
hardening parameters like, Solutionizing Time, Aging Temperature and Ageing Time on
tensile strength of Al-Mg-Si alloy using Taguchi’s Design of Experiments. A linear
regression model is used to predict the response. The derived results indicate that, the
aging temperature and time has imperative impact on the response whereas, solutionizing
time does not have a significant effect. For a definite group of parameters, the hardness
has enhanced from 154 to 210 MPa, leading to an increase in Ultimate Tensile Strength
by nearly 40%.
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Gowri Shankar M.C, Y.M Shivaprakash, Jayashree P.K, Gurumurthy B.M and Sathyashankara Sharma
Keywords: Al-Mg-Si alloy, Design of Experiments, Ultimate Tensile Strength (UTS),
Artificial aging
Cite this Article: Gowri Shankar M.C, Y.M Shivaprakash, Jayashree P.K, Gurumurthy
B.M and Sathyashankara Sharma, Study on Tensile Strength on Artificially Aged Al-MgSi Alloy Using Taguchi’s Technique, International Journal of Mechanical Engineering and
Technology, 10(01), 2019, pp.1312–1320
http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&Type=01
1. INTRODUCTION
The Age Hardening process consists of three main steps namely, Solution Treatment to bring
down segregation in the alloy, quenching to enable for a supersaturated solid solution and Aging
to bring about the formation of coherent precipitates that strengthen the alloy by restricting
dislocation movement. The strengthening of Al-Mg-Si alloys can be brought about by the very
minute secondary phase particles uniformly dispersed within the base matrix; this is achieved by
right heat treatment techniques [1-10]. The existence of majority of solutes like Mg and Si in the
6000 series alloy have led to a remarkable enhancement in strength due to precipitation hardening
[11-14]. Researches on precipitation sequence reveals that, the variation of the hardness versus
aging temperature and time can be associated to the transformation of phase taking place in the
aging treatment process. The superiority of mechanical properties by aging is due to the vacancy
assisted diffusion mechanism in under aged and peak aged conditions [15-18]. The appearance
of GP zones is dependent on the aging temperature, which distorts the lattice planes [19]. This
distortion of the lattice planes will hinder the movement of dislocations until there exists a
coherency in the lattice structure [20-22].
2. METHODOLOGY
2.1. Casting of Specimen
Commercially available Al-Mg-Si alloys are melted in a furnace at 800° C. After complete
melting, an appropriate amount of degasser hexachloroethane tablets are added followed by a
small amount of alkaline powder (to remove impurities forming slag). Mixing was done manually
to allow the gases to escape.
Figure 1: Mold prepared for pouring molten metal after casting
The permanent mold made of cast iron shown in Figure 1, is preheated in a separate furnace
at 600°C for 2 hr. The melt is poured into the preheated permanent mold and allowed to solidify.
Table 1 depicts the nominal composition weight percentage of Al-Mg-Si matrix material.
Table 1 Composition (Wt.%) OF Al-Mg-Si alloy
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Study on Tensile Strength on Artificially Aged Al-Mg-Si Alloy Using Taguchi’s Technique
Material
Si
Cu
Mg
Cr
Al
Wt %
0.60
0.20
0.99
0.25
Bal
0.15 –
0.80
0.04
Bal
0.40
– 1.20
– 0.35
(Cast)
Wt%
0.40
(Std.)
– 0.80
2.2. Artificial aging treatment
The tensile samples are prepared as per ASTM-E10 standards shown in figure 2. These test
specimens are subsequently age hardened by soaking at 550oC for 3 hr followed by sudden
quenching in water medium at ambient temperature. Further the solutionized specimens are
artificially aged in the furnace at 100°C, 150°C and 200°C for 5, 8 and 11hr, obtained during
hardness test to get peak hardness. Figure 3 shows the heat treatment cycle for Al 6061alloy.
3. EXPERIMENTAL DESIGN AND ANALYSIS
3.1. Experimental Design
Classical experimental design methodologies are cumbersome and difficult to use. Hence large
number of additional experiments needs to be conducted when number of parameters is large as
stated by Luo et al., [25]. In this study, the Taguchi method is useful to find optimal parameters
for maximum tensile strength. In the Taguchi method, process parameters, which effect the
product, can be categorized as factors like control and noise factors [23-24]. The former is helpful
to choose the best stability conditions in design, whereas the later represent all factors that brings
about deviation. In Taguchi method, characteristic data is acquired by the use of orthogonal
arrays, and to analyze the performance measure from the data to conclude on the optimal process
parameters. This approach uses a special design of orthogonal arrays to study the entire parameter
space with small number of experiments only. L9 orthogonal array is used with 3 factors and 3
levels. The analysis is made using MINITAB 16 software. The sequence of steps involved in the
age hardening of non-ferrous aluminum alloys consist of solutionizing, quenching and artificial
aging. In the above indicated steps, major process parameters taken into account for the analysis
are Solutionizing time (ts), Aging temperature (Ta) and Aging time (ta) at three levels are chosen
[26]. The factors and levels of experimentation is given in Table 2. The experimental design and
the average tensile strength values are depicted in Table 3.
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Gowri Shankar M.C, Y.M Shivaprakash, Jayashree P.K, Gurumurthy B.M and Sathyashankara Sharma
Figure 2: Sample prepared for Ultimate tensile strength test (ASTM-E10M)
Figure 3: Age hardening treatment cycle for Al 6061 alloy
Table 2 Factors and levels of experimentation
Symbol
A
B
C
Parameters
Solutionizing
Ageing
Ageing Time (h)
Level
1
1
100
5
Level
2
2
150
8
Level
3
3
200
11
Table 3 Experimental design and average measured ultimate tensile strength values
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Study on Tensile Strength on Artificially Aged Al-Mg-Si Alloy Using Taguchi’s Technique
Exp
.
No.
1
2
3
4
5
6
7
8
9
A
1
1
1
2
2
2
3
3
3
Factor
B
10
15
20
10
15
20
10
15
20
C
5
8
11
8
11
5
11
5
8
Ultimate
Tensile
strength
170
185
154
199
192
154
210
185
165
4. RESULTS AND DISCUSSION
In the current work, experiments are conducted for identifying the influence of process
parameters like ts, Ta and ta to maximize UTS. The main effect plots for UTS (larger is the
superior) is shown in figure 4. From the plot it is clear that the aging time and aging temperature
are the significant parameters that has highest influence on the UTS. Lower aging temperature
and higher aging duration results in higher UTS value, but higher aging temperature shows lower
UTS. Increase in temperature makes the aging rate also to increase because of the enhanced rate
of diffusion of solid atoms into the matrix. Solutionizing time found to be least contributing
process parameter to influence the UTS. This is due to the fact that in bare alloy, the effect of
solutionizing time is limited only to confirm complete solubility of β-phase in α-phase [27]. Also
it can be observed from the main effects plot, that solutionizing time of 2 hr, aging temperature
of 100ᴼ C and aging time of 10 hr are the optimum parameter combination to obtain maximum
UTS during age hardening of Al 6061 alloy as shown in figure 5. The measured UTS from
experiment and the predicted values from regression equation are given in Table 4.
From the ANOVA Table (Table 5) it can be noticed that the aging temperature has the highest
contribution (55.74%), followed by aging time (23.94%). Since the P value of solutionizing time
is grater then 0.05, which indicates that solutionizing time doesn’t have significant effect on the
UTS.
We take a measure of the model’s overall performance referred to as the coefficient of
determination and denoted by R2. In the model, R2 is obtained equal to 95.40% for UTS values.
This indicates that the age hardening process parameters explain 95.40% of variance in UTS. The
normal probability plot of the residuals is shown in figure 6. The predicted values are found to
be statistically similar to the actual measured values, based on the probability plot. A check on
the plot in figure 6 shown that the residuals generally fall on a straight line implying that the
errors are distributed normally. Table 4 clearly indicates that, the predicted value obtained from
regression equation is almost same as that of experimental observation. The fit obtained from
experimental UTS values and predicted values are found to be good. The % error between the
experimental results and the predicted values for UTS lie within 0.06 to 4.44. In the prediction of
UTS values the average absolute error for hardness is observed to be around 2.41%. ANOVA
essentially involves the partitioning total variation in an experiment into components ascribable
to the controlled factors and error. ANOVA applied to UTS values is done for a significance level
of α = 0.05, i.e., for a confidence level of 95%. The sources with P values below 0.05 are identified
to have statistically significant effect on the response.
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Gowri Shankar M.C, Y.M Shivaprakash, Jayashree P.K, Gurumurthy B.M and Sathyashankara Sharma
Figure 4: Main effect plot of UTS for the age hardening of Al 6061 alloy
Figure 5: Surface lot of UTS vs aging time and aging Temperature
Figure 6: Normal probability plot for UTS measurement.
Table 4 Regression data showing measured, predicted and residual values for the UTS.
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Study on Tensile Strength on Artificially Aged Al-Mg-Si Alloy Using Taguchi’s Technique
Exp
No.
1
2
3
4
5
6
7
8
9
Measured Predicted
UTS
UTS
(MPa)
(MPa)
170
172.71
185
185.04
154
155.37
199
200.04
192
193.61
154
156.82
210
210.41
185
186.2
165
166.53
Difference
% Error
2.71
4.44
0.04
0.06
1.37
2.32
1.94
2.73
1.61
2.33
2.82
4.78
0.41
0.55
1.2
1.94
1.53
2.55
Average error = 2.41
The regression equation for UTS is,
BHN= 67.0 + 2.17 * Solutionizing Time (A)-0.0967*Aging Temperature (B) + 1.06*Aging
Time (C)
Table 5 Analysis of variance for UTS values
Source
D
F
Seq
SS
Adj
SS
Adj
MS
F
P
%Contrib
ution
Rank
2
48.222
48.22
24.11
16.69
0.057
19.17
3
Solutionizing Time
(A)
Aging Temperature
(B)
Aging Time (C)
2
140.22
140.2
70.11
48.54
0.020
55.74
1
2
60.222
60.22
30.11
20.85
0.046
23.94
2
Residual Error
Total
2
8
2.889
251.55
2.889
1.444
R2
95.40%
5. CONCLUSION
On the basis of results of experiments, the following points are concluded• The experimental results indicate that the aging temperature has the highest influence
on the UTS followed by the aging time.
• Present study shows that maximum UTS is achieved at aging temperature of 100ᴼC,
aging time of 10 hr and solutionizing time of 2 hr.
• It is also observed that UTS decreases with increase in aging temperature due to
enhanced rate of diffusion. From the experiments it is also inferred that solutionizing
time has very less influence on the UTS.
• The analysis of study demonstrates that there is a close match among the experimental
and the predicted values of the UTS.
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Gowri Shankar M.C, Y.M Shivaprakash, Jayashree P.K, Gurumurthy B.M and Sathyashankara Sharma
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