This document summarizes a study analyzing CO2 arc welding parameters to maximize depth of penetration in AISI 1022 steel plates. Response Surface Methodology (RSM) was used to develop models relating welding current, voltage, wire feed rate, and gas pressure to depth of penetration. Central composite design was employed to conduct experiments, from which a quadratic RSM model was developed showing the relationships between parameters and depth of penetration with over 90% accuracy. Linear effects of voltage, wire feed rate, and gas pressure were found to significantly impact depth of penetration, while their interactions did not have significant effects.

1. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 6, November - December (2013) © IAEME
AND TECHNOLOGY (IJMET)
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 4, Issue 6, November - December (2013), pp. 31-36
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IJMET
©IAEME
ANALYSIS OF CO2 WELDING PARAMETERS ON THE DEPTH OF
PENETRATION OF AISI 1022 STEEL PLATES USING RESPONSE
SURFACE METHODOLOGY
Mr. Shukla B.A.(1),
Prof. Phafat N.G.(2)
(1)
Student, M.E. Manufacturing, Mechanical Engineering Department, J.N.E.C. Aurangabad,
Maharashtra, India.
(2)
Associate Professor, Mechanical Engineering Department, J.N.E.C Aurangabad, Maharashtra,
India.
ABSTRACT
This paper concentrates on the analysis of CO2 arc welding parameters to maximize the depth
of penetration using mathematical models based on Response Surface Methodology. Welding
current, welding voltage, wire feed rate and gas pressure were taken as input parameters while the
response was depth of penetration. Central Composite Design (CCD) was used for the experimental
design. RSM based model has been developed to determine the depth of penetration attained by
various welding parameters. The quadratic models developed using RSM shows high accuracy and
can be used for prediction within the limits of the factors investigated.
Keywords: CO2 arc welding, Depth of Penetration, AISI 1022, Response Surface Method.
1. INTRODUCTION
Welding is an important manufacturing process which can join similar and dissimilar metals
of different size and shapes. CO2 arc welding is the process which is widely used in automobile,
aerospace/aircraft, heavy industrial manufacturing industries etc.
For welded joints to retain longer life with high strength, depth of penetration plays an
important role. The depth of penetration is the major response measured in all types of welding
because if the penetration of the molten metal is not up to the mark, there will be occurrence of
cavity which reduces the endurance of a component and the component eventually fails before the
time of its duration. This causes a loss in terms of time, rejection of components and finally money
loss.
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2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 6, November - December (2013) © IAEME
Due to all these problems the depth of penetration should be maintained at proper level
during the welding operation. Most of the research work on the depth of penetration maximization
focused on the optimization of parameters of welding operation for various metals and alloys.
S.W. Campbell et al [1] performed ANN prediction of weld geometry using gas metal arc
welding (GMAW) with alternate shielding gases. S.V. Sapakal and M.T. Telsang [2] has performed
the parametric optimization of MIG welding using Taguchi design method. N.B. Mostafa and M.N.
Khajavi [3] conducted an experiment on Flux cored arc welding (FCAW) with the help of sequential
quadratic programming (SQP) to maximize the weld penetration. Vinod Kumar [4] had performed
modeling of weld bead geometry and shape relationships using RSM technique. As depth of
penetration is a very complicated phenomenon affected by many parameters such as current, voltage,
gas pressure etc. Therefore, it is imperative to develop a reliable model that predicts the weld
penetration to reduce the cost of welding. The important process parameters are determined based on
the previous literature survey. An Response Surface Method (RSM) model is developed that predicts
depth of penetration. RSM is selected because of its capability to learn and simplify from examples
and adjust to changing conditions.
2. RESPONSE SURFACE METHODOLOGY
Response Surface Methodology is one of the optimization techniques in describing the
performance of the welding process and finding the optimum setting of parameters. RSM is a
mathematical-statistical method that used for modeling and predicting the response of interest
affected by some input variables to optimize the response [5].
RSM also specifies the relationships among one or more measured responses and the
essential controllable input factors. When all independent variables are measurable, controllable and
continuous in the process, with negligible error, the response surface model is as follows [5]:
(1)
y= f(x1,x2,…xn)
where “n” is the number of independent variables.
To optimize the response “y”, it is necessary to find an appropriate approximation for the true
functional relationship between the independent variables and the response surface. Usually a
second-order polynomial Equation (2) is used in RSM.
k
k
j =1
j =1
k −1 k
y = β 0 + ∑ β j x j + ∑ β jj x 2 + ∑ ∑ β ij x i x j + ε
j
i
(2)
j
3. EXPERIMENTAL WORK
AISI 1022 steel plates of 100 (length)*90 (width)*6 (thickness) was used as work piece
material for square butt welding for the given study. AISI 1022 has lots of engineering applications
specially in manufacturing sector. AISI 1022 is used by all industry sectors for applications
involving welding plus lightly stressed carburised parts. Typical applications are General
Engineering Parts and Components, Welded Structures etc. Also Carburised components like
Camshafts, Light Duty Gears, Gudgon Pins, Ratchets, Spindles, Worm Gears etc. The chemical
composition of AISI 1022 is shown in Table 1.
C
Mn
0.206% 0.70%
Table 1. Chemical composition of AISI 1022 Steel
Cr
Ni
Mo
S
P
Si
0.02% 0.01% 0.01% 0.039% 0.050% 0.19%
32
Al
0.028%

3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 6, November - December (2013) © IAEME
In the present study four parameters namely welding current, welding voltage, wire feed rate
and gas pressure were considered. For the measurement of depth of penetration optical microscope
was used. A five level central composite design (CCD) was used to study linear, quadratic and two
factor interaction effect between the four process variable and one response (Table 2). The upper
limit of a factor was coded as +2 and the lower limit as -2, coded values for intermediate levels were
calculated from the following relationship:
Xi =
2[2 X − ( X max + X min )]
X max − X min
(3)
Where Xi is the required coded values of a variable X, X is any value of the variable from
Xmin to Xmax. Xmin is the lower level of the variable and Xmax is the upper level of the variable.
Sr. no
1.
2.
3.
4.
5.
Table 2. Factors and their levels
Current (A) Voltage(V)
Wire feed
rate(cm/min)
90
20
10.16
100
25
12.70
110
30
15.24
120
35
17.78
130
40
20.32
Levels
-2
-1
0
1
2
Gas pressure
(psi)
20
30
40
50
60
4. RESULTS AND DISCUSSIONS
For the depth of penetration regression Table 3. Shows the following.
Term
Constant
A
V
WF
GP
A*A
V*V
WF*WF
GP*GP
A*V
A*WF
A*GP
V*WF
V*GP
WF*GP
S = 0.214564
Table 3. Regression table for depth of penetration
Coef
SE Coef
T
6.13857
0.08110
75.694
-0.04722
0.04380
-1.078
-0.71450
0.04380
-16.314
0.48800
0.04380
11.142
0.14633
0.04380
3.341
0.07167
0.04012
1.786
0.07299
0.04012
1.819
0.03174
0.04012
0.791
0.11799
0.04012
2.941
0.01300
0.05364
0.242
0.00800
0.05364
0.149
-0.03575
0.05364
-0.666
-0.03175
0.05364
-0.592
0.00200
0.05364
0.037
-0.02800
0.05364
-0.522
R-Sq = 96.30%
R-Sq(pred) = 80.62%
33
R-Sq(adj) = 93.06%
P
0.000
0.297
0.000
0.000
0.004
0.093
0.088
0.440
0.010
0.812
0.883
0.515
0.562
0.971
0.609

4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 6, November - December (2013) © IAEME
•
•
•
Linear effects: The p-value of current is 0.297 and is greater than 0.05 hence, it has no
significant effect on depth of penetration. While the other parameters namely voltage, wire
feed rate and gas pressure have p-values 0.000, 0.000 and 0.004 which are less than 0.05
hence, these parameters have significant effect on the model and depth of penetration.
Squared effects: The p-value of the squared effect GP*GP = 0.01 is less than 0.05. Hence,
this squared effect has significant effect.
Interaction effect: All interaction effects are greater than 0.05. Therefore, there is no
significant effects of these interaction values on the depth of penetration.
For each term in the model there is a coefficient. Using these coefficients we have
construct equations, linear as well as quadratic representing the relationship between the response
and the factors.
DP = 6.37 - 0.0472 (A) - 0.714 V + 0.488 WF + 0.146 GP
(4)
DP =6.13857-0.04722(A)-0.71450(V)+0.488(WF)+0.14633(GP)+0.07167(A)2+0.07299(V)2+
0.03174(WF)2+0.11799(GP)2+0.013(A*V)+0.008(A*WF)-0.03575(A*GP)-0.03175(V*WF)
+0.002(V*GP)-0.028(WF*GP)
(5)
The actual experimental values and model predicted values of depth of penetration is shown in
Table 4. The values are in close proximity to each other and gives percentage error less than 7%.
run
order
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 4. Experimental design and RSM model adequacy check
Wire feed
Gas
Predicted
Current
Voltage
rate
pressure
value of
(A)
(V)
(cms/min)
(psi)
Actual DP
DP
110
30
20.32
40
7.01
7.342497
110
30
15.24
40
6.11
6.366497
120
35
17.78
50
6.11
6.239115
110
30
15.24
60
7.02
6.659164
110
30
15.24
40
6.11
6.366497
100
25
17.78
50
8.14
7.762546
110
40
15.24
40
5.12
4.937497
110
30
15.24
40
6
6.366497
110
30
15.24
40
6
6.366497
120
25
12.7
30
6.39
6.399449
120
25
17.78
50
7.7
7.668115
100
25
12.7
30
6.6
6.493879
110
30
15.24
40
6.3
6.366497
110
30
15.24
20
6.28
6.073831
110
30
15.24
40
6.28
6.366497
100
35
17.78
30
6.13
6.040879
120
35
17.78
30
6.25
5.946449
90
30
15.24
40
6.64
6.460928
120
35
12.7
30
4.8
4.970449
110
20
15.24
40
7.82
7.795497
34
% Error
4.74
4.198
2.11
5.14
4.198
4.64
3.7
6.1
6.1
0.147
0.455
1.6
1.05
3.28
1.37
1.45
4.856
2.7
3.551
0.31

5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 6, November - December (2013) © IAEME
21
22
23
24
25
26
27
28
29
30
31
100
110
110
100
100
120
100
120
130
120
100
35
30
30
35
25
25
35
25
30
35
25
12.7
15.24
10.16
12.7
17.78
17.78
17.78
12.7
15.24
12.7
12.7
50
40
40
30
30
30
50
50
40
50
50
5.3
6.17
5.6
5.02
7.36
7.74
6.322
6.6
6.289415
5.5
6.65
5.357546
6.366497
5.390497
5.064879
7.469879
7.375449
6.333546
6.692115
6.272066
5.263115
6.786546
1.08
3.18
3.741
0.876
1.49
4.7
0.182
1.395
0.27
4.3
1.6
5. CONCLUSION
This paper has investigated the process parameters of CO2 arc welding and their effects on
depth of penetration with the use of Response Surface Methodology in square butt welding of AISI
1022 steel plates. The paper effectively describes the linear, square and interaction effects on the
RSM based model. The conclusion of the present study were drawn as follows.
• RSM based models has been used to determine the depth of penetration attained by various
drilling parameters. The models developed using RSM were reasonably accurate and can be
used for prediction within the limits of factors investigated.
• From predicted values of RSM model and actual experimental values, the predicted and
measured values are quite close, which indicates that the developed model can be effectively
used to predict the depth of penetration. Also the highest percentage error noticed was 6.1%.
• The R2 value obtained in the regression table is 96.30% which itself is the evidence that the
developed model is good enough for predicting the depth of penetration. Also, higher the
value of R2 the better the model fits your data.
• Welding voltage and Wire feed rate was found to be the most significant factors for
maximizing the depth of penetration followed by gas pressure.
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[1]
[2]
[3]
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