OPTIMIZATION OF PARAMETERS FOR GAS METAL ARC

WELDING OF MILD STEEL USING TAGUCHI’S

TECHNIQUE
Monika1 Jagdip Chauhan2
1
M.Tech Student, 2 Assistant Professor
1,2
Department of Mechanical Engineering
1,2
Guru Jambheshwar University of science and Technology Hisar

Abstract find applications in the manufacture of many

Welding is a process that joining the similar products around us name few ships, rail road
and non-similar metals by the application of equipments, launch vehicles, boilers, nuclear
coalescence. Modern welding techniques are power plants, building construction, pipelines,
used to ensure the optimum production. This aircrafts, automobiles etc. Various welding
research paper represents the optimization of methods available are: Tungsten Inert Gas (TIG)
welding input process parameters for Welding, Metal inert gas (MIG) welding,
obtaining greater weld strength in the Gas Shielded Metal Arc Welding (SMAW), Plasma
Metal Arc Welding (GMAW) of Mild Steel Arc Welding (PAW), Flux Cored Arc Welding
(1018) is presented. The Taguchi method is (FCAW), Submerged Arc Welding (SAW), Gas
used to analyze the effect of welding process Metal Arc Welding (GMAW), Electro Slag
parameter on the weld strength, and Welding (ESW) and Oxyacetylene (OA)
considered process parameters are optimized Welding [22].
to achieve greater weld strength. L9 Welding processes play an important role in
Orthogonal array was selected for analysis of metal fabrication industries. There are various
data. From the investigation of research paper welding techniques, but the most commonly used
we found that the influence of Current, types are tungsten inert gas (TIG) and metal inert
Voltage & Gas Flow Rate on Tensile Strength, gas (MIG/MAG) welding process. In the TIG
Hardness of Weld Zone & Heat Affected Zone welding process a non-consumable electrode is
during welding process was validated by used but in case of MIG welding a consumable
ANOVA using Minitab Software for each wire is used to joining the metal. A metal inert
response were developed. Experimental gas (MIG) welding process consists of AC motor
results are provided to represent the proposed for heating, electrode for melting, water tube for
approach. From the investigation found that cooling and solidification of parent metals and a
when increases the current, voltage and GFR filler material in localized fusion zone by a
tensile strength decreases but in case of transient heat source to form a joint between the
hardness, the value of hardness increases due parent metals. MIG welding parameters are the
to high input rate. most important factors affecting the quality,
Keywords: GMAW, Taguchi method, Tensile productivity and cost of welded joint. Factors
strength and Hardness of the welded zone & such as arc current, arc voltage and welding
Hardness of Heat affected zone. speed and their interactions play a significant role
in the welding process.[24]
I. INTRODUCTION All commercially important metals such as
Welding is a process of joining two materials. It stainless steel, aluminium, carbon steels, high
is a faster process and more economical strength low alloy steel, nickel alloys, copper and
compared to both casting and riveting. Welding titanium, can be welded in all positions with

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GMAW process by choosing appropriate Table 1: Chemical Composition of Base

shielding gas, electrode, and welding variable. Metal- MS 1018
The process is illustrated in Figure 1: C Mn P S Fe
0.18% (0.6- 0.04% 0.05% (98.81-
0.9)% max max 99.26)%

Table 2: Chemical Composition of Electrode-

ER 70 S6

Mn

Mb
Cu

Cr

Fe
Si
C

V
P

S
(0.06-0.15)%

(1.40-1.85)%

0.025 % max

0.035% max

0.15% max
(0.8-0.15)%

0.50% max

0.03% max

0.15% max
Figure 1: MIG welding Process [27]

Balance
II. DESIGN OF EXPERIMENT
The Design of experiment is one of the important
and powerful statistical techniques to study the
effect of multiple variables simultaneously and IV. SIGNAL TO NOISE RATIOS (S/N) FOR
involves a series of steps which must follow a TAGUCHI TECHNIQUES:
certain sequence for the experiment to yield and Noise factors are uncontrollable factors whose
improved understanding of process performance. influences are not known. The ideal product will
In the designed experiments require a certain only respond to the operator’s signals and will be
number of combinations of factors and levels be unaffected by random noise factors. Therefore,
tested in order to observe the results of those test the goal of our quality improvement effort can be
conditions. In the Taguchi approach relies on the stated as attempting to maximize the s/n ratio for
assignment of factors in specific orthogonal the respective product. Taguchi developed a
arrays to determine test combinations. The DOE formulation which is a ratio of controllable
process is made up of three main phases: the factors (signal factors) to uncontrollable factors
conducting phase, the planning phase and the (noise factors). Signal to noise ratio based on
analysis phase. The DOE process is the variance is independent of target value and is
determination of the combination of factors and consistent with Taguchi’s quality objective.
levels which will provide the desired information 1) Larger the better:
[21, 24] n = -10 Log10 [mean of sum of squares
Analysis of the experimental results uses a signal of reciprocal of measured data]
to noise ratio to aid in the determination of the S
best process designs. In the present work, a plan N = -10log (MSD
order for performing the experiments was Where, MSD ∑ 1/Y )
generated by Taguchi method using orthogonal 2) Smaller the better:
array and analysis of parameters was done using n = -10 Log10 [mean of sum of squares
ANOVA technique. This method yields the rank of measured data]
of various parameters with the levels of
S
significance or influence of a factor on a N = -10log (MSD
particular output response.[25]
Where, MSD ∑ Y
III. MATERIAL SELECTION 3) Nominal the best:
Mild Steel 1018 and ER 70 S6 are selected as a n = 10 Log10 [square of mean
base metal and electrode or filler metal /variance]
respectively for performing the experimental S
= 10log (MSD
work. The composition of base metal and the N
electrode are given below in table 1 or table 2: Where, MSD ∑ Y
s
Where, MSD= mean square deviation (which
presents the average of squares of all deviations

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from the target value rather than around the VI. RESULT & DISCUSSION
average value). The aim of the experimental plan is to find the
R = Number of repetitions optimize parameters those are influencing the
Y = Measured data Tensile Strength, Hardness of Welded Zone &
Y= Mean of measured data Heat Affected Zone of the weldment. The
S= Variance experiments were developed based on an
orthogonal array, with the aim of relating the
V. EXPERIMENTATION influence of Welding Current, Voltage and Gas
5.1 Selection of process parameters & their Flow Rate. These design parameters are distinct
levels: and intrinsic feature of the process that influence
In the present study, three 3-level process and determine the composite performance.
parameters i.e. Current, Voltage and Gas Flow
Rate are considered. The values of the welding 6.1 Taguchi analysis for tensile strength
process parameters are shown in Table 3.The The results of tensile strength on different set of
ranges and levels are fixed based on the screening combination of parameters are shown in the table
experiments. The interaction effect between the 5. On the basis of these results, the S/N ratio has
parameters is not considered. The total degrees of been calculated separately for every single no. of
freedom of all process parameters are 8. The experiments with the help of Minitab software.
degrees of freedom of the orthogonal array
should be greater than or at least equal to the Table 5: Tensile Strength Readings & S/N
degrees of freedom of all the process parameters. ratio
Hence, L9 (33) Orthogonal array was chosen Tensi
which has 8 degrees of freedom. S.
Curr Volt Gas le
Table 3: Selected Process Parameters and ent age Flow Stren
no. S/N Ratio
their Levels (Amp (Vol Rate gth
) t) (lpm) (MPa
Parameters Code Level Level Level
)
1 2 3
1 250 30 20 355 51.0046
Welding A 250 300 350 2 250 35 25 372 51.4109
Current (Amp)
3 250 40 30 385 51.7092
Arc B 30 35 40
Voltage(volt) 4 300 30 25 372 51.4109
Gas Flow Rate C 20 25 30 5 300 35 30 378 51.5498
(kg/hr)
6 300 40 20 395 51.9319
Nine Experiments are conducted based on the
7 350 30 30 360 51.1261
orthogonal array, instead of 27
possibilities. 8 350 35 20 369 51.3405
Table 4: Orthogonal array after assignment 9 350 40 25 392 51.8657
of Parameters
6.1.1 Response Tables for Tensile Strength:
Voltage GFR Larger is better
Run Current (volt) (kg/hr) Table 6: Response Table for S/N Ratio of
(Amp) Tensile Strength
1 250 30 20 Level Current Voltage Gas Flow
2 250 35 25 Rate
3 250 40 30 1 51.37 51.18 51.43
4 300 30 25 2 51.63 51.43 51.56
5 300 35 30 3 51.44 51.84 51.46
6 300 40 20 Delta 0.26 0.66 0.14
7 350 30 30 Rank 2 1 3
8 350 35 20
The response tables shows the average of each
9 350 40 25 response characteristic (S/N ratios, means) for
each level of each factor.

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The table includes ranks based on delta statistics, relative importance of each factor, the factor
which compare the relative magnitude of effects. with the biggest sum of squares has the greatest
The delta statistic is the highest minus the lowest impact. These results mirror the factor ranks in
average for each factor. Minitab assigns ranks the response tables.
based on delta values; rank 1 to the highest delta The analysis of variance was carried out at 95%
value, rank 2 to the second highest, and so on. confidence level for the experiments. The main
Use the level averages in the response tables to purpose of analysis of variance is to investigate
determine which level of each factor provides the influence of the design parameters on Tensile
the best result. strength by indicating that which parameters is
significantly affected the quality characteristics.
Main Effects Plot for SN ratios
Data Means In the experimentation work, for S/N ratios of
Current voltage
tensile strength, voltage (p=0.001) is the most
51.8 significant parameter because its p-value is less
51.6
than 0.05.
51.4
M e a n o f S N r a t io s

6.1.3 Percentage Contribution of Parameters

51.2
for S/N Ratios of Tensile Strength:
250 300 350 30 35 40
gas flow rate TENSILE STRENGTH
51.8
0%
3.81% 13.3% Current (13.3
51.6
%)
51.4 Voltage
51.2
(82.82 %)
20 25 30
Gas flow rate
. 82.82% (3.81%)
Signal-to-noise: Larger is better
Error (0.07
Figure 2: Main effects plot for S/N Ratios of %)
tensile strength
Figure 3: Pie Chart for %age Contribution of
In the experimental analysis, the ranks indicate Different Parameters for S/N Ratios of Tensile
that voltage has the greatest influence on the S/N Strength.
ratio followed by current and gas flow rate. In
Taguchi’s experiment, the S/N ratio must be The purpose of ANOVA is to investigate which
maximized. The level averages in the response welding process parameters significantly affect
tables shows that the S/N ratios and the means the quality characteristics. This is accomplished
were maximized when the voltage was 40Volts, by separating the total variability of the Signal to
current was 300Amp and gas flow rate was 25 Noise Ratios, which is measured by the sum of
lpm. So these are the optimum welding squared deviations from the total mean of the
parameters on which the highest tensile strength Signal to noise ratio, into contributions by each
is obtained. welding process parameter and the error.
The percentage contribution by each of the
6.1.2 Analysis of Variance for S/N ratios welding process parameters in the total sum of
(Tensile Strength): the squared deviations was used to evaluate the
Each linear model analysis provides the importance of the process parameters change on
coefficients for each factor at the low level, their the quality characteristic. Fig 3 shows that
p-values and an analysis of variance table. Use voltage has the greatest effect on tensile strength
the results to determine whether the factors are with contribution of 82.82% followed by current
significantly related to the response data and with contribution of 13.30% and gas flow rate
each factor's relative importance in the model. with contribution of 3.81%.
The order of the coefficients by absolute value
indicates the relative importance of each factor 6.2 Taguchi Analysis for Hardness of Welded
to the response, the factor with the biggest Zone:
coefficient has the greatest impact. The The results for hardness of welded zone on
sequential and adjusted sums of squares in the different set of combination of parameters are
analysis of variance table also indicate the shown in the table 7. On the basis of these results,

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the S/N ratio has been calculated separately for

every single no. of experiments with the help of Main Effects Plot for SN ratios
minitab software 15. Data Means
current voltage
45.00
Table 7: Hardness of Welded Zone Readings 44.85
& S/N ratio 44.70

Gas

M e a n o f S N r a t io s
44.55
S. Curr Volt 44.40
Flow Hardne
n ent age S/N
Rate ss of 250 300 350 30 35 40
o. (Am (Volt Ratio gas flow rate
(lpm welded 45.00
p) )
) zone 44.85
44.70
1 250 30 20 158.83 44.0187 44.55
2 250 35 25 166.33 44.4194 44.40

3 250 40 30 170.00 44.6090 20 25 30

Signal-to-noise: Nominal is best
4 300 30 25 163.50 44.2704
5 300 35 30 177.33 44.9756 Figure 4: Graph for S/N ratio of Hardness of
6 300 40 20 177.00 44.9595 Welded Zone
7 350 30 30 171.33 44.6767
8 350 35 20 181.00 45.1536 In the experimental analysis, the ranks indicate
9 350 40 25 183.73 45.2836 that current has the greatest influence on both the
S/N ratio and the mean followed by voltage and
6.2.1 Response Tables for Hardness of gas flow rate. In Taguchi’s experiments, the S/N
Welded Zone: Nominal is best ratio must be maximized. The level averages in
Table 8: Response Table for S/N Ratio the response tables shows that the S/N ratios and
(Hardness) the means were maximized when the current was
Level Current Voltage Gas 350Amp, voltage was 40Volts and gas flow rate
Flow was 30 lpm. So these are the optimum welding
Rate parameters for hardness of welded zone.
1 44.35 44.32 44.71
6.2.2 Analysis of Variance for Hardness of
2 44.74 44.85 44.66 Welded Zone:
3 45.04 44.95 44.75 Each linear model analysis provides the
coefficients for each factor at the low level, their
Delta 0.69 0.63 0.10 p-values and an analysis of variance table. Use
Rank 1 2 3 the results to determine whether the factors are
significantly related to the response data and each
The response table 8. shows the average of each factor's relative importance in the model.
response characteristic (S/N ratios, means) for The analysis of variance was carried out at 95%
each level of each factor. The tables include confidence level. In the experimentation work,
ranks based on Delta statistics, which compare for S/N ratios of hardness of welded zone, current
the relative magnitude of effects. The Delta (p=0.017) and voltage (p=0.018) are the
statistic is the highest minus the lowest average significant parameters because their p-values are
for each factor. Minitab assigns ranks based on less than 0.05.
delta values; rank 1 to the highest delta value,
rank 2 to the second highest, and so on. Use the 6.2.3 Percentage Contribution of Parameters
level averages in the response tables to determine for S/N Ratios of Hardness of Welded Zone:
which level of each factor provides the best result. The purpose of ANOVA is to investigate which
welding process parameters significantly affect
the quality characteristics. This is accomplished
by separating the total variability of the Signal to
noise Ratios, which is measured by the sum of
squared deviations from the total mean of the
Signal to noise ratio, into contributions by each

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welding process parameter and the error. The 6.3.1 Response Tables for Hardness of Heat
percentage contribution by each of the welding Affected Zone: Nominal is best
process parameters in the total sum of the squared Table 10: Response Table for S/ N Ratio of
deviations was used to evaluate the importance Hardness of Heat Affected Zone
of the process parameter change on the quality
characteristic. Level Current Voltage Gas
WELD ZONE HARDNESS
Flow
Rate
1% 1% 1 45.46 45.61 45.59
Current
(50.18 %) 2 45.87 45.70 45.73
Voltage 3 45.97 45.99 45.98
(47.98 %)
Gas flow rate Delta 0.51 0.38 0.39
48% 50%
(0.97%) Rank 1 3 2
Error (0.87 The response table:10 show the average of each
%)
response characteristic (S/N ratios, means) for
each level of each factor. The tables include
Figure 5: Pie Chart for %age Contribution of ranks based on Delta statistics, which compare
Different Parameters for S/N Ratios of Hardness the relative magnitude of effects.
of Welded Zone
Main Effects Plot for SN ratios
Fig 5: shows that current has the greatest effect Data Means
on Hardness of Welded Zone with contribution current voltage
of 50.18% followed by voltage with contribution 46.0

of 47.98% and gas flow rate with contribution of 45.8

0.97% 45.6
M e a n o f S N r a t io s

45.4
6.3 Taguchi Analysis for Hardness of Heat 250 300 350 30 35 40
gas flow rate
Affected Zone (HAZ): 46.0

The results for Hardness of Heat Affected Zone 45.8

on different set of combination of parameters are
shown in the table 9. On the basis of these results, 45.6

the S/N ratio has been calculated separately for 45.4

20 25 30
every single no. of experiments with the help of Signal-to-noise: Nominal is best
minitab software 15.
Table 9: Hardness of Heat Affected Zone Figure 6: Graph for S/N ratio of Hardness of Heat
Readings & S/N ratio Affected Zone
The Delta statistic is the highest minus the lowest
Gas Hard average for each factor. Minitab assigns ranks
S. based on delta values; rank 1 to the highest delta
Curre Volta Flow ness of
n S/N value, rank 2 to the second highest, and so on.
nt ge Rate heat
o. Ratio Use the level averages in the response tables to
(Amp) (Volt) (lpm affect
) ed determine which level of each factor provides the
zone best result.
1 250 30 20 181.33 45.1694 In the experimental analysis, the ranks indicate
2 250 35 25 186.00 45.3903 that current has the greatest influence on both the
3 250 40 30 195.66 45.8300 S/N ratio and the mean followed by gas flow rate
4 300 30 25 191.00 45.6207 and voltage. In Taguchi’s experiments, the S/N
5 300 35 30 200.83 46.0566 ratio must be maximized. The level averages in
6 300 40 20 198.16 45.9403 the response tables shows that the S/N ratios and
7 350 30 30 200.66 46.0492 the means were maximized when the current was
8 350 35 20 192.00 45.6660 350Amp, voltage was 40Volts and gas flow rate
9 350 40 25 203.83 45.1854 was 30 lpm. So these are the optimum welding
parameters for hardness of heat affected zone.

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6.3.2 Analysis of Variance for S/N Ratio process was applied using a specific set of
(Hardness of Heat Affected Zone): controllable parameters Voltage, Current, Gas
Each linear model analysis provides the Flow rate for the response variables of Tensile
coefficients for each factor at the low level, their Strength. L9 orthogonal array, S/N ratio and
p-values and an analysis of variance table. Use analysis of variance were used for this study. The
the results to determine whether the factors are study found that the control factors had varying
significantly related to the response data and each effects on the response variables.
factor's relative importance in the model. From the experimental results of research work
The analysis of variance was carried out at 95% we concluded the following results:
confidence level. In the experimentation work, (1) Taguchi’s experimental design provides a
for S/N ratios of hardness of heat affected zone, simple, systematic and efficient methodology for
current (p=0.039) is the most significant the optimization of the GMAW parameters.
parameter because its p-value is less than 0.05. (2) Optimum parameters for Tensile Strength are

6.3.3 Percentage Contribution of Parameters Voltage Level 3 40 Volts

for S/N Ratios of Hardness of HAZ: Current Level 2 300 Amp
The purpose of ANOVA is to investigate which
welding process parameters significantly affect Gas Flow Level 2 25 Imp
the quality characteristics. This is accomplished Rate
by separating the total variability of the Signal to
noise Ratios, which is measured by the sum of (3) For S/N Ratios of Tensile Strength, voltage
squared deviations from the total mean of the has the greatest effect with contribution of 82.82%
Signal to noise ratio, into contributions by each followed by current with 13.30% and gas flow
welding process parameter and the error. The rate with 3.81%.
percentage contribution by each of the welding (4) Optimum parameters for Hardness of
process parameters in the total sum of the squared Welded Zone are
deviations was used to evaluate the importance Voltage Level 3 40 Volts
of the process parameter change on the quality
characteristic. Current Level 3 350 Amp
Fig 7. Shows that current has the greatest effect Gas Flow Level 3 30 Imp
on Hardness of Heat Affected Zone with Rate
contribution of 47.61% followed by gas flow rate
with contribution of 25.45% and voltage with (5) For S/N Ratios of Hardness of Welded Zone,
contribution of 25.00%. current has the greatest effect with contribution
of 50.18% followed by voltage with 47.98% and
HEAT AFFECTED ZONE gas flow rate with 0.97%
2% HARDNESS (6) Optimum parameters for Hardness of Heat
Current Affected Zone are:
(47.61 %)
Voltage (25 Voltage Level 3 40 Volts
25% %)
48%
Current Level 3 350 Amp
Gas flow rate
25% (25.45%) Gas Flow Level 3 30 Imp
Error (1.94 Rate
%)
(7) For S/N Ratios of Hardness of Heat
Figure7: Pie Chart for %age Contribution of Affected Zone, current has the greatest effect
Different Parameters for S/N Ratios of Hardness with contribution of 47.61% followed by gas
of Heat Affected Zone flow rate with contribution of 25.45% and
voltage with contribution of 25.00%
VII. CONCLUSION
This study presented the optimization of Gas VIII. SCOPE FOR FUTURE WORK
Metal Arc Welding parameters of Mild steel This study presented an efficient method for
1018 by Taguchi’s experimental design. The determining the optimal Gas Metal Arc welding

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parameters for increasing weld ability of Mild "Parametric Optimization of Gas metal
steel 1018 under varying conditions through the arc welding process by using Taguchi
use of the Taguchi’s experimental design. The method on stainless steel AISI 410".
controllable parameters were current, voltage IJRMEET, Vol. 3, Issue 1,pp. 1-9
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ISSN (PRINT): 2393-8374, (ONLINE): 2394-0697, VOLUME-4, ISSUE-8, 2017

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