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Materials Today: Proceedings 5 (2018) 12384–12393 www.materialstoday.com/proceedings

ICMMM - 2017

Study Of Parametric Effects On Mechanical Properties Of Stainless

Steel (AISI 304) And Medium Carbon Steel (45C8) Welded Joint
Using GMAW
Amit Ratan Biswasa, Sadananda Chakrabortya*, Partha Sarathi Ghosha, Dipankar Bosea
a
Mechanical Engineering Department, National Institute of Technical Teachers’ Training & Research, Kolkata, India

Abstract
Gas Metal Arc Welding (GMAW) is widely used for welding of carbon steel, silicon steel, low alloy steel, stainless steel, Al, Mg,
Cu, Ni, Ti and their alloys. Welded surfaces produced are smooth, neat, clean and spatter free which require no further cleaning
so reduces total welding cost. Because of the numerous applications of dissimilar metal welded joints, engineers and researchers
are opting for dissimilar metal welding to create new structures or parts. Welding of dissimilar metals has more challenging task
because the weld ability of dissimilar metals depends on many factors. It is difficult to join two different metals having different
chemical, physical and metallurgical properties. A dissimilar metal weld zone contains a weld deposit with a chemical
composition that differs by several percent from the composition of the two base metals that have been welded together. In the
present study the aim is to weld stainless steel AISI 304 and medium carbon steel 45C8 using GMAW. Yield strength, ultimate
tensile strength, weld zone hardness, weld bead thickness and reinforcement of the welded joint have been reported. The
variables used are welding current, voltage, speed and gas flow rate. Taguchi’s Method has been employed for design of
experiment. Based on ANOVA and S/N ratio analysis, the process parameter which significantly affects the responses is welding
current. In the welded zone, the hardness decreases with increasing welding current. It has been observed that with the increase of
welding current, weld bead thickness increases and reinforcement decreases. Microstructures of the base metals, both HAZs and
weld zone have been investigated. Grain structure changes from base metal to HAZ and HAZ to welded zone. Grain size
becomes more compact in welded zone.
© 2017 Elsevier Ltd. All rights reserved.
Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).

Keywords: GMAW; HAZ; ANOVA; Taguchi Method; Grain Analysis;

1 Introduction
Welding is a permanent joining of similar or dissimilar metals with the application of heat, with or without the
application of pressure and with or without the use of filler metal. It is difficult to join dissimilar materials than

*
Corresponding author. Tel.:9088498582
E-mail address: sadananda116@gmail.com

2214-7853 © 2017 Elsevier Ltd. All rights reserved.

Selection and/or Peer-review under responsibility of International Conference on Materials Manufacturing and Modelling (ICMMM - 2017).
 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393 12385

Nomenclature

GMAW Gas Metal Arc Welding

YS Yield Stress
UTS Ultimate Tensile Strength
ANOVA Analysis of Variance
A Welding Current
B Welding Voltage
C Welding Speed
D Gas Flow Rate

joining the same materials or alloys with minor differences in composition, however many dissimilar materials can
be joined successfully with the appropriate joining process. Joining different metals is to compose different
properties of metals in order to minimize material costs and at the same time maximize the performance of the
equipment and machinery. Improving the ability to join dissimilar materials with engineered properties are enabling
new approaches to light-weighting automotive structures, improving methods for energy production, creating next
generation medical products and consumer devices, and many other manufacturing and industrial uses. Most of the
dissimilar metal joining research during 1970’s were associated with metallic systems most commonly used in
industry including carbon and low alloy steels, stainless steel, nickel, copper and aluminum alloys. Research on
dissimilar metal joining involved titanium alloys, polymers, composites started in 1980. Increased use of these
materials for engineering applications is growing because of special performance requirements for corrosion
resistance, high strength, high temperature strength etc.
On the basis of previous available research works it is revealed that numerous investigations have been carried
out on the dissimilar metal joining by different welding processes [3-5, 7-9]. At present GMAW is a dominant and
most preferred fastening process in almost all industries. Despite having a sixty years history, research and
development still continue to provide improvements with high quality results. The worldwide popularity of MIG
welding is mainly due to its ability to join a wide range of material type and thicknesses in almost all positions with
high deposition rate, excellent weld bead appearance, low heat input and minimum post weld clean-up [5]. Due to
the world wide popularity and ability to weld a wide variety of material types, GMAW welding process has been
selected for the present investigation. From different literature survey it is revealed that different metals such as
stainless steel, mild steel, carbon steel, alloy steels can be joined together using proper welding process. It also
showed that researchers considered different control factors to study different responses [1, 12]. Significant number
of papers have been found on stainless steel and mild steel dissimilar welding, but mostly researchers considered one
response variable either hardness or tensile strength etc. to compare the mechanical properties of dissimilar joints [2,
3]. Again, researchers have shown interest on joining of stainless steel with carbon steel. But problem with carbon
steel is that pre heat is necessary to weld with stainless steel otherwise cracks may propagate near carbon steel plate
[6,10]. There are few papers where stainless steel and medium carbon steel have been taken in to consideration for
joining. The carbon content in medium carbon is very high compared to stainless steel that means hardness is very
high compared to stainless steel. Thus it is challenging to get a joint with desired mechanical properties. So the
present investigation centers around GMAW process for joining of stainless steel and carbon steel considering
current, voltage as control factors along with welding speed and gas flow rate to see their effect on mechanical
properties of the welded joint.
In this experiment Gas Metal Arc Welding (GMAW) has been used to join the base metals Stainless Steel AISI
304 and Medium Carbon Steel 45C8. Parent metals thus selected because of their successful engineering
applications. Fig.1 shows the Gas Metal Arc Welding Setup which has been automated using a profile cutter
machine. Hardness, Tensile Strength, Yield Strength, Weld Bead Width and Reinforcement are selected as a
response. In present study argon is used as shielding gas. It is very efficient one when working with stainless steel.
An attempt has made to investigate and optimize the response variables by varying the input variables through
Taguchi’s Robust Design Methodology and ANOVA statistical tools by using MINITAB 17 software.
12386 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393

1. Experimental Procedure

A semi-automatic setup has been used for butt welding of base metal plates. Input process parameters (welding
current, welding voltage, welding speed and gas flow rate) have been selected based on literature survey and
feasibility of the present setup. Selection of base materials are performed according to the applications and desired
specification. A number of experiments have been performed on dissimilar joining of stainless steel and mild steel
and this dissimilar welded joint has number of real time applications. Now-a-days there is a trend of joining stainless
steel with carbon steels, alloy steels etc. According to the applications and availability in the market stainless steel
AISI 304 and medium carbon steel C45 have been selected for present investigation. In this experiment both metals
having thickness 3 mm are taken. Table 1-3 show chemical composition of AISI 304, 45C8 and ER 308L
respectively.

Fig. 1. GMAW Setup

Design of experiment (DOE) is performed using Taguchi’s design methodology. MINITAB17 has been used to
determine number of runs required to get optimal values of response variables. In this study there are four input
parameters and each having three levels, the Taguchi’s method allows 27 number of experiments (normally 34=81
experiments). Table 5 shows L27 Orthogonal Array and welding process parameters arranged in L27 Orthogonal
Array respectively. A suitable fixture has been designed in fixing the work pieces required for present investigation
(Fig.2).

Fig. 2. Fixture Arrangement for Fixing Specimen

Table 1. Chemical Composition of AISI 304 Stainless Steel
Metal C Mn P S Si Cr Ni

AISI 304 0.05% 1.24% 0.024% 0.020% 0.42% 19.10% 9.05%

Table 2. Chemical Composition of Carbon Steel 45C8

Metal C Mn Si S P
45C8 0.43% 0.74% 0.22% 0.023% 0.030

Table 3. Chemical Composition of ER 308L

Metal C Mn Si S P Cr Ni Mo Cu
ER 308L 0.03% 1-2.5% 0.30-0.65% 0.03% 0.03% 19.5-22% 9-11 0.75% 0.75%
 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393 12387

In present study three levels have been selected i.e. each level having one value of control factor. Here current,
voltage, electrode stick-out and travel angle have three values for three levels. After number of trials, range of
control factors have been selected for the investigation. Table 4 indicates the range of control factors.

Table 4. Range of Control Factors

Sl. No. Variable Values (min-max)
1 Welding Current(A) 140-160 amps
2 Welding Voltage(B) 24-26 volts
3 Welding Speed(C) 4-6 mm/s
4 Gas Flow Rate(D) 6-10 l/min

Table 5.Welding Process Parameters Arranged in L27 Orthogonal Array

Exp. Actual Data of Input Parameters Responses
No.
Current Voltage Welding Gas Flow Hardness UTS Yield Weld Bead Reinforcement
Speed Rate Stress Width
(Amps) (Volts)) (mm)
(mm/sec)
(l/min) (mm)
1 140 24 4 6 97 722 640 5.54 2.24

2 140 24 4 6 97 720 637 5.60 2.22

3 140 24 4 6 96 721 635 5.55 2.20
4 140 25 5 8 95 715 622 5.94 2.16
5 140 25 5 8 96 713 620 6.00 2.13
6 140 25 5 8 95 717 615 5.98 2.15
7 140 26 6 10 94 710 608 6.04 2.07
8 140 26 6 10 93 714 605 6.08 2.05
9 140 26 6 10 94 711 609 6.12 2.04
10 150 24 5 10 92 704 602 6.24 1.96
11 150 24 5 10 93 699 600 6.29 1.95
12 150 24 5 10 92 700 599 6.27 1.94
13 150 25 6 6 91 697 590 6.50 1.90
14 150 25 6 6 92 695 595 6.54 1.91
15 150 25 6 6 91 694 588 6.58 1.89
16 150 26 4 8 90 692 572 6.72 1.72
17 150 26 4 8 90 694 570 6.70 1.68
18 150 26 4 8 91 690 568 6.75 1.67
19 160 24 6 8 89 688 555 6.90 1.55
20 160 24 6 8 90 691 550 6.94 1.50
21 160 24 6 8 89 690 552 6.92 1.49
22 160 25 4 10 88 685 538 7.00 1.45
23 160 25 4 10 87 688 540 7.05 1.38
24 160 25 4 10 90 684 536 7.10 1.36
25 160 26 5 6 87 680 530 7.21 1.25
26 160 26 5 6 88 678 528 7.24 1.23
27 160 26 5 6 87 682 525 7.26 1.20
12388 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393

2. Result Analysis

The variation of S/N ratio values and corresponding ranking of control factors have been generated by using
Taguchi Methodology. The maximum average S/N ratio for hardness has obtained at level 1 for welding current,
level 1 for welding voltage, level 1 for welding speed and level 1 for gas flow rate, i.e. the optimal process
parameters setting for maximum hardness is A1B1C1D1. From Fig. 3, it has clearly shown that for weld zone
hardness, optimal welding current is 140 amps, welding voltage is 24 volt, welding speed is 4 mm/s and gas flow 6
l/min. Fig.4 indicates the variation of S/N ratio values .The maximum average S/N ratio for UTS has obtained at
level 1 for welding current, level 1 for welding voltage, level 1 for welding speed and level 2 for gas flow rate, i.e.
the optimal process parameters setting for UTS is A1B1C1D2. From Fig.4 it has clearly shown that for UTS,
optimal welding current is 140 amps, welding voltage is 24 volt, welding speed is 4 mm/s and gas flow 8 l/min.
Fig.5 indicates the variation of S/N ratio values of control factors. The maximum average S/N ratio for YS has
obtained at level 1 for welding current, level 1 for welding voltage, level 1 for welding speed and level 2 for gas
flow rate, i.e. the optimal process parameters setting for YS is A1B1C3D1. From Fig.5 it has clearly shown that for
YS, optimal welding current is 140 amps, welding voltage is 24 volt, welding speed is 6 mm/s and gas flow 6 l/min.

Main Effects Plot for SN ratios

Data Means
Current Voltage
Mean of SN ratios

39.60
39.45
39.30
39.15
39.00
140 150 160 24 25 26
Welding Speed Gas Flow Rate
39.60
39.45
39.30
39.15
39.00
4 5 6 6 8 10
Signal-to-noise: Larger is better

Fig. 3. Mean S/N Ratio for Weld Zone Hardness

Main Effects Plot for SN ratios

Data Means
Current Voltage
Mean of SN ratios

57.1
57.0
56.9
56.8
56.7
140 150 160 24 25 26
Welding Speed Gas Flow Rate
57.1
57.0
56.9
56.8
56.7
4 5 6 6 8 10
Signal-to-noise: Larger is better

Fig. 4. Mean S/N Ratio for UTS

 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393 12389

Main Effects Plot for SN ratios

Data Means

Current Voltage

Mean of SN ratios
56.0
55.5
55.0
54.5
140 150 160 24 25 26
Welding Speed Gas Flow Rate
56.0
55.5
55.0
54.5
4 5 6 6 8 10
Signal-to-noise: Larger is better

Fig. 5. Mean S/N Ratio for YS

Main Effects Plot for SN ratios

Data Means
Current Voltage
Mean of SN ratios

17.0
16.5
16.0
15.5
140 150 160 24 25 26
Welding Speed Gas Flow Rate
17.0
16.5
16.0
15.5
4 5 6 6 8 10
Signal-to-noise: Larger is better

Fig. 6. Mean S/N Ratio for Weld Bead Width

Main Effects Plot for SN ratios

Data Means

Current Voltage
Mean of SN ratios

7
6
5
4
3

140 150 160 24 25 26

Welding Speed Gas Flow Rate
7
6
5
4
3

4 5 6 6 8 10
Signal-to-noise: Larger is better

Fig. 7. Mean S/N Ratio for Reinforcement

12390 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393

Fig.6 indicates the variation of S/N ratio values of control factors. The maximum average S/N ratio for Weld bead
thickness has obtained at level 1 for welding current, level 1 for welding voltage, level 1 for welding speed and level
2 for gas flow rate, i.e. the optimal process parameters setting for Weld bead width is A3B3C3D2. From Fig.6 it has
clearly shown that for Weld bead thickness, optimal welding current is 160 amps, welding voltage is 26 volt,
welding speed is 6 mm/s and gas flow 8 l/min. Fig.7 indicate the variation of S/N ratio values and corresponding
ranking of control factors. The maximum average S/N ratio for reinforcement has obtained at level 1 for welding
current, level 1 for welding voltage, level 1 for welding speed and level 2 for gas flow rate, i.e. the optimal process
parameters setting for reinforcement is A1B1C3D3. From Fig.7 it has clearly shown that for reinforcement, optimal
welding current is 140 amps, welding voltage is 24 volt, welding speed is 6 mm/s and gas flow 10 l/min.

Table 6. ANOVA for Welding Zone Hardness

Source DF Adj SS Adj MS F-value P-value Percentage (%) contribution
Current 2 1.92268 0.961338 187.48 0.008 85.82
Voltage 2 0.21843 0.109213 21.30 0.040 9.76
Speed 2 0.00329 0.001645 0.32 0.073 0.14
Gas flow rate 2 0.00359 0.001796 0.35 0.070 0.16
Error 18 0.005128 4.12
Total 26 2.24028 100

From the above Table 6, it is concluded that welding current is most significant factor for weldment hardness.
Other factors like welding voltage, welding speed and gas flow rate are insignificant for weldment hardness. P
values are less than 0.05, so the hypothesis is significant and accepted.

Table 7. ANOVA for UTS

Source DF Adj SS Adj MS F-value P-value Percentage (%) contribution
Current 2 0.672397 0.336198 586.28 0.005 90.34
Voltage 2 0.060569 0.030285 52.81 0.010 8.13
Speed 2 0.000538 0.000269 0.47 0.029 0.07
Gas flow rate 2 0.000457 0.000228 0.40 0.025 0.06
Error 18 0.010322 0.000573 1.38
Total 26 0.744283 100

From the above Table 7, it is concluded that welding current is most significant factor for UTS. Other factors like
welding voltage, welding speed and gas flow rate are not so significant for UTS. P values are less than 0.05, so the
hypothesis is significant and accepted. From the above Table 8, it is concluded that welding current is most
significant factor for YS. Other factors like welding voltage, welding speed and gas flow rate are not so significant
for YS. P values are less than 0.05, so the hypothesis is significant and accepted.

Table 8. ANOVA for YS

Source DF Adj SS Adj MS F-value P-value Percentage (%) contribution
Current 2 6.87294 3.43647 2363.76 0.001 88.98
Voltage 2 0.80110 0.40055 275.52 0.008 10.38
Speed 2 0.00853 0.00426 2.93 0.079 0.12
Gas flow rate 2 0.01526 0.00763 5.25 0.016 0.19
Error 18 0.02617 0.00145 0.33
Total 26 7.72400 100
 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393 12391

Table 9. ANOVA for Weld Bead Width

Source DF Adj SS Adj MS F-value P-value Percentage (%) contribution
Current 2 11.7958 5.89792 2894.71 0.004 86.54
Voltage 2 1.6149 0.80743 396.29 0.029 11.85
Speed 2 0.0701 0.03503 17.19 0.044 0.51
Gas flow rate 2 0.1129 0.05647 27.71 0.032 0.83
Error 18 0.0367 0.00204 0.27
Total 26 13.6304 100

From the above Table 9, it is concluded that welding current is most significant factor for weld bead width. Other
factors like welding voltage, welding speed and gas flow rate are not so significant for weld bead width. P values are
less than 0.05, so the hypothesis is significant and accepted.

Table 10. ANOVA for Reinforcement

Source DF Adj SS Adj MS F-value P-value Percentage (%) contribution
Current 2 68.9978 34.4989 1657.14 0.008 88.70
Voltage 2 7.2998 3.6499 175.32 0.020 9.38
Speed 2 0.8595 0.4297 20.64 0.039 1.10
Gas flow rate 2 0.2475 0.1237 5.94 0.048 0.34
Error 18 0.3747 0.0208 0.48
Total 26 77.7794 100

The welding areas of two dissimilar material has been studied through microstructure analysis by the help of
optical microscope under different magnification [6, 10]. The properties of materials have been determined by
describing the crystal structure of the welding surface. Microstructural estimation ranges from simple determination
of definite parameters such as grain size and average grain number to full characterization of estimation of
degradation. In the present study, the specimen has been made through grinding, polishing and etching processes.

Fig. 9. Microstructure of Base Metal AISI 304 Fig. 10. Microstructure of AISI 304 HAZ and Welded Zone

Fig. 11. Welding Zone Microstructure Fig. 12. Weld Bead

12392 Amit Ratan Biswas et al. / Materials Today: Proceedings 5 (2018) 12384–12393

Fig.13. C45 HAZ

Fig. 9- Fig. 13 shows the microstructure of AISI 304 and medium carbon steel 45C8 metal alloy in different areas
like base metal, heat effected zone, weld bead and HAZ zone. Base metal of AISI 304 consists of austenite grains
and a small amount of delta ferrite in the form of transvers line. This exposes a closely full austenitic structure with
a dendritic crystal structure that is well developed in side branches (Fig.11). A cellular structure has been formed
nearer to the base metal of AISI 304 after solidified the fusion zone. The boundary between welding zone and 304
base metal, the formation of microstructure transform to ferrite structure in some of the austenitic grains in base
metal which is close to the HAZ zone. The ferrite structures have stretched closer to the fusion boundary because
more ferrite is usually reorganized on fast cooling after the formation of delta ferrite during the welding process.

4. Conclusions

In the present work, study of metal inert gas arc welding on 3 mm thick carbon steel 45C8 and AISI 304 stainless
steel has been done. Also parametric optimization of process parameters and responses have been studied. The S/N
ratio and ANOVA analysis show which parameter has major influence in the responses. Following conclusions are
derived from the present investigation:
 During tensile test of welded specimens, the failure has taken from the base metal which confirms the
quality and strength of welding and suitability of process parameters.
 The experimental result shows that, welding current is most significant parameter for weld zone hardness.
In the welded zone, the hardness decreases with increasing welding current.
 In case of ultimate tensile strength and yield strength welding current is most significant parameter
followed by welding voltage, welding speed and gas flow rate respectively.
 It is observed that the hardness of weld bead is more than the parent metal because of the dilution at the
weld pool increases the hardness of weld bead.
 The present investigation demonstrates that Taguchi method can be successfully used to analyse and
determine the optimum process parameters to maximize welded zone hardness and tensile strength in MIG
welding.
 The approach used in the present work may be very useful for multi objective optimization in the context of
any machining or manufacturing process involving not only three but also for more than three responses.
 Grain structure changes from base metal to HAZ and HAZ to welded zone. Grain size becomes more
compact in welded zone.

Acknowledgements

I owe special debt of gratitude to the Staff Member of Mechanical Engineering Department of NITTTR, Kolkata for
their constant support in completing the experiments and providing the necessary facilities.

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