assessment of deposition rate in mig welding of … · assessment of deposition rate in mig welding...

IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613

All rights reserved by www.ijsrd.com 2011

Assessment of Deposition Rate in MIG Welding of Metal, Research Paper

Gaurang R. Patel1 Prof. B. D. Patel

2

1ME Student

2Assistant Professor

1,2Department of Mechanical Engineering 1,2

Ahmedabad Institute of Technology

Abstract— Metal inert gas arc welding (MIG) is preferable

more its inherent qualities like easy control of variables,

high quality, deep penetration, smooth finish. The quality of

weld depends on metal deposition rate which in turn

depends on the process parameters. In this present work, the

effect of Taguchi Methodology approach for experimental

investigation of metal inert gas arc welding parameters

welding current, welding voltage and wire feed speed on

metal deposition rate has been studied.

Key words: Taguchi Method and Orthogonal Array

I. INTRODUCTION

Gas metal arc welding (GMAW), sometimes referred to by

its subtypes metal inert gas (MIG) welding or metal active

gas (MAG) welding, is a welding process in which an

electric arc forms between a consumable wire electrode and

the work piece metal(s), which heats the work piece

metal(s), causing them to melt, and join. Along with the

wire electrode, a shielding gas feeds through the welding

gun, which shields the process from contaminants in the air.

The process can be semi-automatic or automatic. A constant

voltage, direct current power source is most commonly used

with GMAW, but constant current systems, as well as

alternating current, can be used. There are four primary

methods of metal transfer in GMAW, called globular, short-

circuiting, spray, and pulsed-spray, each of which has

distinct properties and corresponding advantages and

limitations [1].

Today, GMAW is the most common industrial

welding process, preferred for its versatility, speed and the

relative ease of adapting the process to robotic automation.

Unlike welding processes that do not employ a shielding

gas, such as shielded metal arc welding, it is rarely used

outdoors or in other areas of air volatility. A related process,

flux cored arc welding, often does not use a shielding gas,

but instead employs an electrode wire that is hollow and

filled with flux [2].

To perform gas metal arc welding, the basic

necessary equipment is a welding gun, a wire feed unit, a

welding power supply, an electrode wire, and a shielding

gas supply.

Fig. 1: Welding Gun and Wire Feed Unit

GMAW torch nozzle cutaway image. (1) Torch

handle, (2) Molded phenolic dielectric (shown in white) and

threaded metal nut insert (yellow), (3)Shielding gas diffuser,

(4) Contact tip, (5) Nozzle output face[3].

The typical GMAW welding gun has a number of

key parts a control switch, a contact tip, a power cable, a gas

nozzle, an electrode conduit and liner, and a gas hose. The

control switch, or trigger, when pressed by the operator,

initiates the wire feed, electric power, and the shielding gas

flow, causing an electric arc to be struck. The contact tip,

normally made of copper and sometimes chemically treated

to reduce spatter, is connected to the welding power source

through the power cable and transmits the electrical energy

to the electrode while directing it to the weld area. It must be

firmly secured and properly sized, since it must allow the

electrode to pass while maintaining electrical contact. On

the way to the contact tip, the wire is protected and guided

by the electrode conduit and liner, which help prevent

buckling and maintain an uninterrupted wire feed. The gas

nozzle directs the shielding gas evenly into the welding

zone. Inconsistent flow may not adequately protect the weld

area. Larger nozzles provide greater shielding gas flow,

which is useful for high current welding operations that

develop a larger molten weld pool. A gas hose from the

tanks of shielding gas supplies the gas to the nozzle.

Sometimes, a water hose is also built into the welding gun,

cooling the gun in high heat operations [4].

II. TAGUCHI TECHNIQUES

The Taguchi method involves reducing the variation in a

process through robust design of experiments. The overall

objective of the method is to produce high quality product at

low cost to the manufacturer. The Taguchi method was

developed by Dr. Genichi Taguchi of Japan who maintained

that variation. Taguchi developed a method for designing

experiments to investigate how different parameters affect

the mean and variance of a process performance

characteristic that defines how well the process is

functioning. The experimental design proposed by Taguchi

involves using orthogonal arrays to organize the parameters

affecting the process and the levels at which they should be

varies. Instead of having to test all possible combinations

like the factorial design, the Taguchi method tests pairs of

combinations. This allows for the collection of the necessary

data to determine which factors most affect product quality

with a minimum amount of experimentation, thus saving

time and resources. The Taguchi method is best used when

there are an intermediate number of variables (3 to 50), few

interactions between variables, and when only a few

variables contribute significantly [5].

The Taguchi arrays can be derived or looked up.

Small arrays can be drawn out manually; large arrays can be

derived from deterministic algorithms. Generally, arrays can

be found online. The arrays are selected by the number of

parameters (variables) and the number of levels (states).

This is further explained later in this article. Analysis of


(IJSRD/Vol. 3/Issue 03/2015/500)


variance on the collected data from the Taguchi design of

experiments can be used to select new parameter values to

optimize the performance characteristic. The data from the

arrays can be analyzed by plotting the data and performing a

visual analysis, ANOVA, bin yield and Fisher's exact test, or

Chi-squared test to test significance [5].

III. ANOVA

The ANOVA was used to investigate which design

parameters significantly affect the quality characteristic. The

ANOVA is performed by separating the total variability of

the S/N ratios into contributions by each of the design

parameters and the errors. The total variability of S/N ratio

is measured by the sum of the squared deviations from the

total mean S/N ratio [6].

IV. MATERIAL AND EXPERIMENTAL SETUP

Fig .2: GMAW Circuit Diagram (1) Welding Torch, (2)

Work Piece (3) Power Source, (4) Wire Feed Unit, (5)

Electrode Source,(6) Shielding Gas Supply.

Shielding gases are necessary for gas metal arc

welding to protect the welding area from atmospheric gases

such as nitrogen and oxygen, which can cause fusion

defects, porosity, and weld metal embrittlement if they come

in contact with the electrode, the arc, or the welding metal.

This problem is common to all arc welding processes; for

example, in the older Shielded-Metal Arc Welding process

(SMAW), the electrode is coated with a solid flux which

evolves a protective cloud of carbon dioxide when melted

by the arc. In GMAW, however, the electrode wire does not

have a flux coating, and a separate shielding gas is

employed to protect the weld. This eliminates slag, the hard

residue from the flux that builds up after welding and must

be chipped off to reveal the completed weld [7 & 8].

%ag

e C Mn S P Si Al Cr

Base

Plate

0.15

0

0.82

0

0.0.1

0

0.01

1

0.15

0

0.03

0

0.01

0

Table 1: Chemical Compositions of the MILD STEEL

BASE PLATE

%age C Si Mn P S Cu

Electrode

Wire

0.06

–

0.15

0.80

–

1.15

1.40

–

1.85

0.025

max

0.035

max

0.50

max

Table 2: Chemical Compositions of the Electrode Wire

ER70S-6

Fig. 3: MIG Welding Machine

In my experimental DOE method selected 3 levels

of each input process parameters.

Symbol Control unit factors Unit Low High

P Power Kilo Watt 2 6

F Feed rate mm/sec 3 7

Α Orientation Angle Degree 30 90

P Gas Pressure Bar 10 40

Table 3: Process Input Parameters and Their Levels

V. RESULT AND DISCUSSION

Run

Order

P

(kw)

F

(m/min)

A

(degree)

P

(bar)

D

(kg/hr)

1 4 5 90 25 1.4

2 2 7 90 10 2.83

3 4 5 30 25 2.79

4 4 5 60 25 2.39

5 6 3 90 10 0.83

6 4 5 60 40 1.36

7 2 3 30 40 1.39

8 6 3 30 10 1.54

9 6 3 90 40 1.46

10 2 3 90 10 1.06

11 4 5 60 25 1.56

12 4 5 60 25 1.76

13 6 7 30 10 2.74

14 4 5 60 25 2.1

15 6 7 90 10 3.13

16 6 7 90 40 2.94

17 6 7 30 40 3.46

18 4 5 60 25 1.54

19 6 5 60 25 2.08

20 2 7 30 40 3.34

21 4 7 60 25 2.9

22 4 3 60 25 1.39

23 6 3 30 40 1.58

24 2 7 30 10 3.93

25 2 3 30 10 1.2

26 2 5 60 25 2.06

27 2 7 90 40 3.53

28 4 5 60 10 2.5

29 4 5 60 25 1.56

30 4 5 60 25 1.48




31 2 3 90 40 1.48

Table 4: Experimental Results for Deposition Rate

Source

DF

Seq

SS Contribution

Power 2 0.99842 4.71%

Feed

Rate 2 16.8556 79.59%

Orien-tation

Angle 2 1.58022 7.46%

Gas Pressure 2 0.78299 3.69%

Error 22 0.95868 4.53%

Lack

-of-fit 16

Pure

Error 6

Total 30 100%

Table 5: Summary of ANOVA Calculation for Deposition

Rate

A. Surface Plots Analysis for Deposition Rate:

Fig. 4: Surface Plots Analysis for Deposition Rate

Fig. 5: Surface Plots of Deposition Rate

Run

Order

P

(kw)

F

(m/min)

A

(degree)

P

(bar)

DP

(mm)

1 4 5 90 25 3.96

2 2 7 90 10 1.20

3 4 5 30 25 5.29

4 4 5 60 25 5.00

5 6 3 90 10 5.14

6 4 5 60 40 4.00

7 2 3 30 40 5.76

8 6 3 30 10 5.46

9 6 3 90 40 5.40

10 2 3 90 10 4.52

11 4 5 60 25 4.94

12 4 5 60 25 4.42

13 6 7 30 10 4.30

14 4 5 60 25 4.98

15 6 7 90 10 4.84

16 6 7 90 40 3.52

17 6 7 30 40 3.50

18 4 5 60 25 5.02

19 6 5 60 25 4.75

20 2 7 30 40 3.34

21 4 7 60 25 4.06

22 4 3 60 25 5.28

23 6 3 30 40 5.42

24 2 7 30 10 3.32

25 2 3 30 10 4.75

26 2 5 60 25 2.94

27 2 7 90 40 2.22

28 4 5 60 10 4.91

29 4 5 60 25 4.76

30 4 5 60 25 5.09

31 2 3 90 40 2.22

Table 6: Experimental Results for Depth of Penetration

Source

DF

Seq

SS Contribution

Power 2 11.92392 33.20%

Feed

Rate 2 12.2008 33.37%

Orien-tation Angle 2 5.60274 15.60%

Gas Pressure 2 2.81994 7.85%

Error 22 3.36101 9.36%

Lack

-of-fit 16

Pure

Error 6

Total 30 100%

Table 7: Summary of ANOVA Calculation for Depth of

Penetratio

B. Surface Plots Analysis for Depth of Penetration:

Fig. 6: Surface Plots Analysis for Depth of Penetration

7.5

0.61

2

.542

3

4

4 3.06

ETAR NOITISOPED

ETAR DEEF

REWOP

urface Plot of DEPOSITION RATE vs FEED RATE, S OWERP

7.5

06.1

2

4.5

3

04

4

06 0.308

DEPOSI IT ETAR NO

ETAR DEEF

ELGNA NOIRIENTAO T

urface Plot of DEPOSITION RATE vs FEED RATE, ORIENTATS ON ANGLEI

6

4

2

4

0.3

6

4.526.0

.7 5

DEPTH OF P R NOITATENE

rewoP

eed rF ate

urfaS e Plot of DEPTH OF PENc TRATION vs Power, Feed rateE




Fig. 7: Surface Plots of Depth of Penetration

VI. CONCLUSIONS

In this research study, various process control parameters

like power, feed rate, and orientation angle and gas pressure

have been evaluated to investigate their effects on

Deposition rate and depth of penetration.

1) In the RSM method, the percentage contribution of

power is 0.471 %, Feed rate 79.59 %, orientation

angle 0.746 and gas pressure 3.69 % on deposition

rate.

2) Orientation angle also affects the deposition rate.

At 90 degree orientation angle which gives better

deposition rate as compared to the 30 and 60

degree orientation angle.

3) In the RSM method, the percentage contribution of

power is 33.20 %, Feed rate 33.97 %, orientation

angle 15.60 % and gas pressure 7.85 % on

deposition rate.

4) Power and feed rate is most affected parameter on

depth of penetration. Combination of power and

feed rate value will give the better depth of

penetration.

REFERENCES

[1] http://en.wikipedia.org/wiki/Gas_metal_arc_welding.

[2] In work shop of Ahmedabad institute of technology.

[3] Satyaduttsinh P. Chavda, “A Review on Optimization

of MIG Welding Parameters using Taguchi’s DOE

Method” Volume-4, Issue-1, February-2014, ISSN No.:

2250-0758 Page Number:16-21

[4] Mohammad Mousavi Anzehaee,” A new method to

control heat and mass transfer to work piece in a

GMAW Process” Journal of Process Control 22 (2012)

1087– 1102

[5] S. V. Sapakal,” PARAMETRIC OPTIMIZATION OF

MIG WELDING USING TAGUCHI DESIGN

METHOD” International Journal of Advanced

Engineering Research and Studies/ Vol. I/ Issue

IV/July-Sept., 2012/28-30

[6] Izzatul Aini Ibrahim.” The Effect of Gas Metal Arc

Welding (GMAW) processes on different welding

parameters” Procedia Engineering 41 (2012) 1502 –

1506

[7] Erdal Karadeniz, “The effect of process parameters on

penetration in gas metal arc welding processes”

Materials and Design 28 (2007) 649–656

[8] P.J. Modenesi, “A model for melting rate phenomena in

GMA welding” Journal of Materials Processing

Technology 189 (2007) 199–205

04

032

02

4

0.3

6

4.510.06

5.7

DEPTH OF P NOITARTENE

erusserP saG

eed rateF

urface Plot of DEPTH OF PENETRATIOS vs Gas Pressure, Feed rateN

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