Optimization of mig welding process parameters for maximum yield strength in aisi 1040/EN 8

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Int. J. Mech. Eng. & Rob. Res. 2012 Ajit Hooda et al., 2012

OPTIMIZATION OF MIG WELDING PROCESSPARAMETERS TO PREDICT MAXIMUM YIELD

STRENGTH IN AISI 1040

Ajit Hooda1*, Ashwani Dhingra2 and Satpal Sharma2

*Corresponding Author: Ajit Hooda,[email protected]

In this research work an attempt was made to develop a response surface model to predicttensile strength of inert gas metal arc welded AISI 1040 medium carbon steel joints. The processparameters such as welding voltage, current, wire speed and gas flow rate were studied. Theexperiments were conducted based on a four-factor, three-level, face centred composite designmatrix. The empirical relationship can be used to predict the yield strength of inert gas metal arcwelded AISI 1040 medium carbon steel. Response Surface Methodology (RSM) was applied tooptimizing the MIG welding process parameters to attain the maximum yield strength of thejoint.

Keywords: AISI 1040, EN 8, Metal inert gas welding, Response surface methodology,Optimization, Yield strength

INTRODUCTIONGas Metal Arc Welding (GMAW), sometimesreferred to by its subtypes Metal Inert Gas (MIG)welding or Metal Active Gas (MAG) welding,is a semi-automatic or automatic 0020 Arcwelding process in which a continuous andconsumable wire electrode and a shieldinggas are fed through a welding gun. A constantvoltage, direct current power source is mostcommonly used with GMAW, but constantcurrent systems, as well as alternating current,can be used. There are four primary methods

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1 University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak, India.2 School of Engineering, Gautam Buddha University, Greater Noida, Uttar Pradesh, India.

of metal transfer in GMAW, called globular,short-circuiting, spray, and pulsed-spray, eachof which has distinct properties andcorresponding advantages and limitations.

Originally developed for welding aluminumand other non-ferrous materials in the 1940s,GMAW was soon applied to steels because itallowed for lower welding time compared toother welding processes. Today, GMAW is themost common industrial welding process,preferred for its versatility, speed and therelative ease of adapting the process to robotic

Research Paper

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automation. The automobile industry inparticular uses GMAW welding almostexclusively. Unlike welding processes that donot employ a shielding gas, such as shieldedmetal arc welding, it is rarely used outdoors. Arelated process, flux cored arc welding, oftendoes not utilize a shielding gas, insteademploying a hollow electrode wire that is filledwith flux on the inside.

GMAW is currently one of the most popularwelding methods, especially in industrialenvironments. It is used extensively by the sheetmetal industry and, by extension, theautomobile industry. There, the method is oftenused for arc spot welding, thereby replacingriveting or resistance spot welding. It is alsopopular for automated welding, in which robotshandle the work pieces and the welding gunto quicken the manufacturing process.Generally, it is unsuitable for welding outdoors,because the movement of the surrounding aircan dissipate the shielding gas and thus makewelding more difficult, while also decreasingthe quality of the weld. The problem can bealleviated to some extent by increasing theshielding gas output, but this can be expensiveand may also affect the quality of the weld. Ingeneral, processes such as shielded metal arcwelding and flux cored arc welding arepreferred for welding outdoors, making the useof GMAW in the construction industry ratherlimited. Furthermore, the use of a shielding gasmakes GMAW an unpopular underwaterwelding process, but can be used in spacesince there is no oxygen to oxidize the weld.

Gas metal arc welding is one of theconventional and traditional methods to joinmaterials. A wide range of materials may bejoined by Gas metal arc welding—similar

metals, dissimilar metals, alloys, and non-metals. In the present scenario demand of thejoining of similar materials continuouslyincreases due to their advantages, which canproduce high yield strength, deeperpenetration, continuous welding at higherspeed and small welding defects. GMAWwelding is used because of its advantagesover other welding techniques like high weldingspeeds. Less distortion, no slag removalrequired, high weld metal deposition rate, highweld quality, precise operation, etc. Thedemand for producing joints of dissimilarmaterials is continuously increasing due totheir advantages, which can provideappropriate mechanical properties and costreduction. Design of Experiment (DOE) andstatistical techniques are widely used foroptimization of process parameters. In thepresent study the welding process parametersof GMAW can be optimized to maximize theyield strength of the work piece also reducingthe number of experiments without affectingthe results. The optimization of processparameters can improve quality of the productand minimize the cost of performing lots ofexperiments and also reduces the wastage ofthe resources. The optimal combination of theprocess parameters can be predicted. Thiswork was concerned with the effects of weldingprocess parameters on the yield strength ofAISI 1040 joints.

AISI 1040 is medium carbon steel and is amaterial that is widely used in manufacturingof wide range of machine components and forsimple construction of machines. Austeniticstainless steels are extensively used in nuclearreactors, biomedical implants, as well as incomponents for chemical and food industries

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(Sen and Sen, 2004; and Farias et al., 2007).In considering the engineering materials, themain problem with austenitic stainless steelsis that it has poor wear resistance, yieldstrength, fracture and impact toughness (Shiand Northwood, 1995; and Dearnley andAldrich-Schmith, 2004). In recent years,extensive studies on the improvement ofmechanical properties of these materials havebeen carried out.

The properties such as weld-beadgeometry, mechanical properties, anddistortion can define the joint quality. Generally,all welding processes are used with the aimof obtaining a welded joint with the desiredweld-bead parameters, excellent mechanicalproperties with minimum distortion. In order todetermine the welding input parameters thatlead to the desired weld quality, application ofDesign of Experiment (DOE), evolutionaryalgorithms and computational network arewidely used to develop a mathematicalrelationship between the welding processinput parameters and the output variables ofthe weld joint.

LITERATURE REVIEWThe research on parameter optimization ofdifferent types of welding for obtaining variousresponses in output have been done by anumber of researchers using a wide range ofmaterials. They make use of various types ofmethods, techniques and mathematicalmodels for evaluating and obtaining results.Many researches' have been done researchwork on different materials for obtainingmaximum yield strength and tensile strength.

A response surface model was developedby Faseeulla et al. (2012) to study the

influence of process parameters of weld-bonding on tensile shear strength of the weld-bond of 2 mm thick aluminium alloy 6061 T651sheets. Using model, the significant andcontrollable process parameters of the weld-bonding such as surface roughness, curingtime, welding current, welding time andelectrode pressure are optimized formaximum tensile shear strength of the weldbond. Padmanaban and Balasubramanian(2011) developed an empirical relationship toeffectively predict the tensile strength of pulsedcurrent gas tungsten arc welded AZ31Bmagnesium alloy joints at 95% confidencelevel. The significant process parameters suchas peak current, base current, pulse frequencyand pulse on time were studied. Yahya (2012)observes that the weld strength ofthermoplastics, such as high densitypolyethylene and polypropylene sheets isinfluenced by friction stir welding parameters.The determination of the welding parametersplays an important role for the weld strength.The result also shows that for the influential useof the thermoplastics joints, the weld shouldhave adequate strength. An effectiveprocedure of Response Surface Methodology(RSM) has been utilized for finding the optimalvalues of process parameters while inductionhardening of AISI 1040 under two differentconditions of the material, i.e., rolled andnormalized by Amit and Hari (2011). Theexperiment plan was based on rotatable,Central Composite Design (CCD). Benyounisand Olabi (2008) studied that welding inputparameters play a very significant role indetermining the quality of a weld joint. Bealet al. (2006) investigates the laser fusion of amixture of H13 and Cu powders. TheResponse Surface Methodology (RSM) was

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used to understand the relationship betweenlaser processing parameters and the defectssuch as cracks and porosity to eliminate orreduce cracks and porosity. The result showedthat the optimized process parameters reducethe cracks and porosity from 15.32 to 2.54%.The micro-structural characteristics of the weldjoint using optical, scanning microscopy andEnergy Dispersive Spectroscopy (EDS) andmechanical properties with micro-hardnessand tensile test were studied by Ruan et al.(2012) Twin wire Metal Inert Gas (MIG) arcwelding was employed on 6 mm thick 6082-T6 Al-alloy plate partially with SiO

2 activating

flux. The results shows that the weld jointpenetration with SiO

2 flux was about 26%

deeper than what without SiO2 flux. SiO

2 flux

did not affect the micro-hardness and strengthof the weld joint.

An empirical relationship was developed byPadmanaban and Balasubramanian (2010) topredict tensile strength of the laser beamwelded AZ31B magnesium alloy byincorporating process parameters such aslaser power, welding speed and focal position.The results indicate that the welding speed hasthe greatest influence on tensile strength.Ferritic/Austenitic (F/A) joints are a populardissimilar metal combination used in manyapplications. F/A joints are usually producedusing conventional processes. Laser BeamWelding (LBW) has recently been successfullyused for the production of F/A joints withsuitable mechanical properties. Anawa andOlabi (2008) using a statistical Design ofExperiment (DOE) optimizes the selectedLBW parameters likewise laser power, weldingspeed and focus length. Paventhan et al.(2011) made a attempt to develop an empirical

relationship to predict the tensile strength offriction welded AA 6082 aluminium alloy andAISI 304 austenitic stainless steels joints,incorporating above said parameters.Response Surface Methodology (RSM) wasapplied to optimizing the friction weldingprocess parameters to attain the maximumtensile strength of the joint. Pekkarinena andKujanp (2010) determines empirically, microstructural changes occur in ferritic and duplexstainless steels when heat input is controlledby welding parameters. Using opticalmetallographic methods, micro-structuralchanges in welds were identified andexamined. Zambona et al. (2006) performedCO

2 laser welding on AISI 904L super

austenitic stainless steel sheets, withoptimized processing parameters determinedby means of melt run trial evaluations.

Because of their superior mechanical andcorrosion properties, 304L austenitic stainlesssteel is used widely in industry. Resistance spotweld is most widely used as a joining processfor sheet materials. Dursun (2008) shows thatthe influence of the primary welding parametersaffecting the heat input such as; weld peakcurrent, on the weld quality such as; surfaceappearances, weld nugget size, weldpenetration, weld internal discontinuities,strength and ductility was determined for 304Lresistance spot welded materials.

METHODOLOGYAISI 1040 or EN8 medium carbon steel plates,with chemical composition as shown in table1 and the balance Iron, were selected as basemetal for the experiments. The plates weremachined into 300 mm 150 mm 8 mm asweld blanks. The surface of the plates was

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grind to remove the dust and other foreignparticles. In order to obtain a strong bondedjoint the properties of the base metal and thewelding wire must comply with each other.

The type of material of welding wire totaldepends upon the material that is required tobe welded. So ER 70S-6 was selected aswelding wire, whose chemical composition as

shown in Table 1. The diameter of the welding

wire depends upon the base metal thickness.

As the thickness of base metal was 8 mm,

welding wire with a diameter of 1.2 mm was

selected. The significant welding input

parameters that can affect the output response

were identified and their range of operation

was selected as shown in Table 2.

Material C Mn Si S (max) P (max) Cu (max)

AISI 1040 (EN-8) 0.40 0.75 0.25 0.050 0.040 –

ER 70S-6 0.19 1.63 0.98 0.025 0.025 0.025

Table 1: Chemical Composition of Base Metal and Filler Wire

Parameters Welding Voltage V Welding Current A Wire Speed m/min Gas Flow Rate l/min

Values 23-25 200-220 2.4-3.2 12-16

Table 2: Input Parameters and There Range

In this study thyristorised power source ofESAB make ‘Auto K 400’ was used to join8mm flat plates of EN8 due to their ability toquick arc start, stick out and crater control,Fresh tip Treatment Technology (FTT) toeliminates globule formation at the wire tipduring weld stop and others advantage.

The effect of the process parameters, viz.,voltage, wire speed, welding current and gasflow rate and focusing position on the weld jointyield strength has been investigated. The yieldstrength was tested on FIE make universaltesting machine of model number ‘UTE-60’.

The experimental set up of this researchwork is shown in Figure 1. The micro testingof the material was done on RMM 2microscope. The objective of this study wasto find out the optimal combination of theinput parameter for maximized yield strengthof the weld. In Figures 2 and 3 the AISI 1040

Figure 1: Experimental Setup

medium carbon steel before welding afterwelding are shown.

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Figure 2: AISI 1040 as Base MetalBefore Welding

Figure 3: AISI 1040 Base MetalAfter Butt Welding

Figure 4: Testing Samples of Base Material Before Tensile, Yield Testing and Face andBend Root Tests

RESULTS AND DISCUSSIONThe plates of AISI 1040 medium carbon steelwere welded by using above methods. Thequality of the weld depends upon variousfactors likewise welding speed, voltage,

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current and most importantly on the quality ofthe welder. Using the universal testing machinethe yield strength was calculated. The test

specimens on which experiment was carriedout, before the yield test and after the tests isshown in the Figures 4 and 5.

Figure 5: Broken Test Samples After Yield, Tensile and Bend Tests

Table 3: Levels of Process Input Parameters

Voltage Volts 23 (–1) 24 (0) 25 (+1)

Current Ampere 190 (–1) 200 (0) 210 (+1)

Wire Speed m/min 2.4 (–1) 2.8 (0) 3.2 (+1)

Gas Flow Rate l/min 12 (–1) 14 (0) 16 (+1)

Units Low Level Middle Level High LevelLevel

Parameter

The input variable parameters that wereselected for this work, have three levels – lowlevel, medium level and high level

corresponding to their values. The levels of thesignificant process variables are shown inTable 3.

The results of yield strength test areshown in Table 4. As the transverse andlongitudinal test specimens were preparedfrom the welded plates for yield strength

test in transverse and longitudinal direction.It is clearly indicated that the yield strengthof longitudinal test was greater thantransverse test.

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Table 4: Experimental Design Matrix and Results

1. 23.5 200 2.8 14 367.571 390.411

2. 23.5 200 3.2 14 320.743 372.000

3. 22.5 190 2.4 16 320.057 337.371

4. 24.5 190 2.4 12 373.714 454.114

5. 23.5 200 2.4 14 281.486 389.486

6. 24.5 210 2.4 12 301.200 380.914

7. 23.5 200 2.8 16 304.453 332.160

8. 22.5 210 2.4 16 344.087 362.343

9. 22.5 190 3.2 16 323.600 343.080

10. 24.5 210 3.2 12 300.800 328.506

11. 24.5 210 2.4 16 304.394 318.080

12. 23.5 200 2.8 12 321.600 351.800

13. 24.5 200 2.8 14 308.670 334.874

14. 24.5 190 2.4 16 289.583 314.207

15. 23.5 190 2.8 14 356.400 379.106

16. 24.5 190 3.2 12 312.265 335.090

17. 22.5 210 2.4 12 373.714 398.907

18. 22.5 200 2.8 14 371.048 393.640

19. 23.5 200 2.8 14 328.209 352.000

20. 22.5 190 3.2 12 357.574 381.532

21. 23.5 200 2.8 14 299.421 321.804

22. 24.5 210 3.2 16 307.684 326.249

23. 23.5 200 2.8 14 342.030 364.260

24. 23.5 210 2.8 14 314.050 340.070

25. 22.5 210 3.2 12 368.600 387.636

26. 22.5 190 2.4 12 374.571 396.514

27. 24.5 190 3.2 16 317.475 344.020

28. 22.5 210 3.2 16 370.308 391.379

Run No. Voltage V Current AWire Speed

m/minGas FlowRate l/min

Transverse YieldStrength (MPa)

Longitudinal YieldStrength (MPa)

The value of variable process parameterswelding voltage, welding current, wire speedand gas flow rate, corresponding to themaximum transverse yield strength andlongitudinal yield strength was noted. Thesevalues were the optimized values of inputprocess variables, to obtain the maximum

transverse yield strength and longitudinal yieldstrength in jointed plates of AISI 1040 steel.And the optimum result values are shown inTable 5.

The microstructure of the welded joint thusobtained from joining of two similar plates ofAISI 1040 or EN-8 steel were studied at a

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magnification scale of 100X. Themicrostructure of base metal shows uniformstructure pattern of ferrite and lamellar pearlite.The grain size of the base material was in therange of 6-7 ASTM. And the microstructure ofheat affected zone shows partially elongatedferrite grains in network form, around thelamellar pearlite having grain size of 5-6 ASTM.The microstructure of the test specimen atoptimal combination of process variables,welding voltage, welding current, wire feed rateor wire speed and gas flow rate is shown inFigures 6 and 7.

Due to fine grains size in heat affected zonethe yield strength is highest there. Fortransverse testing, the test specimens werecut at an angle of 900 to the direction of weldingwith weld bead of the joint at center. And testspecimen also have base metal on the both

Yield Test Yield Strength MPa Voltage V Current A Wire Speed m/min Gas Flow Rate l/min

Transverse 374.571 22.5 190 2.4 12

Longitudinal 398.907 22.5 210 2.4 12

Table 5: Optimized Values of Input Parameters

Figure 6: Microstructure of Base MetalAISI 1040

Figure 7: Microstructure of the Heat

ends. The test specimen was broken awayfrom the weld joint of base material end, butnot from the middle of joint. But in case oflongitudinal testing the testing specimen wasprepared from the plate in the direction ofwelding. The test specimen of longitudinaltesting comprises of welded joint only with heataffected zone. So the value of the longitudinalyield strength is greater than the transverseyield strength.

CONCLUSIONThe similar weld joint of AISI 1040 material wasdeveloped effectively with MIG welding withselected range of input variable parameters.

The maximum yield strength both transverseand longitudinal, at the optimum values ofprocess variables-welding voltage, weldingcurrent, wire speed and gas flow rate was

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experimented. The longitudinal yield strengthis greater than the transverse yield strength.

In future, we can state the relationshipbetween the transverse and longitudinal yieldstrength by comparing their values andstudying their microstructure.

ACKNOWLEDGMENTThe authors are grateful to the Paryog LiftingEquipments and RBS Engineering,Ballabgarh, India, for their financial support forthe whole research work. We would like tothank Claas India, Miranda and their allmanagerial staff members of engineeringdepartments for helping in the research work.

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Optimization of mig welding process parameters for maximum yield strength in aisi 1040/EN 8

Engineering

gmaw welding

metal inert gas welding

welding voltage

welding aluminumand

welding gun

arc spot welding

cored arc welding

shieldedmetal arc welding