Prediction of Weld Bead

8/3/2019 Prediction of Weld Bead

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Int J Adv Manuf Technol (2006) 30: 669676DOI 10.1007/s00170-005-0101-2

O RIG IN A L A RTICLE

P. K. Palani . N. Murugan

Development of mathematical models for prediction of weld bead

geometry in cladding by flux cored arc welding

Received: 7 January 2005 / Accepted: 20 June 2005 / Published online: 7 March 2006# Springer-Verlag London Limited 2006

Abstract The mechanical and corrosion resistant proper-ties of cladded components depend on the clad beadgeometries, which in turn are controlled by the process

parameters. Therefore it is essential to study the effect of pro-cess parameters on the bead geometry to enable effectivecontrol of these parameters. The above objective can easily beachieved by developing equations to predict the weld beaddimensions in terms of process parameters. Experiments wereconducted to develop models, using a three factor, five levelfactorial design for 317L flux cored stainless steel wire withIS:2062 structural steel as base plate. The models sodeveloped were checked for their adequacy. Confirmationexperiments were also conducted and the results show that themodels developed can predict the bead geometries and dilu-tion with reasonable accuracy. It was observed from theinvestigation that the interactive effect of the process param-

eters on the bead geometry is significant and cannot beneglected.

Keywords Cladding . GMAW . Weld bead parameters .

Dilution . Response surface methodology

1 Introduction

Engineering components used in many industrial applica-tions are subjected to wear and corrosion, which dictatesfrequent maintenance and jeopardizes reliability. Affectedindustries include aviation, mining, agriculture and power

generation. The replacement cost of many of these components is extremely high. Consequently extension ofservice life can result in significant savings [1]. Also, plates

or tubes of carbon or low alloy steel clad with an alloyedmaterial are an economical solution to meet the increasingdemand of industrial processes for combining elevatedstrength with good corrosion resistance [2]. Weld claddinghas been a popular method for repairing worn out parts orfor achieving a corrosion resistant surface. Cladding is a

process of depositing a relatively thick layer of fillermaterial on a carbon or low alloy steel base metal [1, 3].Among fusion welding processes, flux cored arc welding(FCAW) has been widely used for cladding due to severaladvantages. Process parameters for FCAW should be wellestablished and categorized to enable automation and ro-

botization of arc welding. The selection of welding pro-

cedure must be more specific to ensure that adequate beadquality is obtained [4]. Further to obtain the desired qualitywelds, it is essential to have complete control over therelevant process parameters to obtain the required beadgeometry shown in Fig. 1 and shape relationships on whichthe integrity of a weldment is based [4]. It has also beenreported by some researchers that in FCAW, process qual-ity can be represented by bead shape [5]. Thus, the weld

bead geometry plays an important role in determining themechanical properties of the weld [6]. Therefore, it is veryimportant to select and control the welding process param-eters for obtaining optimal weld bead geometry. Numerousattempts have been made to develop mathematical models

relating process variables and bead geometry for theselection and control of the process variables. These resultsshow that the mathematical models derived from experi-mental results can be used to predict bead geometryaccurately [4, 7].

Also, it has been proved by several researchers thatefficient use of statistical design of experiment techniquesallows development of an empirical methodology to incor-

porate a scientific approach in the welding procedure [710]. Hence, in this investigation, design of experimentswas used to conduct the experiments for exploring theinterdependence of the process parameters.

P. K. Palani (*)Faculty of Mechanical Engineering,Government College of Technology,Coimbatore-13, Indiae-mail: [email protected].: +91-422-245227

N. MuruganDepartment of Mechanical Engineering,Coimbatore Institute of Technology,Coimbatore-14, Indiae-mail: [email protected].: +91-422-2513080


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The main objectives of this study are to (1) developregression models for the prediction of bead width, depthof penetration, height of reinforcement and dilution and to(2) study the effect of process parameters on the beadgeometry using the models so developed.

The study was carried out for 1.2 mm diameter, 317Lstainless steel (AWS: A5-2295; EN 12073) flux cored

wire with base plate as IS:2062 structural steel plate underthe shield of 95% CO2 and 5% Ar gas mixture. Thechemical compositions of base and filler material are givenin Table 1.

2 Plan of investigation

The research work was planned to be carried out in thefollowing steps:

1. Identifying the important process control variables andfinding their upper and lower limits

2. Developing the design matrix and conducting theexperiments as per the design matrix

3. Recording the responses viz., penetration (P), beadwidth (W), reinforcement (R) and calculating %dilution (D)

4. Developing mathematical model, determining the co-efficients of the regression model

5. Checking the adequacy of the model developed6. Presenting the effects of process parameters in

graphical form and analyzing the results

2.1 Identifying the important process control variables

and finding their upper and lower limits

The independently controllable process parameters wereidentified; they are welding current (I), welding speed (S)

and nozzle-to-plate distance (N). Initial trial runs werecarried out with the bead laid on plates by varying one ofthe process parameters whilst keeping the rest of them atconstant values, to obtain the working range of the process

parameters. The working range was decided upon byinspecting the bead for smooth appearance and the absenceof any visible defects. Also it was found that the wire feed

rate is directly proportional to the welding current and therelation is found to be Wf= 6.92+0.0860*I where I is thewelding current in A; Wfis the wire feed rate in m/min andhence it was considered as a dependent variable.

The upper limit of a factor was coded as +1.682 and itslower limit as 1.682, the coded values of the intermediatelevels being calculated from the relationship Xi=1.682*[2X(Xmax+Xmin)]/(XmaxXmin), where Xi is the requiredcoded value of a variable X and X is any value of thevariable from Xmin to Xmax; Xmin is the lower level of thevariable; Xmax is the upper level of the variable. The se-lected values of the process parameters together with theirunits and notations are given in Table 2.

2.2 Developing the design matrix and conductingthe experiments as per the design matrix

A three factor, five level central composite experimentaldesign with six centre points shown in Table 3 was selectedto conduct the experiments.

Structural steel plates of 20 mm thickness were cut into therequired size of 200 mm150 mm by using an oxyacety-lene flame cutting machine. The top surfaces of the test

plates to be cladded were cleaned by means of emery paperand wire brush to remove rust. The experiments were

conducted by laying a single bead on structural steel platesusing 317L stainless steel flux cored wire of 1.2 mmdiameter. Experiments were carried out using the UnimacroEsseti 501 Welding Machine under the shield of 95% Ar

A

B

Area A is added metalArea B is base metal melted% Dilution = [B/(A+B)] x 100

Penetration (P)

Width (W)

Reinforcement (R)

Fig. 1 Weld bead geometry

Table 1 Chemical composition of materials used

S. No. Materials used Element weight %

C Si Mn P S Cr Mo Ni N2 Cu

1 317L (flux cored wire) 0.021 0.89 1.38 0.016 0.007 18.46 3.18 13.10 0.057 0.007

2 IS:2062 0.180 0.180 0.980 0.016 0.016 - - - - -

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and 5% CO2 gas mixture supplied at the rate of 16 l/min.Direct current electrode positive (DCEP) with electrode towork angle of 90 was maintained throughout the study.

2.3 Recording of responses

Twenty experimental runs were conducted as per thedesign matrix at random to avoid any systematic errorcreeping into the system. The surface plates were cross-sectioned at their midpoints to obtain test specimens of

25 mm width. These specimens were ground, polished andetched with 2% nital. Weld bead profiles were traced byusing an optical profile projector and the bead dimensionsviz., width (W), penetration (P) and reinforcement (R) weremeasured. With the help of a digital planimeter area of

penetration and bead area were determined to calculate thepercent dilution (D). The observed and calculated values ofthe bead parameters and dilution are given in Table 3.Figures 2 and 3 show the typical weld bead cross sectionsand weld bead geometry traces, respectively.

2.4 Development of mathematical models

The response function representing any of the weld beaddimensions can be expressed [3, 1016] as

Y f I; S; N (1)

WhereYis the response e.g. penetration, bead width etc.,

I is welding current, AS is welding speed, cm/min

N is nozzle-to-plate distance, mmThe second-order polynomial (regression) equation used

to represent the response surface for three factors could beexpressed as given below:

Y b0 b1I b2S b3N b12IS b13IN

b23SN b11I2 b22S

2 b33N2

(2)

Where bo is the free term of the regression equation, thecoefficients b1, b2 and b3 are linear terms, the coefficients

Table 2 Process variables and their bounds

Process variables Units Notation Factor levels

1.682 1 0 1 1.682

Welding current A I 176 190 210 230 244

Welding speed cm/min S 26 29 34 39 42

Nozzle-to-plate distance mm N 15 17 20 23 25

Table 3 Design matrix andresponses

Expt. run Process variables Bead geometry and dilution

I (A) S (cm/min) N (mm) P (mm) R (mm) W (mm) % D

1 1 1 1 0.80 4.50 9.43 3.77

2 1 1 1 1.10 4.75 13.52 7.11

3 1 1 1 0.75 4.00 8.33 7.72

4 1 1 1 1.00 4.25 12.07 10.00

5 1 1 1 0.90 4.65 9.47 9.18

6 1 1 1 1.10 4.85 12.00 8.08

7 1 1 1 0.75 4.10 9.35 7.52

8 1 1 1 0.76 4.38 11.80 4.48

9 1.682 1 0 0.70 4.12 8.69 7.95

10 1.682 1 0 1.00 4.70 13.58 7.3911 0 1.682 0 1.10 5.10 12.03 6.92

12 0 1.682 0 0.98 4.25 10.00 5.99

13 0 0 1.682 0.90 4.50 11.00 5.68

14 0 0 1.682 0.85 4.53 12.00 7.45

15 0 0 0 0.98 4.40 10.63 6.81

16 0 0 0 1.00 4.50 10.00 8.11

17 0 0 0 0.95 4.24 10.15 7.00

18 0 0 0 0.94 4.35 10.26 7.66

19 0 0 0 0.95 4.49 11.00 6.85

20 0 0 0 1.00 4.60 9.41 8.00

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b11, b22 and b33 are the quadratic terms and the coefficientsb12, b13 and b23 are the interaction terms [1116].

2.5 Estimation of coefficients of the model

The values of the coefficients of the above polynomialwere calculated with the help of Systat, a statisticalsoftware. The estimated coefficients are given in Table 4.

2.6 Checking the adequacy of the model developed

2.6.1 ANOVA

The estimated coefficients obtained above were used toconstruct the model for the response parameter. The ad-equacy of the model so developed was then tested by usingthe analysis of variance (ANOVA) technique which is

presented in Table 5. As per this technique it was found thatcalculated F ratios were larger than the tabulated values at95% confidence level; hence the model is considered to beadequate [17]. One more criterion that is commonly used toillustrate the adequacy of a fitted regression model is the

coefficient of determination (R2

) and adjusted R2

. For themodels developed the calculated R2 and adjusted R2 valuesare provided in Table 5. These values indicate that theregression model is quite adequate [17].

2.7 Testing the coefficients for significance

The values of the regression coefficients give an idea as towhat extent the factors affect the responses. Insignificantcoefficients can be eliminated without sacrificing much ofthe accuracy to avoid cumbersome mathematical labour. Toachieve this the t-test and F tests are used. The test of

significance was done automatically by the SYSTAT soft-ware. During backward steps, a variable is removed fromthe model and during forward steps, a variable is addedautomatically to the model. After determining the signif-

icant coefficients, the final models were constructed byusing only these coefficients.

3 Development of final model

The final mathematical models with parameters in codedform, as determined by the above procedure are presented

below:

P 0:971 0:093 I 0:062 S 0:016 N

0:047 I I 0:02 S S 0:039 N N

0:03 I S 0:042 I N 0:042 SN

(3)

R 4:417 0:143 I 0:253 S

0:038 N 0:067 S S(4)

W 10:531 1:539 I 0:46 S 0:069 N

0:3 N N 0:357 I N(5)

D 7:533 0:039 I 0:001 S 0:266 N

0:275 S S 0:237 N N 1:22 I N

0:375 I S 1:512 SN

(6)

3.1 Scatter diagrams

The validity of the regression models developed werefurther tested by drawing scatter diagrams. A typical scatterdiagram for the depth of penetration is shown in Fig. 4. Theobserved values and predicted values of the responses are

Fig. 2 Typical weld bead crosssections for experimental runs 4,6 and 7

Fig. 3 Typical weld bead ge-ometry traced for experimentalruns 10 and 15 using profileprojector

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scattered close to the 45 line, indicating an almost perfectfit of the developed empirical model [7].

3.2 Confirmation experiments

Experiments were conducted to verify the above developedregression equations (Eqs. 3, 4, 5, 6). Three weld runs weremade using different values of current, welding speed andnozzle-to-plate distance other than those used in the designmatrix and the bead parameters were measured using thesame procedure described in Sect. 2. The results obtainedwere quite satisfactory and the details are presented inTable 6.

4 Results and discussions

4.1 Direct effects of welding variables on beadgeometry

Based on the mathematical models developed for predict-ing the bead geometry and dilution, the effects of welding

process parameters on the bead parameters are presentedgraphically in Figs. 5, 6, 7 and 8. The effects of various

process variables on the bead geometry are presented underdifferent headings as follows.

4.1.1 Effects of process variables on depth ofpenetration

Figure 5 shows that an increase in current results inincreased penetration; thus current is the first parameter to

be considered for decreasing this depth. There is a decreasein penetration with an increase in welding speed; thereforeit assists in penetration control. This is due to the fact that,

at higher welding speeds, the weld pool becomes smaller providing lesser cushioning effect and causing deeperpenetration. If the nozzle-to-plate distance (N) is increased,the depth of penetration at first increases a little and thensharply diminishes.

4.1.2 Effects of process variables on reinforcement (R)

Figure 6 shows the effects of welding current (I), weldingspeed (S) and nozzle-to-plate distance (N) on reinforce-ment (R). It can be observed that an increase in weldingcurrent results in an increase in reinforcement, whereas

with an increase in welding speed, the reinforcement de-creases, which may be attributed to the fact that the fusionrate of the wire is kept constant for all the values of weldingspeeds. Though the height of reinforcement increasesslightly with increase in nozzle-to-plate distance, the effectof N on R is not significant.

4.1.3 Effects of process variables on bead width (W)

Figure 7 shows that the current and welding speed havecontrasting influence on width similar to reinforcement. Itcan be noted that the bead width increases with an increase

in current. Higher deposition rate with higher fluidity of themolten wire may be attributed for this increase in beadwidth with current. Though the nozzle-to-plate distancedoes not have much influence on W, compared to I and S,width first decreases a little and then increases with thefurther increase of N.

4.1.4 Effects of process variables on % dilution (D)

Effects of the welding current, welding speed and nozzle-to-plate distance are depicted in Fig. 8, which shows that

Table 5 ANOVA for the models developed

Bead geometry Sum of the squares Degrees of freedom Mean square F ratio P R2 (%) Adjusted R2 (%)

Regression Residual Regression Residual Regression Residual

Penetration (P) 0.269 0.014 9 10 0.030 0.0014 20.614 0.000 95 90

Reinforcement (R) 1.238 0.148 4 15 0.309 0.0100 31.371 0.000 89 87

Bead width (W) 37.644 4.699 5 14 7.529 0.3360 22.433 0.000 89 85

% Dilution (D) 34.086 4.496 8 11 4.261 0.4090 10.425 0.000 88 80

Tabulated values of F: F0.05 (9, 10) = 3.02; F0.05 (4, 15) = 3.06; F0.05 (5, 14) = 2.96; F0.05 (8, 11)= 2.95

Table 4 Estimated regression coefficients of mathematical modelfor bead geometry parameters

Coefficient Values of coefficients

P R W D

b0 0.971 4.417 10.531 7.533

b1 0.093 0.143 1.539 0.039

b2 0.062 0.253 0.460 0.001

b3 0.016 0.038 0.069 0.266

b1b1 0.047 0.029 0.205 0.171

b2b2 0.020 0.065 0.161 0.258

b3b3 0.039 0.008 0.333 0.220

b1b2 0.030 0.009 0.054 0.375

b1b3 0.042 0.024 0.357 1.220

b2b3 0.042 0.003 0.279 1.512

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the percent dilution increases to a maximum value andstarts decreasing when the values of N and S are increased.This may be due to the fact that the weight of depositedmetal per unit of length decreases when the welding speedincreases; however, on further increase in the weldingspeed, the depth of penetration decreases causing a declinein the dilution. Though the percentage dilution increaseswith an increase in welding current, but effect is not verysignificant.

4.2 Interaction effects of process parameterson bead geometry

4.2.1 Interaction effects of welding current andwelding speed on penetration

From Fig. 9, it is evident that P increases with an increasein welding current at all levels of welding speed. However,if the welding speed is increased above 34 cm/min, Pincreases with an increase in welding current, but the valueof P starts decreasing after reaching a higher value withfurther increase in welding current. This may be due to the

fact that, if the welding speed is reduced, the weld pool

becomes larger; penetration increases, but only to a certainlimit. With increasing welding current the weld pool be-comes larger but at the same time the weld pool cushionsthe arc and prevents deeper penetration.

4.2.2 Interaction effects of welding current andwelding speed on bead width

Figure 10 depicts the effect of I and S on W and it is evident

that the bead width decreases with an increase in weldingspeed for all levels of welding current.

The regions of various weld bead width for differentcombinations of I and S are depicted in Fig. 11 whichshows that, when I and S are increased together, there is anincrease in weld bead width.

4.2.3 Interaction effects of welding current andwelding speed on reinforcement

From Fig. 11, it can be observed that the reinforcementincreases with an increase in welding current for all levels

of welding speed, but it is also evident that the reinforce-

Fig. 4 Scatter diagram for pen-etration model

Table 6 Results of confirmation experiments

Expt. No. Parameters Measured values Predicted values using regression model % Error

I (A) S (cm/min) N (mm) P (mm) W (mm) R (mm) D (%) P (mm) W (mm) R (mm) D (%) P W R D

CON1 230 34 23 0.97 12.2 4.5 6.4 0.92 12.08 4.59 6.3 5.4 1 2 1.6

CON2 200 32 21 0.98 10 4.45 7 0.93 9.9 4.5 6.6 5.3 1 1.1 6

CON3 220 45 18 0.87 9.9 4.22 8.9 0.83 10.4 4.24 9.36 4.8 4.8 0.5 4.9

% Error Measured Value Predicted ValuePredicted Value

100

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6.2

6.4

6.6

6.8

7

7.2

7.4

7.6

-2 -1 0 1 2

I

S

N

%

Dilution(D)

Factors at coded values

Fig. 8 Direct effects of welding current (I), welding speed (S) andnozzle-to-plate distance (N) on % dilution (D)

4

4.2

4.4

4.6

4.8

5

-2 -1 0 1 2

S

N

I

Reinfo

rcement(R),mm


Fig. 6 Direct effects of welding current (I), welding speed (S) andnozzle-to-plate distance (N) on reinforcement (R)

0.65

0.75

0.85

0.95

1.05

1.15

-2 -1 0 1 2

S

N

I

Penetration(P),mm


Fig. 5 Direct effects of welding current (I), welding speed (S) andnozzle-to-plate distance (N) on penetration (P)

7.5

8.5

9.5

10.5

11.5

12.5

13.5

-2 -1 0 1 2

I

N

S

Width(W

),mm


Fig. 7 Direct effects of welding current (I), welding speed (S) andnozzle-to-plate distance (N) on bead width (W)

N = 20 mm

26

29

34

39

42

S, cm/min

1.20

1.00

0.80

0.60

170 190 210 230 250

Penetration(P),mm

Welding Current (I), Amps

Fig. 9 Interaction effects of welding current (I) and welding speed(S) on penetration (P)

Fig. 10 Surface plot for the interaction effects of welding current (I)and welding speed (S) on bead width (W) holding N at 20 mm (level 0)

Fig. 11 Surface plot for the interaction effects of welding current (I)and welding speed (S) on R holding N at 20 mm (level 0)

N = 20 mm

0

2

4

6

8

10

12

170 190 210 230 250

S=42 cm/min

S=39 cm/min

S=34 cm/min

S=29 cm/min

S=26 cm/min%D

ilution(D

)

Welding Current (I), Amps

Fig. 12 Interaction effects of welding current (I) and welding speed(S) on percent dilution (D)

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ment decreases with increasing welding speed for all levelsof welding current. Therefore, the current and weldingspeed can both be used to change the weight of metaldeposited per unit bead length.

4.2.4 Interaction effects of welding current andwelding speed on percent dilution (D)

Figure 12 shows the interaction effects of welding current(I) and welding speed (S) on percent dilution (D). Fromthe figure, it is evident that, if the welding speed isincreased, the value of D increases. But it is interesting tonote that, when the welding current increases, the percentdilution increases, provided that the welding speed isabove 34 cm/min. However the value of D decreases withthe increase in welding current, when the welding speed is

below 34 cm/min. At 34 cm/min, the effect of weldingcurrent is not significant and the value of D remainsunchanged for all levels of welding current.

5 Conclusions

1. Experiments conducted using DOE concepts wereapplied to develop regression models using responsesurface methodology to predict the weld beadgeometry for cladding of 317L flux cored wire onIS:2062 structural steel plates.

2. The values of P, W and R increase with the increase inwelding current, whereas these values decrease withthe increase in welding speed. However, the percentdilution increases with the increase in welding speed(S) and nozzle-to-plate distance (N) to a higher value

but starts decreasing on further increasing S and N.3. It was observed that interaction effects have consider-

able influence over the weld bead geometry and theireffects cannot be neglected.

Acknowledgements The authors wish to thank the All IndiaCouncil for Technical Education, New Delhi and University GrantCommission, New Delhi, India for their financial support for procuring the equipment and materials. The authors also wish tothank M/S Bhler Thyssen Welding, Austria, for sponsoring the317L flux cored wire to carry out this investigation.

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