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JWJ > Volume 38(2); 2020 > Article
Kakaei-Lafdani and Valehi: Numerical Model for Powder Consumption, HAZ Width and Toughness in Tandem Submerged Arc Welding


The two wire tandem submerged arc welding (TSAW) process has attracted widespread attention as an automated welding method in various industries. It provides several advantages including good welding quality and high deposition rate. However, the complexity of arc behavior leads to difficulties in adjusting the main affecting parameters such as amperage, voltage and the nozzles assembly. In the present investigation, a response surface methodology (RSM) and Taguchi’s orthogonal array technique were carried out to determine the influence of the amperage and the voltage of DC and AC currents as well as the assembly of nozzles on the width and toughness of HAZ as well as the consumption of welding powder. The results confirmed the effectiveness of the developed models for predicting experimental evidence with high precision. The input parameters including amperage, voltage and the assembly of nozzles were subsequently adjusted to minimize the HAZ width and powder consumption as well as to maximize HAZ toughness.

1. Introduction

Submerged arc welding (SAW) has been extensively used in various industries, where thick sheets with long welds are involved, e.g. pipe fabrication, ship building and pressure vessels. Compared with other welding methods, higher rate of deposition is obtained by SAW process. It encounters as the main distinguishing feature of SAW method1-3). Compared to conventional SAW process, using the second (trailing) wire in this process (Tandem submerged arc welding) leads to higher productivity as a result of more deposition rates4). However, the complexity of arc behavior leads the setting of amperage and voltage as well as the assembly of nozzles to be more sensitive than the ones for conventional single wire submerged arc welding (SAW) process. Due to strong nonlinearity, numerical simulation promotes the adjustment of main parameters in order to optimize the resulting HAZ length and the powder consumption.

1.1 Heat affected zone (HAZ)

Submerged arc welding is one of the main technological operations in the manufacture process of pipes. However, this method has a significant drawback because of large heat input extends heat affected zone (HAZ) and decreases mechanical properties5).
In fact, the width of HAZ represents the length of a region in which metallurgical changes as well as microstructural evolutions occur. Therefore, controlling the length of this region in order to minimize the metallurgical evolutions leads to improve considerably the mechanical properties of weld6). Heat affected zone affects the mechanical properties of the weld material as the HAZ microstructure has a strong influence on the weld joint properties7).
To a certain extent the HAZ size reflects on the grain coarsening and toughness; a larger/wider HAZ indicates larger grains in the HAZ and thus poor toughness. On the other hand, a narrower HAZ indicates a steeper thermal gradient and thus a faster cooling rate and shorter soaking time and thus finer grain size and better toughness8). Few numerical investigations have been carried out on modeling of HAZ length in SAW method, focused only to address the conventional single wire submerged arc welding8,9). To the best of the author’s knowledge, no attempts have been made until now to analyze the effect of main parameters (amperage and voltage) of AC current, in conjunction with DC current, on the resulting HAZ. Therefore, in the present study, the emphasis is placed on the analysis of the effect of amperage and voltage of DC and AC currents in tandem submerged arc welding (TSAW) on the width of HAZ and its impact toughness. The results show an inverse relationship between the width of HAZ and its impact toughness. Also, among all parameters, I (DC) plays pivotal role regarding both the width of HAZ and its impact toughness.

1.2 powder consumption

In SAW process, the arc is protected by using granular powders (flux) consisting of silica, manganese oxide, calcium fluoride and other compounds. The thick layer of flux covers entirely the molten metal and thus suppresses spark, fumes and ultraviolet radiation that are typical of Shield metal arc welding (SMAW) process10).
Up to now, a large number of studies have been devoted, emphasizing in characterization and optimization of parameters affecting SAW process11-13).
It should be emphasized, however, that few investigations have been carried out to demonstrate the role of parameters influencing the powder consumption in SAW process. Moreover, the mentioned studies have focused only on optimization of parameters in single-wire SAW process which has limited industrial significance. Krishankant et al14) have studied the effect of parameters such as amperage, voltage, welding speed and wire stick out on the powder consumption in single-wire SAW process. The results reveal the voltage plays a significant role in powder consumption. In the present paper, Taguchi method has been carried out to analyze, for the first time, the influence of the assembly (heights, distances and angles) of nozzles on powder consumption in TSAW process. Results reveal that nozzles’ distance is the most influential factor as powder consumption is concerned.

2. Research method

2.1 HAZ

Fabrication of large-diameter pipes is commonly performed by spiral method. In this process, deformed steel coils are spirally welded (as two-side form: internally and externally). Fig. 1 represents the schematic of the external tandem welding for a pipe. In this method, two feed wires, lead wire and trail wire, are utilized independently, operating with DC and AC, respectively. However, the deposition of both wires occurs simultaneously in one weld pool. The specimens prepared by the spiral machine, made by HOESCH Co. (Germany). The pipe mill machine capable of producing pipes with diameters of 16 to 81 inch and the material grades of St37 to X60. Furthermore, a direct current (DC) power supply with constant current and also an alternating current (AC) power supply made by Lincoln Electric Co. were used. The chemical composition of base metal and the specification of the wire and flux are given in Table 1 and Table 2, respectively.
Fig. 1
Schematic representation of TSAW of a pipe
Table 1
Chemical composition of steel
Fe C Si Mn Al S P
98.9 0.142 0.124 0.610 0.035 0.007 0.006
Table 2
Specification of the wire and flux
Welding wire Welding Flux
Inside and outside welding Inside and outside welding
Specification No. (SFA) 5.17 Specification No. (SFA) 5.17
AWS No. EM12 AWS No. F7A4
F.No. 6
A.No. 1 Trade name Kavoshjoosh co.
Size of welding wire (mm) 3-4 Drying tem. (˚C) NA
Trade name Kavoshjoosh co.
In this study, direct current (DC) and alternating current are assumed as the selected variables. Respond surface method (RSM) was used in order to analyze the influence of input parameters on the width and toughness of HAZ. Design of experiment is a structured and organized method used to determine the relationship between the different factors affecting a process and output of that process15).

2.1.1 Model development

Design of experiments (DOE) and regression analysis helps in retrieving a response for independent input parameters. In RSM, the independent input parameters can be shown quantitatively by:
where ε denotes the error seen in response y and surface expressed by f(x1,x2,x3,…,xn) is known as response surface. The response can also be shown by graphical method in the contours plots or three-dimensional space that will help to anticipate shape of response surface.
RSM suitability is determined with the approximation of f. Due to the interaction between variables and surface curvature, lack of fit is formed in first order model so to improve the optimization process in second-order model. An ordinary second order model is given by
where, aii denotes the quadratic effect of xi, ai denotes the linear effect of xi and aij denotes line to line interaction between xi and xj where xi and xj are the design variables. This quadratic model allows to locate the region of optimality besides investigating the entire factor space16). Experimental design was performed with RSM, utilizing the software of Design Expert. Table 3 represents various levels of welding variables.
Table 3
Various levels of amperage and voltage
Parameters Symbol Levels
-2 -1 0 1 2
Direct Amp I(DC) 1000 1050 1100 1150 1200
Direct Volt V(DC) 28 31 34 37 40
Alternate Amp I(AC) 400 430 460 490 520
Alternate Volt V(AC) 28 31 34 37 40
After the welding process, metallographic and charpy V-notch impact specimens were prepared for each trial and tested at 0 °C. The ASTM E23 standard was used to prepare the toughness test specimen. The dimensions of toughness specimens were 55 × 10 × 10 mm with 2 mm deep V-notch.
Thorough examination of weld sections was carried out using stereoscopy and then the width of HAZ was measured by quantitative techniques, performed by Image Analyzer. The results are given in Table 4, as responses.
Table 4
HAZ design matrix
Run DC (I) DC (V) AC (I) AC (V) HAZ (mm) Toughness (J)
1 1100.00 28.00 460.00 34.00 2.08 154
2 1100.00 34.00 460.00 34.00 2.06 155
3 1100.00 34.00 460.00 40.00 2.4 127
4 1100.00 34.00 460.00 34.00 1.99 159
5 1050.00 31.00 490.00 37.00 1.97 164
6 1100.00 34.00 460.00 34.00 2.1 145
7 1100.00 34.00 460.00 34.00 2.1 149
8 1150.00 37.00 490.00 31.00 2.36 130
9 1100.00 40.00 460.00 34.00 2.19 142
10 1150.00 37.00 430.00 31.00 2.28 132
11 1150.00 31.00 490.00 31.00 2.1 147
12 1050.00 37.00 490.00 31.00 1.99 162
13 1200.00 34.00 460.00 34.00 2.61 118
14 1050.00 31.00 490.00 31.00 1.88 165
15 1050.00 37.00 430.00 31.00 1.94 164
16 1150.00 31.00 490.00 37.00 2.6 126
17 1100.00 34.00 460.00 34.00 2.26 141
18 1050.00 37.00 490.00 37.00 2.11 145
19 1100.00 34.00 460.00 34.00 2.06 155
20 1100.00 34.00 460.00 28.00 2.02 158
21 1050.00 37.00 430.00 37.00 1.98 164
22 1100.00 34.00 460.00 34.00 2.13 143
23 1150.00 37.00 430.00 37.00 2.29 130
24 1100.00 34.00 400.00 34.00 2.09 151
25 1000.00 34.00 460.00 34.00 1.83 166
26 1050.00 31.00 430.00 31.00 1.78 178
27 1050.00 31.00 430.00 37.00 2.05 157
28 1150.00 31.00 430.00 37.00 2.28 132
29 1100.00 34.00 520.00 34.00 2.2 141
30 1150.00 37.00 490.00 37.00 2.37 129
31 1150.00 31.00 430.00 31.00 2.1 147
The travel speed is considered to remain constant at 1.75 m/min. For all the test samples, other parameters such as electrodes angles (0̊ for lead wire and 20̊ for trail one) and distances (25 mm) were fixed during welding.
To ensure proximate fitting by a quadratic model, the effectiveness of regression, testing of model coefficients and evaluation of lack of fit (LOF), analysis of variance (ANOVA) method was used. The principles of this method are constructed on the independence and uniform distribution of errors.
When the LOF statistics in ANOVA table becomes insignificant, it means that the related model is trying to fit data completely. The model of HAZ length is expressed by equation (3).
HAZ = - 10.53341 + 3.53333 × 10-3 I(DC) + 0.21389 × V(DC) + 1.25 × 10-3 × I(AC) + 0.23056 × V(AC) + 0.97222 × 10-3 × V(DC) × V(AC) (3)
Where I(DC), V(DC), I(AC) and V(AC) denote ampere of direct current for lead electrode, voltage of direct current for lead electrode, ampere of alternate current for trail electrode and voltage of alternate current for trail electrode, respectively. This relation is obtained after the elimination of insignificant terms from the analysis.
The ability of a model for covering all considered parameters is defined by mean R2 and R2 adj which is necessary for both of them to be close to each other and equal to 100% ideally. Also, predictability of a model to forecast new points in experimentation limits is described via R2 pre that could be raised up to 100% theoretically. PRESS is a quantity that reveals the deviation between the fitted values via model and real observations. This deviation should be at minimum. Table 6 has summarized the adequacy statistics of the suggested models. These evidences imply that the presented models are acceptable reasonably.
Table 5
ANOVA results for HAZ width
Source Sum of Squares df Mean Square F Value p-value PCR
Model 1.02 5 0.2 34.66 < 0.0001 -
A-DC (I) 0.75 1 0.75 127.54 < 0.0001 64
B-DC (V) 0.025 1 0.025 4.32 0.0482 2.15
C-AC (I) 0.034 1 0.034 5.75 0.0243 2.9
D-AC (V) 0.16 1 0.16 27.81 < 0.0001 13.7
BD 0.046 1 0.046 7.87 0.0096 3.9
Residual 0.15 25 5.87E-03 - - 12.9
Lack of Fit 0.11 19 5.53E-03 0.79 0.6788 -
Table 6
Model adequacy statistics
R-Squared Adj. R-Squared Pred. R-Squared Adeq. Precision PRESS
0.87 0.85 0.81 21.84 0.22

2.1.2 Data Analyzing

According to the percent of contribution (PCR) in table 5, calculating by dividing the Sum of Square of each term by total Sum of Squares and shows the amount of each factor contribution in the response, the largest portion in HAZ length is related to I(DC) which might be due to this fact that I(DC) constitutes the largest portion of weld volume. Also the effect of V(AC) on the HAZ length is more than that of V(DC) and there is an interaction between them in Fig. 2.
Fig. 2
The interaction effect of V(DC) × V(AC) on the HAZ width; High level of AC (V) and low level of AC (V) indicate with red lines and black lines, respectively
Obviously, at low levels of V(AC), V(DC) has more significant impact on the width of HAZ than V(AC). The effects of the parameters are shown in Fig. 3.
Fig. 3
The effect of inputs on HAZ width
The results indicate that the amperage has a great impact on the width of HAZ, and hence, it seems that decreasing of amperage is the most effective way to reduce the mentioned width. However, the main issue which arises from the high impact of amperage on the characteristics of weld such as weld profile and deposition rate, is how to decrease the amperage to make minimum effect on these aforementioned properties. This issue can be satisfied by considering Eq. (4) as a relation between the deposition rate (kg/h), amperage (A), electrode extension (mm) and electrode diameter (mm):
where A, B and C are constants. Decreasing the diameter of wire from 4 to 3mm in such a way that the other parameters are maintained in Eq. (3) remain constant, permits nearly about 25% reduction in amperage value while the deposition rate is maintained at a constant value. Thus, using a wire with smaller diameter can be encountered as a practical way in order to reduce the width of HAZ in the tandem method. Fig. 4 displays the effect of the parameters on the impact toughness of HAZ.
Fig. 4
The effect of inputs on HAZ toughness
As can be expected, all input parameters have negative effect on toughness which is well consistent with HAZ width results. Similar to HAZ width, I (DC) is the most influential factor regarding HAZ toughness. Consequently, as mentioned before, there is an inverse relationship between HAZ expanding and impact toughness where I (DC) has a critical role in this arena.
The model of impact toughness is expressed by equation (5). This relation is obtained after the elimination of insignificant terms from the analyses.
Toughness = 584.33513 - 0.26833 × I(DC) - 1.16667 × V(DC) - 0.077778 × I(AC) - 1.94444 × V(AC) (5)
Where I(DC), V(DC), I(AC) and V(AC) denote ampere of direct current for lead electrode, voltage of direct current for lead electrode, ampere of alternate current for trail electrode and voltage of alternate current for trail electrode, respectively

2.1.3 Optimization

The final attractive achievement is the suggestion of the best parameter setting in order to achieve minimum length of HAZ and maximum impact toughness.
Desirability function is an efficient method in solving RSM multi-characteristics. It uses a transform function D(x) that converts values of real observations to a non-dimension scalar di. The values of di generally alter from 0 to 1 where 0 denotes unacceptable case and 1 represents the ideal state. Composite desirability is the weighted geometrical mean of single desirability for each response in multi-response problems. When the total desirability is maximized, optimal conditions are reached17). Fig. 5 describes the conditional statements that have been adjusted to minimize HAZ length.
Fig. 5
Accordingly, the value of composite desirability is taken as 0.944418 which clearly indicates satisfied condition of optimization. After optimization, the optimal parameter solution for the response is provided as follows
I (DC) = 1050, V(DC) = 31, I(AC) = 430, V(AC) = 31
Validation tests based on the results that are previously obtained from optimization were performed. The percentage error is the difference between retested values and the predicted values by the regression model. It means when the errors were diminished, the process and its relative response surfaces were reliable to implement a good reproducibility. The error is shown in Table 7 for the responses. The cross section of the weld bead obtained by optimal welding parameters is illustrated in Fig. 6.
Table 7
Comparison between actual and optimized results
Inputs Responses
I(DC) V(DC) I(AC) V(AC) HAZ Toughness
Predicted 1050 31 430 31 1.79 173
Retested 1.82 178
Error 1.7% 2.9%
Fig. 6
The details of the cross section for the optimal welding

2.2 Powder consumption

The assembly of nozzles is another main factor, influencing the weld appearance, weld quality and powder consumption in TSAW process. The variation in assembly of nozzles not only affects the amount of powder consumption, but also alters the weld profile and quality. Thus, it is significant to understand the influence of adjustment of distances on various welding parameters.
The TSAW process, two wires with DC and AC currents are utilized in close to each other, to prevent the arc blow phenomenon. The former with DC current has a major role in determining the penetration depth, while the latter with AC current controls the weld appearance. It is noteworthy to mention that high welding speeds up to 2m/min can be provided by using multi-wire system in SAW process. The nozzles in DC welding is usually assembled in a vertical form to provide the maximum penetration. Thus, in the present study, the vertical constant angle is also considered for DC welding. Moreover, the parameters have been considered such that the qualified weld achieves in practical TSAW process.

2.2.1 Model Development

The parameters affecting the nozzle assembly and the corresponding levels are given in Table 8.
Table 8
Input parameters and their levels
Parameters Level 1 Level 2 Level 3
Nozzles distance 20 23 26
AC stick out 18 22 26
DC stick out 18 22 26
AC angle 20 25 30
Taguchi method was carried out to perform the experiment on the basis of the standard (orthogonal) array L9, the selection of which was introduced by 4 input parameters and 3 levels for each parameter.
Taguchi method as a robust design process was proposed and developed by Genichi Taguchi, widely used to improve engineering productivity. Basically Taguchi was developed to improve the quality of product, soon after its application was extended to other fields. A Full Factorial Design requires a large number of experiments and it becomes complex, if the number of factors increase. To overcome this problem Taguchi uses a special design of orthogonal array to study the entire process parameter space with a small number of experiments10). In order to analyze the outcomes, the Taguchi method uses a statistical measure of performance called signal-to-noise (S/N) ratio. S/N ratio measure the deviation of quality characteristics from desired values, including the higher-the-better (HTB), the nominal-the-better (NTB) and the lower-the-better (LTB)19,20). The product quality can be improved by maximizing the signal to noise ratio for the respective product21). The S/N ration in Taguchi’s method is obtained by giving formula
where Yi and n are the ith observed value of response and average value of observed response. “Smaller the better approach” (equation (6)) is followed for the response parameter which we desire to be minimum and “larger the better approach” (equation (7)) is followed for response parameter which we need to be maximum18).
Based on the type of solution, which is the amount of the welding powder consumption, the aim is defined as minimizing this consumption, where S/N ratio is obtained via Eq. (6). The powder consumption in experiments is given in Table 9.
Table 9
The values of experimentations
Distance AC Stick out DC Stick out AC Angle Flux consumption (gr)
20 18 18 20 70.35
20 22 22 25 77.4
20 26 26 30 75.7
23 18 22 30 91.5
23 22 26 20 77.9
23 26 18 25 85.9
26 18 26 25 94.35
26 22 18 30 100.6
26 26 22 20 65.79
To illustrate the effect of each adjusted parameters on powder consumption, variance analysis was performed (Table 10).
Table 10
ANOVA results for powder consumption for S/N
Source DF Sum of squares Adj. Sum of squares Adj. Mean Square F P
Distance 2 4.7694 4.7694 2.38469 41.7 0.023
AC stick out 2 0.4217 0.4217 0.21086 3.69 0.213
AC angle 2 3.0287 3.0287 1.51437 26.48 0.036
Residual error 2 0.1144 0.1144 0.05718 - -
Total 8 8.3342 - - - -
As depicted in Table 10, the variables of nozzle distance and angle of AC wire are the most effective parameters to determine the powder consumption. Indeed, the influence of input parameters on the amount of consumption is depicted in Table 11.
Table 11
Rank of inputs on the response
Level Distance AC stick out AC angle
1 -37.43 -38.56 -37.6
2 -38.58 -38.55 -38.65
3 -39.19 -38.1 -38.95
Delta 1.76 0.46 1.35
Rank 1 3 2
Two coefficient of R-sq = 97.93% and R-sq(adj) = 91.72% confirm the accuracy of the proposed model in experimental space.

2.2.2 Data Analyzing

One of the significant achievement in this research, can be encountered as preparing the samples in shop (practical) conditions such that the specimens were prepared from the pipes with diameter of 1622 mm and the thickness of 14.27 mm. The welding Characteristics is shown in Table 12.
Table 12
Welding characteristics
Outside Weld Speed (m/min)
DC AC Flux Wire Dia. (mm) 1.1
Amp. Vol. Amp. Vol.
1100 32 460 35 KJF 610 4 3
As shown in Table 11, three input parameters including nozzle distances, AC angle and AC height have the greatest effect on powder consumption, respectively. Fig. 7 represents the effect of input parameters on S/N ratio. The S/N ratio is a combination of both average and variance of response and we need those levels of inputs whose S/N ratios are maximum in order to minimize powder consumption. Consequently, according to Fig. 7, minimum amount of powder consumption can be obtained by adjustment of nozzles as follows
Distance = 20 (mm), AC Stick out = 26 (mm), AC Angle = 20̊
Fig. 7
The effect of inputs on S/N ratio
Regarding the nozzles setting in the TSAW, there are some pragmatic points which should be addressed accordingly. Increasing the nozzle distance, extends the bead width, accompanied by consumption of more powder to protect the weld. As far as the adjustment of nozzle distance in the TSAW is concerned, it is necessary to mention the significant influence of nozzle distance on profile and quality of the final weld, such that increasing this distance leads to extend the bead width and also decrease the weld height. However, it is essential to adjust the mentioned distance to prevent the formation of distinct two weld pools which in turn results an irregular weld line and probable weld defects such as porosity. On the other hand, the decrease in the distance of nozzles leads to decrease the weld width, whereas the height of weld reinforcement increases.

3. Conclusion

TSAW is encountered as a complex process when compared with conventional SAW, emphasizing the sensitivity of the adjustment of main parameters. In this research impact toughness and the width of heat affected zone as well as powder consumption in tandem submerged arc welding (TSAW) process has been experimentally scrutinized. The direct voltage V(DC), alternating voltage V(AC), direct amp I(DC), alternating amp I(AC), nozzles distance, stick out as well as nozzles angles were considered as input parameters during the external welding of a spiral steel pipe. In order to discern the effect of the aforementioned input parameters and finding those settings causing impact toughness become maximized and HAZ width and powder consumption to be minimized, respond surface modeling and Taguchi method have been used. The results of this study can be summarized accordingly:
  • I(DC) is the most influential parameter as far as impact toughness and HAZ width are concerned; by increasing I(DC), HAZ width considerably increases while impact toughness tend to decrease.

  • There is a clear connection between HAZ width and impact toughness of HAZ; by increasing HAZ width, impact toughness decrease.

  • The most effective way to reduce I(DC) and consequently HAZ width would be using SAW wires with smaller diameters.

  • As can be seen, there is an interaction between V(DC) and V(AC) so that the effect of V(DC) on increasing the width of the HAZ is apparently higher at low level of V(AC).

  • Regarding the width of the HAZ, the influence of I(DC) is undoubtedly greater than I(AC). Conversely, V(AC) seems to be more influential in comparison with V(DC).

  • As can be expected, similar to single wire, current has no effect on the consumption of powder in the tandem method.

With regard to the nozzles setting, nozzles distance in addition to AC nozzle angle play pivotal role in the powder consumption, such that it rises with increasing both mentioned parameters.
  • AC wire stick out has a greater effect on the powder consumption than that of DC one. By increasing the wires stick out, the powder consumption decreases gradually.

  • Generally, all the changes increasing the weld width, will increase the powder consumption.


1. Yawar J, Lal H. Effect of Various Parameters on Flux Consumption, Carbon and Silicon in Submerged Arc Welding (Saw). Int. J. Emerg. Technol. 6 (2) (2015), 176–180

2. Singh R.P, Garg R.K, Shukla D.K. Mathematical modeling of effect of polarity on weld bead geometry in submerged arc welding. J. Manuf. Process. (2016), 21 14–22
3. Barbosa L.H, Modenesi P.J, Godefroid L.B, Arias A.R. Fatigue crack growth rates on the weld metal of high heat input submerged arc welding. Int. J. Fatigue. (2019), 119 43–51
4. Tsuyama T, Nakai K, Tsuji T. Development of submerged arc welding method using hot wire. Weld. World. 58 (5) (2014), 713–8
crossref pdf
5. Derevyagina L.S, Gordienko A.I, А.М. Orishich Malikov A.G, Surikova N.S, Volochaev M. N. Micro- structure of intercritical heat affected zone and toughness of microalloyed steel laser welds. Mater. Sci. Eng. A. 770 (2020),
6. Luo J, Dong Y, Li L, and X, Wang . Microstructure of 2205 duplex stainless steel joint in submerged arc welding by post weld heat treatment. J. Manuf. Process. 16 (1) (2014), 144–148
7. Singh B. Correlation of Flux Ingredients with Width HAZ. J. Weld. Join. 36 (1) (2018), 76–81
crossref pdf
8. Lee C. S, Chandel R. S, Seow H. P. Effect of Welding Parameters on the Size of Heat Affected Zone of Submerged Arc Welding. Mater. Manuf. Process. 15 (5) (2000), 649–666
9. Gunaraj V, Murugan N. Rediction of heat affected zone characteristics in submerged arc welding of structural steel pipes. Weld. Res. 81 (3) (2002), 94–98

10. Choudhary S, Shandley R, Kumar A. Optimization of agglomerated fluxes in submerged arc welding, Materials Today. Proc. 5 (2) (2018), 5049–5057

11. Gunaraja V, Murugan N. Application of Response surface methodology for predicting weld bead quality in submerged are welding of pipes. J. Mater. Process. Technol. 88 (1-3) (1997), 266–275
12. Sailender M, Ch G, Reddy andraMohan, Venkatesh S. Influences of process parameters on weld strength of low carbon alloy steel in purged SAW. Mater. Today Proc. 5 (1) (2018), 2928–2937
13. Kumara A, Maheshwarib S, Kumar S. Sharma Fuzzy Logic Optimization of Weld Properties for SAW Using Silica Based Agglomerated Flux. Proc. Comput. Sci. (2015), 57 1140–1148
14. Krishankant S. Jindal, Kant S. Shekhar Determination of Flux Consumption in Submerged arc Welding by the Effect of Welding Parameters by Using R .S.M Techniques. Global J. Res. Eng. Mech. Mech. Eng. 12 (2) (2012), 21–24

15. Muthu M, Krishnan Maniraj J, Deepak R, Anganan K. Prediction of optimum welding parameters for FSW of aluminium AA6063 alloys and A319 using RSM and ANN. Mater. Today:Proc. 5 (1) (2018), 716–723
16. Singh N, Routara B.C, Das D. Study of machining characteristics of Inconel 601in EDM using RSM. Mater. Today:Proc. 5 (2) (2018), 3438–3449
17. Myers H, Montgomery D. C. Response surface me- thodology, process and product optimization using design experiments. NJ: John Wiley &Sons Inc Hoboken, USA; (2009), p. 349–362

18. Reddy S, Vempati K, Raju Brahma, Venkata K. Subbaiah Optimization of Welding Parameters of Ti 6al 4v Cruciform shape Weld joint to Improve Weld Strength Based on Taguchi Method. Mater. Today:Proc. 5 (2) (2018), 4948–4957
19. Hou T. H, Su C. H, Liu W. L. Parameters optimization of a nano-particle wet milling process using the Taguchi method, response surface method and genetic algorithm. Powder Technol. 173 (3) (2007), 153–62
20. Alafaghani A, Qattawi A. Investigating the effect of fused deposition modeling processing parameters using Taguchi design of experiment method. J. Manuf. Proc. (2018), 36 164–174
21. Naik A. B, Reddy A. C. Optimization of Tensile Strength in TIG Welding Using Method Taguchi and Analysis of Variance (ANOVA). Therm. Sci. Eng. Prog. 8 (2018), 327–339
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