Optimization of Pulsed Current TIG Welding Parameters on Al-Sic Metal Matrix Composite to Achieve Maximum Bending Strength

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Optimization of pulsed current TIG welding parameters on Al-SiC metal matrix composite to achieve maximum bending strength

Article in Advances in Natural and Applied Sciences · April 2017

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ISSN: 1995-0772 Published BYAENSI Publication EISSN: 1998-1090 http://www.aensiweb.com/ANAS 2017 Special 11(6): pages 416-422 Open Access Journal

Optimization of pulsed current TIG welding parameters on Al-SiC metal matrix composite to achieve maximum bending strength

1Sivachidambaram Pichumani, 2Raghuraman Srinivasan and 3Venkatraman Ramamoorthi

1,2,3School of Mechanical Engineering, SASTRA University, Thanjavur, India – 613401

Received 28 January 2017; Accepted 22 March 2017; Available online 28 April 2017

Address For Correspondence: Raghuraman Srinivasan, School of Mechanical Engineering, SASTRA University, Thanjavur, India – 613401 E-mail: [email protected]

Copyright © 2017 by authors and American-Eurasian Network for ScientificInformation (AENSI Publication). This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

ABSTRACT Pulse on time, pulse frequency, peak current and base current are the important parameters to be optimized in Pulsed Current TIG (PCTIG) welding of Al-SiC metal matrix composite. Experiments were designed and conducted using L9 orthogonal array technique. Various values obtained for optimal PCTIG welding parameters namely, peak current, base current, pulse on time and pulse frequency were 160A, 60A, 50% and 5Hz respectively. This resulted in a higher weld zone bending strength of 1.77KN. These results were achieved by developing regression equation & empirical model and were verified using experimental trail runs. This empirical model was also used for identifying significant factors which were responsible for improved weld zone bending strength.

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INTRODUCTION

In metal matrix composite, aluminium is an extensively used metal matrix material and SiC, TiB2, TiC, B4C are commonly used reinforcements [1]. Aluminium silicon carbide composite material is well known for its good wear resistance [2] and higher strength to weight ratio[3]. Stir casting process is mainly used for manufacturing of aluminium silicon carbide (Al-SiC) composite because of its higher production rate [4]. It also gives homogeneous mixture of aluminium metal matrix with silicon carbide particle reinforcement [5]. It is the most suitable and economical way of producing Al-SiC composite while compared to other manufacturing processes such as powder metallurgy route and spray coating process[6]. Welding of aluminium alloys and aluminium metal matrix composite materials using arc welding such as Tungsten Inert Gas (TIG) welding is comparatively cheaper. Major challenge of this is the reduced weld strength [7]. Constant current TIG welding on aluminium alloys causes reduced weld strength due to higher heat input and lesser cooling rate of weld pool. This results in coarse grain structure in weld zone and induces thermal stresses in heat affected zone [8]. During TIG welding of Al-SiC composite, SiC is dissociated into Silicon (Si) and Carbon (C). Further carbon combines with aluminium (Al) matrix and form (aluminium carbide) Al4C3 + (silicon) Si. Al4C3 phase is more brittle in nature, thus resulting in considerable loss in weld strength and ductility [9]. This restricts aluminium carbide formation during TIG welding on Al-SiC composite, resulting in chances of improved weld strength and ductility.

ToCite ThisArticle: Sivachidambaram Pichumani, Raghuraman Srinivasan and Venkatraman Ramamoorthi, Optimization of pulsed current TIG welding parameters on Al-SiC metal matrix composite to achieve maximum bending strength. Advances in Natural and Applied Sciences. 11(6); Pages: 416-422 417 Raghuraman Srinivasan et al., 2017/Advances in Natural and Applied Sciences. 11(6) Special 2017, Pages: 416-422

The problem of coarse grain microstructure during TIG welding on aluminium alloys could be rectified by using surface nucleation agent such as scandium [10], microcooler addition such as silicon and titanium powders [11], arc oscillation [12], effect of pulsing current method on aluminium alloy 6061 tensile behaviour [13] and pulsing current on aluminium alloy 7075 fatigue behaviour [14] so as to obtain fine grain microstructure. Among the above methods, pulsing current method has wide acceptance, as it can be employed in real time industrial applications with minimum modifications in the existing system [15]. In pulsed current TIG (PCTIG) welding, peak current gives adequate penetration and bead contour [16], while base current maintains stable arc. Pulse frequency gives enough time to transfer the heat from weld zone and heat affected zone to base material region [17]. This in turn reduces the width of the heat affected zone and thermally induced stresses [18]. From the literature [19] it is clear that the optimized PCTIG welding parameters gives reduced heat input, higher cooling rate and fine grain microstructure. This improves weld strength in aluminium alloys when compared to normal continuous current TIG welding. So this shows the significance of optimizing the PCTIG welding parameters. Regression equations were used to estimate the strength of the weld. Empirical model was developed by earlier researchers, to optimize the pulsed current welding parameters using various methods such as surface response method [20], Hooke and Jeevas algorithm [21] and Taguchi L8 orthogonal array method [22]. To study the outcome of PCTIG welding parameters like pulse on time, pulse frequency, peak current and base current on weld bending strength, empirical models and regression equations have to be developed. To predict the weld bending strength of Al-SiC composite same method could be followed. To formulate the empirical model and regression equation, Design Expert 7 statistical software was used.

Experiment: The experiments were carried out and the responses were recorded. The empirical relationships were developed to predict the weld zone bending strength using following steps. To know the working limits of the PCTIG welding parameters, on a 5mm plate of Al-SiC composite, number of trail runs were performed. Following results were observed from the trial runs.

Table 1: PCTIG welding parameters and levels Parameter Levels 1 2 3 Peak Current 140A 150A 160A Base Current 40A 50A 60A Pulse On Time 40% 50% 60% Pulse Frequency 2Hz 5Hz 10Hz

(1) When peak current was greater than 160 A, it resulted in excessive penetration of the weld. Lack of fusion and incomplete penetration were resulted when peak current was less than 140 A. So peak current values were chosen between 140A and 160A. (2) Unstable arc and arc wandering were observed when the base current was greater than 60 A. When the base current was reduced below 40 A, shorter arc length was formed. Thus welding cannot be performed under this condition. This resulted in lower working limit of base current of 40A and higher limit of 60A. (3) When the pulse frequency was less than 2 Hz, welded samples showed weld beads similar to that of constant current TIG welding. Arc spatter was observed when pulse frequency was greater than 10Hz. So working limit for pulse frequency was selected to be between 2Hz & 10Hz. (4) Overheating of tungsten electrode was observed when pulse on time was greater than 60%, where as when the pulse on time was less than 40%, it resulted in poor weld bead surface appearance. Setting lower limit and higher limit for pulse on time was chosen to be between 40% and 60%. Experimental runs were decided using 4 factors and 3 levels as given in the Table 1. Using Taguchi L9 orthogonal array, 9 experiments were designed and various conditions are furnished in Table 2.

Table 2: Experimental conditions for PCTIG welding and recorded responses PCTIG Peak Current (A) Base Current (A) Pulse On Time (%) Pulse Frequency (Hz) Bending strength Welding Condition (KN) 1 160 40 60 10 1.32 2 140 60 60 2 1.38 3 150 60 40 10 0.88 4 140 40 40 5 1.22 5 150 50 60 5 1.27 6 140 50 50 10 1.3 418 Raghuraman Srinivasan et al., 2017/Advances in Natural and Applied Sciences. 11(6) Special 2017, Pages: 416-422

7 160 50 40 2 0.99 8 160 60 50 5 1.46 9 150 40 50 2 0.88

Experiments were carried out using different pulsed current parameters designed with 4 factors and 3 levels of Taguchi L9 orthogonal array as mentioned in previous section. Autogenous welding was performed on Al- 8%SiC composite material with a plate thickness of 5mm using ADOR CHAMPTIG 300AD welding machine. Bend test was performed using same machine with the standard of ASTM E190 on sub sized sample with dimensions of 100mm x 30mm x 5mm (L x W x T). All the experimental results were observed and recorded and is furnished in Table 2. These experimental conditions and the resulting responses were fed to Design Expert 7 software. Using this software, regression equation and empirical model were developed, to predict the weld bending strength of Al-SiC composite and optimize the PCTIG welding parameters.

Developing empirical model: Statistical and mathematical techniques can be used for developing empirical relationships. By these techniques the influence of parameters on response can be studied easily. It can also be used for optimizing the conditions based on desired response and also be employed for predicting the response [16]. Experimental design was done in Design Expert 7 statistical software package making using of Taguchi L9 orthogonal array. Regression equation and correlation coefficients were also developed using Design Expert 7 statistical software. Peak current, base current, pulses on time and pulse frequency are the functions of weld zone bending strength. The empirical model developed using regression equation includes main factors and first order interaction of all factors. This can be expressed in the form of first order polynomial equation as specified in equation (1).

R  Z0  Z1  Z2  Z3  Z 4  Z12  Z 23 Z 41  Z 24  Z13  Z34 (1) R: Response as weld zone bending strength. A: Peak current, B: Base current, C: Pulse on time, D: Pulse frequency, Z0: Average response, Z1, Z2,..., Z34: Regression coefficients. The regression coefficients depend on, the main factors and interaction of factors. Regression co-efficient were solved in Design Expert 7 statistical software, to obtain regression equations and predict the weld zone micro hardness.

Table 3: Regression equation Response Regression equation Coefficient of correlation (r2) Bending strength R = 1.21 + (0.24*A) + (0.04*B) + (0.16*C) + (0.31*D) + (0.03*A*B) - 0.99 (0.02*B*C) + (0.52*C*D)

Correlation Coefficient 'r2' shows how nearer the predicted values are, to the experimental values. Correlation coefficients for regression equations are shown in Table 4. Values of correlation are having higher values and it was showing significant effect of main factors and their interactions with response. This was checked using analysis of variance (ANOVA). (Y Y )2 2  predicated average (2) r = 2 (Yexpermental Yaverage ) r2: Correlation Coefficient Y predicated: Predicated value of the response Y experimental: Experimental value of the responses Calculation of correlation coefficient using predicated value and experimental value for the same experimental condition was done using equation (2). Fig. 1 shows the graph with experimental values and predicated value of weld zone bending strength. From the graph it is clear that the percentage of error is below 3% between experimental value and predicated value. In Fig. 1, most of the predicated values and experimental values of weld zone bending strength coincides each other, consistent result were obtained through regression equation for weld zone bending strength. Hence the regression models are valid within the range of pulsed current parameters.

419 Raghuraman Srinivasan et al., 2017/Advances in Natural and Applied Sciences. 11(6) Special 2017, Pages: 416-422

Fig. 1: Predicted value vs actual value of weld zone bending strength.

Table 4 shows the percentage of error between experimental value and predicated value developed using regression equation. These values were plotted into error graph in Fig. 1.

Table 4: Percentage of error in bending strength PCTIG welding condition Experimental Value (KN) Predicated Value (KN) Percentage of Error (%) 1 1.32 1.32 0.20 2 1.38 1.38 0.32 3 0.88 0.89 -0.61 4 1.22 1.23 -0.59 5 1.27 1.30 -2.25 6 1.3 1.29 0.83 7 0.99 1.00 -0.90 8 1.46 1.45 0.98 9 0.88 0.86 2.03

Fig. 2: Bending strength – (pulse on time – 50%, pulse frequency – 10Hz)

Analysis of contour plots: The Contour plots were generated using Design Expert software to study the interaction effect of pulsed current TIG welding parameters such as pulse on time, pulse frequency, peak current and base current on weld zone bending strength. Fig. 2 to Fig. 6 shows contour plots which predict the weld zone bending strength with X-axis as base current & Y-axis as peak current. Pulse on time and pulse frequency values were made constant in all graphs. Comparison of these graphs shows the effect of pulsed current parameters on weld zone bending strength. This is explained in the following sections. Using regression equation, weld zone bending strength was optimized. Pulsed current TIG welding parameters such as peak current, base current, pulse on time and pulse frequency were developed using Design Expert statistical software. Optimized condition result was observed and depicted in Fig.7. Three trail runs were performed in the optimized pulsed current TIG welding condition with pulse on time of 50% and pulse frequency of 5Hz. This is due to the limitation of PCTIG welding machine specification. PCTIG welding parameters and weld zone bending strength from trail runs are tabulated in Table 5.

420 Raghuraman Srinivasan et al., 2017/Advances in Natural and Applied Sciences. 11(6) Special 2017, Pages: 416-422

Fig. 3: Bending strength – (pulse on time – 50%, pulse frequency – 2Hz).

Fig. 4: Bending strength – (pulse on time – 60%, pulse frequency – 5Hz)

Results in figures 2 and 3 shows that the bending load is 1.18KN when pulse on time is considered to be 50%, peak current is 160A and base current is 50 to 60A with 10Hz and 2Hz pulse frequency. In figure 4, it is observed that the bending load is 1.35KN for the pulsed current parameter conditions such as peak current of 160A, base current of 60A, pulse on time of 60% and pulse frequency of 5Hz. When the pulse on time is 40%, peak current is 150-160A, base current is 40-50A, pulse frequency is 5Hz it resulted in 1.47KN of bending load as shown in 5. The maximum bending load of 1.68KN was observed for peak current of 160A, base current of 60A, pulse on time of 50% and pulse frequency of 5Hz as depicted in figure 6.

Fig. 5: Bending strength – (pulse on time – 40%, pulse frequency – 5Hz).

Table 5: Optimized value vs experimental Description Optimized Actual Condition Condition Peak Current (A) 160 160 Base Current (A) 60 60 Pulse On Time (%) 54.79 50 Pulse Frequency (Hz) 5.12 5 Predicted Value Experiment Value Desirability = 0.99 Trail 1 Trail 2 Trail 3 Bending strength (KN) 1.77 1.65 1.62 1.68

421 Raghuraman Srinivasan et al., 2017/Advances in Natural and Applied Sciences. 11(6) Special 2017, Pages: 416-422

Fig. 6: Bending strength – (pulse on time – 50%, pulse frequency – 5Hz)

It was observed that a slightest variation in pulse frequencies below and above 5Hz, resulted in reduced bending load. Pulse on time, peak & base current differences also has great significance on bending load. From Table 5, it shows that the consistent result was obtained from the optimized condition developed using regression equation. Fig.7 shows increase in peak current and base current as 3:1 ratio with pulse on time as 50-55% and pulse frequency 5-6Hz showed higher weld bending strength.

Conclusions: Regression equation was developed to predict the weld zone bending strength of Al-8% SiC composite, welded using PCTIG welding. PCTIG welding parameters like pulse on time, pulse frequency, peak current and base current were closely studied. Using regression equation, empirical model was developed to obtain, optimized results for the PCTIG parameters. The resultant optimized values for pulse on time, pulse frequency, peak current and base current were 54.79%, 5.12Hz, 160A and 60A respectively. Optimized predicted value of weld zone bending strength has been observed as 1.77 KN. Trail runs were performed for optimized PCTIG welding condition to check the consistency of the model, which resulted only 8% of deviation between experimental values and predicted values. This deviation is due to the change in value of pulse on time of 50% instead of 54.79% and pulse frequency of 5Hz instead of 5.12Hz. The effect of each PCTIG welding parameters and interaction between two or more parameters on weld zone bending strength were studied. Key findings of the study of PCTIG welding on Al-8%SiC composite 5mm thick plate within a chosen set of parameters were, (a) Peak current & base current should be 160A & 60A respectively, (b) Pulse on time is recommended to be 50% to 55%, (c) Recommended pulse frequency to be 5Hz.

ACKNOWLEDGMENT

This study was supported by SASTRA University R&M funding (SASTRA/ R&M/ 0028/ SoME-005/ 2012-13). Authors gratefully acknowledge SASTRA University, Thanjavur, India for the same..

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