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Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint
Materials Today: Proceedings xxx (xxxx) xxx
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint A. Sasikumar a,⇑, S. Gopi a, M. Sathish Kumar b, L. Selvarajan c a
Department of Production Engineering, Government College of Technology, Coimbatore 641013, India Department of Mechanical Engineering, SNS College of Engineering, Coimbatore 641107, India c Department of Mechanical Engineering, Mahendra Institute of Technology, Namakkal 637503, India b
a r t i c l e
i n f o
Article history: Received 13 November 2019 Received in revised form 8 January 2020 Accepted 11 January 2020 Available online xxxx Keywords: Friction stir welding Aluminium alloy Powder mixing ratio Response surface methodology Tensile strength
a b s t r a c t Friction Stir Welding (FSW) process parameters and tool parameters are playing pivotal role in the weld joint characteristics. The combination is selected for the investigation of AA6082 and AA5052, which finds major application in ship structural frame and building constructions. Along with these usual parameters the composition of filler elements is considered in this work to improve the weld joint strength. The process parameters considered in this study are rotational speed, welding speed, shoulder penetration, filler holes center distance, and powder mixing ratio. The Central Composite Design (CCD), the most commonly used Response Surface Methodology (RSM) is considered to develop the prediction equation. A validation analysis is carried out and the results were compared with the relative impact of input parameters on tensile strength. The maximum tensile strength of fabricated joint was obtained with the process parameters combination of 1000 rpm rotational speed, 125 mm/min welding speed, 0.15 mm shoulder penetration, 2 mm filler holes center distance, and powder mixing ratio of 95% Mg and 5% Cr. Ó 2020 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the International Mechanical Engineering Congress 2019: Materials Science.
1. Introduction The friction stir welding (FSW) is a solid state metal joining technique developed by The Welding Institute (TWI). The FSW technique is used in high strength aluminium alloys which are difficult to join with conventional techniques. In this technique, the joint of a material is plasticized by heat generated in friction between the base metal plate surface and the contact surface of a special tool [1]. Many of the literatures are focused on similar material joints on soft metals like aluminium, magnesium and its alloys. Few investigations have been carried out on dissimilar joints. A few researches have been carried out on joint strength and microstructural analysis of friction stir welded AA6082 and AA5052 alloy. Most of the research workers have considered the plate thickness of 6 mm or below 6 mm as base material. Very few researchers have carried out the mechanical characterization of 8 mm thick plate material in friction stir welding. Tungsten tool material with a hexagonal pin profile has provided good stir force ⇑ Corresponding author.
and provides a higher material flow. It withstands high temperature and provides longer tool life [2–5]. The complete control over the relevant process parameters is needed to maximize the tensile strength on which the quality of a weldment is based [6,7]. The several mathematical methods can be applied to define the desired response variables. These statistical models have the relationship between the input parameters and output responses. The exact functional relationship between the independent variables and the response variable can be developed by using Response Surface Methodology (RSM), it is also helpful to characterize the nature of the joints. It is an efficient statistical design of experimental techniques, which allows development of an empirical methodology and used to incorporate a scientific approach in the fusion welding procedures [8–10]. The specific input parameter, filler has considered in this research work to enhance the joint strength. The two different parameters filler holes center distance and powder mixing ratio are considered to get the prediction equation [11]. Therefore, in this research work, RSM is used to find the empirical relationship between the input parameters (Rotational speed, welding speed,
E-mail address: [email protected] (A. Sasikumar). https://doi.org/10.1016/j.matpr.2020.01.258 2214-7853/Ó 2020 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the International Mechanical Engineering Congress 2019: Materials Science.
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
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A. Sasikumar et al. / Materials Today: Proceedings xxx (xxxx) xxx
shoulder penetration, filler holes center distance and powder mixing ratio of Mg and Cr) and the response such as tensile strength.
Table 1 Chemical composition (wt%) of aluminium alloys. Alloy elements
2. Experimental procedure The experimental parameters such as rotational speed, welding speed, shoulder penetration, filler holes center distance and powder mixing ratio were considered. The schematic diagram of weld specimen is shown in Fig. 1. After many trials, the range of the rotational speed and welding speed were taken from 600 rpm to 1400 rpm and 60 mm/min to 180 mm/min respectively. Shoulder penetration was gradually increased in five steps of 0.05 mm from 0 mm to 0.25 mm. Along the butting surface of the weld specimen, the holes were drilled having dimensions of 2 mm in diameter, 3 mm in depth, and maintained the filler holes center distance in zig zag position. The ranges were taken from 0 mm to 4 mm. The filler holes center distance in zig zag positions are 0 mm, 1 mm, 2 mm, 3 mm and 4 mm respectively. In the weld stir zone the average weight percentage of Mg and Cr was determined. With the help of average weight percentage of Mg and Cr in the weld stir zone the weight percentage ratio was calculated. The weight percentage ratio of Mg and Cr fillers were calculated from the total weight of the filler. The weight percentage of Mg and Cr powder mixing ratios were maintained at 90:10, 92.5:7.5, 95:5, 97.5:2.5 and 100:0. In this study tool shoulder diameter of 20 mm, pin length of 7.6 mm and hexagonal profile pin diameter of 8 mm was used. The chemical compositions and mechanical properties of the weld base metals are given in Tables 1 and 2 respectively. AA5052 and AA6082 alloy of 8 mm thick plates was used as the base metal. The base metal plates were cut into 150 mm 75 mm dimension. Aluminium alloy 6082 provides better strength and Aluminium alloy 5052 exhibits better corrosion resistance property. The square butt joint configuration was prepared to fabricate FSW joints. To get the adjacent holes for conducting FSW the drilled holes was aligned in a zig-zag position. While conducting FSW, AA5052 plate was placed in the advancing side and AA6082 plate in retreating side. High heat and wear resistant tool made of tungsten carbide were used to fabricate the weld joints. The tool geometry with hexagonal pin profile is shown in Fig. 2. By using HMT FN2V vertical milling machine having capacity of 7.5 Hp and 1800 rpm is used for performing FSW operation. Response Surface Methodology (RSM) is a mathematical and statistical technique [12]. It is used for analysing problems in which several independent variables influence a dependent variable or response. The aim is to optimize the process parameters and enhance the responses. In various experimental conditions, it represents an independent factor in quantitative form as given in
Si Cr Mg Mn Fe Cu Zn Ni Ti Al
Alloy AA5052
AA6082
0.049 0.196 2.629 0.016 0.186 0.006 0.009 0.04 0.016 Balance
1.0 0.05 0.82 0.52 0.27 0.02 0.1 – 0.03 Balance
Table 2 Mechanical properties of aluminium alloys. Properties
UTS (MPa) YS (MPa) Elongation (%) Hardness (HV) Density (g/mm3) Melting point (°C)
Alloy AA5052
AA6082
217 168 19.5 85 2680 607
330 279 13 120 2700 555
Fig. 2. (a) Hexagonal pin profile with tool geometry (b) Photograph of hexagonal pin profile.
Eq. (1). The variables (x1, x2, x3. . . xk of k quantitative factors) can be formed as the functional relationship or response (Y) as follows:
Y ¼ uðx1 ; x2 ; x3 . . . xk Þ er
Fig. 1. (a) Zig zag hole positions enlarged view (b) Weld specimen schematic diagram (c) Butt welding area of the plate (d) Weld specimen isometric view.
ð1Þ
The residual er is the measure of experimental errors. The characteristic is respondingto a given set of independent variables. As per ASTM E8M-04 guidelines the tensile specimens of the welded joints were prepared, to required dimensions shown in Fig. 3(a) [13]. A 100 kN servo ball screw driven loaded universal testing machine with a cross head speed of 1 mm/min were used to
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
A. Sasikumar et al. / Materials Today: Proceedings xxx (xxxx) xxx
3
Fig. 3. (a) Schematic representation of tensile specimen (b) Tensile specimens for after tensile test.
Table 3 Central composite Design matrix. Experimental details
Result
Exp. no
Response
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Input parameters R (rpm)
W (mm/min)
P (mm)
C (mm)
M (%)
TS (MPa)
800 1200 800 1200 800 1200 800 1200 800 1200 800 1200 800 1200 800 1200 600 1400 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000
90 90 150 150 90 90 150 150 90 90 150 150 90 90 150 150 120 120 60 180 120 120 120 120 120 120 120 120 120 120 120 120
0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.15 0.15 0.15 0.15 0.05 0.25 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15
1 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3 2 2 2 2 2 2 0 4 2 2 2 2 2 2 2 2
97.5:2.5 92.5:7.5 92.5:7.5 97.5:2.5 92.5:7.5 97.5:2.5 97.5:2.5 92.5:7.5 92.5:7.5 97.5:2.5 97.5:2.5 92.5:7.5 97.5:2.5 92.5:7.5 92.5:7.5 97.5:2.5 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 90.0:10 100.0:0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0
132 139 140 143 136 144 145 149 139 148 140 146 139 140 142 149 145 154 143 151 143 148 148 152 145 150 172 173 172 173 172 173
function of rotational speed (R), welding speed (W), shoulder penetration (P), filler holes center distance (C), and powder mixing ratio (M) and it can be expressed as:
Y ¼ f ðR; W; P; C; MÞ
ð2Þ
The second order regression equation used to represent the response surface ‘Y’ is given by:
Y ¼ bo þ Rbi xi þ Rbii x2i þ Rbij xi xj þ er
ð3Þ
The Design Expert V11 software suggests that the higher order of polynomial, where the additional terms are significant and the model is not aliased. The tensile strength (TS) of the FSW joints is a function of rotational speed (R), welding speed (W), shoulder penetration (P), filler holes center distance (C), and powder mixing ratio (M). It can be articulated as:
TS ¼ bo þ b1 ðRÞ þ b2 ðWÞ þ b3 ðPÞ þ b4 ðCÞ þ b5 ðMÞ þ b11 R2 þ b22 W2 þ b33 P2 þ b44 C2 þ b55 M2 þ b12 ðRWÞ þ b13 ðRPÞ þ b14 ðRCÞ þ b15 ðRMÞ þ b23 ðWPÞ þ b24 ðWCÞ þ b25 ðWMÞ þ b34 ðPCÞ þ b35 ðPMÞ þ b45 ðCMÞ
ð4Þ
where, bo is the average of responses and b1, b2. . ., b45 are coefficients that depends on respective primary, interaction and square effects of factors. All the coefficients were tested for their significance at the 95% confidence level applying Fisher’s F-test using Design-Expert V11 statistical software package. The final models were developed by using these coefficients only. The final empirical relationships are used to evaluate the tensile strength of the welded region as given below:
TS ¼ f172:47 þ 2:62ðRÞ þ 2:21ðWÞ þ 1:12ðPÞ þ 0:9583ðCÞ þ 0:7917ðMÞ þ 0:6875ðRMÞ þ 0:9375ðWPÞ
conduct tensile test. From each joint, three tensile specimens were prepared and the average of three results is given in Table 3. The specimens after tensile tests is shown in Fig. 3(b).
9:375ðWCÞ 0:5625ðWMÞ 1:44ðPCÞ þ 0:6875ðPMÞ þ 0:5625ðCMÞ 5:72ðR2 Þ 6:34ðW2 Þ 6:72ðP2 Þ 5:59ðC2 Þ 6:22ðM2 Þg MPa
3. Results and discussions RSM central composite design (CCD) has selected for five factors – five levels to get the prediction equation. The Table 3 shows the suitable half factorial 32 set of coded conditions to form the design matrix. First 26 experimental conditions are in non-centered level and centered in last 6 experiments. As detailed by the design matrix, 32 joints were fabricated. The RSM was applied to developing the mathematical model in the form of a regression equation for the quantitative characteristics of the friction stir welded AA5052 and AA6082 alloys. In this RSM, the independent variable was viewed as a surface to which a mathematical is fitted. The tensile strength of the joints represented by TS, the response (Y) is a
ð5Þ
The analysis of variance (ANOVA) was used to test the empirical relationship. Table 4 shows that the ANOVA test results for the tensile strength. The Model F-value of 382.31 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise. P-values less than 0.05 indicate model terms are significant. In this case R, W, P, C, M, RM, WP, WC, WM, PC, PM, CM, R2, W2, P2, C2, and M2 are significant model terms. Values greater than 0.1 indicate the model terms are not significant. The Lack of Fit F-value of 2.83 implies the Lack of Fit is not significant relative to the pure error. There is a 13.69% chance that a Lack of Fit F-value, this large could occur due to noise. The Predicted R2 of 0.9699 is in reasonable agreement with the Adjusted R2 of 0.996 because the difference is less than 0.2. Adequate Preci-
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
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Table 4 ANOVA test results for Tensile strength. Source
Sum of Squares
Degree of freedom
Mean Square
F-value
P-value
Significance
Model R* W* P* C* M* RW RP RC RM* WP* WC* WM* PC* PM* CM* R2* W2* P2* C2* M2* Residual Lack of Fit Pure Error Cor Total Std deviation Mean CV (%) PRESS
4581.38 165.37 117.04 30.38 22.04 15.04 1.56 1.56 0.0625 7.56 14.06 14.06 5.06 33.06 7.56 5.06 958.37 1179.41 1323.03 916.91 1133.37 6.59 5.09 1.5 4587.97 0.7741 149.53 0.5177 138.07
20 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 6 5 31 R2 Adjusted R2 Predicted R2 Adeq. Precision
229.1 165.4 117 30.38 22.04 15.04 1.56 1.56 0.063 7.56 14.06 14.06 5.06 33.06 7.56 5.06 958.4 1179 1323 916.9 1133 0.599 0.849 0.3
382.31 276.01 195.34 50.69 36.79 25.1 2.61 2.61 0.1043 12.62 23.47 23.47 8.45 55.18 12.62 8.45 1599.48 1968.39 2208.1 1530.29 1891.55
<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0004 0.1346 0.1346 0.7528 0.0045 0.0005 0.0005 0.0143 <0.0001 0.0045 0.0143 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Significant
2.83
0.1369
Not significant
0.9986 0.996 0.9699 63.9163
*Significant.
sion measures the signal to noise ratio. A ratio greater than 4 is desirable. In this model, 63.916 indicates an adequate signal. This model can be used to direct the design space. Perturbation plot shown in Fig. 4 symbolizes the influence of the friction stir welding parameters on the tensile strength. This graph illustrates how the response varies as each factor moves from a chosen reference point, with all other factors held constant
Fig. 4. Perturbation plot for effect of interacting of all factors on the tensile strength.
as the reference value. A steep curvature in a factor indicates that the response is sensitive to that factor. Hence, the plot shows that the factor, rotational speed is most influenced the tensile strength followed by welding speed, filler holes center distance, powder mixing ratio and shoulder penetration. A contour plot is a graph that can used to understand the relationship between two factors on the response. Fig. 5 shows that how rotational speed and powder mixing ratio affect the response of tensile strength. The dark
Fig. 5. Contour plot showing the effect factors on Tensile strength.
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
A. Sasikumar et al. / Materials Today: Proceedings xxx (xxxx) xxx Table 5 Validation test results. Experimental details Input parameters Rotational speed 1000 rpm Welding speed 125 mm/min Shoulder penetration 0.15 mm Filler holes center distance 2 mm Powder mixing ratio 95% of magnesium, 5% of chromium
Exp. no 1
2
3
Response Tensile strength (MPa) Actual Predicted % of error % of accuracy Actual Predicted % of error % of accuracy Actual Predicted % of error % of accuracy
165.534 173.059 4.34 95.66 166.021 173.059 4.06 95.94 164.826 173.059 4.75 95.25
red region has identified the higher value of the response. The rotational speed with powder mixing ratio is the most important interaction factor on tensile strength followed by shoulder penetration, welding speed and filler holes center distance. The contour plot represents a peak tensile strength in rotational speed of 1045.739 rpm and powder mixing ratio of 95.194% magnesium and 4.806% chromium. In the peak region, the predicted value of tensile strength is 173.059 MPa. 3.1. Optimization of process parameters The optimal welding parameter combinations which provide better mechanical properties of the welded joint can be gained by using optimization study [14]. Indeed, once the model is developed and checks the competence that the optimization criteria can able to achieved to gain optimum welding parameters. Maximize the tensile strength is the main objective of this research work. The input process parameters were set in the range. The optimal solution was based on the optimization criteria determined by design expert software. The maximum tensile strength was obtained by the optimum process parameters rotational speed 1045.739 rpm, welding speed 125.019 mm/min, shoulder penetration 0.154 mm, filler holes center distance 2.066 mm and powder mixing ratio 95.194% of magnesium, 4.806% of chromium. The optimal conditions that can lead the maximum tensile strength to 173.059 MPa [15–17]. 3.2. Confirmation of the developed models The predicted optimum parameters for the filler added FSW based on the levels is given in Table 5. With the optimum parameter combination, the validation tests were conducted and the tensile strength was found. Due to the limitation for setting the parameters to the predicted value, the round off value is chosen for confirmation test. The 95% of tensile strength accuracy value was obtained by using the optimal parameters. 4. Conclusions The experiments were successfully conducted onAA6082 and AA5052 using friction stir welding. From these experiments the following major conclusions were drawn.
5
The maximum tensile strength of the welded joint was predicted by using RSM technique. The most predominant interaction factor to enhance the maximum tensile strength was the interaction of rotational speed and powder mixing ratio. The joint fabricated with a rotational speed of 1000 rpm, welding speed of 125 mm/min, shoulder penetration of 0.15 mm, filler holes center distance of 2 mm and powder mixing ratio of 95% Mg and 5% Cr are the optimal input parameters to obtain a maximum tensile strength around 173 MPa. CRediT authorship contribution statement A. Sasikumar: Conceptualization, Methodology, Investigation, Formal analysis, Validation, Writing - original draft. S. Gopi: Conceptualization, Methodology, Investigation, Formal analysis, Validation, Writing - review & editing, Supervision. M. Sathish Kumar: Resources, Writing - review & editing. L. Selvarajan: Resources, Writing - review & editing. References [1] W.M. Thomas, E.D. Nicholas, J.C. Needham, M.G. Murch, P. Temple-Smith, C.J. Dawes, Friction stir butt welding (The Welding Institute TWI), UK patent, 1993, 9125978.8. [2] H.M. Anil Kumar, V. Venkata Ramana, Mayur Pawar, Experimental study on dissimilar friction stir welding of aluminium alloys (5083–H111 and 6082–T6) to investigate the mechanical properties, Mater. Sci. Eng. (2018) 330. [3] S. Gopi, K. Manonmani, Influence of shoulder profile and shoulder penetration on joint strength of friction stir welded AA6082 in conventional milling machine, Eur. J. Scientific Res. 73 (1) (2012) 20–32. [4] V. RajKumar, M. Venkatesh Kannan, P. Sadeesh, N. Arivazhagan, K. Devendranath Ramkumar, Studies on effect of tool design and welding parameters on the friction stir welding of dissimilar aluminium alloys AA 5052 – AA 6061, Proc. Eng. 75 (2014) 93–97. [5] S. Gopi, K. Manonmani, Study of friction stir welding parameters in conventional milling machine for 6082–T6 aluminium alloy, Aust. J. Mech. Eng. 10 (2012) 129–140. [6] M.I.I. Mahamud, M. Ishak, A.M. Halil, Study of dissimilar welding AA6061 aluminium alloy and AZ31B magnesium alloy with ER5356 filler using friction stir welding, Mater. Sci. Eng. 238 (2017) 1–8. [7] Huihong Liu, Jeong-Won Choi, Ushioda Kohsaku, Hidetoshi Fujii, Effect of an Al filler material on interfacial microstructure and mechanical properties of dissimilar friction stir welded Ti/Mg joint, Mater. Charact. 155 (2019) 109801. [8] R.K. Kesharwani, S.K. Panda, S.K. Pal, Multi objective optimization of friction stir welding parameters for joining of two dissimilar thin aluminium sheets, Proc. Mater. Sci. 6 (2014) 178–187. [9] Arun Kumar Kadian, Pankaj Biswas, Effect of tool pin profile on the material flow characteristics of AA6061, J. Manuf. Processes 26 (2017) 382–392. [10] A. Farzadi, M. Bahmani, D.F. Haghshenas, Optimization of operational parameters in friction stir welding of AA7075-T6 aluminum alloy using response surface method, Arab. J. Sci. Eng. 42 (11) (2017) 4905–4916. [11] A. Sasikumar, S. Gopi, Dhanesh G. Mohan, Effect of magnesium and chromium fillers on the microstructure and tensile strength of friction stir welded dissimilar aluminium alloys, Mater. Res. Express 6 (2019) 2053–11591. [12] S. Rajakumar, C. Muralidharan, V. Balasubramanian, Predicting tensile strength, hardness and corrosion rate of friction stir welded AA6061-T6 aluminium alloy joints, Mater. Des. 32 (2011) 2878–2890. [13] ASTM-E08-04, Standard test method for tension testing of metallic materials. Annual book of ASTM standards 2006, section 3, vol. 03.01. Metals test methods and analytical procedure, p. 90. [14] B. Ravi Sankar, P. Umamaheswarrao, Modelling and optimisation of friction stir welding on AA6061 alloy, Mater. Today:. Proc. 4 (2017) 7448–7456. [15] Jitender Kundu, Hari Singh, Modelling and analysis of process parameters in friction stir welding of AA5083-H321 using response surface methodology, Adv. Mater. Process. Technol. 4 (2017) 183–199. [16] S.P. Jung, T.W. Park, Y.G. Kim, Fatigue strength optimisation of friction stir welded A6005–T5 alloy sheets, Sci. Technol. Weld. Joining 15 (2010) 473–478. [17] C.R. Renjith, Rathish Raghupathy, Dhanesh G. Mohan, Optimization of process parameters for friction stir lap welding of AA6061-T6 and AA7075-T6 aluminum alloys using taguchi technique, Int. J. Res. Technol. Stud. 3 (2016) 721–735.
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint A. Sasikumar a,⇑, S. Gopi a, M. Sathish Kumar b, L. Selvarajan c a
Department of Production Engineering, Government College of Technology, Coimbatore 641013, India Department of Mechanical Engineering, SNS College of Engineering, Coimbatore 641107, India c Department of Mechanical Engineering, Mahendra Institute of Technology, Namakkal 637503, India b
a r t i c l e
i n f o
Article history: Received 13 November 2019 Received in revised form 8 January 2020 Accepted 11 January 2020 Available online xxxx Keywords: Friction stir welding Aluminium alloy Powder mixing ratio Response surface methodology Tensile strength
a b s t r a c t Friction Stir Welding (FSW) process parameters and tool parameters are playing pivotal role in the weld joint characteristics. The combination is selected for the investigation of AA6082 and AA5052, which finds major application in ship structural frame and building constructions. Along with these usual parameters the composition of filler elements is considered in this work to improve the weld joint strength. The process parameters considered in this study are rotational speed, welding speed, shoulder penetration, filler holes center distance, and powder mixing ratio. The Central Composite Design (CCD), the most commonly used Response Surface Methodology (RSM) is considered to develop the prediction equation. A validation analysis is carried out and the results were compared with the relative impact of input parameters on tensile strength. The maximum tensile strength of fabricated joint was obtained with the process parameters combination of 1000 rpm rotational speed, 125 mm/min welding speed, 0.15 mm shoulder penetration, 2 mm filler holes center distance, and powder mixing ratio of 95% Mg and 5% Cr. Ó 2020 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the International Mechanical Engineering Congress 2019: Materials Science.
1. Introduction The friction stir welding (FSW) is a solid state metal joining technique developed by The Welding Institute (TWI). The FSW technique is used in high strength aluminium alloys which are difficult to join with conventional techniques. In this technique, the joint of a material is plasticized by heat generated in friction between the base metal plate surface and the contact surface of a special tool [1]. Many of the literatures are focused on similar material joints on soft metals like aluminium, magnesium and its alloys. Few investigations have been carried out on dissimilar joints. A few researches have been carried out on joint strength and microstructural analysis of friction stir welded AA6082 and AA5052 alloy. Most of the research workers have considered the plate thickness of 6 mm or below 6 mm as base material. Very few researchers have carried out the mechanical characterization of 8 mm thick plate material in friction stir welding. Tungsten tool material with a hexagonal pin profile has provided good stir force ⇑ Corresponding author.
and provides a higher material flow. It withstands high temperature and provides longer tool life [2–5]. The complete control over the relevant process parameters is needed to maximize the tensile strength on which the quality of a weldment is based [6,7]. The several mathematical methods can be applied to define the desired response variables. These statistical models have the relationship between the input parameters and output responses. The exact functional relationship between the independent variables and the response variable can be developed by using Response Surface Methodology (RSM), it is also helpful to characterize the nature of the joints. It is an efficient statistical design of experimental techniques, which allows development of an empirical methodology and used to incorporate a scientific approach in the fusion welding procedures [8–10]. The specific input parameter, filler has considered in this research work to enhance the joint strength. The two different parameters filler holes center distance and powder mixing ratio are considered to get the prediction equation [11]. Therefore, in this research work, RSM is used to find the empirical relationship between the input parameters (Rotational speed, welding speed,
E-mail address: [email protected] (A. Sasikumar). https://doi.org/10.1016/j.matpr.2020.01.258 2214-7853/Ó 2020 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the scientific committee of the International Mechanical Engineering Congress 2019: Materials Science.
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
2
A. Sasikumar et al. / Materials Today: Proceedings xxx (xxxx) xxx
shoulder penetration, filler holes center distance and powder mixing ratio of Mg and Cr) and the response such as tensile strength.
Table 1 Chemical composition (wt%) of aluminium alloys. Alloy elements
2. Experimental procedure The experimental parameters such as rotational speed, welding speed, shoulder penetration, filler holes center distance and powder mixing ratio were considered. The schematic diagram of weld specimen is shown in Fig. 1. After many trials, the range of the rotational speed and welding speed were taken from 600 rpm to 1400 rpm and 60 mm/min to 180 mm/min respectively. Shoulder penetration was gradually increased in five steps of 0.05 mm from 0 mm to 0.25 mm. Along the butting surface of the weld specimen, the holes were drilled having dimensions of 2 mm in diameter, 3 mm in depth, and maintained the filler holes center distance in zig zag position. The ranges were taken from 0 mm to 4 mm. The filler holes center distance in zig zag positions are 0 mm, 1 mm, 2 mm, 3 mm and 4 mm respectively. In the weld stir zone the average weight percentage of Mg and Cr was determined. With the help of average weight percentage of Mg and Cr in the weld stir zone the weight percentage ratio was calculated. The weight percentage ratio of Mg and Cr fillers were calculated from the total weight of the filler. The weight percentage of Mg and Cr powder mixing ratios were maintained at 90:10, 92.5:7.5, 95:5, 97.5:2.5 and 100:0. In this study tool shoulder diameter of 20 mm, pin length of 7.6 mm and hexagonal profile pin diameter of 8 mm was used. The chemical compositions and mechanical properties of the weld base metals are given in Tables 1 and 2 respectively. AA5052 and AA6082 alloy of 8 mm thick plates was used as the base metal. The base metal plates were cut into 150 mm 75 mm dimension. Aluminium alloy 6082 provides better strength and Aluminium alloy 5052 exhibits better corrosion resistance property. The square butt joint configuration was prepared to fabricate FSW joints. To get the adjacent holes for conducting FSW the drilled holes was aligned in a zig-zag position. While conducting FSW, AA5052 plate was placed in the advancing side and AA6082 plate in retreating side. High heat and wear resistant tool made of tungsten carbide were used to fabricate the weld joints. The tool geometry with hexagonal pin profile is shown in Fig. 2. By using HMT FN2V vertical milling machine having capacity of 7.5 Hp and 1800 rpm is used for performing FSW operation. Response Surface Methodology (RSM) is a mathematical and statistical technique [12]. It is used for analysing problems in which several independent variables influence a dependent variable or response. The aim is to optimize the process parameters and enhance the responses. In various experimental conditions, it represents an independent factor in quantitative form as given in
Si Cr Mg Mn Fe Cu Zn Ni Ti Al
Alloy AA5052
AA6082
0.049 0.196 2.629 0.016 0.186 0.006 0.009 0.04 0.016 Balance
1.0 0.05 0.82 0.52 0.27 0.02 0.1 – 0.03 Balance
Table 2 Mechanical properties of aluminium alloys. Properties
UTS (MPa) YS (MPa) Elongation (%) Hardness (HV) Density (g/mm3) Melting point (°C)
Alloy AA5052
AA6082
217 168 19.5 85 2680 607
330 279 13 120 2700 555
Fig. 2. (a) Hexagonal pin profile with tool geometry (b) Photograph of hexagonal pin profile.
Eq. (1). The variables (x1, x2, x3. . . xk of k quantitative factors) can be formed as the functional relationship or response (Y) as follows:
Y ¼ uðx1 ; x2 ; x3 . . . xk Þ er
Fig. 1. (a) Zig zag hole positions enlarged view (b) Weld specimen schematic diagram (c) Butt welding area of the plate (d) Weld specimen isometric view.
ð1Þ
The residual er is the measure of experimental errors. The characteristic is respondingto a given set of independent variables. As per ASTM E8M-04 guidelines the tensile specimens of the welded joints were prepared, to required dimensions shown in Fig. 3(a) [13]. A 100 kN servo ball screw driven loaded universal testing machine with a cross head speed of 1 mm/min were used to
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
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Fig. 3. (a) Schematic representation of tensile specimen (b) Tensile specimens for after tensile test.
Table 3 Central composite Design matrix. Experimental details
Result
Exp. no
Response
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Input parameters R (rpm)
W (mm/min)
P (mm)
C (mm)
M (%)
TS (MPa)
800 1200 800 1200 800 1200 800 1200 800 1200 800 1200 800 1200 800 1200 600 1400 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000
90 90 150 150 90 90 150 150 90 90 150 150 90 90 150 150 120 120 60 180 120 120 120 120 120 120 120 120 120 120 120 120
0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.15 0.15 0.15 0.15 0.05 0.25 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15
1 1 1 1 1 1 1 1 3 3 3 3 3 3 3 3 2 2 2 2 2 2 0 4 2 2 2 2 2 2 2 2
97.5:2.5 92.5:7.5 92.5:7.5 97.5:2.5 92.5:7.5 97.5:2.5 97.5:2.5 92.5:7.5 92.5:7.5 97.5:2.5 97.5:2.5 92.5:7.5 97.5:2.5 92.5:7.5 92.5:7.5 97.5:2.5 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 90.0:10 100.0:0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0 95.0:5.0
132 139 140 143 136 144 145 149 139 148 140 146 139 140 142 149 145 154 143 151 143 148 148 152 145 150 172 173 172 173 172 173
function of rotational speed (R), welding speed (W), shoulder penetration (P), filler holes center distance (C), and powder mixing ratio (M) and it can be expressed as:
Y ¼ f ðR; W; P; C; MÞ
ð2Þ
The second order regression equation used to represent the response surface ‘Y’ is given by:
Y ¼ bo þ Rbi xi þ Rbii x2i þ Rbij xi xj þ er
ð3Þ
The Design Expert V11 software suggests that the higher order of polynomial, where the additional terms are significant and the model is not aliased. The tensile strength (TS) of the FSW joints is a function of rotational speed (R), welding speed (W), shoulder penetration (P), filler holes center distance (C), and powder mixing ratio (M). It can be articulated as:
TS ¼ bo þ b1 ðRÞ þ b2 ðWÞ þ b3 ðPÞ þ b4 ðCÞ þ b5 ðMÞ þ b11 R2 þ b22 W2 þ b33 P2 þ b44 C2 þ b55 M2 þ b12 ðRWÞ þ b13 ðRPÞ þ b14 ðRCÞ þ b15 ðRMÞ þ b23 ðWPÞ þ b24 ðWCÞ þ b25 ðWMÞ þ b34 ðPCÞ þ b35 ðPMÞ þ b45 ðCMÞ
ð4Þ
where, bo is the average of responses and b1, b2. . ., b45 are coefficients that depends on respective primary, interaction and square effects of factors. All the coefficients were tested for their significance at the 95% confidence level applying Fisher’s F-test using Design-Expert V11 statistical software package. The final models were developed by using these coefficients only. The final empirical relationships are used to evaluate the tensile strength of the welded region as given below:
TS ¼ f172:47 þ 2:62ðRÞ þ 2:21ðWÞ þ 1:12ðPÞ þ 0:9583ðCÞ þ 0:7917ðMÞ þ 0:6875ðRMÞ þ 0:9375ðWPÞ
conduct tensile test. From each joint, three tensile specimens were prepared and the average of three results is given in Table 3. The specimens after tensile tests is shown in Fig. 3(b).
9:375ðWCÞ 0:5625ðWMÞ 1:44ðPCÞ þ 0:6875ðPMÞ þ 0:5625ðCMÞ 5:72ðR2 Þ 6:34ðW2 Þ 6:72ðP2 Þ 5:59ðC2 Þ 6:22ðM2 Þg MPa
3. Results and discussions RSM central composite design (CCD) has selected for five factors – five levels to get the prediction equation. The Table 3 shows the suitable half factorial 32 set of coded conditions to form the design matrix. First 26 experimental conditions are in non-centered level and centered in last 6 experiments. As detailed by the design matrix, 32 joints were fabricated. The RSM was applied to developing the mathematical model in the form of a regression equation for the quantitative characteristics of the friction stir welded AA5052 and AA6082 alloys. In this RSM, the independent variable was viewed as a surface to which a mathematical is fitted. The tensile strength of the joints represented by TS, the response (Y) is a
ð5Þ
The analysis of variance (ANOVA) was used to test the empirical relationship. Table 4 shows that the ANOVA test results for the tensile strength. The Model F-value of 382.31 implies the model is significant. There is only a 0.01% chance that an F-value this large could occur due to noise. P-values less than 0.05 indicate model terms are significant. In this case R, W, P, C, M, RM, WP, WC, WM, PC, PM, CM, R2, W2, P2, C2, and M2 are significant model terms. Values greater than 0.1 indicate the model terms are not significant. The Lack of Fit F-value of 2.83 implies the Lack of Fit is not significant relative to the pure error. There is a 13.69% chance that a Lack of Fit F-value, this large could occur due to noise. The Predicted R2 of 0.9699 is in reasonable agreement with the Adjusted R2 of 0.996 because the difference is less than 0.2. Adequate Preci-
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
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Table 4 ANOVA test results for Tensile strength. Source
Sum of Squares
Degree of freedom
Mean Square
F-value
P-value
Significance
Model R* W* P* C* M* RW RP RC RM* WP* WC* WM* PC* PM* CM* R2* W2* P2* C2* M2* Residual Lack of Fit Pure Error Cor Total Std deviation Mean CV (%) PRESS
4581.38 165.37 117.04 30.38 22.04 15.04 1.56 1.56 0.0625 7.56 14.06 14.06 5.06 33.06 7.56 5.06 958.37 1179.41 1323.03 916.91 1133.37 6.59 5.09 1.5 4587.97 0.7741 149.53 0.5177 138.07
20 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 6 5 31 R2 Adjusted R2 Predicted R2 Adeq. Precision
229.1 165.4 117 30.38 22.04 15.04 1.56 1.56 0.063 7.56 14.06 14.06 5.06 33.06 7.56 5.06 958.4 1179 1323 916.9 1133 0.599 0.849 0.3
382.31 276.01 195.34 50.69 36.79 25.1 2.61 2.61 0.1043 12.62 23.47 23.47 8.45 55.18 12.62 8.45 1599.48 1968.39 2208.1 1530.29 1891.55
<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0004 0.1346 0.1346 0.7528 0.0045 0.0005 0.0005 0.0143 <0.0001 0.0045 0.0143 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Significant
2.83
0.1369
Not significant
0.9986 0.996 0.9699 63.9163
*Significant.
sion measures the signal to noise ratio. A ratio greater than 4 is desirable. In this model, 63.916 indicates an adequate signal. This model can be used to direct the design space. Perturbation plot shown in Fig. 4 symbolizes the influence of the friction stir welding parameters on the tensile strength. This graph illustrates how the response varies as each factor moves from a chosen reference point, with all other factors held constant
Fig. 4. Perturbation plot for effect of interacting of all factors on the tensile strength.
as the reference value. A steep curvature in a factor indicates that the response is sensitive to that factor. Hence, the plot shows that the factor, rotational speed is most influenced the tensile strength followed by welding speed, filler holes center distance, powder mixing ratio and shoulder penetration. A contour plot is a graph that can used to understand the relationship between two factors on the response. Fig. 5 shows that how rotational speed and powder mixing ratio affect the response of tensile strength. The dark
Fig. 5. Contour plot showing the effect factors on Tensile strength.
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258
A. Sasikumar et al. / Materials Today: Proceedings xxx (xxxx) xxx Table 5 Validation test results. Experimental details Input parameters Rotational speed 1000 rpm Welding speed 125 mm/min Shoulder penetration 0.15 mm Filler holes center distance 2 mm Powder mixing ratio 95% of magnesium, 5% of chromium
Exp. no 1
2
3
Response Tensile strength (MPa) Actual Predicted % of error % of accuracy Actual Predicted % of error % of accuracy Actual Predicted % of error % of accuracy
165.534 173.059 4.34 95.66 166.021 173.059 4.06 95.94 164.826 173.059 4.75 95.25
red region has identified the higher value of the response. The rotational speed with powder mixing ratio is the most important interaction factor on tensile strength followed by shoulder penetration, welding speed and filler holes center distance. The contour plot represents a peak tensile strength in rotational speed of 1045.739 rpm and powder mixing ratio of 95.194% magnesium and 4.806% chromium. In the peak region, the predicted value of tensile strength is 173.059 MPa. 3.1. Optimization of process parameters The optimal welding parameter combinations which provide better mechanical properties of the welded joint can be gained by using optimization study [14]. Indeed, once the model is developed and checks the competence that the optimization criteria can able to achieved to gain optimum welding parameters. Maximize the tensile strength is the main objective of this research work. The input process parameters were set in the range. The optimal solution was based on the optimization criteria determined by design expert software. The maximum tensile strength was obtained by the optimum process parameters rotational speed 1045.739 rpm, welding speed 125.019 mm/min, shoulder penetration 0.154 mm, filler holes center distance 2.066 mm and powder mixing ratio 95.194% of magnesium, 4.806% of chromium. The optimal conditions that can lead the maximum tensile strength to 173.059 MPa [15–17]. 3.2. Confirmation of the developed models The predicted optimum parameters for the filler added FSW based on the levels is given in Table 5. With the optimum parameter combination, the validation tests were conducted and the tensile strength was found. Due to the limitation for setting the parameters to the predicted value, the round off value is chosen for confirmation test. The 95% of tensile strength accuracy value was obtained by using the optimal parameters. 4. Conclusions The experiments were successfully conducted onAA6082 and AA5052 using friction stir welding. From these experiments the following major conclusions were drawn.
5
The maximum tensile strength of the welded joint was predicted by using RSM technique. The most predominant interaction factor to enhance the maximum tensile strength was the interaction of rotational speed and powder mixing ratio. The joint fabricated with a rotational speed of 1000 rpm, welding speed of 125 mm/min, shoulder penetration of 0.15 mm, filler holes center distance of 2 mm and powder mixing ratio of 95% Mg and 5% Cr are the optimal input parameters to obtain a maximum tensile strength around 173 MPa. CRediT authorship contribution statement A. Sasikumar: Conceptualization, Methodology, Investigation, Formal analysis, Validation, Writing - original draft. S. Gopi: Conceptualization, Methodology, Investigation, Formal analysis, Validation, Writing - review & editing, Supervision. M. Sathish Kumar: Resources, Writing - review & editing. L. Selvarajan: Resources, Writing - review & editing. References [1] W.M. Thomas, E.D. Nicholas, J.C. Needham, M.G. Murch, P. Temple-Smith, C.J. Dawes, Friction stir butt welding (The Welding Institute TWI), UK patent, 1993, 9125978.8. [2] H.M. Anil Kumar, V. Venkata Ramana, Mayur Pawar, Experimental study on dissimilar friction stir welding of aluminium alloys (5083–H111 and 6082–T6) to investigate the mechanical properties, Mater. Sci. Eng. (2018) 330. [3] S. Gopi, K. Manonmani, Influence of shoulder profile and shoulder penetration on joint strength of friction stir welded AA6082 in conventional milling machine, Eur. J. Scientific Res. 73 (1) (2012) 20–32. [4] V. RajKumar, M. Venkatesh Kannan, P. Sadeesh, N. Arivazhagan, K. Devendranath Ramkumar, Studies on effect of tool design and welding parameters on the friction stir welding of dissimilar aluminium alloys AA 5052 – AA 6061, Proc. Eng. 75 (2014) 93–97. [5] S. Gopi, K. Manonmani, Study of friction stir welding parameters in conventional milling machine for 6082–T6 aluminium alloy, Aust. J. Mech. Eng. 10 (2012) 129–140. [6] M.I.I. Mahamud, M. Ishak, A.M. Halil, Study of dissimilar welding AA6061 aluminium alloy and AZ31B magnesium alloy with ER5356 filler using friction stir welding, Mater. Sci. Eng. 238 (2017) 1–8. [7] Huihong Liu, Jeong-Won Choi, Ushioda Kohsaku, Hidetoshi Fujii, Effect of an Al filler material on interfacial microstructure and mechanical properties of dissimilar friction stir welded Ti/Mg joint, Mater. Charact. 155 (2019) 109801. [8] R.K. Kesharwani, S.K. Panda, S.K. Pal, Multi objective optimization of friction stir welding parameters for joining of two dissimilar thin aluminium sheets, Proc. Mater. Sci. 6 (2014) 178–187. [9] Arun Kumar Kadian, Pankaj Biswas, Effect of tool pin profile on the material flow characteristics of AA6061, J. Manuf. Processes 26 (2017) 382–392. [10] A. Farzadi, M. Bahmani, D.F. Haghshenas, Optimization of operational parameters in friction stir welding of AA7075-T6 aluminum alloy using response surface method, Arab. J. Sci. Eng. 42 (11) (2017) 4905–4916. [11] A. Sasikumar, S. Gopi, Dhanesh G. Mohan, Effect of magnesium and chromium fillers on the microstructure and tensile strength of friction stir welded dissimilar aluminium alloys, Mater. Res. Express 6 (2019) 2053–11591. [12] S. Rajakumar, C. Muralidharan, V. Balasubramanian, Predicting tensile strength, hardness and corrosion rate of friction stir welded AA6061-T6 aluminium alloy joints, Mater. Des. 32 (2011) 2878–2890. [13] ASTM-E08-04, Standard test method for tension testing of metallic materials. Annual book of ASTM standards 2006, section 3, vol. 03.01. Metals test methods and analytical procedure, p. 90. [14] B. Ravi Sankar, P. Umamaheswarrao, Modelling and optimisation of friction stir welding on AA6061 alloy, Mater. Today:. Proc. 4 (2017) 7448–7456. [15] Jitender Kundu, Hari Singh, Modelling and analysis of process parameters in friction stir welding of AA5083-H321 using response surface methodology, Adv. Mater. Process. Technol. 4 (2017) 183–199. [16] S.P. Jung, T.W. Park, Y.G. Kim, Fatigue strength optimisation of friction stir welded A6005–T5 alloy sheets, Sci. Technol. Weld. Joining 15 (2010) 473–478. [17] C.R. Renjith, Rathish Raghupathy, Dhanesh G. Mohan, Optimization of process parameters for friction stir lap welding of AA6061-T6 and AA7075-T6 aluminum alloys using taguchi technique, Int. J. Res. Technol. Stud. 3 (2016) 721–735.
Please cite this article as: A. Sasikumar, S. Gopi, M. Sathish Kumar et al., Predicting tensile strength of filler added friction stir welded AA6082 and AA5052 dissimilar joint, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.258