EFFECT OF PROCESS PARAMETERS ON THE TENSILE STRENGTH OF FRICTION STIR WELDED DISSIMILAR ALUMINUM JOINTS

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1 Journal of Engineering Science and Technology Vol. 10, No. 6 (2015) School of Engineering, Taylor s University EFFECT OF PROCESS PARAMETERS ON THE TENSILE STRENGTH OF FRICTION STIR WELDED DISSIMILAR ALUMINUM JOINTS R. PADMANABAN 1, *, V. BALUSAMY 2, K. N. NOURANGA 1 1 Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamilnadu, India 2 P.S.G College of Technology, Coimbatore, India *Corresponding Author: dr_padmanaban@cb.amrita.edu Abstract Friction stir welding is one of the recent solid state joining processes that has drawn the attention of the metal joining community. In this work the effects of tool rotation speed (TRS) and welding speed (WS) on the tensile strength of dissimilar friction stir welded AA2024-AA7075 joints are investigated. Response surface methodology is used for developing a mathematical model for the tensile strength of the dissimilar aluminum alloy joints. The model is used to investigate the effect of TRS and WS on the tensile strength of the joints. It is seen that the tensile strength of the joint increases with the increase in TRS up to a limit of 1050 rpm and decreases thereafter. The tensile strength of the joints is also seen increasing with the WS up to 15 mm/min. Further increase in WS results in a reduction of the tensile strength of the joints. Keywords: Friction stir welding, Tensile strength, Mathematical model, Response surface methodology. 1. Introduction Friction stir welding (FSW) is a solid state joining process invented at The Welding Institute, Cambridge by Thomas et al. [1]. FSW has enabled the joining of materials that were considered difficult to be joined by conventional processes. The process uses frictional heat to join two materials that are in the form of plates. The basic principle of the FSW process is illustrated in Fig. 1 [2]. In this process, a rotating tool with a profiled pin is slowly inserted into the abutting edges of the plates and then moved along the length of the joint. The material under the tool is plastically deformed and it flows around the tool. As the tool moves forward, the material behind the tool cools down and a joint is formed in the solid state. 790

2 Effect of Process Parameters on the Tensile Strength of Friction Stir Nomenclatures b 0, b 1, Coefficients of regression equation Abbreviations SD Standard Deviation TRS Tool Rotation Speed TS Tensile Strength WS Welding Speed Fig. 1. Schematic of Friction Stir Welding. The process has numerous advantages which make it a preferred choice in a number of industries and for futuristic applications as detailed by Mishra and Ma [2]. The FSW process parameters play a primary role in deciding the strength and efficiency of the joints. The tool rotation speed (TRS) and welding speed (WS) are two important parameters influencing joint characteristics. The effect of these parameters on temperature distribution, material flow, microstructural evolution and mechanical properties decide the process window boundaries for a given material. FSW, ever since its invention has been extensively studied by researchers. Liu et al. [3] bring out the relation between welding parameters and tensile properties of AA2017-T351. Peel et al. [4] examine the microstructure and mechanical properties of friction stir (FS) welded aluminum alloy AA5083 under different conditions. Lim et al. [5] explore the influence of TRS and WS on the tensile behaviour of friction stir (FS)Welded AA6061-T651 alloy. Minton and Mynors [6] present a methodology for determining the process window for a given material. Sheikhi and Dos Santos [7] study the influence of welding parameters and welding tools on weld quality and mechanical properties of tailor welded blanks of AA6181- T4. Elangovan and Balasubramanian [8] examine the effect of different tool pin profiles and shoulder diameters on the formation of friction stir processing zone in AA6061 aluminum alloy. Liu and Ma [9] get AA6061-T651 FS welded joints under different process parameters and tool dimensions.

3 792 R. Padmanaban et al. Rajamanickam and Balusamy [10] study the effect of TRS and WS on temperature distribution and mechanical properties of FS welded aluminum alloy AA2014. Elangovan et al. [11] develop a mathematical model, incorporating FSW process parameters, to predict the tensile strength of friction stir welded aluminium alloy AA2219. Rajakumar and Balasubramanian [12] investigate the properties of FS welded joints made using six different grades of aluminium alloys. The joining of dissimilar materials is now becoming an inevitable requirement in many engineering applications and as such studies on joining of dissimilar materials is gaining momentum significantly. FSW paves the way for joining materials difficult to be joined by conventional methods. For example, in the case of automotive components, there is a need to weld aluminum and steel, which is practically impossible using conventional fusion welding techniques. Murr [13] presents a review that summarises FSW of similar and dissimilar material systems. Khodir and Shibayanagi [14] examine the effect of welding speed and location of base materials on microstructure, hardness distributions and tensile properties of dissimilar FS welded joints of AA 2024-T3 and AA7075-T6. DaSilva et al. [15] investigate the effect of joining parameters on tensile strength, hardness, material flow and microstructure of dissimilar FS welded joints between AA2024-T3 and AA7075-T6. Bahemmat et al. [16] study the effect of FSW parameters on the weldability, mechanical properties and grain size of FS welded dissimilar aluminum alloys AA2024-T4 and AA7075-O. Aluminum alloys of dissimilar combinations are required to be joined for many industrial applications. The 2xxx (Al-Cu) and 7xxx (Al-Zn-Mg) series alloys have potential application in modern and future aircrafts [17]. Of late, the skin and stringers in aircrafts (made of AA7075 and AA2024 respectively) are invariably joined using FSW. These alloys are difficult to be welded using arc welding processes due to hot cracking and stress corrosion cracking. Hence it is worthwhile to study and evaluate FSW process applied to these alloys. It can be seen from the aforesaid discussions that work done in this area are a few. So further investigation on FSW of these two dissimilar materials is surely worthwhile. Response surface methodology is used to develop a mathematical model for the tensile strength of AA2024 and AA7075 dissimilar joints. The developed model is used to study the effect of process parameters on the tensile strength of the joints. 2. Experimental Procedure AA2024 and AA7075 plates each of size mm are friction stir welded using a vertical milling centre shown in Fig. 2. The mechanical properties of the base materials are given in Table 1. The fixture for holding the aluminum plates during the FSW trials is made of mild steel plate of thickness 20 mm. A cylindrical threaded tool made of high speed steel, with a shoulder diameter of 17.5 mm, pin diameter of 5 mm and height 4.65 mm is used for the trials. The tool is fabricated using turning and thread grinding processes and no heat treatment is given to the tool. The pin is penetrated to a predetermined depth of 4.7 mm at the interface of the faying surfaces of the plates to be welded. After the dwell time of 45 seconds, the tool is given the forward motion till the collar end reaches other edge of the plates and joint is formed. The ranges for the process parameter are decided based on general appearance as also the visible quality of the weld to be obtained. It is seen that the heat

4 Effect of Process Parameters on the Tensile Strength of Friction Stir generation is not sufficient for TRS less than 900 rpm. On the contrary for TRS above 1200 rpm the heat generation is very high resulting in flash defects. When WS is less than 10 mm/min, defects occurred in the nugget zone and at WS higher than 20 mm/min, the machine is seen unstable resulting in tool failure. FSW trials are conducted as per face centred central composite design listed in Table 2. Table 1. Base Material Properties. Material Name AA2024-T3 AA7075-T6 Yield Strength (MPa) Ultimate Tensile Strength (MPa) Percent Elongation Micro hardness (VHN) The FS welded plates are sliced using a power hacksaw and tensile test specimens are prepared as per ASTM standard E8M-04 as shown in Fig. 3. The tensile tests are conducted using a Tinius Olsen computerised tensile testing machine, with a capacity of 25 kn at a cross head speed of 0.1 mm/min. The average tensile strength (TS) of three specimens corresponding to each set of parameters is given in Table 2. The predicted TS and its deviation from measured tensile strength are also given in the Table 2. The maximum efficiency obtained in this study is 58.2 % for joint number 9. Fig. 2. Experimental Setup Used. Fig. 3. Tensile Test Specimen, as per ASTM E8M-04 ([18]).

5 794 R. Padmanaban et al. The analysis of the fracture surface of tensile-tested specimens is carried out using a JEOL (model-jsm 6360) scanning electron microscope (SEM). The examination of fracture surface of the AA2024-AA7075 joints tested reveals an array of randomly distributed micro voids as shown in the Fig. 4. Failure of tensiletested specimens, in all cases, is governed by coalescence of micro voids. Similar results were reported in Cavaliere et al. [19]. Table 2. Matrix of Experiments and Results. S. No. N V TRS WS Measured TS Predicted (rpm) (mm/min) (MPa) TS (MPa) Error Fig. 4. Fractured Surface of a Tensile-Tested Specimen (SEM Image). 3. Development of the Model Response Surface Methodology (RSM) is used to develop a mathematical model for determining the tensile strength of the dissimilar FS welded joints as a function of TRS and WS. The TS of the joints in terms of TRS (N) and WS (V) is given by the second order polynomial Eq. (1), given below: 2 2 TS =b 0+b1 N+b2V+b11 N +b22v +b12 NV (1)

6 Effect of Process Parameters on the Tensile Strength of Friction Stir where b 0 is the average of responses and b 1, b 2 b 12 depend on the main and interaction effects of parameters. Details regarding RSM, experimental design and the development of the regression model can be found in Raymond et al. [20]. Here the coefficients are determined using the commercial statistical package Minitab and all the coefficients are evaluated and tested for their significance at 95% confidence level. The final model for determining the tensile strength of the welded specimens given below (Eq. (2)) is obtained by incorporating the significant coefficients identified. 2 2 TS = (N) (V) (N ) (V ) (2) Table 3. ANOVA. Source DF Sum of Squares Mean Squares F P Regression Linear N V Square N*N V*V Residual error Lack-of-Fit Pure Error Total SD = , R 2 = , Press = , R 2 Pred = , R 2 adj = The adequacy of the developed model is assessed using ANOVA and the results are tabulated in Table 3. If the probability value P is less than 5% for specific terms, then those terms are significant in the developed model. The P-Values for linear as well as quadratic terms are very small (less than ). The interaction effect of tool rotational speed with welding speed (N V) and the lack of fit are not significant. The lack of fit, on the quadratic model is seen to have a large P-Value (>0.05), implying that the quadratic model is adequate. The coefficient of determination (R 2 = ) signifies that only less than 1% of the total variations are not explained by the model. The coefficients R 2 adj (=0.9904) and R 2 pred (=0.9946) also indicate that insignificant terms are not included in the model. The measured and predicted tensile strength are seen to have a close correlation as depicted in Fig. 5. The data points come close to making a straight line, indicating the correlation between the two variables. In addition, the coefficient of correlation for the present case is found to be , which indicates positive correlation between the measured and predicted tensile strength. The normal probability plot of residuals is shown in Fig. 6 in which the residuals of the tensile strength lie on a straight line. This indicates that the errors obtained while comparing the predicted value and the measured value are distributed normally. For the developed model, the errors are found to be normally distributed and the P- value for lack of fit is not less than 5%, hence the developed model is highly adequate.

7 796 R. Padmanaban et al Predicted Tensile Strength (MPa) Experimental Tensile Strength (MPa) Fig. 5. Correlation Plot of Experimental and Predicted TS. 4. Results and Discussion Fig. 6. Normal Probability Plot of Residuals. FSW of AA2024-AA7075 is successfully completed at TRS and WS ranging from 900 rpm to 1200 rpm and 10 mm/min to 20 mm/min respectively. RSM is

8 Effect of Process Parameters on the Tensile Strength of Friction Stir used to develop the model for tensile strength of the joints. The developed model is used to study the effect of TRS and WS on the tensile strength of the joints. The results are depicted graphically in Figs Effect of tool rotation speed The tensile strength (TS) of all the joints is found to be lower than the TS of the base material. At low TRS, the heat generation is not sufficient to soften the material and therefore results in inefficient mixing of the materials. Hence the TS of the joints are found to be low. It is seen from Fig. 7 that the TS increases with increase in TRS right from 900 rpm to around 1100 rpm. This is basically due to increased heat generation obtained with increase in TRS resulting in better material flow and mixing of the materials. Increasing TRS beyond 1100 rpm causes reduction in tensile strength which can be attributed to increase in grain size due to grain growth at higher peak temperature. Further to this a high TRS (beyond 1100 rpm) produces flash and tunnel defects probably due to stirring effect of the pin at high speed. Elangovan and Balasubramanian [21] report similar results in their work. The aforesaid flash and tunnel defects seen when the TRS is increased beyond 1100 rpm can be attributed to the increased turbulence in the weld zone as reported by Elangovan et al. [18]. It is also seen that the pattern of variation of tensile strength remains the same irrespective of WS. It is seen that the joints made at a TRS around 1050 rpm yield the maximum tensile strength for a given WS WS=10 mm/min WS=15 mm/min WS=20 mm/min Tensile Strength (MPa) Tool Rotation Speed (rpm) Fig. 7. Variation of Tensile Strength with TRS at different WS Effect of welding speed The effect of WS on the tensile strength of the FS welded AA2024-AA7075 joint is shown in Fig. 8. At low WS, prolonged exposure of the work pieces to friction

9 798 R. Padmanaban et al. heating and the stirring of the tool results in the formation of flash defects leading to weak joints. It is seen from Fig. 8 that tensile strength of the joints increase with increase in WS approximately up to 15 mm/min irrespective of the TRS. Further increase in WS results in a reduction of tensile strength. The same trend is observed at all values of TRS. The tensile strength of joints fabricated at a WS of 20 mm/min, are lower than those fabricated at 10 mm/min and 15 mm/min. At higher WS, the weld area is exposed to friction heating for a shorter time, resulting in insufficient heating and poor plastic flow of the metal resulting in void formation. These voids act as stress raisers and affect the TS of the joint. This is in conformity with the observations made by Elangovan and Balasubramanian [21] TRS=900 rpm TRS=1050 rpm TRS=1200 rpm Tensile Strength (MPa) Welding Speed (mm/min) Fig. 8. Variation of Tensile Strength with WS at Different TRS. 280 Tensile Strength (MPa) Welding Speed (mm/min) Tool Rotation Speed (rpm) Fig. 9. Surface Plot of Tensile Strength.

10 Effect of Process Parameters on the Tensile Strength of Friction Stir The surface plot and contour plot showing the variation of tensile strength with TRS and WS are shown in Figs. 9 and 10 respectively. The plots reveal that strong welded joints between AA2024-AA7075 can be obtained when the TRS and WS are within 1075 rpm to 1125 rpm and 13 mm/min to 15 mm/min respectively. It is observed for the contour plot that maximum TS is obtained when the TRS and WS are respectively 1090 rpm and mm/min. Fig. 10. Contour Plot of Tensile Strength. 5. Conclusions Dissimilar aluminum alloys AA 2024 and AA 7075 are friction stir welded under varying TRS and WS, and the tensile strength of the joints are measured. RSM is used to develop a mathematical model (regression) for tensile strength in terms of TRS and WS. The regression model is used to investigate the effect of TRS and WS on the tensile strength of the joints. The following conclusions are made from the investigations. Both the TRS and WS will affect the TS of the joints. The tensile strength increases with increase in TRS up to a value of 1050 rpm. Further increase in TRS would result in a reduction of tensile strength. Similarly the tensile strength of joints increases with increase in WS up to 15 mm/min. Further increase in WS also results in a reduction in tensile strength. Surface and contour plots reveal that the tensile strength would be very near to maximum when the TRS and WS are within 1075 rpm to 1125 rpm and 13 mm/min to 15 mm/min respectively. The scope of this study is to determine the effect of tool rotation speed and welding speed on the tensile strength of friction stir welded dissimilar aluminum joints. The study can be further extended incorporating parameters like axial

11 800 R. Padmanaban et al. pressure, tool shoulder diameter, pin diameter, pin height and pin profiles. The effect of post weld heat treatment on the microstructure and mechanical properties of dissimilar friction stir welded joints can also be studied. Optimisation techniques can be used to determine the exact values of optimal process parameters. References 1. Thomas, W.M.; Nicholas, E.D.; Needham, J.C.; Murch, M.G.; Temple- Smith, P.; and Dawes, C.J. (1991). Friction stir butt welding.the Welding Institute,Cambridge,UK,GB patent No PCT/GB92/02203, International patent application No. PCT/GB92/ Mishra, R.S.; and Ma, Z.Y. (2005). Friction stir welding and processing. Materials Science and Engineering: R: Reports, 50(1-2), Liu, H.J.; Fujii, H.; Maeda, M.; and Nogi, K. (2003). Tensile properties and fracture locations of friction-stir-welded joints of 2017-T351 aluminum alloy. Journal of Materials Processing Technology, 142(3), Peel, M.; Steuwer, A.; Preuss, M.; and Withers, P. J. (2003). Microstructure, mechanical properties and residual stresses as a function of welding speed in aluminium AA5083 friction stir welds. Acta Materialia, 51(16), Lim, S.; Kim, S.; Lee, C.-G.; and Kim, S. (2004). Tensile behavior of friction-stri-welded Al 6061-T651. Metallurgical and Materials Transactions A, 35(9), Minton, T.; and Mynors, D.J. (2006). Utilisation of engineering workshop equipment for friction stir welding. Journal of Materials Processing Technology, 177(1-3), Sheikhi, S.; and Dos Santos, J.F. (2007). Effect of process parameter on mechanical properties of friction stir welded tailored blanks from aluminium alloy 6181-T4. Science and Technology of Welding and Joining, 12(4), Elangovan, K.; and Balasubramanian, V. (2008). Influences of tool pin profile and tool shoulder diameter on the formation of friction stir processing zone in AA6061 aluminium alloy. Materials & Design, 29(2), Liu, F.C.; and Ma, Z.Y. (2008). Influence of tool dimension and welding parameters on microstructure and mechanical properties of friction-stirwelded 6061-t651 aluminum alloy. Metallurgical and Materials Transactions A, 39(10), Rajamanickam, N.; and Balusamy, V. (2009). Effect of process parameters on thermal history and mechanical properties of friction stir welds. Materials & Design, 30(7), Elangovan, K.; Balasubramanian, V.; and Babu, S. (2008). Developing an empirical relationship to predict tensile strength of friction stir welded AA2219 Aluminum Alloy. Journal of Materials Engineering and Performance, 17(6), Rajakumar, S.; and Balasubramanian, V. (2012). Establishing relationships between mechanical properties of aluminium alloys and optimised friction stir welding process parameters. Materials & Design, 40,

12 Effect of Process Parameters on the Tensile Strength of Friction Stir Murr, L. (2010). A review of FSW research on dissimilar metal and alloy systems. Journal of Materials Engineering and Performance, 19(8), Khodir, S.A.; and Shibayanagi, T. (2008). Friction stir welding of dissimilar AA2024 and AA7075 aluminum alloys. Materials Science and Engineering: B, 148(1-3), Da Silva, A.A.M.; Arruti, E.; Janeiro, G.; Aldanondo, E.; Alvarez, P.; and Echeverria, A. (2011). Material flow and mechanical behaviour of dissimilar AA2024-T3 and AA7075-T6 aluminium alloys friction stir welds. Materials & Design, 32(4), Bahemmat, P.; Haghpanahi, M.; Besharati Givi, M.; and Reshad Seighalani, K. (2012). Study on dissimilar friction stir butt welding of AA7075-O and AA2024-T4 considering the manufacturing limitation. The International Journal of Advanced Manufacturing Technology, 59(9-12), Acerra, F.; Buffa, G.; Fratini, L.; and Troiano, G. (2010). On the FSW of AA2024-T4 and AA7075-T6 T-joints: an industrial case study. The International Journal of Advanced Manufacturing Technology, 48(9), Elangovan, K.; Balasubramanian, V.; and Babu, S. (2009). Predicting tensile strength of friction stir welded AA6061 aluminium alloy joints by a mathematical model. Materials & Design, 30(1), Cavaliere, P.; Cerri, E.; and Squillace, A. (2005). Mechanical response of aluminium alloys joined by friction stir welding. Journal of Materials Science, 40(14), Raymond, H.M.; Douglas, C.M.; and Christine, M.A.C. (2001). Response surface methodology: Process and product optimization using designed e4xperiments. (3 rd ed.). John Wiley & Sons Inc. 21. Elangovan, K.; and Balasubramanian, V. (2008). Influences of tool pin profile and welding speed on the formation of friction stir processing zone in AA2219 aluminium alloy. Journal of Materials Processing Technology, 200(1-3),