Optimization of Friction Stir Welding Parameters for AA3003 Aluminum Alloy Joints Using Response Surface Methodology

Transcription

1 International Journal of Mechanics and Solids. ISSN Volume 12, Number 1 (2017), pp Research India Publications Optimization of Friction Stir Welding Parameters for AA3003 Aluminum Alloy Joints Using Response Surface Methodology * Amit Goyal Research Scholar Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of science and Technology, Murthal Sonepat, India. Punit Kumar Rohilla Research Scholar Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of science and Technology, Murthal Sonepat, India. Atul Kumar Kaushik Research Scholar Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of science and Technology, Murthal Sonepat, India. Abstract This research article deals with the study on influence of friction stir welding parameters on the ultimate tensile strength of AA3003 aluminium alloy joints. Response surface methodology is utilized for establishing a empirical relation to predict the ultimate tensile strength of joints produced using friction stir welded method. Analysis of variance test is applied to check the adequacy of the developed model. The process parameters i.e. welding speed, rotational speed and tool tilt angle are optimized using the developed model and are set to be mm/min, rpm and 1.52 respectively. Keywords: FSW, RSM, UTS, aluminium alloy, optimization. * Corresponding Author

2 16 Amit Goyal, Punit Kumar Rohilla & Atul Kumar Kaushik 1. INTRODUCTION The demand of aluminium alloys in manufacturing sector is escalating day by day due to its remarkable amalgamation of characteristics like lighter weight, good strength, good weldability and high corrosion resistance. Nowadays these alloys known to be better alternate to ferrous metals in numerous sectors like aeronautics, automobile and military applications. Aluminium alloy AA3003 has a vital position in the class of light structural materials and is widely used in automotive industries, heat exchangers, container, storage tanks, fan blades, and walkways [1-3].The applicability of such materials is sometimes doubtful as conventional joining methods present some difficulties and disadvantages like porosity, oxidation and solidification cracks, in joining them. The increasing demand of aluminium based alloys in the manufacturing sector motivates the researchers and technologists to focus upon the more trustworthy and competent joining processes [4], and it is still an open challenge to fabricate high quality joint of these alloys [5]. Friction stir welding (FSW) is emerging as a green solid state joining method having enough competence to weld the materials having low melting point, especially aluminium alloys due to its attractive benefits like avoidance of solidification cracks, low distortion and residual stresses, environment friendliness. The ultimate tensile strength of joints fabricated using FSW may be up to 30% greater as compared to conventional welding techniques [6]. In FSW a tailor made rotating tool is forced to penetrate the work piece until the tool pin is completely inserted in the material and shoulder of the welding tool touches top surface of the specimens, as explained in Figure 1. Friction between the top surface of the specimens and tool shoulder serves as a source for generation of heat required to bond the metals to be welded [7].FSW process parameters like tool rotational and transverse speed, axial load, tool material characteristics, tool tilt angle influences the quality of joints [8]. Many researchers studied the effect of different process parameters like tool geometry [9-10], rotational and transverse speed [11], on weld quality of friction stir welded joints. Kalemba and Dymek [12] analyzed the weld quality of AA7136-T76 fabricated by FSW by varying the rotational speed of the welding tool. Figure 1. Friction stir welding- schematic view

3 Optimization of friction stir welding parameters for AA3003 aluminum alloy.. 17 Various methods have been utilized by the technologists for developing and analyzing the models and value assessment of different industrial problems [13-17]. Despite of having numerous applications, aluminium alloy AA3003 is the least studied material in terms of exploring the feasibility of applying FSW in fabricating high quality welding joints. The current investigation is an endeavor to study the influence of process parameters on the weld strength of AA3003 joints and to establish a mathematical relation to predict the ultimate tensile strength (UTS) of the joints fabricated by FSW, with the help of response surface methodology (RSM). 2. MATERIALS AND METHODOLOGY 2.1 Identification of potential FSW parameters Trial experiments were carried out to spot the potential FSW process parameters affecting weld strength of AA3003 joints. Tool rotational speed (N), welding speed (S) and tool tilt angle ( ) were chosen for the present investigation and the working range of selected parameters was also decided through primary trail runs based upon one factor at a time (OFAT) technique, in which one factor is varied at different levels keeping other factors at some predefined fixed level. The range of the identified process parameters was selected so as to ensure the joint to be free from any visible defects like blow hole, surface crack. The selected parameters along with the levels are presented in Table 1. Table 1: Levels of Selected parameters Parameters Rotational speed N(rpm) Welding speed S (mm/min) Tool tilt angle (degree) Level FSW tool and work material Square pin profiled tool, as shown in Figure 2, of H13 hot die steel was used for welding because of its suitability and far-reaching appliance. The fabrication was carried out in CNC turning center and EDM process so as to ensure the accurate profile and concavity of the welding tool. The fabricated tool was hardened to 45

4 18 Amit Goyal, Punit Kumar Rohilla & Atul Kumar Kaushik HRC by heat treatment to reduce the amount of wear and tear. Table 2 details the characteristics of the welding tool used in the present study. Figure 2: FSW tool The base material, used for the exploration on influence of FSW process parameters on the quality of joints, was taken as rolled sheet of AA3003 aluminium alloy having 5 mm thickness. A shear cutting press was used to slice down the sheet into 150mm x 75 mm size specimens. A special fixture was fabricated to hold and clamp the workpiece in position and to withstand the welding forces. Table 3 and Table 4 present the chemical composition and properties of AA3003 aluminium alloy respectively. Table 3: Chemical Composition of AA3003 Elements Mn Fe Cu Zn Si Al Wt % Balance Table 4: Mechanical Properties of AA3003 Material UTS(MPa) Yield Strength(MPa) % Elongation Hardness(HV) AA Design of experiments 3-factor 5-level, rotatable central composite design matrix, having 20combinations of different levels of selected parameters, was used in optimization. The upper and lower limit of a factor is coded as and respectively. The selected design is composed of 2 3 =8 full factorial, 6 center and 6 star points. Table 5 presents the

5 Optimization of friction stir welding parameters for AA3003 aluminum alloy.. 19 selected design matrix in coded and actual values of different levels of process parameters. Table 5: Design of experiments Std. order Process parameters (coded) Process parameters (actual) Response UTS (MPa) N S N (rpm) S (mm/min) (degree)

6 20 Amit Goyal, Punit Kumar Rohilla & Atul Kumar Kaushik 2.4 Experiments A CNC vertical milling center was employed to execute the experiments as per the design of experiments. A tailor made fixture as demonstrated in Figure 3, was fabricated to clutch and lock the specimens so as to withstand the welding forces. The guidelines of ASTM-E8 M04 standard were followed in preparation of tensile test samples from the welded specimens. A hydraulic powered universal testing machine (UTM) (capacity 1000 KN, make: Aimil limited) was used to carry out tensile test of the samples. Three tensile test samples were severed and tested from each weldment so as to ensure the accuracy in obtaining the joint s tensile strength. The average of three readings for each joint is tabulated in Table 5. The tensile test specimens are shown in Figure 4. Figure 3: FSW fixture Figure 4:tensile test specimens 3. RESULTS AND DISCUSSION 3.1Model development The relation between UTS and identified parameters i.e. tool rotational speed (N), welding Speed (S) and tool tilt angle (θ) may be manifested as: Y (UTS) = f (N, S, θ) The selected polynomial uses to represent the response surface for the three factors can be manifested as Y b0 b1 N b2s b3 b11n b22s b33 b12ns b13n b23s Design Expert DX10 software package was used to determine the values of coefficients in the above equation as presented in Table 6 and their significance were tested at 95% confidence level applying Fisher s F-test. Based upon the calculated coefficient, following empirical mathematical relation was set up to predict the UTS of AA3003 joints. UTS = N+2.04S+0.99θ-6.33N S θ NS+1.36Nθ+1.59Sθ

7 Optimization of friction stir welding parameters for AA3003 aluminum alloy.. 21 Table 6: Calculated regression coefficients Intercept (b 0) N (b 1) S (b 2) θ (b 3) N-S (b 12) N-θ (b 13) S-θ (b 23) N 2 (b 11) S 2 (b 22) θ 2 (b 33) The developed model was checked for adequacy using analysis of variance test (ANOVA) and the outcome is presented in Table 7. The F-value for lack of fit is which implies that the lack of fit is insignificant relative to the pure error. The developed model is said to be adequate as the model F-value is The goodness of fitness of the model may be judged by the value of coefficient of determination R 2, which should be approaching 1 for a good model. The predicted R 2 value for the model is 0.80 which implies that 80% of the experimental data is compatible with the predicted data. The adjusted R 2 value for the model is 0.91 proving the significance of the model. Source Sum of Squares Table 7: ANOVA test results D.O.F Mean Square F Value Prob>F Results Model < Significant N S θ N-S N-θ S-θ N < S < θ < Residual Lack of Fit Not Significant Pure Error Cor. Total The difference of the values of predicted and adjusted coefficients of determination is less than 0.2 which indicates the sensible agreement. The signal to noise ratio is

8 22 Amit Goyal, Punit Kumar Rohilla & Atul Kumar Kaushik measured by adequate precision and should be greater than 4. In this case, the ratio comes to be indicating the adequacy of signal and consequently implies that the developed model can be employed to navigate the designed domain. Figure 5: Normal probability plot Figure 6: Scatter diagram for UTS Figure 5 presents the normal probability plot, showing the residuals falling on a straight line indicating the normally distributed errors for the developed model. The plot as shown in Figure 6 presents the kind of fit between the experimental data and the predicted data. Almost all the values are spreaded near to the 45 0 line which indicate the perfect fitness of the developed model. 3.2 Model Validation Three random combinations of rotational speed, welding speed and tool tilt angle were taken, other than those of design matrix, to accomplish the confirmation experiments. The results of the confirmation tests and % error are tabulated in Table 8. Rotational speed (rpm) Table 8: Confirmation tests results Parameters UTS (MPa) % Error Welding speed (mm/min) Tool tilt angle ( 0 ) Experimental Predicted % % %

9 Optimization of friction stir welding parameters for AA3003 aluminum alloy Parameter optimization It is always been desirable for the Engineers to find out such combinations of welding parameters for which performance characteristics like strength, microhardness, corrosion rate reach their optimum values. RSM is one of the most significant techniques which is recently been used to optimize the process parameters. It is a compilation of statistical and mathematical techniques to solve the problem having several independent variables (process parameters) influencing a dependent variable. Values of process parameters to achieve optimum UTS are set up to be rpm rotational speed, mm/min welding speed and 1.52 tool tilt angle. (a) (b) In the current examination, RSM technique was employed to develop empirical mathematical relation to predict the UTS and to optimize the FSW parameters for AA3003 aluminium alloy joints. Figure 7-8 presents the influence of process parameters on the UTS of FS welded 3003 aluminium alloy joints. It is clear from

10 24 Amit Goyal, Punit Kumar Rohilla & Atul Kumar Kaushik Figure 7 (a) and (b) that the UTS of the AA3003 joints increase as the tool rotational speed goes on increasing up to a level and then starts decreasing. This pattern may be understand by the grain size refinement with the augment in the rotational speed up to a particular level and then by grains coarsening at very high rotational speeds due to turbulence in flow of the soften material. Welding speed and tool tilt angle follows almost similar pattern in terms of effect on ultimate tensile strength. Prediction N S Prediction N (a) (b)

11 Optimization of friction stir welding parameters for AA3003 aluminum alloy.. 25 Figure 7 presents the 3-dimensional surface plot of UTS obtained through the developed empirical model. Figure 8 shows the contour plots indicating the feasible independence of the parameters, considering one out of three parameters in the middle and remaining two factors on x-axis and y-axis respectively. The apex of the response plot indicates the optimum valve of UTS. In the present study the optimum value of UTS is MPa, found through the analysis of response surface and contour plots. The 4. CONCLUSION The present study was an attempt to effectuate empirical relation between UTS and FSW process parameters of AA3003 aluminium alloy joins and the outcomes are as following 1. Feasible working range of FSW parameters is found to get defect free AA3003 aluminium alloy joints. 2. Response surfaces were plotted to examine the influence of process parameters on the weld quality in terms of UTS of AA3003 aluminium alloy FS welded joints. 3. A mathematical model was developed for prediction of UTS as a function of welding speed, rotational speed and tool tilt angle. 4. The adequacy of the developed model is checked and found to be satisfactory. 5. The values of rotational speed, welding speed and tool tilt angle, to get the optimum UTS of MPa, is found to be rpm, mm/min and 1.52 respectively. REFERENCES [1] Abnar, B., Kazeminezhad, M., & Kokabi, A. H. (2015). Effects of heat input in friction stir welding on microstructure and mechanical properties of AA3003-H18 plates. Transactions of Nonferrous Metals Society of China, 25(7), pp [2] Huang, H. W., & Ou, B. L. (2009). Evolution of precipitation during different homogenization treatments in a 3003 aluminum alloy. Materials and Design, 30(7), pp [3] Jaradeh, M. M. R., & Carlberg, T. (2011). Solidification Studies of 3003 Aluminium Alloys with Cu and Zr Additions. Journal of Materials Science and Technology, 27(7), pp [4] Moreira, P. M. G. P., de Jesus, A. M. P., Ribeiro, A. S., & de Castro, P. M. S. T. (2008). Fatigue crack growth in friction stir welds of 6082-T6 and 6061-T6 aluminium alloys: A comparison. Theoretical and Applied Fracture Mechanics, 50(2), pp [5] Moshwan, R., Yusof, F., Hassan, M. A., & Rahmat, S. M. (2015). Effect of tool rotational speed on force generation, microstructure and mechanical properties of friction stir welded Al-Mg-Cr-Mn (AA 5052-O) alloy. Materials and Design, 66, pp

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