# Experimental Investigation of AA6063 Welded Joints Using FSW

Authors: T. Rajkumar; K. Radhakrishnan; C. Rajaganapathy; S. P. Jani; Nowshadth Ummal Salmaan
Journal: Advances in Materials Science and Engineering
 (2022)

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## Abstract

The AA6063 aluminium alloy has gained widespread use in manufacturing the light-weighted structures which requires a high strength to weight ratio, and it possesses an excellent corrosive resistance in T6 heat-treated (solution heat treated and artificially aged) condition. The process of friction stir welding (FSW) is an emerging joining process of solid state that does not melt and recast the material being welded, as opposed in various other fusion welding processes, which are extensively utilized for combining the structural alloys of aluminium. The process of connecting separate components with external heat has resulted in induced stress on metals. The stir welding using friction was introduced in order to reduce the formation in residual stress during the joining process. The aluminium alloy AA6063 plates were fused utilising the friction stir welding procedure in this study. The studies were carried out using various combinations of speed in rotary condition, speed in transverse condition, and stress in axial condition. The generated joints that are welded was analysed mechanically and microstructurally. The maximum hardness of the mechanical joints produced is 93.25 HV, and the maximum tensile strength is 286.15 N/mm2. According to the results of the response surface analysis, transverse and rotary velocities possess a notable impact in hardness and durability, respectively.


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## Body

## 1. Introduction

Friction stir welding (FSW) is a solid phase welding technology that capacitate for welding of a wide range of parts and geometries of various structural alloys such as Al-alloys, Cu-alloys, and steel [4–8]. FSW is a late approach which uses an incombustible rotary tool for welding to produce heat by friction and plasticity in the fusing area, influencing junction formation much as the substance is still solid. The weld, on average, reduces the thickness of the parent metal by 3–6 percent [1,2]. The stir action is provided by the revolving tool, which plasticizes metal within a restricted zone while moving metal from the pin’s leading face to the trailing edges. The tool and the work piece to be connected are moved in relation to each other to the point where the tool tracks along the weld interface. The weld cools as the tool passes over it, cementing the two plates [3].This procedure can locally wipe out the defects that usually arise in fusion welding of Al-alloys such as porosity formation [9–13] accordingly improvising the physical strength and malleability, enhancing resistive property to corrosive and fatigue of the substance, and upgrading malleability along with enhancing different possessions. The goal of this research is to optimise the parameters which can be listed as the rotating speed (RS), velocity in welding (WS), and the angle of tool tilt (TTA) in order to achieve superior mechanical properties such as strength in tensile property and firmness of the friction stir welding joint on alloys of aluminium (AA6063).The investigations are devised by the Taguchi design concept. Three-factor and three-level design matrices have been developed by using MINITAB 17 software package.The tool is not consumed in the FSW process when mixing and joining the workpiece materials. As a result, it is referred to as nonconsumable tool. The tool with the pin in the shoulder is introduced to the neighbouring edges of the plate and moved in a line until it reaches the conclusion of the process [14–21]. Because of its energy efficiency and economic considerations, it is a cutting-edge approach in the metal joining process. The general arrangement of solid-state joining techniques is depicted in Figure 1.Figure 1
General arrangement of FSW.


## 2. Methodology

### 2.1. Needs of DOE

DOE, or design of experiments, is used in a variety of industries, such as in the improvement and optimization of manufacturing processes. The fabrication of wafers in the electronics business, the manufacturing of engines in the auto industry, and the blending of substances in the pharmaceutical sector are all common examples.


#### 2.1.1. Taguchi Orthogonal Array

Orthogonal arrays are a type of conventional experimental design that only takes a minimal number of trials to determine the primary elements that influence output, as shown in Table1. The 9-run array is preferable (if cost and time allow) because each level of any one parameter gets evaluated along with all three levels of the other parameters. Of course, either array here is less expensive to perform than a full factorial analysis, because a full factorial analysis requires N = LP = 33 = 27 runs. Variables are assigned to columns based on the primary factor, as specified by the orthogonal array.Table 1
Taguchi L9 orthogonal array.
Trial no.Taguchi L9 (parameters = 3 and levels = 3)Rotational speedWelding speedTool tilt angle156060025608013560100247306015730802673010007900602890080099001001


## 2.1. Needs of DOE

DOE, or design of experiments, is used in a variety of industries, such as in the improvement and optimization of manufacturing processes. The fabrication of wafers in the electronics business, the manufacturing of engines in the auto industry, and the blending of substances in the pharmaceutical sector are all common examples.


### 2.1.1. Taguchi Orthogonal Array

Orthogonal arrays are a type of conventional experimental design that only takes a minimal number of trials to determine the primary elements that influence output, as shown in Table1. The 9-run array is preferable (if cost and time allow) because each level of any one parameter gets evaluated along with all three levels of the other parameters. Of course, either array here is less expensive to perform than a full factorial analysis, because a full factorial analysis requires N = LP = 33 = 27 runs. Variables are assigned to columns based on the primary factor, as specified by the orthogonal array.Table 1
Taguchi L9 orthogonal array.
Trial no.Taguchi L9 (parameters = 3 and levels = 3)Rotational speedWelding speedTool tilt angle156060025608013560100247306015730802673010007900602890080099001001


## 2.1.1. Taguchi Orthogonal Array

Orthogonal arrays are a type of conventional experimental design that only takes a minimal number of trials to determine the primary elements that influence output, as shown in Table1. The 9-run array is preferable (if cost and time allow) because each level of any one parameter gets evaluated along with all three levels of the other parameters. Of course, either array here is less expensive to perform than a full factorial analysis, because a full factorial analysis requires N = LP = 33 = 27 runs. Variables are assigned to columns based on the primary factor, as specified by the orthogonal array.Table 1
Taguchi L9 orthogonal array.
Trial no.Taguchi L9 (parameters = 3 and levels = 3)Rotational speedWelding speedTool tilt angle156060025608013560100247306015730802673010007900602890080099001001


## 3. Experimental Work

The materials utilized in this experiment were 6 mm thick aluminium alloy AA6063-T6 plates. For friction stir welding, the rolled plates were cut and machined into the appropriate shapes of 120 mm long and 100 mm broad. Welding was done on an FSW machine, which uses a tool with a design that fits the job. Table2 shows chemical composition of AA6063.Table 2
Chemical composition of AA 6063.
ElementsSiFeCuMnMgCrZnTiAlPercentage0.2–0.60.350.10.10.45–0.90.10.10.1RemTool RS, tool TS, and TTA are the process parameters. FSW was performed using a cylindrical tool that is made of high-speed steel (HSS) with a threaded pin along a 16 mm shoulder diameter, 5.7 mm length in pin, and 6 mm diameter in pin (Figure2). The pin was positioned in the joint line’s middle. Figure 3 shows FSW arrangements.Figure 2
Geometry of the FSW tool.Figure 3
General arrangement of FSW.


### 3.1. Procedure Parameters and Its Levels

The experiments were designed using Taguchi’s method [22, 23]. Throughout three different parameters and three different levels, an orthogonal array of L9 was employed. The range of parameters was determined based on multiple experimental trials [24–30]. The independently variable major process parameters that govern aspect ratio were discovered. The Taguchi orthogonal array selector for the parameters and its levels are given in Table 3.Table 3
Process parameters and design levels.
S. no.ParametersLevels1231RS (rpm)5607309002WS (mm/min)60801003TTA (degree)012


## 3.1. Procedure Parameters and Its Levels

The experiments were designed using Taguchi’s method [22, 23]. Throughout three different parameters and three different levels, an orthogonal array of L9 was employed. The range of parameters was determined based on multiple experimental trials [24–30]. The independently variable major process parameters that govern aspect ratio were discovered. The Taguchi orthogonal array selector for the parameters and its levels are given in Table 3.Table 3
Process parameters and design levels.
S. no.ParametersLevels1231RS (rpm)5607309002WS (mm/min)60801003TTA (degree)012


## 4. Results and Analysis

### 4.1. Tensile Test

Each welded plate was made to tensile test specimens in line with ASTM E8M-04 specifications. The proportions of the testing specimen in tensile property are shown in Figure4. Tensile test specimens are described in Figure 4 which were made with a wire cut EDM. Tensile specimens in transverse section with a length of gauge having 57 mm and a width of 13 mm were made from the weld samples (overall length: 136 mm). Nine illustrative specimens were tensile-tested at a nominal ambient room temperature with a universal tensile testing machine. Figure 5 shows the ASTM standard tensile specimen.Figure 4
Dimensions of the tensile specimen.Figure 5
Tensile specimen.The tensile test findings for the experiment are shown in Table4 and Figure 6.Table 4
Tensile test results obtained for various tensile specimens.
Trial no.RS (rpm)WS (mm/min)TTA (degree)Ultimate tensile strength (N/mm2)1560600286.152560801235.8935601002120.5747306012055730802107.6967301000151.2879006021308900800133.3399001001233.33Figure 6
Graph of tensile strength.


### 4.2. Hardness Test

The Vickers microhardness testing machine was assessed to assess microfirmness values along the welded zone of samples. Vickers microhardness testing technique IS: 1501 was used to take hardness measurements at various places with an applied load of 100 gm. A square-based pyramid diamond intender with an angle of apex about 136° is utilized in Vickers test. The indenter is pressed through the surface of the specimen for 10 to 15 seconds under force. The indentation diagonalsd (mm2) are measured following the load provided, and the indenter is withdrawn. The hardness number of Vickers HV is obtained by splitting the applied load F (kgf) by the exterior surface area A of the indentation (mm). As a result, the HV is given in Table 5 and Figure 7.Table 5
Hardness test results.
Trial no.Rotational speed (rpm)Welding speed (mm/min)Tool tilt angle (degree)Hardness (HV)156060086.12256080193.253560100281.45473060186.12573080289.026730100084.12790060280.25890080085.359900100187.35Figure 7
Graph of hardness.


### 4.3. Analysis of S/N Ratio

(1)SN=−10log101n∑i=1n1Yi2.Taking the first trial, −10 log10 [1/2 × ((1/286.152) + (1/862))] = 41.32 dB.Table6 shows response values and S/N ratio outcomes for experiments. A high S/N number corresponds to better performance regardless of the performance characteristic category. Table 7 shows the outcomes of creating a response table for RS, WS, and TTA in an integrated way.Table 6
Response values and S/N ratio values for experiments.
Exp. no.Rotational speed (RPM)Welding speed (mm/min)Tool tilt angle (degree)Tensile strength (MPa)Hardness (HV)S/N ratio1560600286.158641.32472560801235.899341.752535601002120.518139.56147306012058640.99625730802107.698939.737267301000151.288440.328879006021308039.67748900800133.338540.117599001001233.338741.2353Table 7
Response table for signal to noise ratios.
LevelsRS (rpm)WS (mm/min)TTA (degree)140.8840.6740.59240.3540.5441.33340.3440.3839.66Delta0.540.291.67Rank231Larger is betterThe most significant factor, according to the delta values from Table6, is angle, of tool tilt following the rotary velocity, and finally welding speed. The main effect plots displayed in Figures 8–10 were created using MINITAB 17 software and the answer statistics and ratio of s/n values from Table 6.Figure 8
The main effect plots for SN ratios.Figure 9
The main effect plots for tensile strength (MPa).Figure 10
The main effect plots for hardness (HV).The larger-the-better criterion was used to calculate S/N ratio values. In a major effect plot, if the line’s inclination is higher, the corresponding parameters are more significant, and if the line’s inclination is lower, the impacts of the corresponding factor are lower. The major effect graphs at the highest S/N ratio values of response variables corresponding to each factor can be used to determine the best parametric setting. The best condition isA1, B1, and C2 (i.e., rotary speed (A) = 560 RPM, speed of welding (B) = 60 mm/min, and angle of tool tilt (C) = 1 degree).


### 4.4. Analysis of Variance (ANOVA)

The F value is utilized to trail the importance of an element in the ANOVA (Table8) by set side-by-side model variance along with the variance of residual (derived by splitting the model’s mean square through the mean square of residue) [31–33]. If the difference in the value is close in proximity to one another, the ratio obtained would be close to one, and any of the factors will be less likely to have a substantial impact on the response. A higher value of F for a limiting factor indicates that the limiting factor has a larger consequence on the characteristics. The maximum value of F in the operation is obtained through a tool tilt angle of 9.22, as shown in Table 8. Table 9 and Figure 11 show the optimum condition and percentage contribution of parameters.Table 8
Analysis of variance for S/N ratios.
SourcesDFAdj SSAdj MSFPRotational speed (RPM)20.56340.281681.240.447Welding speed (mm/min)20.12760.063780.280.781Tool tilt angle (degree)24.19962.09989.220.098Residual error20.45530.22765Total85.3458Table 9
Optimum condition and percentage contribution of parameters.
S. no.FactorsLevel descriptionRankContribution (%)1Rotational speed (rpm)560210.502Welding speed (mm/min)6032.303Tool tilt angle (degree)1178.50(2)PercentagecontributionP=SS′ASST×100.Figure 11
Contribution of process parameters.Rotational speed (rpm) = 0.5634/5.3458 × 100 = 10.5%.Welding speed (mm/min) = 0.1276/5.3458 × 100 = 2.3%.Tool tilt angle (degree) = 4.1996/5.3458 × 100 = 78.5%.Error (E) = 0.4553/5.3458 × 100 = 8.5%.


### 4.5. Regression Model Analysis

Regression equations for output response, respectively, as shown in Tables10 and 11, give actual and predicted value of tensile and hardness.Table 10
Actual values and predicted values of tensile strength.
Exp. no.Tensile strength (MPa)Actual valuePredicted value1286.15256.722235.89201.923120.57147.124205197.015107.69142.216151.28193.617130137.38133.33188.79233.33133.9Table 11
Actual values and predicted values of hardness.
Exp. no.Hardness valuesActual valuePredicted value186882938738186486855898568486780838858598784Tensile strength (MPa) = 395 − 0.143 RS (RPM) − 0.97 WS (mm/min) − 35.4 tool tilt angle (degree).Hardness (HV) = 92.2 − 0.0078 RS (RPM) + 0.0000 WS (mm/min) − 0.83 tool tilt angle (degree).Taking the first trail, tensile strength (MPa) = 395 − 0.143 (560) − 0.97 (60) − 35.4 (0) = 256.75 MPA.Hardness (HV) = 92.2 − 0.0078 (560) + 0.000 (60) − 0.83 (0) = 87.83 = 88 Hv.In a coordinate plane, the graph plot shows ordered pairs ofX and Y variables. It provides a clear visual representation of the relationship between the two variables and aids in regression model interpretation. The experimental and anticipated weld strength and hardness values obtained from the regression models are plotted and are practically identical in Figures 12 and 13, indicating that the constructed regression models are well-fitted.Figure 12
Interaction effects of rotational speed and welding speed on tensile strength.Figure 13
Interaction effects of rotational speed and tool tilt angle on tensile strength.


## 4.1. Tensile Test

Each welded plate was made to tensile test specimens in line with ASTM E8M-04 specifications. The proportions of the testing specimen in tensile property are shown in Figure4. Tensile test specimens are described in Figure 4 which were made with a wire cut EDM. Tensile specimens in transverse section with a length of gauge having 57 mm and a width of 13 mm were made from the weld samples (overall length: 136 mm). Nine illustrative specimens were tensile-tested at a nominal ambient room temperature with a universal tensile testing machine. Figure 5 shows the ASTM standard tensile specimen.Figure 4
Dimensions of the tensile specimen.Figure 5
Tensile specimen.The tensile test findings for the experiment are shown in Table4 and Figure 6.Table 4
Tensile test results obtained for various tensile specimens.
Trial no.RS (rpm)WS (mm/min)TTA (degree)Ultimate tensile strength (N/mm2)1560600286.152560801235.8935601002120.5747306012055730802107.6967301000151.2879006021308900800133.3399001001233.33Figure 6
Graph of tensile strength.


## 4.2. Hardness Test

The Vickers microhardness testing machine was assessed to assess microfirmness values along the welded zone of samples. Vickers microhardness testing technique IS: 1501 was used to take hardness measurements at various places with an applied load of 100 gm. A square-based pyramid diamond intender with an angle of apex about 136° is utilized in Vickers test. The indenter is pressed through the surface of the specimen for 10 to 15 seconds under force. The indentation diagonalsd (mm2) are measured following the load provided, and the indenter is withdrawn. The hardness number of Vickers HV is obtained by splitting the applied load F (kgf) by the exterior surface area A of the indentation (mm). As a result, the HV is given in Table 5 and Figure 7.Table 5
Hardness test results.
Trial no.Rotational speed (rpm)Welding speed (mm/min)Tool tilt angle (degree)Hardness (HV)156060086.12256080193.253560100281.45473060186.12573080289.026730100084.12790060280.25890080085.359900100187.35Figure 7
Graph of hardness.


## 4.3. Analysis of S/N Ratio

(1)SN=−10log101n∑i=1n1Yi2.Taking the first trial, −10 log10 [1/2 × ((1/286.152) + (1/862))] = 41.32 dB.Table6 shows response values and S/N ratio outcomes for experiments. A high S/N number corresponds to better performance regardless of the performance characteristic category. Table 7 shows the outcomes of creating a response table for RS, WS, and TTA in an integrated way.Table 6
Response values and S/N ratio values for experiments.
Exp. no.Rotational speed (RPM)Welding speed (mm/min)Tool tilt angle (degree)Tensile strength (MPa)Hardness (HV)S/N ratio1560600286.158641.32472560801235.899341.752535601002120.518139.56147306012058640.99625730802107.698939.737267301000151.288440.328879006021308039.67748900800133.338540.117599001001233.338741.2353Table 7
Response table for signal to noise ratios.
LevelsRS (rpm)WS (mm/min)TTA (degree)140.8840.6740.59240.3540.5441.33340.3440.3839.66Delta0.540.291.67Rank231Larger is betterThe most significant factor, according to the delta values from Table6, is angle, of tool tilt following the rotary velocity, and finally welding speed. The main effect plots displayed in Figures 8–10 were created using MINITAB 17 software and the answer statistics and ratio of s/n values from Table 6.Figure 8
The main effect plots for SN ratios.Figure 9
The main effect plots for tensile strength (MPa).Figure 10
The main effect plots for hardness (HV).The larger-the-better criterion was used to calculate S/N ratio values. In a major effect plot, if the line’s inclination is higher, the corresponding parameters are more significant, and if the line’s inclination is lower, the impacts of the corresponding factor are lower. The major effect graphs at the highest S/N ratio values of response variables corresponding to each factor can be used to determine the best parametric setting. The best condition isA1, B1, and C2 (i.e., rotary speed (A) = 560 RPM, speed of welding (B) = 60 mm/min, and angle of tool tilt (C) = 1 degree).


## 4.4. Analysis of Variance (ANOVA)

The F value is utilized to trail the importance of an element in the ANOVA (Table8) by set side-by-side model variance along with the variance of residual (derived by splitting the model’s mean square through the mean square of residue) [31–33]. If the difference in the value is close in proximity to one another, the ratio obtained would be close to one, and any of the factors will be less likely to have a substantial impact on the response. A higher value of F for a limiting factor indicates that the limiting factor has a larger consequence on the characteristics. The maximum value of F in the operation is obtained through a tool tilt angle of 9.22, as shown in Table 8. Table 9 and Figure 11 show the optimum condition and percentage contribution of parameters.Table 8
Analysis of variance for S/N ratios.
SourcesDFAdj SSAdj MSFPRotational speed (RPM)20.56340.281681.240.447Welding speed (mm/min)20.12760.063780.280.781Tool tilt angle (degree)24.19962.09989.220.098Residual error20.45530.22765Total85.3458Table 9
Optimum condition and percentage contribution of parameters.
S. no.FactorsLevel descriptionRankContribution (%)1Rotational speed (rpm)560210.502Welding speed (mm/min)6032.303Tool tilt angle (degree)1178.50(2)PercentagecontributionP=SS′ASST×100.Figure 11
Contribution of process parameters.Rotational speed (rpm) = 0.5634/5.3458 × 100 = 10.5%.Welding speed (mm/min) = 0.1276/5.3458 × 100 = 2.3%.Tool tilt angle (degree) = 4.1996/5.3458 × 100 = 78.5%.Error (E) = 0.4553/5.3458 × 100 = 8.5%.


## 4.5. Regression Model Analysis

Regression equations for output response, respectively, as shown in Tables10 and 11, give actual and predicted value of tensile and hardness.Table 10
Actual values and predicted values of tensile strength.
Exp. no.Tensile strength (MPa)Actual valuePredicted value1286.15256.722235.89201.923120.57147.124205197.015107.69142.216151.28193.617130137.38133.33188.79233.33133.9Table 11
Actual values and predicted values of hardness.
Exp. no.Hardness valuesActual valuePredicted value186882938738186486855898568486780838858598784Tensile strength (MPa) = 395 − 0.143 RS (RPM) − 0.97 WS (mm/min) − 35.4 tool tilt angle (degree).Hardness (HV) = 92.2 − 0.0078 RS (RPM) + 0.0000 WS (mm/min) − 0.83 tool tilt angle (degree).Taking the first trail, tensile strength (MPa) = 395 − 0.143 (560) − 0.97 (60) − 35.4 (0) = 256.75 MPA.Hardness (HV) = 92.2 − 0.0078 (560) + 0.000 (60) − 0.83 (0) = 87.83 = 88 Hv.In a coordinate plane, the graph plot shows ordered pairs ofX and Y variables. It provides a clear visual representation of the relationship between the two variables and aids in regression model interpretation. The experimental and anticipated weld strength and hardness values obtained from the regression models are plotted and are practically identical in Figures 12 and 13, indicating that the constructed regression models are well-fitted.Figure 12
Interaction effects of rotational speed and welding speed on tensile strength.Figure 13
Interaction effects of rotational speed and tool tilt angle on tensile strength.


## 5. Interaction Effects of Process Variables

Figures12 and 13 show the interaction effects of the specified process factors on tensile strength. Tensile strength is less affected by RS and WS. Tensile strength is mostly affected by RS and tool tilt angle.The impact of rotating speed and welding speed on hardness is reduced, as shown in Figures14 and 15. The impact of rotary velocity and angle of tool tilt on hardness is greater.Figure 14
Interaction effects of rotational speed and welding speed on hardness.Figure 15
Interaction effects of rotational speed and tool tilt angle on hardness.


## 6. Metallographic Observations

The distinct zones in microstructure of the welded samples are studied using metallographic inspection of transverse cross sections [34–37]. Due to differences in grain size and orientation, various microstructural zones listed as stir zone (SZ), heat-affected zone (HAZ), and thermo-mechanically affected zone (TMAZ) of comparable FS welded joints have been found using scanning electron microscopy (SEM). There is a distinct interaction between the HAZ, TMAZ, and SZ regions of the FSW joint (Figure 16).Figure 16
Microstructures of HAZ + TMAZ of the FS welded joint.According to ASTM E-2142, the microstructural study was done in the transverse (YZ) plane. The material was segmented in the proper direction, installed, and cleaned to remove any remaining cutting damage. It was enough to finish the polishing procedure with a quick chemical polish in the OPS solution before etching in a solution of 4 ml HF, 4 ml H2SO4, and 2 g CrO3 in 90 ml water for optical microscopy. Electro polishing the sample in 30 percent nitric acid/methanol for 20–30 seconds was required for the more demanding requirements of scanning electron microscopy (SEM). A Philips XL30 FEGSEM, interfaced to a HKL channel EBSD system, was used to generate SEM pictures and electron backscatter diffraction (EBSD) patterns at 15–30 kV and a current of roughly 4 nA.Figure17 indicates that the grains in the stir region are fine and equiaxed, whereas the other regions have higher mechanical strength and ductility. During the FSW process, TMAZ is exposed to both temperature and deformation. Due to insufficient heating, recrystallization did not occur in this zone, albeit, it did undergo some plastic deformation. Mechanical processes have no influence on the HAZ, and there is no plastic deformation in the HAZ [38].Figure 17
Microstructures of TMAZ + HAZ of the FS welded joint.The number of tunnels and pores grows as welding speed increases and flaws travel upright to the aluminium weld nugget [39]. Due to the tool’s lesser time to plasticize and reframe the substances around the pin, and as the highest temperature of the weld drops, the flow stress of the materials rises, resulting in nonsufficient deformation in plasticity of the material at the welding area [40]. In this case, the tool is unable to complete the line of weld and consolidate materials in the zone of welding, resulting in the formation of a tunnel.The analysis of elements or chemical characteristics of a substance is carried out using energy dispersive X-ray analysis (EDXA). It is relied on an interactivity between an X-ray source and a sample. The fundamental conception is that each element possesses a distinctive atomic structure, allowing for a unique set of peaks on its electromagnetic emission spectrum, is predicted to play a large role in its portrayal capabilities. The EDX (Figure18) analysis is effective for identifying materials and impurities, as well as determining their relative concentrations on the specimen’s surface.Figure 18
EDX mappings of the FS welded joint.


## 7. Conclusion

With experimental analysis and outcomes, a thorough experimental inquiry is processed to assess the effect of major FSW processive parameters. The Taguchi L9 orthogonal planned experiments have been offered as a method of determining the FSW parameters for welded aluminium alloy (6063) joints. The ANOVA table and main effect charts reveal that tool tilt angle and rotary velocity have a notable impact on tensile strength and hardness. Welding speed has a smaller impact.The processive parameters were tuned for maximum tensile strength and hardness of the welded connection, with 560 rpm, 60 mm/min, and 1 degree as the best levels of tool rotating velocity, speed of welding, and angle of tool tilt, respectively. In addition, the predictions generated by regression analysis are very similar to the comparison results.



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