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Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique
Materials Today: Proceedings xxx (xxxx) xxx
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique M. Shunmugasundaram a,⇑, A. Praveen Kumar a, L. Ponraj Sankar b, S. Sivasankar c a
Department of Mechanical Engineering, CMR Technical Campus, Hyderabad 501401, India Department of Civil Engineering, CMR Institute of Technology, Hyderabad 501401, India c Department of Civil Engineering, CMR Technical Campus, Hyderabad 501401, India b
a r t i c l e
i n f o
Article history: Received 9 November 2019 Received in revised form 3 January 2020 Accepted 5 January 2020 Available online xxxx Keywords: Friction stir welding Dissimilar alloys Taguchi technique ANOVA Tensile strength
a b s t r a c t Friction stir welding is a non consumable material state welding process for joining of dissimilar aluminum alloys and is used in aerospace, railway, automotive and nautical industries. The welding excellence of this friction stir welding type depends upon the process parameters such as the rotational speed of the tool, the welding speed, and the tilt angle. Welding of dissimilar aluminum alloys AA6063 and AA5052 plates is carried out by friction stir welding process and the process parameters are optimized using Taguchi L9 orthogonal design of experiments. The optimum process parameters are identified to maximize the tensile strength of the weld joint. The ideal range of process parameters and their possessions upon the strength of the weld joints is analyzed by ANOVA. The sheets are effectively welded by friction stir welding process and the welded sheets are experienced the tension test at room temperature to scrutinize the strength. The result shows that the welding speed is more influential than the feed and tilt angle to join these dissimilar joints. Ó 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the First International conference on Advanced Lightweight Materials and Structures.
1. Introduction Friction stir welding (FSW) is a non-consumable tough-state joint welding process in which a rotating tool with a shoulder and a tool pin profile travel along the metal surfaces of two closely clamped plates mounted on a backplate [1,2]. The shoulder has a stiff contact with the welding plates top surface. The heat produced by friction on the shoulder and lightens the material to be welded at a lower level on the surface of the pin. Drastic plastic deformity and stream of such plasticized metal plates happen as the instrument is transferred across the heating path [3,4]. The machine put at the front of the joining tools and the wrapping surface where a welded joint is formed. The plate where the forward side known as the rotation path is comparable to the welding joint, while the additional aspect is called the retreating side. This distinction may result in convection imbalance [5,6]. The movement of the metal and the characteristics of the welds two faces. For e.g., in the heat-affected area on the withdrawing side, the strength of specific age-hardened aluminum alloys generally lower, which becomes the site of tensile fracturing in ⇑ Corresponding author. E-mail address: [email protected] (M. Shunmugasundaram).
cross-weld testing [7,8]. The FSW is beneficial to solder the structure of the butt, lap, T, and other welding joints in a wide range of plastic duration and thickness. It was used to weld combinations of dissimilar materials, especially those who have near melting temperatures and related behaviors such as warm robustness [9]. It is not practical to joint-most alloys by fusion welding, but it can be welded by friction swirl welding. As described above, the performance of joints is calculated in the metal joining system using mechanical characteristics such as tensile strength, stiffness, the durability of break, elongation, etc. Therefore, other performance characteristics need to be weighed in order to select the right system variable in friction stir welding [10,11]. Several researchers studied optimizing FSW system parameters by design of experiment (DOE) using Taguchi methodology where explored an efficient approach for optimizing the 6 mm thick aluminum alloys of FSW process parameters [12]. The machine rotating speed and the welding speed are called system joining parameters. Such parameters are evaluated and tests configured using the Taguchi approach at the high tool rotational speed and low welding speed. It is found that 23 percent of tool rotational speed was the largest contribution to the effect on tensile strength and 16 percent of welding speed was the lowest. Design of experiment (DOE) is a research transposition wherein the parameters
https://doi.org/10.1016/j.matpr.2020.01.122 2214-7853/Ó 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the First International conference on Advanced Lightweight Materials and Structures.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
2
M. Shunmugasundaram et al. / Materials Today: Proceedings xxx (xxxx) xxx
that come into the system are significantly altered and the effect on the response variables is calculated [13,14]. The DOE is an effective way to maximize the volume of data collected and reduce the volumes of data to be acquired by decreasing the number of trials [15,16]. To develop the number of welding tests, the experimental procedure Taguchi L9 orthogonal is implemented. Using the wire cut EDM (Electrical discharge machining), the conventional ASME hardness skeleton is obtained for the tensile test. The plates are assembled easily and the sample sheets are tested at room temperature using a Rockwell hardness tester to fine-tune the strength of the welded specimen [17,18]. In this study, the impact on the microstructure and mechanical properties of Friction Stir Welded joint of 6063 and 5052 alloys, such as rotational speed, movement speed, and location of the sheets, was predicted using Taguchi process. The study of the signal to noise ratio (S/N) shows that peak tensile capacity was reached [19,20]. 2. Materials and methods 2.1. Selection of materials In this research, dissimilar aluminum alloys 6063 and 5052 are selected to find the optimized process parameters to join those by FSW. Nowadays, both aluminum sheets and plates are extensively utilized in automobile industries and aircraft for structural purposes. These dissimilar aluminum alloys are having good formability and weldability. The specimens are developed by cutting the dissimilar alloys into the required dimensions (200 mm 75 mm 8 mm). Chemical composition of aluminum alloy 6063 and 5052 are displayed in Tables 1 and 2, respectively [21]. 2.2. Fabrication of tool pin profiles The tools for the friction stir welding process are developed by surface grinding and lathe machine. In this present experimental
analogy, high-speed steel (HSS) alloy is selected as a welding tool material. It has very high hardness and good wear-resistant with more toughness. Based on the literature, hexagonal shape tool pin profile is selected with a 20 mm shoulder diameter, 5.5 mm pin length and 6 mm and 6 pin diameter. Pictorial view of the tool and hexagonal tool pin profile is shown in Fig. 1a, b. 2.3. Determining the welding parameters and their levels Taguchi anticipated a procedure to design the experimental method to examine the effect of all input process parameters on top of output response parameters by the minimum number of experiments. This method is time-saving technique as well as one of the most cost-effective to investigate and optimize the input process parameters. Formerly, the level of input process parameters and their levels are to be recognized predetermined to develop the number of experiments that have to be performed. In this paper, three are considered to weld the dissimilar alloys and they are tool rotational speed, welding speed, and tilt angle. The three levels of input process parameters are tabularized in Table 1. The most suitable orthogonal array must be selected depending on the number of Degrees of Freedom (DOF) of the input process parameters. The total degrees of freedom of the input process parameter must be lesser than that of the degrees of freedom of the chosen orthogonal array. The DOF of each input process parameter is considered by subtracting one from the total number of levels of the chosen process parameters which is tabulated in Table 3. Because the degrees of freedom of three input process factors with three different levels become six, the L9 Orthogonal Array is chosen and developed nine different combinations of input process parameters. The friction stir welding process parameters were preferred in this analysis associate the tool rotational speed of 650, 750, and 850 rpm, welding speed of 20, 30 and 40 mm/min and tilt angle of 1, 1.5 and 2 degrees these process parameters are listed in the
Table 1 Chemical composition of 6063 aluminum alloy. Components
Al
Mg
Cr
Cu
Fe
Ti
Mn
Zn
Si
wt%
97.65
0.45–0.9
0–0.1
0.1
0.35
0–0.1
0.1
0–0.1
0.2–0.6
Table 2 Chemical composition of 5052 aluminum alloy. Components
Al
Cr
Cu
Fe
Mg
Ti
Mn
Zn
Si
wt%
98.45
0.15–0.35
0.1
0.4
0.1
0–0.1
0.1
0–0.1
0.25
Fig. 1. (a) FSW welding tool; (b) Hexagonal pin profile.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
M. Shunmugasundaram et al. / Materials Today: Proceedings xxx (xxxx) xxx Table 3 Selected input parameters and their different levels with DOF. Parameter
Unit
Tool rotational speed Welding speed Tilt angle Total DOF
RPM mm/min degree
Levels
DOF
I
II
III
650 20 1
750 30 1.5
850 40 2
2 2 2 6
Table 3, and remaining process parameters are kept as constant. After formative, the FSW process parameters and their levels must be intended the degree of freedom (DOF) to identify the number of experiment runs in the Taguchi technique. By using the Taguchi approach, orthogonal array (L9) is selected as shown in Table 4. This array has nine experiments and the combination of process parameters is tabulated in Table 5. 2.4. Experimental procedure The experiments are carried out on a vertical milling machine with the special attachments for the friction stir welding process. The friction stir welding experimental arrangement is shown in
Table 4 Customary L9 orthogonal array. Experiment No.
Tool rotational speed
Welding speed
Tilt angle
1 2 3 4 5 6 7 8 9
1 1 1 2 2 2 3 3 3
1 2 3 1 2 3 1 2 3
1 2 3 2 3 1 3 1 2
Table 5 Different combinations of process parameters using orthogonal array. Experiment No.
Tool rotational speed
Welding speed
Tilt angle
1 2 3 4 5 6 7 8 9
650 650 650 750 750 750 850 850 850
20 30 40 20 30 40 20 30 40
1 1.5 2 1.5 2 1 2 1 1.5
3
Fig. 2. The aluminum alloy plates of 6063 and 5052 are tightly fixed over the table with the fixtures. Now, as shown in Table 3, the welding process is performed as per the L9 orthogonal array. The spindle rotational movement is initiated when the milling device clicks on and the instrument comes into contact with both the aluminium alloy surface. The pin of the device is pierced to solder between the dissimilar aluminium alloys. The welding tool is given some time as it rotates due to frictional heating in connection with the aluminium alloy surfaces to loosen the product. This process is known as a period of preheating and dwelling. The friction table is granted forward movement after the dwelling time, resulting in weld creation. After the weld is made, the machine is withdrawn. As per the ASTM standard (Fig. 3), all nine tensile test samples were extracted using CNC (Computerized Numerical Control) wire cut EDM (Electrical Discharge Machine). The specimens are extracted perpendicular to the path of welding. In-room temperature, the friction stir welded specimens are extracted and performing tensile tests on a standard 250 kN Instron test machine. The extracted and tested specimens are shown in Fig. 4. 3. Result and discussion The dissimilar aluminium alloys are welded using friction stir welding. The Taguchi method is used to find the number of trials and ANOVA (Analysis of Variance) table is used to analyze the input and output responses. This approach is utilized to find the optimal process parameters of the FSW process. For each test, the welded specimen’s response tensile strength is measured and reported in Table 6. 3.1. Taguchi parametric optimization The Taguchi method is being used to seek suitable combinations of process parameters to achieve maximum tensile strength. This approach is used to seek the desired quality based on the analysis of the input and output parameters. Using this approach, device architecture and parametric layout were easily accomplished. Larger is better has selected as the null hypothesis to achieve the higher tensile strength with optimum process parameters (a = 0.05). It means that the confidence level is chosen as 95%.
Fig. 3. ASME standard of tensile test specimens.
Fig. 2. Friction stir welding setup.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
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Fig. 4. (a) Extracted tensile test specimen (b) Tested specimens.
Table 6 Tensile strength of the specimen with the combinations of process parameters. Experiment No.
Tool rotational speed
Welding speed
Tilt angle
Tensile Strength
1 2 3 4 5 6 7 8 9
650 650 650 750 750 750 850 850 850
20 30 40 20 30 40 20 30 40
1 1.5 2 1.5 2 1 2 1 1.5
131.26 128.85 124.56 128.31 126.77 141.58 151.78 147.08 125.49
3.2. Signal-to-noise ratio (S/N) The S/N ratio has been utilized to take care of the performance distinctive sensitivity that is examined in a controlled manner. The expression signal shows the multiplicative effect of the mean for the output feature, and the affectation noise demonstrates the unwanted effect for the output functionality that influences the outcome as the factors have been called noise factors outside. The S/N ratio has been utilized to take care of the performance distinctive sensitivity that is examined in a controlled manner. Then click Quill It on the right to summarize your input. Usually, the S/N ratio contains three forms of performance characteristics, including the nominal-the-better, the larger-the-better, and the lower-the-better [10]. Table 7 displays the S/N ratio of each experiment and it shows that there is not that much variation in the S/N ratio values. It varies from 41.9076 and 43.6243 for the corresponding experiment numbers are 3 and 7. The responses of S/N ratios and means over tensile strength are shown in Tables 8 and 9 and the main effects are displayed in Figs. 5 and 6. Tables 8 and 9 show that the rotational speed is having the most influence on tensile strength and the tilt angle shows more impact on the response over the welding
Table 7 Tensile strength of the specimen with S/N ratio. Experiment No.
Tensile Strength
S/N ratio
1 2 3 4 5 6 7 8 9
131.26 128.85 124.56 128.31 126.77 141.58 151.78 147.08 125.49
42.3626 42.2017 41.9076 42.1652 42.0603 43.0200 43.6243 43.3511 41.9722
Table 8 Response table for S/N ratios of Tensile strength. Level
Tool rotational speed
Welding speed
Tilt angle
1 2 3 Delta Rank
42.16 42.42 42.98 0.83 1
42.72 42.54 42.30 0.42 3
42.91 42.11 42.53 0.80 2
Table 9 Response Table for Means of Tensile strength. Level
Tool rotational speed
Welding speed
Tilt angle
1 2 3 Delta Rank
128.2 132.2 141.5 13.2 1
137.1 134.2 130.5 6.6 3
140.0 127.6 134.4 12.4 2
speed. Figs. 5 and 6 proves that the tensile strength will be high when the tool rotational speed is maximum and welding speed and tilt angle are minima. 3.3. Analysis of variance (ANOVA) The ANOVA is a numerical method, which can be useful for evaluating the effect of different input variables from a set of experiments carried out based on DOE for the system. It is used to measure and govern such parameters along with degrees of freedom (DOF), mean squares (V), the number of squares (S), etc. in a generic tabular format. It is not possible to find the influence of specific variables on the whole system when using the Taguchi approach while also using ANOVA, assessing the ratio of the input of that parameter. Tables 10 and 11 show the ANOVA table for tensile strength based on S/N ratios and means. Based on the P-value, the influence of process parameters can be checked. If the P-value is less than the ‘‘a” value, the null hypothesis will be accepted and higher than that it will be rejected. From Tables 10 and 11, The P-value of tool rotational speed is lesser than the ‘‘a”. So, it is influenced by the tensile strength of the weld specimen. The P-value of the tilt angle is nearby ‘‘a” value, it illustrates that it may influence on the output response. The P-value for welding speed is higher than the ‘‘a” value and it shows that is not influenced by the tensile strength. 3.4. Contour plot analysis of tensile strength Contour plot analysis is used to check the impact of two process parameters on the responses (tensile strength). Fig. 7 shows that
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
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Fig. 5. Main effects plot for S/N ratios of tensile strength.
Fig. 6. Main effects plot for means of tensile strength.
Table 10 Analysis of variance for SN ratios of tensile strength. Source
DF
Seq SS
Adj SS
Adj MS
F
P
Tool rotational speed Welding speed Tilt angle Residual Error Total
2 2 2 2 8
1.0693 0.2631 0.9564 1.0097 3.2986
1.0693 0.2631 0.9564 1.0097
0.5347 0.1315 0.4782 0.5049
1.06 0.26 0.95
0.0486 0.0793 0.0514
Table 11 Analysis of variance for means of tensile strength. Source
DF
Seq SS
Adj SS
Adj MS
F
P
Tool rotational speed Welding speed Tilt angle Residual Error Total
2 2 2 2 8
276.11 65.14 232.25 251.37 824.87
276.11 65.14 232.25 251.37
138.06 32.57 116.12 125.69
1.10 0.26 0.92
0.0477 0.0794 0.0520
the Contour plot of tensile strength versus welding speed and tool rotational speed. The tensile strength is high when the welding speed is low and tool rotational speed is high. Fig. 8 shows that the contour plot of tensile strength versus tilts angle and tool rotational speed. The tensile strength is high when the tilt angle is low;
tool rotational speed and tilt angle are high. Fig. 9 illustrates that the contour plot of tensile strength versus welding speed and tilt angle. The tensile strength is high, while the tilt angle is high and welding speed is high and when the tilt angle is low and welding speed is high.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
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effects on the welded joints of the tensile strength. The result shows that the tool rotational speed is 850 rpm, the welding speed is 20 mm/min, and the tilt angle is 2° are the optimized independent process parameters to maximize the tensile strength. CRediT authorship contribution statement M. Shunmugasundaram: Conceptualization, Experimentation, Methodology and Writing - original draft. A. Praveen Kumar: Supervision and Validation. L. Ponraj Sanker: Review and editing. S. Sivasankar: Methodology and optimization. Declaration of Competing Interest
Fig. 7. Contour plot of tensile strength vs. welding speed and tool rotational speed.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References
Fig. 8. Contour plot of tensile strength vs. tilt angle and tool rotational speed.
Fig. 9. Contour plot of tensile strength vs. tilt angle and welding speed.
4. Conclusions In this work, FSW is used to join the two dissimilar aluminium alloys. The number of welding tests is finalized in the experimental process by Taguchi L9 orthogonal array. The wire-cut EDM is used to obtain the regular ASME tensile sample specimen. The sheets are welded effectively and the welded dissimilar aluminium sheets are measured at room temperature using a standard testing machine to test the tensile strength. Testing is conducted out to achieve the most optimal (optimum) set of chosen parameters and their
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Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
Contents lists available at ScienceDirect
Materials Today: Proceedings journal homepage: www.elsevier.com/locate/matpr
Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique M. Shunmugasundaram a,⇑, A. Praveen Kumar a, L. Ponraj Sankar b, S. Sivasankar c a
Department of Mechanical Engineering, CMR Technical Campus, Hyderabad 501401, India Department of Civil Engineering, CMR Institute of Technology, Hyderabad 501401, India c Department of Civil Engineering, CMR Technical Campus, Hyderabad 501401, India b
a r t i c l e
i n f o
Article history: Received 9 November 2019 Received in revised form 3 January 2020 Accepted 5 January 2020 Available online xxxx Keywords: Friction stir welding Dissimilar alloys Taguchi technique ANOVA Tensile strength
a b s t r a c t Friction stir welding is a non consumable material state welding process for joining of dissimilar aluminum alloys and is used in aerospace, railway, automotive and nautical industries. The welding excellence of this friction stir welding type depends upon the process parameters such as the rotational speed of the tool, the welding speed, and the tilt angle. Welding of dissimilar aluminum alloys AA6063 and AA5052 plates is carried out by friction stir welding process and the process parameters are optimized using Taguchi L9 orthogonal design of experiments. The optimum process parameters are identified to maximize the tensile strength of the weld joint. The ideal range of process parameters and their possessions upon the strength of the weld joints is analyzed by ANOVA. The sheets are effectively welded by friction stir welding process and the welded sheets are experienced the tension test at room temperature to scrutinize the strength. The result shows that the welding speed is more influential than the feed and tilt angle to join these dissimilar joints. Ó 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the First International conference on Advanced Lightweight Materials and Structures.
1. Introduction Friction stir welding (FSW) is a non-consumable tough-state joint welding process in which a rotating tool with a shoulder and a tool pin profile travel along the metal surfaces of two closely clamped plates mounted on a backplate [1,2]. The shoulder has a stiff contact with the welding plates top surface. The heat produced by friction on the shoulder and lightens the material to be welded at a lower level on the surface of the pin. Drastic plastic deformity and stream of such plasticized metal plates happen as the instrument is transferred across the heating path [3,4]. The machine put at the front of the joining tools and the wrapping surface where a welded joint is formed. The plate where the forward side known as the rotation path is comparable to the welding joint, while the additional aspect is called the retreating side. This distinction may result in convection imbalance [5,6]. The movement of the metal and the characteristics of the welds two faces. For e.g., in the heat-affected area on the withdrawing side, the strength of specific age-hardened aluminum alloys generally lower, which becomes the site of tensile fracturing in ⇑ Corresponding author. E-mail address: [email protected] (M. Shunmugasundaram).
cross-weld testing [7,8]. The FSW is beneficial to solder the structure of the butt, lap, T, and other welding joints in a wide range of plastic duration and thickness. It was used to weld combinations of dissimilar materials, especially those who have near melting temperatures and related behaviors such as warm robustness [9]. It is not practical to joint-most alloys by fusion welding, but it can be welded by friction swirl welding. As described above, the performance of joints is calculated in the metal joining system using mechanical characteristics such as tensile strength, stiffness, the durability of break, elongation, etc. Therefore, other performance characteristics need to be weighed in order to select the right system variable in friction stir welding [10,11]. Several researchers studied optimizing FSW system parameters by design of experiment (DOE) using Taguchi methodology where explored an efficient approach for optimizing the 6 mm thick aluminum alloys of FSW process parameters [12]. The machine rotating speed and the welding speed are called system joining parameters. Such parameters are evaluated and tests configured using the Taguchi approach at the high tool rotational speed and low welding speed. It is found that 23 percent of tool rotational speed was the largest contribution to the effect on tensile strength and 16 percent of welding speed was the lowest. Design of experiment (DOE) is a research transposition wherein the parameters
https://doi.org/10.1016/j.matpr.2020.01.122 2214-7853/Ó 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the First International conference on Advanced Lightweight Materials and Structures.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
2
M. Shunmugasundaram et al. / Materials Today: Proceedings xxx (xxxx) xxx
that come into the system are significantly altered and the effect on the response variables is calculated [13,14]. The DOE is an effective way to maximize the volume of data collected and reduce the volumes of data to be acquired by decreasing the number of trials [15,16]. To develop the number of welding tests, the experimental procedure Taguchi L9 orthogonal is implemented. Using the wire cut EDM (Electrical discharge machining), the conventional ASME hardness skeleton is obtained for the tensile test. The plates are assembled easily and the sample sheets are tested at room temperature using a Rockwell hardness tester to fine-tune the strength of the welded specimen [17,18]. In this study, the impact on the microstructure and mechanical properties of Friction Stir Welded joint of 6063 and 5052 alloys, such as rotational speed, movement speed, and location of the sheets, was predicted using Taguchi process. The study of the signal to noise ratio (S/N) shows that peak tensile capacity was reached [19,20]. 2. Materials and methods 2.1. Selection of materials In this research, dissimilar aluminum alloys 6063 and 5052 are selected to find the optimized process parameters to join those by FSW. Nowadays, both aluminum sheets and plates are extensively utilized in automobile industries and aircraft for structural purposes. These dissimilar aluminum alloys are having good formability and weldability. The specimens are developed by cutting the dissimilar alloys into the required dimensions (200 mm 75 mm 8 mm). Chemical composition of aluminum alloy 6063 and 5052 are displayed in Tables 1 and 2, respectively [21]. 2.2. Fabrication of tool pin profiles The tools for the friction stir welding process are developed by surface grinding and lathe machine. In this present experimental
analogy, high-speed steel (HSS) alloy is selected as a welding tool material. It has very high hardness and good wear-resistant with more toughness. Based on the literature, hexagonal shape tool pin profile is selected with a 20 mm shoulder diameter, 5.5 mm pin length and 6 mm and 6 pin diameter. Pictorial view of the tool and hexagonal tool pin profile is shown in Fig. 1a, b. 2.3. Determining the welding parameters and their levels Taguchi anticipated a procedure to design the experimental method to examine the effect of all input process parameters on top of output response parameters by the minimum number of experiments. This method is time-saving technique as well as one of the most cost-effective to investigate and optimize the input process parameters. Formerly, the level of input process parameters and their levels are to be recognized predetermined to develop the number of experiments that have to be performed. In this paper, three are considered to weld the dissimilar alloys and they are tool rotational speed, welding speed, and tilt angle. The three levels of input process parameters are tabularized in Table 1. The most suitable orthogonal array must be selected depending on the number of Degrees of Freedom (DOF) of the input process parameters. The total degrees of freedom of the input process parameter must be lesser than that of the degrees of freedom of the chosen orthogonal array. The DOF of each input process parameter is considered by subtracting one from the total number of levels of the chosen process parameters which is tabulated in Table 3. Because the degrees of freedom of three input process factors with three different levels become six, the L9 Orthogonal Array is chosen and developed nine different combinations of input process parameters. The friction stir welding process parameters were preferred in this analysis associate the tool rotational speed of 650, 750, and 850 rpm, welding speed of 20, 30 and 40 mm/min and tilt angle of 1, 1.5 and 2 degrees these process parameters are listed in the
Table 1 Chemical composition of 6063 aluminum alloy. Components
Al
Mg
Cr
Cu
Fe
Ti
Mn
Zn
Si
wt%
97.65
0.45–0.9
0–0.1
0.1
0.35
0–0.1
0.1
0–0.1
0.2–0.6
Table 2 Chemical composition of 5052 aluminum alloy. Components
Al
Cr
Cu
Fe
Mg
Ti
Mn
Zn
Si
wt%
98.45
0.15–0.35
0.1
0.4
0.1
0–0.1
0.1
0–0.1
0.25
Fig. 1. (a) FSW welding tool; (b) Hexagonal pin profile.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
M. Shunmugasundaram et al. / Materials Today: Proceedings xxx (xxxx) xxx Table 3 Selected input parameters and their different levels with DOF. Parameter
Unit
Tool rotational speed Welding speed Tilt angle Total DOF
RPM mm/min degree
Levels
DOF
I
II
III
650 20 1
750 30 1.5
850 40 2
2 2 2 6
Table 3, and remaining process parameters are kept as constant. After formative, the FSW process parameters and their levels must be intended the degree of freedom (DOF) to identify the number of experiment runs in the Taguchi technique. By using the Taguchi approach, orthogonal array (L9) is selected as shown in Table 4. This array has nine experiments and the combination of process parameters is tabulated in Table 5. 2.4. Experimental procedure The experiments are carried out on a vertical milling machine with the special attachments for the friction stir welding process. The friction stir welding experimental arrangement is shown in
Table 4 Customary L9 orthogonal array. Experiment No.
Tool rotational speed
Welding speed
Tilt angle
1 2 3 4 5 6 7 8 9
1 1 1 2 2 2 3 3 3
1 2 3 1 2 3 1 2 3
1 2 3 2 3 1 3 1 2
Table 5 Different combinations of process parameters using orthogonal array. Experiment No.
Tool rotational speed
Welding speed
Tilt angle
1 2 3 4 5 6 7 8 9
650 650 650 750 750 750 850 850 850
20 30 40 20 30 40 20 30 40
1 1.5 2 1.5 2 1 2 1 1.5
3
Fig. 2. The aluminum alloy plates of 6063 and 5052 are tightly fixed over the table with the fixtures. Now, as shown in Table 3, the welding process is performed as per the L9 orthogonal array. The spindle rotational movement is initiated when the milling device clicks on and the instrument comes into contact with both the aluminium alloy surface. The pin of the device is pierced to solder between the dissimilar aluminium alloys. The welding tool is given some time as it rotates due to frictional heating in connection with the aluminium alloy surfaces to loosen the product. This process is known as a period of preheating and dwelling. The friction table is granted forward movement after the dwelling time, resulting in weld creation. After the weld is made, the machine is withdrawn. As per the ASTM standard (Fig. 3), all nine tensile test samples were extracted using CNC (Computerized Numerical Control) wire cut EDM (Electrical Discharge Machine). The specimens are extracted perpendicular to the path of welding. In-room temperature, the friction stir welded specimens are extracted and performing tensile tests on a standard 250 kN Instron test machine. The extracted and tested specimens are shown in Fig. 4. 3. Result and discussion The dissimilar aluminium alloys are welded using friction stir welding. The Taguchi method is used to find the number of trials and ANOVA (Analysis of Variance) table is used to analyze the input and output responses. This approach is utilized to find the optimal process parameters of the FSW process. For each test, the welded specimen’s response tensile strength is measured and reported in Table 6. 3.1. Taguchi parametric optimization The Taguchi method is being used to seek suitable combinations of process parameters to achieve maximum tensile strength. This approach is used to seek the desired quality based on the analysis of the input and output parameters. Using this approach, device architecture and parametric layout were easily accomplished. Larger is better has selected as the null hypothesis to achieve the higher tensile strength with optimum process parameters (a = 0.05). It means that the confidence level is chosen as 95%.
Fig. 3. ASME standard of tensile test specimens.
Fig. 2. Friction stir welding setup.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
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Fig. 4. (a) Extracted tensile test specimen (b) Tested specimens.
Table 6 Tensile strength of the specimen with the combinations of process parameters. Experiment No.
Tool rotational speed
Welding speed
Tilt angle
Tensile Strength
1 2 3 4 5 6 7 8 9
650 650 650 750 750 750 850 850 850
20 30 40 20 30 40 20 30 40
1 1.5 2 1.5 2 1 2 1 1.5
131.26 128.85 124.56 128.31 126.77 141.58 151.78 147.08 125.49
3.2. Signal-to-noise ratio (S/N) The S/N ratio has been utilized to take care of the performance distinctive sensitivity that is examined in a controlled manner. The expression signal shows the multiplicative effect of the mean for the output feature, and the affectation noise demonstrates the unwanted effect for the output functionality that influences the outcome as the factors have been called noise factors outside. The S/N ratio has been utilized to take care of the performance distinctive sensitivity that is examined in a controlled manner. Then click Quill It on the right to summarize your input. Usually, the S/N ratio contains three forms of performance characteristics, including the nominal-the-better, the larger-the-better, and the lower-the-better [10]. Table 7 displays the S/N ratio of each experiment and it shows that there is not that much variation in the S/N ratio values. It varies from 41.9076 and 43.6243 for the corresponding experiment numbers are 3 and 7. The responses of S/N ratios and means over tensile strength are shown in Tables 8 and 9 and the main effects are displayed in Figs. 5 and 6. Tables 8 and 9 show that the rotational speed is having the most influence on tensile strength and the tilt angle shows more impact on the response over the welding
Table 7 Tensile strength of the specimen with S/N ratio. Experiment No.
Tensile Strength
S/N ratio
1 2 3 4 5 6 7 8 9
131.26 128.85 124.56 128.31 126.77 141.58 151.78 147.08 125.49
42.3626 42.2017 41.9076 42.1652 42.0603 43.0200 43.6243 43.3511 41.9722
Table 8 Response table for S/N ratios of Tensile strength. Level
Tool rotational speed
Welding speed
Tilt angle
1 2 3 Delta Rank
42.16 42.42 42.98 0.83 1
42.72 42.54 42.30 0.42 3
42.91 42.11 42.53 0.80 2
Table 9 Response Table for Means of Tensile strength. Level
Tool rotational speed
Welding speed
Tilt angle
1 2 3 Delta Rank
128.2 132.2 141.5 13.2 1
137.1 134.2 130.5 6.6 3
140.0 127.6 134.4 12.4 2
speed. Figs. 5 and 6 proves that the tensile strength will be high when the tool rotational speed is maximum and welding speed and tilt angle are minima. 3.3. Analysis of variance (ANOVA) The ANOVA is a numerical method, which can be useful for evaluating the effect of different input variables from a set of experiments carried out based on DOE for the system. It is used to measure and govern such parameters along with degrees of freedom (DOF), mean squares (V), the number of squares (S), etc. in a generic tabular format. It is not possible to find the influence of specific variables on the whole system when using the Taguchi approach while also using ANOVA, assessing the ratio of the input of that parameter. Tables 10 and 11 show the ANOVA table for tensile strength based on S/N ratios and means. Based on the P-value, the influence of process parameters can be checked. If the P-value is less than the ‘‘a” value, the null hypothesis will be accepted and higher than that it will be rejected. From Tables 10 and 11, The P-value of tool rotational speed is lesser than the ‘‘a”. So, it is influenced by the tensile strength of the weld specimen. The P-value of the tilt angle is nearby ‘‘a” value, it illustrates that it may influence on the output response. The P-value for welding speed is higher than the ‘‘a” value and it shows that is not influenced by the tensile strength. 3.4. Contour plot analysis of tensile strength Contour plot analysis is used to check the impact of two process parameters on the responses (tensile strength). Fig. 7 shows that
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
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Fig. 5. Main effects plot for S/N ratios of tensile strength.
Fig. 6. Main effects plot for means of tensile strength.
Table 10 Analysis of variance for SN ratios of tensile strength. Source
DF
Seq SS
Adj SS
Adj MS
F
P
Tool rotational speed Welding speed Tilt angle Residual Error Total
2 2 2 2 8
1.0693 0.2631 0.9564 1.0097 3.2986
1.0693 0.2631 0.9564 1.0097
0.5347 0.1315 0.4782 0.5049
1.06 0.26 0.95
0.0486 0.0793 0.0514
Table 11 Analysis of variance for means of tensile strength. Source
DF
Seq SS
Adj SS
Adj MS
F
P
Tool rotational speed Welding speed Tilt angle Residual Error Total
2 2 2 2 8
276.11 65.14 232.25 251.37 824.87
276.11 65.14 232.25 251.37
138.06 32.57 116.12 125.69
1.10 0.26 0.92
0.0477 0.0794 0.0520
the Contour plot of tensile strength versus welding speed and tool rotational speed. The tensile strength is high when the welding speed is low and tool rotational speed is high. Fig. 8 shows that the contour plot of tensile strength versus tilts angle and tool rotational speed. The tensile strength is high when the tilt angle is low;
tool rotational speed and tilt angle are high. Fig. 9 illustrates that the contour plot of tensile strength versus welding speed and tilt angle. The tensile strength is high, while the tilt angle is high and welding speed is high and when the tilt angle is low and welding speed is high.
Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122
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effects on the welded joints of the tensile strength. The result shows that the tool rotational speed is 850 rpm, the welding speed is 20 mm/min, and the tilt angle is 2° are the optimized independent process parameters to maximize the tensile strength. CRediT authorship contribution statement M. Shunmugasundaram: Conceptualization, Experimentation, Methodology and Writing - original draft. A. Praveen Kumar: Supervision and Validation. L. Ponraj Sanker: Review and editing. S. Sivasankar: Methodology and optimization. Declaration of Competing Interest
Fig. 7. Contour plot of tensile strength vs. welding speed and tool rotational speed.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References
Fig. 8. Contour plot of tensile strength vs. tilt angle and tool rotational speed.
Fig. 9. Contour plot of tensile strength vs. tilt angle and welding speed.
4. Conclusions In this work, FSW is used to join the two dissimilar aluminium alloys. The number of welding tests is finalized in the experimental process by Taguchi L9 orthogonal array. The wire-cut EDM is used to obtain the regular ASME tensile sample specimen. The sheets are welded effectively and the welded dissimilar aluminium sheets are measured at room temperature using a standard testing machine to test the tensile strength. Testing is conducted out to achieve the most optimal (optimum) set of chosen parameters and their
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Please cite this article as: M. Shunmugasundaram, A. Praveen Kumar, L. Ponraj Sankar et al., Optimization of process parameters of friction stir welded dissimilar AA6063 and AA5052 aluminum alloys by Taguchi technique, Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2020.01.122