International Journal of Mechanical and Materials Engineering (IJMME), Vol.6 (2011), No.2, 300-306
OPTIMIZATIONAL STUDY OF FRICTION WELDING OF STEEL TUBE TO ALUMINUM TUBE PLATE USING AN EXTERNAL TOOL PROCESS C.V. Kumar, S. Muthukumaran, A. Pradeep and S.S. Kumaran Department of Metallurgical and Materials Engineering, National Institute of Technology, Tiruchirappalli-620015, Tamilnadu, India Email:
[email protected] Received 22 February 2011, Accepted 23 August 2011
free weld joints and better strength (kumaran et al., 2010a). The various process parameters affect the joint strength is tool rotation speed, tool shoulder diameter, pin clearance, plunge depth and tube projection. In order to produce good quality weld joint, it is vital to set proper welding process parameters. Generally, the welding process is a multi-input and multi-output Process in which there exists a close relationship between the quality of joints and the welding parameters. Taguchi’s statistical design is a powerful technique which is used to identify the most significant process parameter by the conduct of relatively fewer experiments (Montgomery, 2006; Sathiya et al., 2006). In the present study, friction welding of steel tube to commercial aluminum tube plate using an external tool has been performed. The input parameters considered in this study are tool rotation speed, tool shoulder diameter and pin clearance and the output parameter is joint strength. Three levels of process parameters have been used in this study. Taguchi L9 orthogonal array has been used to identify the most influential process parameter. This is followed by determining the percentage of contribution of each parameter using Analysis of Variance (ANOVA). Then Genetic Algorithm (GA) has been used to derive the optimized process parameters of the FWTPET.
ABSTRACT In the present study steel tube and commercially pure aluminum tube plate are joined by friction welding of tube to tube plate using an external tool (FWTPET) and the process parameters are optimized. Taguchi’s L9 orthogonal array approach has been applied to determine the most influential control factors in order to yield better joint strength. The practical feasibility of the application of GA to FWTPET process has been validated by means of observing the deviation between predicted and experimentally obtained welding process parameters. The percentage contributions of each process parameters have been obtained using statistical analysis of variance (ANOVA). Keywords: Friction welding; FWTPET; Tube to tube plate welding; Taguchi method; Genetic Algorithm; ANOVA 1. INTRODUCTION Several situations arise in industrial practice which calls for joining of dissimilar materials. The joining of dissimilar metals is generally more challenging than that of similar metals because of difference in the physical, mechanical and metallurgical properties of the parent metals to be joined. The main issues of the steel to aluminum fusion welding come from the large difference between their melting temperatures, the nearly zero solid solubility of iron in aluminum and the formation of brittle aluminum-rich intermetallic compounds such as Fe2Al5 and FeAl3 (Sierra et al., 2007). Friction welding (FW) is a solid state welding process for joining materials, which involves generation of heat by the conversion of mechanical energy into thermal energy at the interface of the work pieces without using electrical energy or heat from other sources during rotation under pressure. This process is suitable to make joints which are of a highquality, precise and high-efficiency (Li et al., 2009). Friction welding of tube to tube plate using an external tool (FWTPET) was invented in the year 2006 and patented by one of the present authors (Muthukumaran, 2008). The prime advantage of this process is to weld similar and dissimilar materials and easy for automation. The joint produced by this process exhibits enhanced mechanical properties with lesser energy consumption (Muthukumaran, 2010). The use of backing block in the FWTPET process leads to defect
2. EXPERIMENTAL PROCEDURE The FWTPET machine developed in-house is shown in Figure 1. The external tool consists of a shoulder and pin as shown in Figure 2. The faying surfaces should be clean and free from all contaminants such as grease, adsorbed film, etc. A suitable hole is drilled in a plate and the tube is fitted to the tube plate and the assembly is clamped in the FWTPET machine table. The FWTPET machine consists of tool holder, spindle, table and supporting structure. 2.1 Principle of FWPET The tool is lowered during rotation and heat is generated due to friction when the shoulder touches the plate. The plate metal gets plasticised and the plastic flow of metal takes place towards the centre of the tool axis and flows through the holes in the tube and fills the gap, forming a bond between the tube and plate. The tool is withdrawn after a predetermined time. The role of cylindrical pin is to restrict the material movement and apply pressure between the tube and
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plate. The bonding takes place between surfaces which are subjected to both high pressure and temperature. In case of FWTPET, both the work pieces are kept stationary and the tool is rotating in axial direction during welding. 2.2 FWTPET Procedure All the experiments have been conducted using 6 mm rolled plates of commercially pure aluminum and cut into the required sizes (50 mm x 70 mm). Similarly, steel tubes of 19 mm external diameters and 15mm inner diameters have been cut into required size (40 mm height). This is followed by drilling of 19 mm diameter holes in the aluminum plate. The tubes are cut into required size and holes (2 mm diameter) are drilled on the faying surface of the tube. Then the tubes are assembled in their respective holes with 2 mm depth from the tube plate surface.
Figure 2 Schematic sketch showing principle of operation of FWTPET Backing block is used to provide support for the tube to tube plate assembly and to restrict the deformation of plate during welding due to axial load.The backing block employed in this study is made up of steel block with a central hole and a depth of 20 mm and 30 mm respectively. The tube to tube plate assembly is placed in the backing block and firmly clamped on the machine vice. Tools made of tool steel have been used to fabricate FWTPET joints with different tool shoulder diameters (24mm, 26mm, 28mm) and pin diameters (14mm, 13mm, and 12mm). The chemical composition of the commercial pure aluminum tube plate and SA106 Grade B steel tube materials are shown in Table1&2.
Figure 1 Machine used for FWTPE
Table 1Chemical composition of commercially pure aluminum plate
Wt%
Elements V Si 0.0001 0.0006
Fe 0.0007
Cu 0.0013
Mg 0.0021
Mn 0.0001
Ti 0.0001
Zn 0.0002
Cr 0.0001
Al Bal
Table 2 Chemical composition of SA106 Grade B steel tube
Wt%
Elements C Mn 0.30 0.41
P 0.035
S 0.035
Si 0.10
Cu 0.40
2.3 Taguchi Method Taguchi method is an efficient problem solving tool, which can improve the performance of the product, process, design and system with a significant reduction in experimental time and cost (Lakshminarayanan et al., 2009; Benyounis et al., 2008; Kim et al., 2003). Taguchi method employs a special design of orthogonal arrays to study entire process parameters space with small number of experiments (Sharma et al. 2005; Vijian et al., 2006; Anawa et al., 2008). In the present study L9 orthogonal array has been selected. Three process parameters considered in this study; tool rotational speed (rpm), shoulder diameter (mm) and pin clearance (mm). The factors and their corresponding levels are presented in Table 3.
Ni 0.40
Cr 0.40
Mo 0.15
V 0.08
Fe Bal
Table 3 L9 Orthogonal array factors and levels Factors A(Tool Rotating speed, rpm) B(Shoulder diameter, mm) C(Pin Clearance, mm)
Levels 1 2 710 1120
3 1400
24
26
28
1
2
3
2.4 Analysis of variance (ANOVA) The statistical analysis of variance (ANOVA) has been performed to predict the statistical significance of the
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process parameters. It helps to determine the effect of individual input parameter on output parameters. The purpose of the ANOVA test is to investigate the significance of the process parameters which affect the joint strength of FWTPET joints 2.5 Genetic Algorithm Genetic algorithms are one of the best ways to solve a problem and able to create a high quality solution. Genetic algorithms use the principles of selection and evolution to produce several solutions to a given Problem. It generates solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. GA has wide variety of applications in engineering problems because of simplicity and ease of operation (kumaran et al., 2010b). To find the exact process parameters, an objective function is required. The objective function is given by: Joint strength = f (Speed, Shoulder diameter, Pin clearance). The objective function has been determined by Regression analysis.
Figure 3 Sample loaded in Hounsfield Tensometer
Welding constraints The practical constraints imposed during welding process are stated as follows: Parameter bounds: Bounds on tool rotational speed (S) SL ≤ S ≤ S H Where SL = 710 rpm SH = 1400 rpm are lowest and highest speed respectively. Bounds on shoulder diameter (SD) SDL ≤ SD ≤ SDH Where SDL = 24 mm SDH = 28 mm are lowest and highest shoulder diameter respectively Bounds on pin clearance (PC) PCL ≤ PC ≤ PCH Where PCL = 1 mm PCH = 3 mm are lowest and highest pin clearance respectively.
Figure 4 Pull test specimen
3. RESULTS AND DISCUSSIONS 3.1 Pull Test
Figure 5 Tensile test sample showing fracture at the interface
Hounsfield Tensometer has been used for pull test as shown in Fig 4. A hole of 8 mm diameter is drilled on the tube and plate in order to assemble the connecting rods in the tensile test specimen as shown in Figure 4. The sample is firmly held in its position with the help of nuts and bolts in the tensometer using the connecting rods. Load is gradually applied until the specimen fractures. A fractured pull test sample is shown in the Figure 5. Two samples were tested in each combination of process parameters and the average value is chosen for optimization using Taguchi method. The samples are welded according to L9 Orthogonal array and the input parameters and the output characteristics of L9 orthogonal array are presented in Table 4. Joint strength is the main characteristic considered in this investigation describing the quality of FWTPET joints.
In order to asses, the influence of factors on the response, the mean and Signal-to-Noise ratio (S/N) for each control factor can be calculated. In this study, the S/N ratio was chosen according to the criterion Larger the better, in order to maximize the response. MINITAB software has been used to determine the influence of process parameters (factors) on the joint strength (response). The response table for means and S/N ratio are presented in Table 5 and Table 6 respectively. It is clear that a larger S/N ratio corresponds to better quality characteristics and the mean effect (Figure.6) and S/N ratio (Figure.7) for joint strength are calculated by statistical software.
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Table 4 Input parameters and output characteristics of orthogonal array Experimental run 1 2 3 4 5 6 7 8 9
Input parameters Shoulder diameter (mm) 24 26 28 24 26 28 24 26 28
Rotating Speed (mm) 710 710 710 1120 1120 1120 1400 1400 1400
Pin Clearance (mm) 1 2 3 2 3 1 3 1 2
Output Factors Joint Strength (MPa) 43.58 24.67 63.30 32.10 31.25 64.96 49.34 63.32 58.38
Table 5 Response Table for Means Level
Speed (rpm)
Shoulder diameter (mm)
Pin clearance (mm)
1
43.8500
41.6733
57.2867
2
42.7700
39.7467
38.3833
3
57.0133
62.2133
47.9633
Delta
14.2433
22.4667
18.9033
Rank
3
1
2 Figure 6 Main effects plot generated by MINITAB software
Table 6 Response Table for S/N Ratio Level
Speed (rpm)
Shoulder diameter (mm)
Pin clearance (mm)
1
32.2191
32.2599
35.0232
2
32.0933
31.2571
31.0996
3
35.0734
35.8688
33.2630
Delta
2.9800
4.6117
3.9236
Rank
3
1
2
The joint strength is found to be maximum when tool rotational speed, tool shoulder diameter and pin clearance are 1400 rpm, 28 mm and 1mm respectively. Figure 7 Effects plot for S/N ratio freedom, sum of squares, variance and percentage of contribution as shown in Table 7. The results of ANOVA indicate that the considered process parameters are highly significant factors affecting the strength of FWTPET joints.
3.3 Analysis of variance (ANOVA) Each of the parameter has been analyzed using by (ANOVA) which is standard statistical technique to provide a measure of confidence (Ibrahim et al., 2010). The ANOVA computes quantities such as degree of
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1399 rpm, shoulder diameter of 27.9 mm and pin clearance of 1.08 mm.
Figure 8 Percentage contributions of process parameters Based on the results, tool shoulder diameter is found to be the most influencing process parameter (47.40%) followed by pin clearance (27.31%) and speed (19.22%) as presented in Table 6. The percentage contribution of each of the process parameter is shown in Figure8.
Figure 9 Optimized results found in Genetic Algorithm The predicted joint strength for the optimized condition is 68.45 MPa. Experiments are conducted with tool rotation speed of 1400 rpm, tool shoulder diameter of 28 mm and the pin clearance of 1 mm. Theoretical and experiments values are shown in Table 8 and the result shows that, there is a slight deviation between the theoretically predicted and experimentally obtained joint strength. This conform the practical applicability of GA to FWTPET process.
3.4 Genetic Algorithm GA provides the exact combination of input process parameters to achieve maximum joint strength. The optimized parameters for obtaining maximum tensile strength are shown in Figure 9. Based on the optimum process parameters, validation experiment has been conducted and the optimum values of process parameters have been found to be tool rotation speed of
Table 7 Analysis of Variance for joint strength, using Adjusted SS for Tests Source Tool speed
rotational
Shoulder diameter Pin Clearance Error Total
DF
*Seq SS
*Adj SS
*Adj MS
*F
*P
Percentage contribution
2
377.31
377.31
188.66
3.16
0.240
19.22
2 2 2 8
930.35 536.04 119.33 1963.04
930.35 536.04 119.33
465.18 268.02 59.67
7.80 0.49
0.114 0.182
47.40 27.31 6.07 100
*Seq SS- Sequential Sum of Squares *Adj SS- Adjusted Sum of Squares *Adj MS- Adjusted Mean Squares *F- Statistical test
*P- Statistical value
Table 8 Optimized results Tool rotational speed (rpm)
Tool Shoulder diameter (mm)
Pin (mm)
GA
1399
27.98
1.08
68.45
Experimental value
1400
28
1
67.99
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of
Clearance
Joint (MPa)
strength
FWTPET welded joint is shown in Figure.11 and reveals that the continuous bonding has taken place between tube and plate. The microstructure reveals that aluminum is partially fused near the bond interface and the fine grains are found in the steel tube side. During tool rotation, the tool shoulder touches the aluminum plate metal, it undergoes plasticized and fills the hole in the steel tube is shown in the Figure 11.The steel tube side micro structure reveals the fine grained ferrites near the bond interface and this is due to the combined effect of both severe plastic deformation and higher cooling rate.
3.5 Macrostructure and Microstructure After the completion of welding, the FWTPET joints samples obtained at optimized conditions (1400 rpm speed, 28mm tool shoulder diameter and 1mm pin clearance) are machined for macro and micro structural examinations. The samples are polished and etched. The macrostructure of the samples are shown in the Figure.10. The macrostructure reveals that defect free bond has been obtained.
4. CONCLUSIONS The steel tube to commercially aluminum tube plate samples are successfully welded by FWTPET process with which has wider industrial applications. Taguchi L9 Orthogonal array has been used in this study and the tool shoulder diameter is found to be the most influential process parameter in deciding the joint strength. The joint strength obtained with the optimized process parameters are tool rotational speed 1400 rpm, shoulder diameter 28 mm, pin clearance1 mm is 67.99 MPa. The percentage of contribution of each process parameter has been found by ANOVA and the tool shoulder diameter possess highest contribution (47.40%) followed by pin clearance (27.31%) and tool rotation speed (19.22%). The microstructure reveals that grain refinement has occurred in the bond interface at the steel tube side and partially fused aluminium metal flow has been visible at the plate side.
Figure 10 Cross section of bond interface
ACKNOWLEDGMENTS The authors wish to acknowledge the financial support provided by the Ministry of Human Resource and Development (MHRD), Government of India, and New Delhi to carry out this research work. REFERENCES Anawa, E.M and Olabi, A.G. 2008. Optimization of tensile strength of ferritic/austenitic laser welded components, Optics and Lasers in Engineering 46: 571- 577. Ghani, J.A., Choudary, I.A and Hassan, H.H. 2004. Application of taguchi method in the optimization of end milling parameters, Journal of Material Processing Technology 145: 84-92. Ibrahim, M.H.I., Muhamad, N., Sulong, A.B., Jamaludin, K.R., Ahmad, S and Noor, N.H.M. 2010. Optimization of Micro Metal Injection molding for highest Green strength by using Taguchi Method, International journal of Mechanical and Materials Engineering 5(2): 282289. Kim, D and Rhee, S. 2001. Optimization of arc welding process parameters using a genetic algorithm, The Welding journal:184-189. Lakshminarayanan, A., Balasubramanian, V. 2008. Process parameters optimization for friction stir welding of RDE-40 aluminum alloy using Taguchi
Figure 11 Various zones of microstructure of welded sample During welding, the tool is lowered axially towards the work piece and tool shoulder touches the Al plate and the plate undergoes severely plastic deformation condition and a metal flow occupies the gap in the tube and form a bond between them. The microstructure of
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technique, Transaction of Non ferrous Metal Society of China 18: 548-554. Meshram, S.D., Mohandas, T and Madhusudhan Reddy, P. 2007. Friction welding of dissimilar pure metals, Journal of Material Processing technology 184:330-337. Montgomery, D.C. 2006. Design and Analysis of Experiments, IV Edition, NY: John Willey& Sons. Muthukumaran, S., A process for friction welding of tube to tube sheet or plate by adopting an external tool, Indian patent Application No. 189/KOL/06 filed on 07-03-2006, patent No.21744. Muthukumaran, S., VijayaKumar, C., Pradeep, A and kumaran, S.S. 2010. Mechanical and Metallurgical Properties of aluminum 6061 alloy tube to tube plate welded joints by friction welding using an external tool process, International Welding Symposium 2010: 235-239. Paneerselvam, k., Aravindan, S and Noorul Haq, A. 2009. Hybrid of ANN with genetic algorithm for optimization of friction vibration joining process of plastics, journal of Advanced Manufacturing Technology 42: 669-677. Sathiya, P., Aravindan, S and Noorul Haq, A. 2006. Optimization of Friction welding parameters with multiple performance characteristics, International journal of Mechanical and Materials Design 3: 309318.
Satyanarayanan, V.V., Madhusudhan Reddy, G and Mohandas, T. 2005. Dissimilar Metal friction welding of austenitic- ferritic stainless steels, Journal of Materials Processing and Technology 160: 128-137. kumaran, S.S., Muthukumaran, S and Vinodh, S. 2010a. Optimization of Friction welding of tube to tube plate using an external tool, Structural and Multidisciplinary optimization 42: 449-457. kumaran, S.S., Muthukumaran, S and Vinodh, S. 2010b. Experimental and numerical investigation of weld joints produced by friction welding of tube to tube plate using an external tool, International Journal of Engineering Science and Technology 2:109-117. Sierra, G., Peyre, P., Deschaux-Beaume, F., Stuart, D and Fras, G. 2007. Steel to aluminum key hole laser welding, Material Science and Engineering A 447:197-208. Vijian, P and Arunachalam, V.P. 2006. Optimization of Squeeze casting process parameters using taguchi Analysis, International Journal of Advanced Manufacturing Technology 30:1122-1127. Li, W.Y., Min Yu, Jinglong Li, Guifeng Zhang and Shiyuan Wang. 2009. Characterizations of 21-4N to 4Cr9 Si2 stainless steel dissimilar joint bonded by electric-resistance-heat –aided friction welding, Materials and Design 30: 4230-4235.
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