Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

30120140502018

221 views

Published on

Published in: Technology
  • Be the first to comment

  • Be the first to like this

30120140502018

  1. 1. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 162 TENSILE BEHAVIOUR OF ALUMINIUM PLATES (5083) WELDED BY FRICTION STIR WELDING Er. Jaitinder Mittal (AP), Er. Kumar Gaurav (Assot. Prof.) (ME Deptt.,GTBKIET,Chhapinwali,Malout/PTU Jalandhar, India) ABSTRACT Using arc welding, gas welding and other welding process, it is very difficult to weld the aluminum alloys. Friction stir welding, on the other hand, can be used to join most Al alloys and better surface finishing is achieved. Although the work piece does heat up during friction stir weld, the temperature does not reach the melting point. In this research work, various welding parameters, like rotational speed, welding speed and pin diameter was considered for experimentation to weld Al alloy 5083 and its effect on tensile strength. Mathematical models were developed from the data generated using the two level full factorial technique. Significance of the coefficients and adequacy of the developed models has been checked using student‘t’ test and ‘F’ test respectively. Developed model have been found to be adequate up to 95% of level of significance. The influence of welding parameters has been presented in graphical form for better understanding. The combined effects of welding parameters on the mechanical properties are also presented in graphical form. Tensile strength decreases with increase in rotational speed, tensile strength increases with increase in welding speed, tensile strength decreases with increase in pin diameter and at low rotational speed of tool and high welding speed, there is maximum tensile strength. Key words:- Friction stir welding, Tensile properties, Mathematical models, FSW parameters. 1. INTRODUCTION 1.1 Welding Welding can be defined as the joining of two components by a coalescence of the surfaces in contact with each other. This coalescence can be achieved by melting the two parts together – fusion welding or by bringing the two parts together under pressure, perhaps with the application of heat, to form a metallic bond across the interface. This is known as solid phase joining (Mathers, 2002). INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND TECHNOLOGY (IJMET) ISSN 0976 – 6340 (Print) ISSN 0976 – 6359 (Online) Volume 5, Issue 2, February (2014), pp. 162-170 © IAEME: www.iaeme.com/ijmet.asp Journal Impact Factor (2014): 3.8231 (Calculated by GISI) www.jifactor.com IJMET © I A E M E
  2. 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 163 Welding is the most economical and efficient way to join metals permanently. Welding ranks high among industrial processes and involves more sciences and variables than those involved in any other industrial process. In many cases welding is the most cost effective and structurally sound joining technique. Welding can be performed almost anywhere outdoors, indoors, under sea or in space (Rossi, 1954). 1.2 Friction stir welding Friction stir welding is an innovative solid state welding process invented in December, 1991 by Wayne Thomas at The Welding Institute (TWI), Cambridge, United Kingdom. It has been found as one of the most significant welding process invention from the last two decades. It can be considered as a hot working process in which a large amount of a deformation is imparted to the work piece through the rotating pin and the shoulder (Pflluger, 1996). No melting occurs in this process and the developed welds have a fine grained, hot worked condition with no entrapped oxides or gas porosity. No shielding gas or flux is used. The joining does not involve any use of filler metal. 1.2.1 Friction Stir Welding Equipment The major equipments used in FSW are: • Tool • Conventional Vertical Milling Machine • Fixture. 1.2.2 Principle of working (www.google.co.in, friction stir welding process) Friction stir welding is a variant of friction welding that produces a weld between two work pieces by heating and plastic displacement caused by a rapidly rotating tool that traverse the weld joint. Heating is done by both frictional rubbing between the tool and the work pieces and by visco- plastic dissipation of the deforming material at high strain rates. Friction stir welding uses a non consumable, rotating welding tool to create heat locally. A common tool design is the shape of a rod with concave area with a pin, coaxial with the axis of rotation. The work pieces are rigidly clamped and are supported by a backing plate, or anvil, that bears the load form the tool and constrains deformation of the material at the backside of the joint. 2. DESIGN OF EXPERIMENTS 2.1 General Quantitative Approach This approach is based on the principles of statistics. It has been popular for the research in the field of medicines and agriculture for a long time. However, this approach has been used recently in the field of welding to predict the effect of input parameters on output parameter or response. This approach has a number of advantages over the classical approach. The most important advantage is that several parameters can be studied simultaneously at different levels on the response and in addition to the process optimization: the interactions between two or more parameters could also be evaluated. In general the statistical method of designing experiments helps in minimizing the time and the cost of experimentation. In this technique experiments are conducted as per the design matrix. Based on the experimental data generated regression equations are derived using the method of least squares. The statistical significance of coefficients of the regression equations are tested using students ‘t’ test. The coefficient having higher the value of ‘t’, more significant it becomes. After dropping insignificant coefficients, adequacy of the final model is determined by applying ‘F’ test. In this manner adequate model within the given confidence level can be developed. These developed models can be used for prediction the effects of control variables on the required responses.
  3. 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 164 Table 2.1 Welding parameters used and their limits Parameters Units Symbols Designation Upper limit Lower limit Tool RPM Rpm R X1 1100 750 Welding speed mm/min S X2 150 90 Pin diameter Mm D X3 8 6 2.2 Development of design matrix Table 2.2 Design Matrix S.No. R 1 S 2 D 3 1 + + + 2 - + + 3 + - + 4 - - + 5 + + - 6 - + - 7 + - - 8 - - - 2.3 Experimental procedure All the friction stir welds were performed with a vertical milling machine that was set up for performing such welds. The initial joint configuration was obtained by securing the base plates (100 x 50 x 6 mm) of Al-5083 alloy on to a specially designed fixture. Two friction stir welding tools with pin diameters (D) 8mm and 6mm, 5.8 mm long (h) and shoulder diameter (25mm) were used. The three welding parameters were considered i.e. Tool rotation speed, welding speed and tool pin diameter. Table 2.3 Coefficients of model S.No. Coefficient of Regression Due to 1 b0 Combined effect of all parameters 2 b1 Tool RPM (R) 3 b2 Welding speed (S) 4 b3 Pin diameter (D) 5 b12 Interaction of R & S 6 b13 Interaction of R & D 7 b23 Interaction of S & D
  4. 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 165 Table 2.4 Design Matrix for calculating the value of coefficients b0 b1 R b2 S b3 D b12 RS b13 RD b23 SD +1 +1 +1 +1 +1 +1 +1 +1 -1 +1 +1 -1 -1 +1 +1 +1 -1 +1 -1 +1 -1 +1 -1 -1 +1 +1 -1 -1 +1 +1 +1 -1 +1 -1 -1 +1 -1 +1 -1 -1 +1 -1 +1 +1 -1 -1 -1 -1 +1 +1 -1 -1 -1 +1 +1 +1 2.4 Developed model Developed models could be obtained by putting the values of the regression coefficients obtained from equation (2) in the selected model, Y = b0 + b1R + b2S + b3D + b12RS + b13RD + b23SD ----------------(1) 3. EXPERIMENTAL WORK The friction stir welding process was performed on a vertical milling machine. The specially designed fixture was clamped on bed of vertical milling machine. The tool was mounted on the vertical spindle. Then two prepared aluminum pieces were clamped into the fixture. Then the rotating tool was made to embed into the butt joint. Then after some time, when there was sufficient heating was achieved due to friction between tool and plates, the bed was given automatic feed, along the joint direction. Thus the welding was achieved. Thus total 8 experiments were performed. The welding parameters were selected as per design matrix. The trials were repeatedly three times for determining the adequacy of mathematical models. Thus total 24 trials were performed. After that the pieces were cut into the samples of required dimensions for performing the tensile tests, impact tests, and micro hardness tests. 3.1 Mathematical model for tensile strength 3.1.2 Observation Table for Tensile Strength The observed values for tensile strength for the specimens are tabulated as: Table 3.1 Observation table for tensile strength Sr. No. T1 (Set 1) N/mm2 T2 (Set 2) N/mm2 T3 (Set 3) N/mm2 1 277 278 281 2 283 282 283 3 278 280 279 4 275 276 278 5 280 283 280 6 288 287 284 7 283 280.5 280 8 283.5 284 280
  5. 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 166 3.1.3 Variance of Optimization for Tensile Strength Variance of optimization for tensile strength is calculated by taking the values of tensile strength from first two sets. Table 3.2 shows the Variance of optimization for tensile strength. Table 3.2 Variance of optimization for tensile strength Tensile Strength N/mm2 S2 y = 2 ΣN i=1 ∆T2 /N T1 T2 Tm ∆T ∆T2 277 278 277.5 0.5 0.25 283 282 282.5 -0.5 0.25 278 280 279 1 1 275 276 275.5 0.5 0.25 280 283 281.5 1.5 2.25 288 287 287.5 -0.5 0.25 283 280.5 281.75 -1.25 1.5625 283.5 284 283.75 0.25 0.0625 Σ∆T2 =5.875 S2 y =1.46875 Coefficients of regression for model for tensile strength were calculated (Table 3.3) as Table 3.3 Coefficients of Regression for Tensile Strength Mathematical Model Coefficient Factor Value b0 Combined effects of all factors 281.125 b1 Tool rotation speed (R) -1.1875 b2 Welding speed (S) 1.125 b3 Pin diameter (D) -2.5 b12 Interaction of R & S -1.5625 b13 Interaction of R & D 0.8125 b23 Interaction of S & D 0.25 The model for tensile strength can be obtained by putting the values of coefficients in Equation (1): T= 281.125-1.1875R+1.125S-2.5D-1.5625RS+0.8125RD+0.25SD ‘t’ values for coefficients of regression for tensile strength were calculated as: These values were compared with the‘t’ value taken from standard Table 5 [7]. The value of’t’ is 2.306. Hence the coefficients of regression having‘t’ values less than 2.306 were treated as insignificant and were dropped from final model.
  6. 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 167 Table 3.4‘t’ Values for tensile strength mathematical model Coefficient Factor Value |bi| ‘t’ Value b0 Combined effects of all factors 281.125 656.1007 Significant b1 Tool rotation speed (R) 1.1875 2.771435 Significant b2 Welding speed (S) 1.125 2.62557 Significant b3 Pin diameter (D) 2.5 5.8346 Significant b12 Interaction of R & S 1.5625 3.646625 Significant b13 Interaction of R & D 0.8125 1.896245 Insignificant b23 Interaction of S & D 0.25 0.58346 Insignificant The table shows that the coefficients b3 and b13 are insignificant, so these coefficients have to be dropped from the model. Now the final model becomes: T= 281.125-1.1875R+1.125S-2.5D-1.5625RS 3.1.4 Variance of Adequacy for Tensile Strength Variance of adequacy for tensile strength is calculated by taking the third set values and estimated values. Table 3.5 Variance of adequacy for tensile strength Tensile Strength N/mm2 S2 ad = 2 ΣN i=1 ∆T2 /N Tp T3 ∆T ∆T2 279.75 281 -1.25 1.5625 285.25 283 2.25 5.0625 280.125 279 1.125 1.265625 279.375 278 1.375 1.890625 279.25 280 -0.75 0.5625 284.75 284 0.75 0.5625 280.625 280 0.625 0.390625 279.875 280 -0.125 0.015625 Σ∆T2 =11.3125 S2 ad = 2.828125
  7. 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 168 3.1.5 Analysis of Variance for Tensile Strength ‘F’ values thus obtained and denoted as Fm were compared from the standard Table 8.4 [7] of Ft at (4,8, 0.5). as Fm<Ft, it was found that the model was adequate at 95% level of significance thus justifying the use of assumed polynomial. Table 3.6 Analysis of variance of mathematical model Degree of Freedom Variance of Adequacy Variance of Response ‘F’–Ratio Model (Fm) ‘F’-Ratio Table Adequacy of Model F N S2 ad S2 y Fm= S2 ad/ S2 y at 4, 8, 0.5 Whether Fm<Ft 4 8 2.828125 1.46875 1.925532 3.84 Yes It is observed that the value of Fm is less than the value of Ft, so the developed model is an adequate model. 4. RESULT & DISCUSSION 4.1 Results The final proposed mathematical models for tensile strength is given below: T= 281.125-1.1875R+1.125S-2.5D-1.5625RS These mathematical models can be used to predict the effects of the parameters of the tensile strength. These can be used to predict tensile strength substituting the values of respective factors in coded form. These models are also useful to enhance the productivity and quality of weld. 4.2 Influence of Tool Rotational Speed on Tensile Strength It can be concluded that as the rpm increases, the tensile strength decreases significantly. At high rpm, high heat is evolved, due to which the coarse micro structure is produced, as a result the tensile strength is decreased. Also a higher rotational speed causes excessive release of stirred material to the upper surface, which resultantly leaves the voids in the FSW zone. Due to it, there is decrease in tensile strength of the material. When a force is applied to a metal, the layers of atoms within the crystal structure move in relation to adjacent layers of atoms. This process is referred to as slip. Grain boundaries tend to prevent slip. The smaller the grain size, larger will be the grain boundary area. Decreasing the grain size of the metal tends to retard slip and thus increases the strength of the metal. 4.3 Influence of Welding Speed on Tensile Strength It can be concluded that as the welding speed increases, the tensile strength also increases. It is because by increasing the welding speed, there is slow heat input. The slow heat input give relatively high cooling rates, which generates fine grained heat affected zones and less brittlement. This results in increase in tensile strength. 4.4 Influence of pin diameter on Tensile Strength It can be concluded, that as the pin diameter increases, the tensile strength will decreases. It is because of, if we increase the pin diameter, welding will affect the more area of the plates.
  8. 8. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 169 4.5 Interactive Effect of tool rotation speed and Welding Speed on Tensile Strength The tensile strength decreases from 285 to 279.5 with increase in rotational speed 750 to 1100 rpm and at the maximum welding speed i.e. 150mm/min. And on the other hand at the minimum welding speed i. e. 90mm/min, tensile strength remains constant. 5. CONCLUSION AND FUTURE SCOPE • Two Level Factorial Design is found to be effective tool to investigate the interaction effects of parameters on the required response. • Proposed models are adequate at 95% confidence level, thus justifying the use of assumed polynomials. • Tensile Strength decreases with increase in rotational speed of tool. • Tensile Strength increases with increase in welding speed. • Tensile Strength decreases with increase in pin diameter. • Prediction of the Tensile Strength at any combination of the two parameters welding speed and Rotation speed can be done. • At low rotational speed of tool and high welding speed, there is maximum Tensile Strength. Scope for future work • Effects of welding parameters on the other mechanical properties like impact strength, bending strength, fatigue behaviour, compressive strength can also be studied. • Dissimilar metals can be joined with the help of FSW process and study of welding parameters can be done. • Effects of different types of tool materials can be studied on FSW process. • Effects of different types of tool shapes can be studied on FSW process. • FSW process can be studied for suitability for welding other materials like copper, magnesium, titanium, steel etc. • Effects of vertical downward force can be studied on the defects and grain structure produces in the weld metal zone. REFERENCES 1. A. H. Feng and Z. Y. Ma, Formation of Cu2FeAl7 phase in friction-stir-welded SiCp/Al-Cu- Mg composite. Scipta Materialia 57 (2007) 1113-1116. 2. R. W. Fonda and J. F. Bingert, Texture variations in an aluminium friction stir weld. Scipta Materialia 57 (2007) 1052-1055. 3. Allan, R. Pfluger., Richard, E. Lewis., Weld imperfections, Proceedings of a symposium at Lockheed palo Alto Research Laboratory, Polo Alto, California, 1996. 4. Yasunari Tozaki, Yoshihiko Uematsu, Keiro Tokaji, Effect of tool geometry on microstructure and static strength in friction stir spot welded aluminium alloys, International Journal of Machine Tools & Manufacture 47 (2007) 2230-2236. 5. N. Afrin, D. L. Chen, X. Cao and M. Jahazi, Strain hardening behaviour of a friction stir welded magnesium alloy. Scripta Materialia 57 (2007) 1004-1007. 6. Montegomery, D.C., Design and Analysis of Experiments, New York, John Willey & Sons, 1984. 7. Rao, Singiresu. S., Engineering Optimization Theory & Practice. New Age International Ltd. Publishers, 2002. 8. www.google.co.in, books, colegrov 2000, material flow in FSW.
  9. 9. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online), Volume 5, Issue 2, February (2014), pp. 162-170, © IAEME 170 9. T. Minton, D.J. Mynors, Utilization of Engineering Workshop Equipment for FSW, Journal of Materials Processing Technology, 177, pp 336-339, 2006. 10. G. H. Payganeh, N. B. Mostafa Arab, Y. Dadger Asl, F. A. Ghasemi and M. Saeidi Boroujeni, Effects of FSW process parameters on appearance and strength of polypropylene composite welds, International journal of the Physical sciences vol. 6(19), pp. 4595-4601, 16 sept. 2011. 11. Mathers, G. 2002, The welding of aluminium and its alloys. 12. www.google.co.in, friction stir welding process. 13. Kannan.P, K.Balamurugan and K. Thirunavukkarasu, “Experimental Investigation on the Influence of Silver Interlayer in Particle Fracture of Dissimilar Friction Welds”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 3, Issue 2, 2012, pp. 32 - 37, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359. 14. D. Kanakaraja, P. Hema and K. Ravindranath, “Comparative Study on Different Pin Geometries of Tool Profile in Friction Stir Welding using Artificial Neural Networks”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 4, Issue 2, 2013, pp. 245 - 253, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359. 15. D.Muruganandam and Dr.Sushil lal Das,, “Friction Stir Welding Process Parameters for Joining Dissimilar Aluminum Alloys”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 2, Issue 2, 2011, pp. 25 - 38, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.

×