Investigations on friction stir welding process to optimize the multi responses using GRA method

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The research mainly focused on optimizing the multi responses i.e. tensile strength, impact Strength and elongation while conducting the experiments on Friction Stir Welding process.

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Nội dung Text: Investigations on friction stir welding process to optimize the multi responses using GRA method

International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 03, March 2019, pp. 341–352, Article ID: IJMET_10_03_035 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed INVESTIGATIONS ON FRICTION STIR WELDING PROCESS TO OPTIMIZE THE MULTI RESPONSES USING GRA METHOD Bazani Shaik Research Scholar, Department of Mechanical Engineering, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, INDIA Dr. G. Harinath Gowd Professor, Department of Mechanical Engineering, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, INDIA Dr. B. Durga Prasad Professor, Department of Mechanical Engineering, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, INDIA ABSTRACT The research mainly focused on optimizing the multi responses i.e. tensile strength, impact Strength and elongation while conducting the experiments on Friction Stir Welding process. With the help of trial experiments and based on the literature, the following input parameters i.e. tool rotational speed, weld speed and tilt angle are identified as the most influencing parameters and are used in the current study. Experiments are carried out using the Taguchi L9 design. Al7075-T651 and Al6082-T651 aluminium alloys are taken as the parent materials. The tool used is Taper threaded tool. This FSW uses no filler metal to join two work pieces. A study has been made while selecting the tool type. Detailed influences are discussed in the paper. The Grey relational analysis method is applied to optimize the output responses. Further plots are drawn between the input process parameters and the output responses. Overall the method finds best in multi-response optimization of FSW process. Key words: Aluminium alloys, FSW process, Multi-Response Optimization, Taguchi based GRA Cite this Article: Bazani Shaik, Dr. G. Harinath Gowd, Dr. B. Durga Prasad, Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method, International Journal of Mechanical Engineering and Technology 10(3), 2019, pp. 341–352. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3 http://www.iaeme.com/IJMET/index.asp 341 editor@iaeme.com
Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method 1. INTRODUCTION The Friction Stir Welding (FSW) process is very widely used to join the high strength aluminum alloys as it is very difficult to weld them using fusion welding technique. Another disadvantage with the Fusion welding process is poor solidification and porosity in the fusion zone. This FSW process was invented by Thomas et al. in the year 1991. Since then it is growing its importance in the field of aerospace and automobile industries. The FSW process is very advantages over other methods as the material subjected to FSW does not melt and recast, Less distortion, lower residual stresses and almost no welding defects [1]. Also FSW process completely eliminates the radiation effect and the harmful emissions of gases which come during the fusion welding process. FSW is also considered as an environmental friendly and energy efficient process. This process doesnot require any shielding gas. It produces joints with excellent metallurgical properties in the joint area. This FSW process uses a non consumable tool which is rotating with shoulder surface and the unique pin design is plunged in between the abutting surface of the plates to be joined. The base plates are fixed to the worktable with a specially designed fixture and support back plates. Because of the frictional heat generated between the rotating tool and the work material, the work material around the tool pin gets softened which allows the material to flow along the welding line without reaching its melting point. The FSW tool is designed to serves the following two functions. 1. Heating the work pieces and 2. To make the material flow along the joining line to produce the joint. The principle of working is shown in Fig 1. Figure 1 A Schematic View of Friction Stir Welding [1] The strength of FSW joint depends on the right combination of input parameters. As the process is complex, the following parameters (i.e. Rotational Speed, Welding Speed, Axial force, Tool geometry, pin length, tool shoulder diameter, pin diameter, Tool tilt angle etc) should be controlled in a proper manner to obtain the acceptable welding joints. So keeping its growing importance and its suitability to weld the sample of Aluminum alloys, this FSW process is chosen as the research area. Mainly investigations carried out on Aluminum alloys7075Al and 7050Al. Using FSW process, both the alloys were butt welded. To find the optimal process parameters to achieve the best welded joints interms of strength without compromising the quality and cost, several papers related to the FSW process and the methodologies published by researchers refereed and the following sections explains the key points in brief. The dissimilar aluminum alloys of AA2024and AA6061 investigated by using response surface method on three level factors box Behnken matrix data regression and graphical analyses done and ANOVA model also checked out. By controlling of welding http://www.iaeme.com/IJMET/index.asp 342 editor@iaeme.com
Bazani Shaik, Dr. G. Harinath Gowd, Dr. B. Durga Prasad speed 40mm/min and rotational speed 500rpm, Tool pin diameter by validation of responses on tensile strength optimizes error 5% with high accuracy of friction stir welding process [2].Welding of 0.5 mm thin Al6061-T6 on different welding speeds of 150mm/min and 200mm/min, efficiency joint 74%, elongation 8% and bending value 1800 reduced heat loss and fixture of close clamping of both sides welding of thin sheets. Heat affected zone and thermo mechanic affected zone increased with increase of welding speed and observed on thin sheets distortion is higher welds at lower welding speeds[3]. Dissimilar welding of reinforced aluminum plates and Tic nanoparticles or done free weld defects and mechanical properties of elastic modulus and hardness has nano scale and micro scale. The friction stir process of passes of rotational speed 1500rpm and welding speed 85mm/min and optical, scanning electron micrographs on EDS analysis. By the addition of nano particle tensile strength and elongation are slightly increased[4]. TheDissimilar welding is carried out on Al1100 and Al441 steel plates following the Taguchi design by varying the following parameters tool offset, depth plunge, rotational speed and welding speed [5].Examined the Microstructural developments at different zones whenjoining Al1050 and Al.-matrix nano composite with a rotational speed 1200rpm, welding speed 50mm/min. The tensile strength improved by 128 Mpa and hardness of stir zone by170% geometrical locations and texture components are varied at stir zone[6]. Investigated SAF2205 and 304 stainless steel fatigue, residual stresses are used by base model of continuum damage mechanics and specimen width of least 30 %weld sample of residual relaxation due to cutting consideration and Joining’s of Al3003 and SUS304 steel of fatigue crack propagation and fracture toughness examined temperature of 5000C and dwell time 60s [7,8]. Studied the effects of rotational speed, tilt angle, welding speed on the tensile strength by carrying out the experiments based on L9 design on the following alloys Al-5083-H321. The grey relational analysis method is also tested in [9]. After thorough investigations, it is found that the Grey Relational Analysis method is used very limited by the researchers. Hence an attempt is been made to investigate the FSW process using GRA method. 2. EXPERIMENTAL WORK The experimentation was done at the FSW setup available at Annamalai university, Tamilnadu. The specifications of the machine are shown in the Table 1. and the setup on which the experiments are carried out is shown in Fig 2. Table 1. Machine Specifications Table Size 2m Length x 1m Width Workable Area of Table 1m Length x 1m Width Drive Motor 1RPM to 3000RPM Motor Capacity 13KW(Servo) X-Axis Motor -3KW(Servo) Range-1mm/min to 1000mm/min Y-Axis Motor-3KW(Servo) Range-1mm/min to 1000mm/min http://www.iaeme.com/IJMET/index.asp 343 editor@iaeme.com
Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method Figure 2 Experimental Setup of FSW The Aluminum alloys Al7075T651 and Al6082T651are chosen as the work materials because of its increasing importance in the aerospace and automobile industries. The dissimilar butt welding joints are prepared using the FSW process. The chemical composition of both the alloys are presented in the Table 2. and its mechanical properties are shown in the Table 3. Table 2.The Chemical compositions on Al7075-T651 and Al6082-T651 (percentage of weight) Elements Si Fe Cu Mn Mg Cr Ni Zn Ti Al Al7075- T651 0.12 0.2 1.4 0.63 2.53 0.2 0.004 5.62 0.03 89.26 Al6082- T651 1.05 0.26 0.04 0.68 0.8 0.1 0.005 0.02 0.01 97.03 Table 3. Mechanical properties of Aluminum Alloys Impact Strength Elongation (%) Al alloy Tensile Strength (MPa) (J) 7075-T651 220 15 17 6082-T651 330 10 9 The base plates are cut in to 100mm × 50mm×6mm samples and a total of 9 butt welded joints are prepared using the FSW setup. Taguchi L9 orthogonal array is used to design the experiments. Research is carried out on the Taper threaded tool. The tool is specially made using the M2Grade SHSS is shown in Fig 3. and dissimilar weld position of friction stir welding shown in Fig 4. The probe length is 6mm. Whereas the diameter of the shoulder is 18mm. The process is controlled with the help of a computer. Edge preparation is done for the base materials. A dissimilar butt weld is being made by clamping the materials using fixtures by placing AA7075T651 and AA6082T651 on Advancing Side and Retreating Side respectively by opting the parameters-rotational speed(RS), Welding Speed(WS), Tilt Angle(TA) are investigated for pilot study and literature review i.e. Three levels shown in Table4. The test specimens are prepared according to the ASTM standards. Grey relational analysis of Taguchi are used on orthogonal array of L9 selection for responses tensile strength, Elongation, Impact strength are most important moderation quality of butt joint weld. Grey relational analysis are used for output variables to get maximum values. Orthogonal array L9 experimental plan given in Table 5. Al7075T651 in advancing side and Al6082T651 in retreating side for best joining and development of mechanical properties. The http://www.iaeme.com/IJMET/index.asp 344 editor@iaeme.com
Bazani Shaik, Dr. G. Harinath Gowd, Dr. B. Durga Prasad friction stir welding specimens are cut in sections of transverse as per ASTME8. The weld specimens are appropriately prepared for metallurgical examination and Investigated to improve micro structures of aluminum alloys..The tensile test specimensTensile test specimen’s failure of weakest zoneare shown in Fig 7. and specimens of impact strength shown in Fig 8. The tensile specimens tested at room temperature on 100KN Universal Testing Machine Model F-100.Tensile strength test results are shown in Table 7. Elongation percentage are also shown in Table 7. Table 4 Levels of Process parameters Levels Sno Parameters Notation Unit -1 0 -1 Rotational 1 RS rpm 1150 1250 1350 speed Welding 2 WS mm/min 40 50 60 speed 3 Tilt angle TA Degree 1 2 3 Table 5 Experimental plan through L9 orthogonal array Sno Rotational Speed(rpm) Weld Tilt Angle(0) Speed(mm/min) 1 -1 -1 -1 2 -1 0 0 3 -1 1 1 4 0 -1 0 5 0 0 1 6 0 1 -1 7 1 -1 1 8 1 0 -1 9 1 1 0 Figure 3 Taper threaded tool http://www.iaeme.com/IJMET/index.asp 345 editor@iaeme.com
Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method Figure 4 Dissimilar weld position of friction stir welding Figure 7 Tensile test specimen’s failure of weakest zone Figure 8 Specimens of Impact Testing http://www.iaeme.com/IJMET/index.asp 346 editor@iaeme.com
Bazani Shaik, Dr. G. Harinath Gowd, Dr. B. Durga Prasad Table 7. Average response values of different responses Sno Rotational Weld Tilt Tensile Impact Elongation Speed Speed Angle Strength Strength % rpm mm/min Degree Mpa Joules 1 1150 40 1 171.5 9.38 9.44 2 1150 50 2 175.39 12 10.11 3 1150 60 1 168.51 10.87 9.33 4 1250 40 2 160.04 11.25 5.64 5 1250 50 2 161.82 12 8.14 6 1250 60 2 151.29 9.18 5.14 7 1350 40 3 162.58 13 10 8 1350 50 3 164.23 14.8 10.78 9 1350 60 3 157.8 10 10.14 The Table 7. gives the measured output responses i.e. Tensile strength, Impact strength and Elongation. The tensile strength is maximum when the rotational speed is 1150 rpm, weld speed is 50mm/min and tilt angle is 2degree. At this combination the joint shows more strength. Whereas the impact strength is 12 joules and elongation is 10.11 Percent. The Impact strength is maximum when the rotational speed is 1350 rpm, weld speed is 50mm/min and tilt angle is 3 degrees. The maximum elongation is at the point where rotational speed is 1350 rpm, weld speed is 50mm/min and tilt angle is 3 degrees. It can also be observed that Impact strength and Elongation are maximum at the same combination. Also the tensile strength is more than the average value at that combination. Hence the same combination can also be treated as the best combination obtained from the experimental results. The microstructures were taken at that combination and are presented in this paper. This can be further optimized by applying the GRA method and it can be further improvised. 3. TAGUCHI BASED GREY RELATIONAL ANALYSES: The unknown information process isdetermining system on statistical optimization Techniques. The Taguchi method is power full technique for optimization for different engineering problems. A characteristics of quality can optimize problem by Technique of Taguchi. The multiple responses of problem optimize inadequate by Taguchi. The analyzing and solving of responses multiple for engineering problems. Grey relational analysis of Taguchi is best method. In 1982 Deng suggest GRA analyzes incomplete or unknown information on outcome of different responses of parameters. The steps of GRA Technique as Follows:  Grey relational generation is also called as original data of normalization.  Grey relational coefficient compute.  Grey relational grade compute.  Finding optimum sequence.  Analyses of variance.  Optimal prediction of Grey relational grade.  Experiment confirmation performance. http://www.iaeme.com/IJMET/index.asp 347 editor@iaeme.com
Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method 3.1. Grey relational generation The analysis of preprocessing data is also called as generation of grey relation. The relational sequence of data composed values of experiments are form in comparable sequence interval 0 and 1. The three different characteristics quality applied i.e. nominal is better, larger is better, smaller is better most part performed. The original sequence is minimizing ‘smaller the better ‘characteristic used normalize sequence reference. Selected quality characteristics type is ‘large is better’ with calculation of grey relational generation Equation (1) (1) Although of series max as well as min is max together with min series of values, after data processing generation of sequence. i=1,2,3….m and k=1,2,3…. n, data of experimental is n and experiments of m. 3.2. Coefficient of grey relation The Normalizing process on coefficient of grey relational is calculated to identify relationship between comparability sequence and reference sequence. Grey relational coefficients calculated corresponding variations considering Equations (2) and (3). | | (2) (3) Where series of variation and series of relation series of interference , identification coefficient, which generally 0.5 parameters are weightage equal.Grey relational coefficient experiment are calculated by orthogonal array of L9 of equation (3). 3.3. Grey relational grade For compatibility series and reference series grey relation grade performed for calculate strength relationship and values are 0 and 1. The GRG has better relation for higher value. Generally, for calculating grey relation grade is grey relational coefficient average summation of equation (4). ∑ (4) Although is grey relational grade execution of characteristics of number n experiment ith. The normalized or ideal value are closer to experimental results and correspondence to GRG of larger value. 3.4. Parameter prediction for optimal value The effects of different parameters are calculated and best response of grey relational grade are closer as a 1 and optimal welding condition of parameters has highest mean GRG value. 3.5. ANOVA Performance http://www.iaeme.com/IJMET/index.asp 348 editor@iaeme.com
Bazani Shaik, Dr. G. Harinath Gowd, Dr. B. Durga Prasad Statistical significance of different parameters for performance of ANOVA probability p value is used and contribution of parameter response can resolute results of ANOVA. 3.6. Prediction parameters for optimal level The optimal level of different parameters for resolution of prediction of GRG value by using equation (5) ∑ (5) Although is mean total of GRG,q is parameters number , is GRG mean value of optimal level qth parameter. 4. SIGNAL-TO-NOISE RATIO Table 4 shows responses of average values on input parameter settings. The responses in three parameters calculated by signal-to-noise ratio. Higher values of Tensile strength, Elongation, Impact strength gives better concert on welding. The equation (6) is a signal-to-noise ratio of calculation. Signal-to-noise ratio ( )∑ (6) Although experimental reproduction of n number and Yijk variable response of ith characteristic execution of experiment jth experiment with trail kth. Figure 9 Plot for Tensile Strength of signal-to-noise-ratio The process parameters of each level for calculation of signal-to-noise-ratio value is considered rotational speed RS 1250 rpm, welding speed WS 50 mm/min and tilt angle TA 20are better characteristics performance of S/N ratios shown in Fig. 9. http://www.iaeme.com/IJMET/index.asp 349 editor@iaeme.com
Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method Figure 10 Plot for Elongation of signal-to-noise-ratio The process parameters of each level for calculation of signal-to-noise-ratio value is considered rotational speed RS 1350 rpm, welding speed WS 50mm/min and tilt angle TA 30are better characteristics performance of S/N ratios shown in Fig. 10. Figure 11 Plot for Impact Strength of signal-to-noise-ratio The process parameters of each level for calculation of signal-to-noise-ratio value is considered rotational speed RS 1250 rpm, welding speed WS50mm/min and tilt angle TA 20are better characteristics performance of S/N ratios shown in Fig. 11. http://www.iaeme.com/IJMET/index.asp 350 editor@iaeme.com
Bazani Shaik, Dr. G. Harinath Gowd, Dr. B. Durga Prasad 5. CONCLUSIONS The following conclusions are drawn from the research carried out on FSW process.  Multi responses i.e.tensile strength, impact Strength and elongation were optimized applying the method of Taguchi based Grey relational analysis.  Two dimensional plots are drawn and analyzed to find the exact relationships between the input process parameters and the output responses.  Taguchi based L9 is used to carry out the experiments by varying the process parameters i.e.rotational speed, welding speed and tilt angle.  The tensile strength is maximum 175.39 Mpa, when the rotational speed is 1150 rpm, weld speed is 50mm/min and tilt angle is 2degree.  The Impact strength is maximum 14.8J, when the rotational speed is 1350 rpm, weld speed is 50mm/min and tilt angle is 3 degrees.  The maximum elongation 10.78% is at the point where rotational speed is 1350 rpm, weld speed is 50mm/min and tilt angle is 3 degrees.  It can also be observed that Impact strength and Elongation are maximum at the same combination. Also the tensile strength is more than the average value at that combination. Hence the same combination can also be treated as the best combination obtained from the experimental results.  SN Plots drawn and analyzed the results using GRA technique. Overall the GRA method finds suitable for multi response optimization of FSW process REFERENCES [1] Z. Y. Ma, A. H. Feng, D. L. Chen & J. Shen (2017): Recent Advances in Friction Stir Welding/Processing of Aluminum Alloys: Microstructural Evolution and Mechanical Properties, Critical Reviews in Solid State and Materials Sciences, DOI:10.1080/10408436.2017.1358145. [2] K. Jagathesh, M.P. Jenarthanan, P. Dinesh Babu & C. Chanakyan (2016): Analysis of factors influencing tensile strength in dissimilar welds of AA2024 and AA6061 produced by Friction Stir Welding (FSW), Australian Journal of Mechanical Engineering, DOI:10.1080/14484846.2015.1093229. [3] Shuja Ahmed, Probir Saha, Development and testing of fixtures for friction stir welding of thin aluminum sheets, Journal of Materials Processing Tech.252 (2018) 242–248. [4] D. A. Dragatogiannis, E. P. Koumoulos, I. Kartsonakis, D. I. Pantelis, P. Karakizis & C. A. Charitidis (2015): Dissimilar Friction Stir Welding Between 5083 and 6082 Al Alloys Reinforced with Tic Nanoparticles, Materials and Manufacturing Processes, DOI:10.1080/10426914.2015.1103856. [5] H. A. Derazkola, H.J. Aval and M. Elyasi, Analysis of process parameters effects on dissimilar friction stir welding of AA1100 and A441 AISI steel, Science and Technology of Welding and Joining, Institute of Materials, Minerals and Mining, DOI:10.1179/1362171815Y.0000000038. [6] F. Khodabakhshi, A. Simchi, A. H. Kokabi, A. P. Gerlich, M. Nosko & P. Švec (2016): Influence of hard inclusions on microstructural characteristics and textural components during dissimilar friction-stir welding of an PM Al–Al2O3–SiC hybrid nanocomposite http://www.iaeme.com/IJMET/index.asp 351 editor@iaeme.com
Investigations on Friction Stir Welding Process to Optimize the Multi Responses Using GRA Method with AA1050 alloy, Science and Technology of Welding and Joining, DOI:10.1080/13621718.2016.1251714. [7] Zhang, W., Jiang, W., Zhao, X., Tu, S-T., Fatigue life of a dissimilar welded joint considering the weld residual stress: Experimental and finite element simulation, International Journal of Fatigue (2018), doi:https://doi.org/10.1016/j.ijfatigue.2018.01.002. [8] Hidehito Nishida, Tomo Ogura, Ryoichi Hatano, Hirotaka Kurashima, Misuo Fujimoto & Akio Hirose (2016): Fracture toughness and fatigue crack behavior of A3003/SUS304 lap friction stir welded joints, Welding International, DOI:10.1080/09507116.2016.1223206. [9] Jitender Kundu & Hari Singh (2016) Friction stir welding: multi-response optimization using Taguchi-based GRA, Production & Manufacturing Research, 4:1, 228-241, DOI: 10.1080/21693277.2016.1266449. [10] Bazani Shaik, Dr.G. Harinath Gowd and Dr.B. Durga Prasad, Experimental Investigations On Friction Stir Welding Process to Join Aluminum Alloys, International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 15 (2018) pp. 12331-12339. [11] Bazani Shaik, G. Harinath Gowd and B. Durga Prasad, An Optimization and Investigation Of Mechanical Properties and Microstructures On Friction Stir Welding Of Aluminium Alloys, International Journal of Mechanical and Production Engineering Research and Development (IJMPERD), ISSN(P): 2249-6890; ISSN(E): 2249-8001, Vol. 9, Issue 1, Feb 2019, 227-240. http://www.iaeme.com/IJMET/index.asp 352 editor@iaeme.com