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Optimization of TIG Welding Process Parameters With SS316 Material Using Taguchi Design
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Optimization of TIG Welding Process Parameters With SS316 Material Using Taguchi Design
1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 10 Issue: 11 | Nov -2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 793 Optimization of TIG Welding Process Parameters With SS316 Material Using Taguchi Design Mr. Parmar Nikhil A.1, Mr. Rakesh H.Patel2 1Student, Dept. of Mechanical Engineering, Sankalchand patel university,Gujarat, India 2Professor, Dept. of Mechanical Engineering, Sankalchand patel university,Gujarat, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Tungsten Inert Gas welding is a popularmethod for connecting ferrous and nonferrous metals. In which anon- consumable tungsten electrode and workpiece form an arc, while argon shields the molten metal from the atmosphere. TIG welding will use to join 3 mm-thick SS316 sheets. Welding current, gas flow rate, and front/back width are the input/output parameters. The Taguchimethodrecommended orthogonal array design to assign experiment factors. 9 Taguchi L9 orthogonal array experiments will design. ANOVA and S/N ratio will use to optimize welding parameters. After analysis, front and back width control factors are most significant. Keywords: Tig welding, Anova,Taguchimethod, Minitab, Stainless Steel. 1. INTRODUCTION Welding fuses metals or thermoplastics, unlike brazing and soldering, which do not melt the base metal. This method is employed in sculpture and manufacture. The weld pool is formed by melting the base metal with filler material. The pool cools and produces a connection that may be stronger than the parent metal depending on the weld configuration (butt, complete penetration, fillet, etc.). Pressure alone or with heat can weld. Welding requires a barrier to prevent filler metal or molten metal contamination or oxidation. A welding junction is any point or edge that joins metal or plastic parts. Their shape depends on the geometrysoldered between metal orplastic work pieces.TheAmerican Welding Society classifies joints as butt, corner, edge, lap, and tee. These layouts can vary at the welding spot. 2. OBJECTIVE 1. 1. For this experiment, I have chosen a 3mm thick SS316 sheet material. 2. Using a L9 orthogonal array, the Taguchi method was chosen. 3. Arrange for L9-Based Tig Welding Task 4. Locate the Welding Job's Output Parameters (Front Width, Back Width) 5. Use this study to optimise the process parameters by analysing their effect on the weld bead geometry. 3. TAGUCHI DESIGN To improve process and product design, Taguchi is looking for easily controllable factors and their settings that reduce product response variability while maintaining a desired mean response. Byadjusting thoseparameterstotheirsweet spots, we may make the product more resistanttovariations in both operating and environmental circumstances. Removing the bed effect rather than the cause of the bed effect allows for more stable and high-quality goods to be obtained during the Taguchi parameter design stage. In addition, the method can save money and eliminate wasted goods by systematically applying it at the pre-production stage (off line), which means fewer tests are needed to determine cost-effective process conditions. Fig-1: Pictorial views of Taguchi steps 4. SELECTION OF PROCESS PARAMETERS After study the various research paper and we decide the Input parameters Factor A : Welding Current (A) Factor B : Gas flow rate (LPM)
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 10 Issue: 11 | Nov -2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 794 Parameter that remains constant Work Piece Thickness Output Parameter Front width & Back width Table-1: Process Parameter Level Thickness Paramet ers L-1 L-2 L-3 3mm Welding Current 70 80 90 Gas Flow Rate 4 6 8 Table-2: Levels of the orthogonal array L9 Ex. No. Welding Current Gas Flow Rate Plate Thick Ness 1. 70 4 3 2. 70 6 3 3. 70 8 3 4. 80 4 3 5. 80 6 3 6. 80 8 3 7. 90 4 3 8. 90 6 3 9. 90 8 3 5. EXPERIMENTAL WORK 5.1 Specimen Preparation The plates are prepared and then set on the workstation. They are made of stainless steel SS316 alloy and have dimensions of 60x40 mm anda thickness of 3 mm. The welding electrode must be held at a right angle to the surface being welded. The welding of the plates began with a single pass. The samples are fused together while maintaining the different parameters. Fig-2: The SS316 material thicknesses used for the work piece Test results for tig welding machine Fig-3: welded work Visual inspections are used to verify penetration after welding the work parts. Rejected specimens are those with inadequate penetration. By utilising a travelling microscope to measure the front and back widths, the impact of welding settings on bead geometry may be examined. Table-3: Experiment Ex. No. Welding Current Gas Flow Rate Plate Thick Ness Front Width Back Width 1 70 4 3 5.10 4.42 2 70 6 3 5.06 4.66 3 70 8 3 4.31 4.77 4 80 4 3 5.83 5.98 5 80 6 3 5.45 4.52 6 80 8 3 4.81 4.33 7 90 4 3 8.49 4.46 8 90 6 3 8.20 4.00 9 90 8 3 6.14 4.41
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 10 Issue: 11 | Nov -2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 795 6. RESULTS & DISCUSSION Fig-4: Analysis of the front width's main effect Main plot effect for front width at 3 mm thickness at varying welding current and gas flow rate is shown above. At welding current 70 AMP and gas flow rate 8 LPM, the front width is minimum and at 90 AMP and gas flow rate 4 LPM, it is maximum. Fig-5: Analysis of the back width's main effect The above image shows how welding current and gas flow rate affect the main plot for back width at 3 mm thickness. Welding currents of 90 AMP and gas flow rates of 6 LPM result in the narrowest possible back width, while welding currents of 80 AMP and gas flow rates of 4 LPM yield the widest. 7. CONCLUSION Minitab and anova were used to analyse front and rear widths on 3mm-thick SS316 material. The L9 orthogonal array tests use welding current and gas flow rate. Experimental data was evaluated with Minitab 16. Analysis yielded the following conclusions. A process parameter's effect depends on the response. A important parameter's percentage contribution and objective metric-induced behaviour modification. The tests showed that the front width can be as narrow as 4.31 mm at 8 LPM gas flow and as wide as 8.49 mm at 90 AMP welding current and 4 LPM gas flow. The maximum back width was 5.98 mm at 80 AMP and 4 LPM gas flow, while the minimum was 4 mm at 90 AMP and 6 LPM. From Anova analysis and experimental data i have conclude that most significant parameter isweldingcurrentonoutput parameters. Gas flow rate is minmum effect on output parameters compare to welding current. REFERANCES [1] Asif Ahmad, Shahnawaj Alam “Integration of RSM with Grey based Taguchi Method for optimization of pulsed TIG welding process parameters”(2019) [2] Pramod Kumar , Rajesh Kumar , Abdul Arif , M. Veerababu “Investigation of numerical modelling of TIG welding of austenitic stainless steel (304L)”(2020) [3] Purusothaman M, Captain Prabhakaran M, Brabu S, Venkatesan S P, SenthilkumarG“ Experimental Investigation and Optimization of Welding Parameters for A TIG Welding With SS410 Using ANOVA”(2020) [4] D Kumaravel, K.Arunkumar “Optimization of Weld Quality of SS410 in TIG Welding”(2017) [5] K. RAJASEKHAR, C. RAJESH, Dr. B. JAYACHANDRAIAH “ EXPERIMENTAL INVESTIGATION & ANALYSISOFSS304L& SS410 WELD CHARACTERISTICS USING TIG WELDING”(2018) [6] Pramod Kumar , Abdul Arif , A. Chiranjeevi V.S. Prasad , Puli Danaiah , Akhilesh Kumar Singh , Mohan Patro , K. Sivarama Kishorea, M. Murugan “ Study of Welding process parameter in TIG joining of Aluminum Aolly (6061)”(2021) [7] Sanjay Kumar, Satyasreet Jena, Varun Lahoty, M.K.Paswan. B. Sharma, D.Patel,S.B.Prasad, Vinod Kumar Sharma “ Experimental investigation onthe effectofwelding parameters of TIG welded joints using ANOVA”(2019) [8] K.S.Pujari, D.V.Patil Gurunath.Mewundi “ Selection of GTAW process parameter and optimizing the weld pool geometry for AA 7075-T6 Aluminium alloy”(2017)
4.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 10 Issue: 11 | Nov -2023 www.irjet.net p-ISSN: 2395-0072 © 2023, IRJET | Impact Factor value: 8.226 | ISO 9001:2008 Certified Journal | Page 796 [9] M. Venkata Ramana, B.V.R. Ravi Kumar , M. Krishna , M. Venkateshwar Rao, V.S. Kumar “ Optimization and influence of process parameters of dissimilar SS304L –SS430 joints produced by Robotic TIG welding”(2019) [10] Zhandong Wan , Danyang Meng , Yue Zhao, Dengkui Zhang , Qiang Wang , Jiguo Shan , Jianling Song , Guoqing Wang , Aiping Wu “ Improvement on the tensile properties of 2219-T8 aluminum alloy TIG welding joint with weld geometry optimization”(2021) [11] Balram Yelamasetti , G. Rajyalakshmi “ Effect of TIG, pulsed TIG and Interpulse TIG welding techniques on weld strength of dissimilar joints between Monel 400 and AISI 316”(2019) [12] Arun Kumar Srirangan, Sathiya Paulraj “ Multi- response optimization of process parameters for TIG welding of Incoloy 800HT by Taguchi grey relational analysis”(2015) [13] M. Ramarao, M. Francis Luther King, A. Sivakumar , V. Manikandan , M. Vijayakumar , Ram Subbiah “ Optimizing GMAW parameters to achieve high impact strength of the dissimilar weld joints using Taguchi approach”(2021) [14] Amit Kumar, M K Khurana and Gaurav Singh “ Modeling and Optimization of Friction Stir Welding Process Parameters for Dissimilar Aluminium Alloys”(2018) [15] Ajay Prakash Pasupulla, Habtamu Abebe Agisho , Suresh Seetharaman , S. Vijayakumar “ Characterizationand analysis of TIG welded stainless steel 304 alloy plates using radiography and destructive testing techniques”(2021) [16] Chao Chen, Chenglei Fan, Xiaoyu Cai, Sanbao Lin, Zeng Liu, Qingkai Fan, Chunli Yang “ Investigation of formation and microstructure of Ti-6Al-4V weld bead during pulse ultrasound assisted TIG welding”(2019) [17] Daniel Bacioiu, GeoffMelton,MayorkinosPapaelias,Rob Shaw “ Automated defect classificationofSS304TIGwelding process using visible spectrum camera and machine learning”(2019) [18] Nabendu Ghosh, Pradip Kumar Pal, Goutam Nandi and Ramesh Rudrapati “ Parametric Optimization of Gas metal arc welding process by PCA based Taguchi method on Austenitic Stainless Steel AISI 316L”(2016)
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