پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شماره‌ها | 419 |
| تعداد مقالات | 5,516 |
| تعداد مشاهده مقاله | 6,268,222 |
| تعداد دریافت فایل اصل مقاله | 5,426,846 |
Modeling and Optimization of Flux Assisted Tungsten Inert Gas Welding Process Using Taguchi Method and Statistical Analysis | ||
| AUT Journal of Mechanical Engineering | ||
| مقاله 10، دوره 4، شماره 3، آذر 2020، صفحه 415-424 اصل مقاله (1.31 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/ajme.2019.16890.5839 | ||
| نویسندگان | ||
| Masoud Azadi Moghaddam؛ Farhad Kolahan* | ||
| Ferdowsi University of Mashhad | ||
| چکیده | ||
| Flux assisted tungsten inert gas welding process known as activated tungsten inert gas welding process is being extensively used in order to improve the performance of tungsten inert gas welding process. In this paper, welding current, welding speed and welding gap have been considered as process input variables in fabricating of AISI316L austenitic stainless steel parts. Depth of penetration and weld bead width have been taken in to account as process response parameters. In this paper SiO2, Nano-particles have been considered as an activating flux. To gather required data for modeling and optimization purposes, Taguchi method has been employed. Then, process response parameters have been measured and their corresponding signal to noise ratios have been calculated. Next, different regression equations have been applied on signal to noise ratio values and the most fitted ones have been selected. Furthermore, welding current has been determined as the most important parameter affects depth of penetration and weld bead width with 68% and 88% percent contribution respectively. Next, signal to noise analysis, in such a way that weld bead width minimized and depth of penetration is maximized has been used. Finally, experimental performance evaluation tests have been carried out, based on which it can be concluded that the proposed procedure is quite efficient (with less than 7% error) in modeling and optimization of the process. | ||
| کلیدواژه‌ها | ||
| Modeling؛ Depth of penetration؛ Weld bead width؛ Design of experiments؛ Signal to noise analysis | ||
| مراجع | ||
|
[1] H. Y. Huang, S. W. Shyu, K. H. Tseng, C. P. Chou, Evaluation of TIG flux welding on the characteristics of stainless steel, journal of Science and Technology of Welding and Joining, 10(5) (2005) 566−573. [2] S. W. Shyu, H. Y. Huang, K. H. Tseng, C. P. Chou, Study of the performance of stainless steel A-TIG welds, Journal of Materials Engineering and Performance, 17(2) (2008) 197−201. [3] H. Fujii, T.L.U.S.P. Sato, K. Nogi, Development of an advanced A-TIG (AA-TIG) welding method by control of Marangoni convection, Materials Science and Engineering: A , 495(7) (2008) 296−303. [4] E. Ahmadi, A. R. Ebrahimi, R. A. Khosroshahi, Welding of 304L Stainless Steel with Activated Tungsten Inert Gas Process (A-TIG), International Journal of ISSI, 10(1) (2013), 27-33. [5] S.P. Lu, D.Z. Li, H. Fujii, K. Nogi, Time dependent weld shape in Ar–O2 shielded stationary GTA welding, Journal of Material Science and Technology, 23(5) (2007) 650−654. [6] M. Moradi, M. Ghoreishi, M.J. Torkamany, Modeling and Optimization of Nd: YAG Laser-TIG Hybrid Welding of Stainless Steel, Journal of lasers in Engineering, 27(2) (2014) 211–230. [7] M. Ragavendran, N. Chandrasekhar, R. Ravikumar, M. Vasudevan, A.K. Bhaduri, Optimization of hybrid laser – TIG welding of 316LN steel using response surface methodology (RSM), Optics and Lasers in Engineering, 94(6) (2017) 27-36. [8] H.C. Chen, F.L. Ng, Z. Du, Hybrid laser-TIG welding of dissimilar ferrous steels: 10 mm thick low carbon steel to 304 austenitic stainless steel, Journal of Manufacturing Processes, 47 (2) (2019) 324-336. [9] K.H. Dhandha, V.J. Badheka, Effect of activating fluxes on weld bead morphologyof P91 steel bead-on-plate welds by flux assisted tungsten inert gas welding process, journal of Material and Manufacturing Processes, 17(2) (2015) 48–57. [10] R.S. Vidyarthy, A. Kulkarni, D.K. Dwivedi, Study of microstructure and mechanical property relationships of A-TIG welded P91-316L dissimilar steel joint, Materials Science & Engineering A, 695 (17) (2017) 249-257. [11] K.D. Ramkumar, V. Varma, M. Prasad, N.D. Rajan, Effect of activated flux on penetration depth, microstructure and mechanical properties of Ti-6Al-4V TIG welds, Journal of Materials Processing Tech. 261(3) (2018) 233–241. [12] V. Kumar, B. Lucas, D. Howse, G. Melton, S. Raghunathan, L. Vilarinho, Investigation of the A-TIG Mechanism and the Productivity Benefits in TIG Welding. In JOM-15, Fifteenth International Conference on the Joining of Materials, December 2009. [13] G. Venkatesan, J. George, M. Sowmyasri, V. Muthupandi, Effect of Ternary Fluxes on Depth of Penetration in A-TIG Welding of AISI 409 Ferritic Stainless Steel, Procedia Materials Science, 5(2) (2014) 2402-2410. [14] T.S. Chern, K.H. Tseng, H.L. Tsai, Study of the characteristics of duplex stainless steel activated tungsten inert gas welds, Materials & Design, 32 (1) (2011) 255-263. [15] S. Tathgir, A. Bhattacharya, Activated-TIG welding of different steels: influence of various flux and shielding gas, Materials and Manufacturing Processes, 31(3) (2015) 335–342. [16] F. Kolahan, M. Azadi Moghaddam, The use of Taguchi method with grey relational analysis to optimize the EDM process parameters with multiple quality characteristics, Scientia Iranica B, 22(2) (2015) 530-538. [17] R. Pamnani, M. Vasudevan, T. Jayakumar, P. Vasantharaja, Development of Activated Flux, Optimization of Welding Parameters and Characterization of Weld Joint for DMR-249A Shipbuilding Steel, Transactions of the Indian Institute of Metals, 70(1) (2017) 49–57. [18] G. Venkatesan, V. Muthupandi, J. Justine, Activated TIG welding of AISI 304L using mono- and tri-component fluxes, The International Journal of Advanced Manufacturing Technology, 93(1-4) (2017) 329–336. [19] K.H. Tseng, C.Y. Hsu, Performance of activated TIG process in austenitic stainless steel welds, Journal of Materials Processing Technology, 211(5) (2011) 503–512. [20] M. Vishwakarma, V.V.K. Parashar, Regression Analysis and Optimization of Material Removal Rate on Electric Discharge Machine for EN-19 Alloy Steel, International Journal of Scientific and Research Publications, 2(11) (2012) 167-175. [21] D. Vishnu, R.I. Asal, T. Patel, B. Alok, Optimization of Process Parameters of EDM Using ANOVA Method, International Journal of Engineering Research and Applications, 3 (2) (2013) 1119-1125. [22] M. Azadi Moghaddam, F. Kolahan, Application of orthogonal array technique and particle swarm optimization approach in surface roughness modification when face milling AISI1045 steel parts, Journal of Industrial Engineering International, 12(2) (2016) 199–209. | ||
|
آمار تعداد مشاهده مقاله: 453 تعداد دریافت فایل اصل مقاله: 560 |
||