Development of Artificial Neural Network Models for Predicting Weld Output Parameters in Advanced Fusion Welding of a Magnesium Alloy

K.M. Oluwasegun^1, , O.A Ojo¹, O.T Ola², A. Birur³, J. Cuddy³ and K. Chan⁴

¹Department of Mechanical Engineering, University of Manitoba, Winnipeg, Manitoba, Canada

²Technology Access Centre for Aerospace and Manufacturing, Red River College of Applied Arts, Science and Technology, Winnipeg, Manitoba, Canada

³Standard Aero Limited, Winnipeg, Manitoba, Canada

⁴Huys Limited, Toronto, Ontario, Canada

Cite this paper:
K.M. Oluwasegun, O.A Ojo, O.T Ola, A. Birur, J. Cuddy and K. Chan. Development of Artificial Neural Network Models for Predicting Weld Output Parameters in Advanced Fusion Welding of a Magnesium Alloy. American Journal of Modeling and Optimization. 2018; 6(1):18-34. doi: 10.12691/ajmo-6-1-2

Abstract

This paper describes the development of artificial neural network (ANN) models and multi-response optimization technique to predict and select the best welding parameters during Hybrid Laser Arc Welding (HLAW), Hot Wire Cladding (HWC) and Cold Metal Transfer (CMT) of ZE41-T5 alloy. To predict the performance characteristics, namely; weld depth, underfill, percentage defect and total accumulated pore length, artificial neural network models were developed using Levenberg-Marquardt algorithm. ZE41-T5 was selected as the material to be welded with AZ61 alloy as filler material. Experiments were planned using a 3-factor central composite design and were performed under different welding conditions of laser power, travel speed, wire feed rate, current and frequency. The responses were optimized concurrently using ANN Levenberg-Marquardt algorithm. Finally, experimental confirmations were carried out to identify the effectiveness of ANN. A good agreement was obtained between the experimental output data and ANN predicted results.

Keywords:
hybrid laser arc welding hot wire cladding cold metal transfer artificial neural network optimisation

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Figures

References:

[1]	Pollock TM. (2010). Science 328 (5981): 986-987.
[2]	Wise M, Calvin K, Thomson A, Clarke L, Bond-Lamberty B, Sands R, Smith SJ, Janetos A, Edmonds J. (2009). Science 324 (5931): 1183-1186.
[3]	Kump LR. (2002). Nature 419: 188-190.
[4]	Agnew WG. (1974). Science 183 (4122): 254-256.
[5]	Begum S, Chen DL, Xu S, Luo AA. (2009). International Journal of Fatigue 31 (4): 726-735.
[6]	Begum S, Chen DL, Xu S, Luo AA. (2009). Metallurgical and Materials Transaction A 40(1): 255-267.
[7]	Behler K, Berkmanns J, Ehrhardt A, Frohn W. (1997). Materials & Design 18(4-6): 261-267.
[8]	Schubert E, Klassen M, Zerner I J, Walz C, Sepold G. (2001). Journal of Materials Processing Technology 115 (1): 2-8.
[9]	Cao X, Jahazi M, Immarigeon JP, Wallace W J. (2006). Journal of Materials Processing Technology 171 (2): 188-204.
[10]	Weisheit A, Galun R, Mordike BL. (1998). Welding Journal 77 (4): 149-154.
[11]	Zhao H, DebRoy T. (2001). Welding Journal 80 (8): 204-210.
[12]	Sun Z, Pan D, Wei J. (2002). Science and Technology of Welding and Joining 7: 343-351.
[13]	Zhang J, Shan J G, Ren J.L, Wen P. (2013). Welding Journal 92 (8): 101-109.
[14]	Roepke C, Liu S, Kelly S, Martukanitz R. (2010). Welding Journal 89 (7): 140-149.
[15]	Sachez-Amaya JM, Boukha Z, Amaya-Vazquez MR, Botana FJ. (2012). Welding Journal 91 (5):155-161.
[16]	Victor B, Farson DF, Ream S Walters CT. (2011). Welding Journal 90 (6):113-120.
[17]	Matsunawa A, Kim JD, Seto N, Mizutani M, Katayama S J. (1998). Journal of Laser Applications 10 (6,): 247-254.
[18]	Tucker JD, Nolan TK, Martin AJ, Young GA. (2012). JOM 64 (12):1409-1417.
[19]	Madison J D, Aagesen L K. (2012). Scripta Materialia 67 (9). 783-786.
[20]	Salminen A, Phiili H, Purtonen, T. (2010). Journal of Mechanical Engineering Science 224(5): 1019-1029.
[21]	Harvilla D, Rominger V, Holzer M, Harrer T, Andrew A, Advanced Welding Techniques with Optimized Accessories for High Brightness 1µm Lasers,” in High-Power Laser Materials Processing: Lasers, Beam Delivery, Diagnostics, and Applications II, Proceedings of SPIE, (2013) 8603.
[22]	Ilar T, Eriksson I, Powell J, Kaplan A. (2012). Physics Procedia 39:27-32.
[23]	Blecher JJ, Palmer TA, Debroy T. (2015). Welding Journal 94 (3): 73-82.
[24]	Hu B, Richardson IM. (2006). Welding in the World 50 (7-8): 51-57.
[25]	Maamar H, Otmani RR, Fahssi T, Debbache N, Allou D. (2008). Hradec and Moravici-METAL, 5: 13-15.
[26]	Kim JS, Watanabe T, Yoshida Y. (1995). Journal of Material Science Letters 14 (22): 1624-1626.
[27]	Ola OT, Doern FE. (2014). Materials and Design 57: 51-59.
[28]	Matsunawa A, Kim JD Katayama S, Porosity formation in laser welding-mechanisms and suppression methods, International Congress on Applications of Lasers and Electro-Optics-ICALEO. (1997). Miami 73-82.
[29]	Shtrikman MM, Pinskiia AV, Filatovb AA, Koshkinb VV, Mezentsevab EA, Guk NV. (2011). Welding International 25 (6): 457-462.
[30]	Devletian JH, Wood WE. (1983). Welding Research Council Bulletin 290: 1-18.
[31]	Kou S, (2002). Welding metallurgy,” Second edition, New York, John Wiley & Sons, Inc.
[32]	Norris JT, Robino CV, Hirschfeld DA, Perricone MJ. (2011). Welding Journal 90:198-203.
[33]	Daugherty WJ, Cannell GR. (2003). Practical Failure Analysis 3 (4): 56-62.
[34]	Liu L M, Song G, Zhu M S. (2008). Metallurgical and Materials Transaction A, 39A: 1702-1711.
[35]	Qui X, Song G. (2010). Materials & Design 31 (1):605-609.
[36]	Shahi AS, Pandey S. (2006). Science and Technology of Welding and Joining 11 (6):634-640.
[37]	Lv S X, Tian X B, Wang H T, Yang S Q. (2007). Science and Technology of Welding and Joining 12 (5): 431-435.
[38]	Prasad V V S, Rao A S, Prakash U, Baligidad R G. (2002). Science and Technology of Welding and Joining 7 (2): 102-106.
[39]	Francis J. A. (2002). Science and Technology of Welding and Joining 7 (5): 331-338.
[40]	Tuseka J, Suban M J. (2003). Journal of Materials Processing Technology 133 (1-2): 207-213.
[41]	Cao X, Jahazi M, Xiao, Immarigeon JP. (2005). Materials and Manufacturing Processes 20, (6): 987-1004.
[42]	Pickin C, Young K. (2006). Science and Technology of Welding and Joining 11 (4): 1-3.
[43]	Agudo L, Jank N, Wagner J. (2008). Steel research International 79 (7): 530-535.
[44]	Pickin C, Williams S, Lunt M. (2011). Journal of Materials Processing Technology 211 (3):496-502.
[45]	Widen J, Bergmann JP, Frank H.J. (2006). Journal of Thermal Spray Technology 15 (4):779-784.
[46]	Ramanathan K, Periasamy VM, Natarajan U. (2008). Portgaliae Electrochimica Acta 26, (4): 361-368.
[47]	Subramaanian S, Periasamy VM, Pushpavanam M, Ramasamy K. (2009). Portgaliae Electrochimica Acta, 27 (1): 47-55.
[48]	Haykin S (1999). Neural Networks: A Comprehensive Foundation, 2nd Edition, Prentice Hall, New Jersey.
[49]	Reed RD. (1999). Neural Smithing, MIT Press, Cambridge, MA.
[50]	Hagan MT, Demuth HB, Beale MH. (1996). Neural Network Design, PWS Publishing Company, Boston, MA.