The use of Taguchi and approximation methods to optimize the laser hybrid welding of a 5052-H32 aluminium alloy plate

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Volumn 222, Issue 4, 2008, Pages 507-518

  Song, C Y ^a   Park, Y W ^a   Kim, H R ^b   Lee, K Y ^a   Lee, J ^a  

^a Yonsei University   (South Korea)

^b Hyundai Heavy Industries   (South Korea)

Author keywords

5052 H32 aluminium alloy; Approximation models; Laser hybrid welding; Taguchi method; Welding parameters

Indexed keywords

ALLOYS; ALUMINUM; ALUMINUM ALLOYS; ALUMINUM CLADDING; DENSITY (OPTICAL); DIFFRACTIVE OPTICAL ELEMENTS; FEEDFORWARD NEURAL NETWORKS; LASER BEAM WELDING; LASERS; LIGHT METALS; NEURAL NETWORKS; OPTICAL PROPERTIES; PARAMETER ESTIMATION; POLYNOMIAL APPROXIMATION; RADIAL BASIS FUNCTION NETWORKS; STRESSES; TAGUCHI METHODS; THERMOANALYSIS; WELDING;

5052-H32 ALUMINIUM ALLOY; ALUMINIUM ALLOYS; APPROXIMATION METHODS; APPROXIMATION MODELS; HYBRID WELDING; LASER HYBRID WELDING; MECHANICAL RESPONSES; NON-LINEAR; OPTIMAL WELDING; PARAMETER DESIGNS; PARAMETER VARIATIONS; PHYSICAL PHENOMENON; RADIAL BASIS FUNCTION NEURAL NETWORK; RESPONSE SURFACE METHOD; TAGUCHI; TAGUCHI METHOD; TRANSIENT THERMAL ANALYSIS; WELDING CONDITIONS; WELDING PARAMETERS; WELDING PROCESSES;

DESIGN OF EXPERIMENTS;

EID: 45949099624     PISSN: 09544054     EISSN: None     Source Type: Journal    
DOI: 10.1243/09544054JEM946     Document Type: Article

References (23)

1. Bagger, C. and Olsen, F. O. Review of laser hybrid welding. J Laser Applic., 2005, 17(1), 2-14.
2. Hu, B. and den Ouden, G. Synergetic effects of hybrid laser/arc welding. Sci. Technol. Weld. and Joining, 2005, 10(4), 427-431.
3. Moore, P. L., Howse, D. S., and Wallach, E. R. Micro-structures and properties of laser/arc hybrid welds and autogenous laser welds in pipeline steels. Sci. Technol. Weld. and Joining, 2004, 9(4), 314-322.
4. Graf, T. and Staufer, H. Laser-hybrid welding drives VW improvements. Weld. J., 2003, 82, 42-28.
5. Rayes, M. E., Walz, C., and Sepold, G. The influence of various hybrid welding parameters on bead geometry. Weld. J., 2004, 147-153.
6. Lingdren, L. E. Finite element modeling and simulation of welding, part 3: efficiency and integration. J. Thermal Stresses, 2001, 305-334.
7. Zhu, X. K. and Chao, Y. J. Effects of temperature-dependent material properties on welding simulation. Comput. Structs, 2002, 967-976.
8. Rosala, G. F., Day, A. J., and Wood, A. S. A finite element model of electrofusion welding of thermoplastic pipes. Proc. Instn Mech. Engrs, Part E: J. Process Mechanical Engineering, 1997, 211, 137-146.
9. Siddique, M. and Abid, M. Finite element simulation of mechanical stress relieving in welded pipe-flange joint. Proc. IMechE, Part E: J. Process Mechanical Engineering, 2006, 220, 17-30.
10. Chakravarti, A., Malik, L. M., and Goldak, J. Prediction of distortion and residual stresses in panel welds. Symposium on Computer modeling of fabrication processes and constitutive behavior of metals, Ottawa, Ontario, 1986, pp. 547-561 (Canadian Government Publishing Centre, Ottawa, Ontario).
11. Fujii, S., Takahashi, N., Sakai, S., Nakabayashi, T., and Muro, M. Development of 2D simulation model for laser welding. SPIE Proc., 2000, 3888, 218-228.
12. Frewin, M. R. and Scott, D. A. Finite element model of pulsed laser welding. Weld. J., 1999, 78, 15-22.
13. Carmlgnanl, C., Mares, R., and Toselli, G. Transient finite element analysis of deep penetration laser welding process in a single pass butt-welded thick steel plate. Comput. Methods Appl. Mechanics Engng, 1999, 197-214.
14. Canas, J., Picon, R., Paris, F., Blazquez, A., and Marin, J. C. A simplified numerical analysis of residual stresses in aluminum welded plates. Comput. Structs, 1996, 9-69.
15. Taguchi, G. and Wu, Y. T. Introduction to off-line quality control, 1980, pp. 49-67 (Central Japan Quality Control Association, Nagoya, Japan).
16. Andrews, J. D. and Bartlett, L. M. Using statistically designed experiments for safety system optimization. Proc. Instn Mech. Engrs, Part E: J. Process Mechanical Engineering, 2004, 218, 53-63.
17. Goldak, J., Chakravarti, A., and Bobby, M. A new element model for welding heat source. Metallurg. Trans. B, 1984, 15, 299-305.
18. Nguyen, N. T., Mal, Y. W., Simpson, S., and Ohta, A. Analytical approximate solution for double ellipsoidal heat source in finite thick plate. Weld. J., 1997, 83, 412-416.
19. Myers, R. H. and Montgomery, D. C. Response surface methodology: process and product optimization using designed experiments, 1995, Wiley Series in Probability and Statistics (Wiley, New York).
20. Steele, N. C., Reeves, C. R., Nicolas, M., and King, P. J. Radial basis function artificial neural networks for the inference process in fuzzy logic based control. Computing, 1995, 99-117.
21. Broomhead, D. S. and Lowe, D. Multivariable functional interpolation and adaptive networks. Complex System, 1988, 2, 321-355.
22. Gomm, J. B., Weerasinghe, M., and Williams, D. Diagnosis of process faults with neural networks and principal component analysis. Proc. Instn Mech. Engrs, Part E: J. Process Mechanical Engineering, 2000, 214, 131-143.
23. Fraser, A. W., Martin, E. B., and Morris, A. J. Neural network modelling and prediction in multipass steel processing. Proc. Instn Mech. Engrs, Part E: J. Process Mechanical Engineering, 2004, 218, 121-132.