Modeling and optimization of MAG welding for gas pipelines using regression analysis and simulated annealing algorithm

This study established input-output relationships for metal active gas (MAG) welding for gas pipelines. Regression analysis (RA) was performed on data collected as per Taguchi design of experiments. Adequacy of RA model was verified using ANOVA method. RA model was then embedded into a simulated annealing (SA) algorithm to determine optimal process parameters for weld bead geometry specification. Proposed method is found quite effective in predicting process parameters for weld bead geometry.

[1]  V. Balasubramanian,et al.  Optimization of process parameters for friction stir welding of cast aluminium alloy A319 by Taguchi method , 2009 .

[2]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[3]  I. S. Kim,et al.  An investigation of a mathematical model for predicting weld bead geometry , 1996 .

[4]  H. P. Seow,et al.  Effect of increasing deposition rate on the bead geometry of submerged arc welds , 1997 .

[5]  Ill-Soo Kim,et al.  Sensitivity analysis for process parameters influencing weld quality in robotic GMA welding process , 2003 .

[6]  Farhad Kolahan,et al.  Simultaneous job scheduling and tool replacement based on tool reliability by proposed Tabu-SA algorithm , 2009 .

[7]  Y. S Tarng,et al.  Modeling, optimization and classification of weld quality in tungsten inert gas welding , 1999 .

[8]  Young-Soo Yang,et al.  Sensitivity analysis for process parameters in GMA welding processes using a factorial design method , 2003 .

[9]  Davi Sampaio Correia,et al.  Comparison between genetic algorithms and response surface methodology in GMAW welding optimization , 2005 .

[10]  Chia-Ming Chang,et al.  The use of grey-based Taguchi methods to determine submerged arc welding process parameters in hardfacing , 2002 .

[11]  Y. S. Tarng,et al.  The Use of Fuzzy Logic in the Taguchi Method for the Optimisation of the Submerged Arc Welding Process , 2000 .

[12]  Emile H. L. Aarts,et al.  Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[13]  S. Rhee,et al.  Determination of optimal welding conditions with a controlled random search procedure , 2005 .

[14]  P. Venkataraman,et al.  Applied Optimization with MATLAB Programming , 2001 .

[15]  J. Tušek,et al.  Algorithmic optimisation of parameters in tungsten inert gas welding of stainless steel sheet , 2001 .