Multi-objective multi-parameter optimization of the industrial LBW process using a new optimization algorithm

The concept of automation has been brought into the industries in order to increase the production rate and at the same time to minimize the production cost. The LBW process is widely replacing manual welding processes in many fabrication industries owing to the high level of automation. In the present work, an attempt is made to achieve conflicting objectives by finding optimum parameter settings for the LBW process. A recently developed advanced optimization algorithm is applied for parameter optimization of the LBW process. Two different multi-objective optimization examples are considered and significant improvement is obtained by the proposed optimization algorithm as compared with the earlier works.

[1]  V. Balasubramanian,et al.  Optimization of laser beam welding process parameters to attain maximum tensile strength in AZ31B magnesium alloy , 2010 .

[2]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[3]  G. Casalino,et al.  An ANN and Taguchi algorithms integrated approach to the optimization of CO2 laser welding , 2006, Adv. Eng. Softw..

[4]  R. Venkata Rao,et al.  Advanced Modeling and Optimization of Manufacturing Processes: International Research and Development , 2013 .

[5]  G. Casalino.  Statistical analysis of MIG-laser CO2 hybrid welding of Al–Mg alloy , 2007 .

[6]  Sudipto Chaki,et al.  Estimation and optimization of depth of penetration in hybrid CO2 LASER-MIG welding using ANN-optimization hybrid model , 2010 .

[7]  Pietro Mario Lugarà,et al.  Comparison of two different nozzles for laser beam welding of AA5083 aluminium alloy , 2005 .

[8]  Abdel-Monem El-Batahgy,et al.  Effect of laser welding parameters on fusion zone shape and solidification structure of austenitic stainless steels , 1997 .

[9]  Olcay Ersel Canyurt,et al.  Estimation of laser hybrid welded joint strength by using genetic algorithm approach , 2008 .

[10]  M. Hashmi,et al.  Effect of laser welding parameters on the heat input and weld-bead profile , 2005 .

[11]  K. Y. Benyounis,et al.  Multi-response optimization of CO2 laser-welding process of austenitic stainless steel , 2008 .

[12]  Paulraj Sathiya,et al.  Optimization of laser butt welding parameters with multiple performance characteristics , 2011 .

[13]  R. Venkata Rao,et al.  Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems , 2012, Inf. Sci..

[14]  E. Anawa,et al.  Using Taguchi method to optimize welding pool of dissimilar laser-welded components , 2008 .

[15]  Young Whan Park,et al.  Process modeling and parameter optimization using neural network and genetic algorithms for aluminum laser welding automation , 2008 .