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In any welding process to
In any welding process, to achieve the desired properties, it is necessary to carry out the welding using optimised parameters. To obtain the optimised parameters, the scientific method is to use optimisation techniques. In the present work, Taguchi based grey relation analysis method has been used to optimise the parameters. Quite a good number of published literatures have proved the usability of optimisation techniques for both non-fusion and fusion welding including laser welding process of different materials. Ajith et al. [9] have used ANN to optimise friction welding of UNS S32205 duplex stainless steel and Magudeeswaran et al. [10] have optimised ATIG welding parameters using Taguchi followed by ANOVA and Pooled ANOVA to achieve the desired width to depth ratio to avoid hot cracking in the same material. Tamrin et al. [11] have optimised laser lap welding process using grey relational analysis for dissimilar welding of Quizartinib to glass based ceramics to arrive at the optimum joint characteristics like joint strength, etc. and found that welding speed has the maximum influence on the joint characteristics. Zhao et al. [12] optimised laser welding process for welding of thin gauge galvanised steel using response surface methodology (RSM) and they have found that welds made with optimised parameters had good bead geometry values. They could also find out that with optimisation, the process efficiency could be enhanced and the average aspect ratio could be increased from 0.62 to 0.83. Reisgen et al. [13] have optimised CW CO2 laser welding parameters like laser power, welding speed and focus position using RSM for welding of dissimilar thickness of Advanced High Strength Steels of DP 600 and TRIP steel to achieve good bead geometry parameters, mechanical properties and formability at a reduced cost of fabrication. Olabi et al. [14] have optimised laser welding parameters like laser power, welding speed and focal position using a combined approach with Artificial Neural Network (ANN) and Taguchi analysis to achieve optimal bead geometry values like the ratios of penetration to fusion zone width and penetration to HAZ width. They have arrived at an ANN model that will work for all the range of parameters experimented. Ruggiero et al. [15] have optimised CW CO2 laser welding parameters using RSM for welding of dissimilar joint involving AISI 316 austenitic stainless steel and low carbon steel to arrive at optimum bead geometry values and welding cost. They have also found welding speed to be the most influencing parameter and the welding cost was found to be greatly reduced based on their devised formula with the optimised parameters. E.M. Anawa and Olabi [16] have used Taguchi approach with ANOVA to arrive at the optimum set of laser welding parameters for achieving good mechanical properties tested by notched tensile specimen for a dissimilar combination of AISI 316 austenitic stainless steel to AISI 1008 low carbon steel. The mechanical properties of welded joints with optimum parameters were found to be better than the base material. They have found laser power to be the most influencing factor in determining the strength of such dissimilar joints. The authors have also optimised the parameters for obtaining good fusion zone properties for the same combination of materials and they have found that with respect to the fusion zone properties, welding speed had the greatest influence [17]. The optimisation technique was found to be a very useful tool even for welding of nonmetals like plastics. Kumar et al. [18] have optimised the laser transmission welding parameters like current, standoff distance and clamping for welding of plastics. Pan et al. [19] used Taguchi method to optimise pulsed Nd:YAG laser welding parameters for welding of AZ31B Magnesium alloy to achieve the maximum tensile strength. The optimisation could yield a parametric combination that could increase the tensile strength by 2.5× compared to the original value as set for laser welding. Benyounis et al. [20] analysed the effect of laser power, welding speed and focal position of the laser beam with respect to the workpiece surface using RSM for CW CO2 laser welding of medium carbon steel in butt joint configurations. They have concluded that the proposed model could accurately predict the responses like depth of penetration, weld width and HAZ width within the parametric range that have been experimented. All the reported works not only prove the usefulness of the optimisation techniques for optimising the laser welding process for different materials but also prove to be a scientific way to reduce the number of experiments to arrive at a parameter to achieve the desired weld quality.