TIG welding with single-component fluxes

The objective of this paper is to present an integrated approach using the Taguchi method (TM), grey relational analysis (GRA) and a neural network (NN) to optimize the weld bead geometry in a novel gas metal arc (GMA) welding process. The TM is first used to construct a database for the NN. The GRA is adopted to solve the problem of multiple performance characteristics in a GMA welding process using activating flux. The grey relational grade obtained from the GRA is used as the output of the back-propagation (BP) NN. Then, a NN with the Levenberg-Marquardt BP (LMBP) algorithm is used to provide the nonlinear relationship between welding parameters and grey relational grade of each weldment. The optimal parameters of the novel GMA welding process were determined by simulating parameters using a well-trained BPNN model. Experimental results illustrate the proposed approach.

The use of the Taguchi method with grey relational analysis and a neural network to optimize a novel GMA welding process

Effect of activating flux on arc shape and arc voltage in tungsten inert gas welding

Tungsten inert gas (TIG) welding process is generally used to produce high quality weld joints of 9Cr-1Mo steel. However, there is limitation associated with the depth of penetration achievable in single pass autogenous welding. Specific activated flux has been developed in the present work to enhance the depth of penetration up to 6 mm in single pass by A-TIG welding. 9Cr-1Mo steel A-TIG weld joint using activated flux was made in single pass welding while the multipass TIG weld joint using modified 9Cr-1Mo filler wire was made in seven passes. The enhancement in depth of penetration during A-TIG welding process for this steel was attributed to arc constriction. The strength properties of the A-TIG weld joint was superior to that of the multipass TIG weld joint. The multipass TIG weld joint exhibited slightly improved impact toughness than the A-TIG weld joint in PWHT condition. Therefore, there was no degradation in the microstructure and mechanical properties of the weld joint produced by A-TIG welding...

Effect of Activated Flux on the Microstructure and Mechanical Properties of 9Cr-1Mo Steel Weld Joint

Optimization of A-TIG welding process parameters for 9Cr-1Mo steel has been carried out using response surface methodology (RSM) and genetic algorithm (GA). RSM has been used to obtain the design matrix for generating data on the influence of process parameters on the response variables. A second-order response surface model was developed for predicting the response for the set of given input variables. Then, numerical and graphical optimization was performed using RSM to obtain the target depth of penetration (DOP) and heat-affected zone (HAZ) width using desirability approach. Multiple regression models were developed based on the generated data, and then the models were used in GA to determine the optimum process parameters for achieving the target DOP and HAZ width. GA-based models employed two different selection processes. Both the RSM- and GA-based models suggested a number of solutions in terms of process parameters, and the identified solutions were validated by experiments. GA-based model employ...

I. Perryman

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