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Optimising process parameters for gas tungsten arc welding of an austenitic stainless steel using genetic algorithm

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Abstract

Automated Gas Tungsten Arc Welding (GTAW) with filler wire addition using a wire feeder is a candidate process for welding of 316LN austenitic stainless steel, which is the major structural material for the Indian 500 MWe Fast Breeder Reactors. In GTAW, the quality of the weld is characterized by the weld-bead geometry as it influences the mechanical properties and its performance during service. This paper discusses the development of computational model using genetic algorithm for determining the optimum/near-optimum GTAW process parameters for obtaining the target weld-bead profile during automatic welding of 316LN stainless steel. Using the experimental data generated on the influence of process variables on weld-bead geometry, regression models correlating the weld-bead shape parameters with the process parameters were developed for determining the objective function in genetic algorithm. Close agreement was achieved between the target weld-bead profile and the model-computed weld-bead profile. This study has shown that use of genetic algorithm is an appropriate methodology for optimising process parameters to obtain target weld-bead profile in GTAW with wire feeder of 316LN stainless steel.

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Authors and Affiliations

  1. Indira Gandhi Centre for Atomic Research, Kalpakkam, 603 102, Tamilnadu, India

    M. Vasudevan, M. V. Kuppuswamy & A. K. Bhaduri

Authors
  1. M. Vasudevan
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  2. M. V. Kuppuswamy
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  3. A. K. Bhaduri
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Correspondence to M. Vasudevan.

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Vasudevan, M., Kuppuswamy, M.V. & Bhaduri, A.K. Optimising process parameters for gas tungsten arc welding of an austenitic stainless steel using genetic algorithm. Trans Indian Inst Met 63, 1–10 (2010). https://doi.org/10.1007/s12666-010-0001-5

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  • DOI: https://doi.org/10.1007/s12666-010-0001-5

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