Optimization of GMAW Process Parameters in Austenitic Stainless Steel Cladding Using Genetic Algorithm Based Computational Models

Weld cladding is a process of depositing a thick layer of anticorrosive metal on a corrosive substrate surface to impart better corrosion resistance properties. In weld cladding process, the difficulty generally encountered will be the problem of selecting optimum combination of input process parameters to achieve the desired dilution level. Until recently trial and error methods were employed to determine the optimum process parameters, which result in wastage of cost and time. This paper focuses on optimization of GMAW process parameters, which are used for deposition of austenitic stainless steel on low carbon structural steel plates. Experiments were conducted based on four-factor five-level central composite rotatable design with full replication technique. Mathematical models relating to gas metal arc welding process parameters to clad bead geometry were developed using multiple regression method. Developed mathematical models are helpful in predicting the clad bead geometry and in setting process parameters at optimum values to accomplish the desirable dilution level at relatively low cost with a high degree of reproducibility. The accuracy of the results was tested by conducting conformity tests using the same experimental set up. Moreover, Genetic Algorithm tool with GUI available in MATLAB 7.0 was used to optimize the process parameters to achieve optimum dilution.