ABSTRACT

The laser cladding technique is useful for enhancing the surface performance and extending the life of many components in severe wear and corrosive environments. The aim of the present study is to develop a model relating independent variables, laser power (2200–2800 W), powder-feed rate (30–50 g/min), laser-scanning speed (800–1200 mm/min) and the focal position of the laser beam (15–35 mm), with the dependent variable, Vickers hardness number, and optimize the process parameters to achieve maximum hardness in CO2 laser cladding of Inconel 625 powder on AISI 304 SS substrate. The models were developed using curve fitting and artificial neural network (ANN) models by fitting the experimental data and comparing the predicted values from the models with the experimental values. The model developed by curve fitting method was employed to optimize the hardness using first derivative test, generalized reduced gradient (GRG) and grey-relational analysis (GRA). The maximum hardness of 374 was achieved by first derivative test at optimal laser power, powder-feed rate, laser-scanning speed, and the focal position of the laser beam of 2554 W, 999 mm/min, 30 mm and 40.5 g/min, respectively.