Parameter Forecasting of Laser Welding on Strength, Deformation and Failure Load of Transformed Induced Plasticity (TRIP) Steel using Experimental and Machine Learning Approach

Abstract

The aim of the current research work is to study the effect of different mechanical parameters like laser power, laser velocity, and laser incident light over the mechanical strength of the laser welded steel material by artificial intelligence approach. The Knime software were used to establish algorithm model to predict the machining input parameters. The results very well matches with practical results ca. the strength of up to 95.14%, which is much more than the accepted results at the early stage of the experiments. Besides, our results also showed good strength with minimum deformation which is clearly seen in the mathematical presentation.