Investigations on Mechanical Behaviour and Failure Mechanism of Resistance Spot-Welded DP590 Steel Using Artificial Neural Network

Abstract

Modelling of the spot weld responses, i.e. shear-tensile strength, coach-peel strength, mean dynamic contact resistance and nugget diameter, was carried out along with the optimization of weld process parameters, i.e. weld current, weld time and electrode force. The experiments for weld fabrication were designed using face-centred central composite design under response surface methodology. Experimental results acquired from the designed experiments were used to generate prediction models of the responses using the artificial neural network approach. Hybrid artificial neural network-genetic algorithm technique was used in order to obtain the optimized welding process parameters. Validation checks were done for the optimized parameters and responses in order to justify the adequacy of the models and optimized value. Failure mode analysis was done to determine the plasticity fraction and to relate this with the mode of failure and microhardness values. The shear-tensile strength, coach-peel strength and nugget diameter increase with the corresponding increase in the amount of heat input during the weld fabrication. The optimum process parameters are 8.98 kA of weld current, 284.92 ms of weld time and 3.04 kN of electrode force leading to the response values as shear-tensile strength of 21.93 kN.