Investigating the effect of tensile shear strength of resistance spot welding using a neuro fuzzy control system

Resistance spot welding (RSW) stands out as a widely adopted method, especially in the automotive sector, for joining thin sheets of various materials. This study focuses on optimizing RSW strength by controlling both dynamic and static parameters in which fuzzy logic-based model can forecast the RSW reaction to the tensile shear strength, and nugget size. The process factors for the RSW process include welding current, electrode force, steel thickness, welding time, and tensile shear strength. A fuzzy logic model that forecasts the impact of the input factors on the replies was built using the experimental data. As a result, the proposed model is significantly reducing the energy consumption to 5253.8 J, marking a substantial improvement over the reference study’s energy expenditure of 26,000 J and the tensile strength of the weld to 594 N, surpassing the reference study’s result 350 N.