Modeling and Optimization of Rubber to Steel Adhesion on the basis of Experimental Data using Combined RSM/ANN Approach

A combined RSM/ANN approach was employed to study effects of different formulation agents on rubber to steel cord adhesion in a steel belt tire formulation. Feed forward artificial neural network with high accuracy was successfully developed on the basis of experimental data collected according to the Box Behnken designs and guidelines of response surface models.