Experimentation and its Prediction of Process Parameters Effects on Elongation in Tensile Test of AISI 1008 Steel Using ANN Model

Tensile testing, also known as tension testing is a fundamental material technology test in which a sample is subjected to uniaxial tensile loading until failure. The results from the test are commonly used to select a material for different applications, for quality control, and to predict how a material will react under other types of forces. Properties directly measured using the tensile test are ultimate tensile strength, change in dimension along length and width. As a result of tensile test, properties like modulus of elasticity, Poisson's ratio, ultimate strength, yield strength and strain hardening properties can also be determined. In the present paper, experimental works of tensile testing to predict certain outputs have been carried out. Here, an attempt has been made to use Neuro solution for the artificial neural network (ANN) applying to tensile test to predict output parameter. The ANN was subsequently trained with experimental data. Testing of the ANN has been carried out using experimental data not used during training. The results showed that the outcomes of the calculation are in good agreement with the experimental data; this indicates that the developed neural network can be used as an alternative way for calculating the repetitive process parameters.