Experimental and numerical investigation of formability for austenitic stainless steel 316 at elevated temperatures

Abstract

Sheet metal forming at elevated temperature is not much used in industries but it is going to be a very important process in the future. The present work is aimed to investigate the formability of austenitic stainless steel 316 at elevated temperatures. Limiting drawing ratio and thickness of the drawn cup are the indicators of formability in deep drawing. In the present investigation circular blanks are deep drawn at room temperature, 150 °C and 300 °C using a 20 ton hydraulic press coupled with a furnace. Finite element simulations are carried out using Dynaform with LS-Dyna solver. Simulations and experimental results show an increase in the limiting drawing ration as the temperature increases and a decrease in the thickness of the drawn cup without any fracture. An artificial neural network model is developed for the prediction of the cup thickness at different locations. Based on the input variables, such as distance from the center of the cup, temperature and LDR, a back propagation neural network model to predict the thickness as output was develop. The comparison between these sets of results indicates the reliability of the predictions. It was found that there is a good agreement between the experimental and predicted values.

Keywords

• Deep drawing
• Limiting drawing ratio
• Formability
• Finite element
• Neural network