Prediction of flow stress in isothermal compression of Ti60 alloy using an adaptive network-based fuzzy inference system

Isothermal compression of Ti60 titanium alloy at the deformation temperatures ranging from 960 to 1110 °C, the strain rates ranging from 0.001 to 10 s−1 and the height reductions of 60% were carried out on a Gleeble–3800 simulator. An adaptive network-based fuzzy inference system (ANFIS) model has been established to predict the flow stress of Ti60 alloy during hot deformation process. A comparative evaluation of the predicted and the experimental results has shown that the ANFIS model used to predict the flow stress of Ti60 titanium alloy has a high accuracy. The maximum difference and the average difference between the predicted and the experimental flow stress are 13.83% and 5.15%, respectively. The comparison between the predicted results based on the ANFIS model for flow stress and those using the regression method has illustrated that the ANFIS model is more efficient in predicting the flow stress of Ti60 alloy.

► An ANFIS model was established to predict the flow stress of Ti60 alloy during hot deformation process.
► Flow stress of Ti60 alloy decreases with increasing temperature and decreasing strain rate.
► The ANFIS model predicted more accurately than regression method.