Current trends in the progress of technology demand availability of materials resources
ahead of the advancing fronts of the application areas. During the last couple of decades …

Neural networks have pervaded all aspects of materials science resulting in the discovery of
new phenomena and have been used in quantitative design and control. At the same time …

In the hot-rolling metal forming process, the consistency and accuracy of the thickness of the
metal strip are the most important factors for the product quality control. The current method …

An artificial neural network (ANN) optimized by genetic algorithm (GA) is an established
prediction model of bending force in hot strip rolling. The data are collected from factory of …

This paper introduces an artificial neural network (ANN) application to a hot strip mill to
improve the model's prediction ability for rolling force and rolling torque, as a function of …

The problems of the strip flatness defects are always severe in the tandem cold rolling
process. It is of great significance to predict flatness for flatness control according to the …

In the present investigation, a hot rolling process of AA5083 aluminum alloy is simulated
using the finite element method. The temperature distribution in the roll and the slab, the …

The accurate prediction of strip crown is the precondition of the shape preset model in hot
strip rolling. In this study, a new hybrid strip crown forecasting model is proposed in …

Steel manufacturers are under pressure to improve their productivity and to optimize their
process parameters to maximum efficiency and quality. Indeed, one of the keys to achieve …

This study introduces a non-destructive method by applying convolutional neural networks
(CNN) to predict the micro-hardness of the thread-rolled steel. Material microstructure …