This work describes the application of neural networks in the modeling of hot rolling processes. This relatively new technique of Artificial Intelligence was conceived more than fifty years ago, but it only became really feasible with the arrival of low cost computer processing power. The first papers about its utilization in the hot rolling field were published about six years ago. Although the first results were promising, there is still some lack of confidence about its real performance under industrial conditions, which is preventing the exclusive use of this new tool in the modeling of hot rolling processes. However, neural networks are already being used, as a standard feature, in hybrid automation models for hot strip mills, where th...
This paper presents a mathematical model developed by means of an analytical function whose shape de...
In this paper, the problem of system identification for the lateral motion of a strip in hot finishi...
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Applications of neural networks in the rolling of steel are reviewed. The first papers on the topic ...
The paper presents a model based on neural networks which is able to predict the time required to pa...
In this study, an artificial neural network model is proposed to predict the flow stress variations ...
The mathematical modeling of the rolling process involves several parameters that may lead to non-li...
In the paper we describe the industrial process of hot rolling of steel. In cooperation with Arcelor...
The paper presents a model for predicting the roll wear in the hot rolling process. It includes all ...
The factors of influence involved in many metallurgical problems are featured by a non-linear relati...
Rolling is one of the most complicated processes in metal forming. Knowing the exact amount of basic...
A study was performed to develop new techniques for rolling mill setup and supervisory control. The ...
The paper deals with the application of neural network modelling to the real-time prediction of the ...
The rheological behaviour of mild steel subjected to hot forming was modelled through a parallel dis...
While processing polymetallic ores at the non-ferrous metallurgy problems arises connecting with the...
This paper presents a mathematical model developed by means of an analytical function whose shape de...
In this paper, the problem of system identification for the lateral motion of a strip in hot finishi...
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Applications of neural networks in the rolling of steel are reviewed. The first papers on the topic ...
The paper presents a model based on neural networks which is able to predict the time required to pa...
In this study, an artificial neural network model is proposed to predict the flow stress variations ...
The mathematical modeling of the rolling process involves several parameters that may lead to non-li...
In the paper we describe the industrial process of hot rolling of steel. In cooperation with Arcelor...
The paper presents a model for predicting the roll wear in the hot rolling process. It includes all ...
The factors of influence involved in many metallurgical problems are featured by a non-linear relati...
Rolling is one of the most complicated processes in metal forming. Knowing the exact amount of basic...
A study was performed to develop new techniques for rolling mill setup and supervisory control. The ...
The paper deals with the application of neural network modelling to the real-time prediction of the ...
The rheological behaviour of mild steel subjected to hot forming was modelled through a parallel dis...
While processing polymetallic ores at the non-ferrous metallurgy problems arises connecting with the...
This paper presents a mathematical model developed by means of an analytical function whose shape de...
In this paper, the problem of system identification for the lateral motion of a strip in hot finishi...
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...