Application of Electrical Driving to Existing Rolling Mills

A Chance–constrained Robust Mpc and Application to Hot Rolling Mills

Most approaches of chance–constrained robust MPC utilise an open– loop model for uncertainty prediction; this results in conservative control. To avoid this some approaches propose robust MPC (RMPC) based on closed–loop prediction, and these often give improved dynamic performance at a small expense to constraint handling performance. The aim of this paper is to extend the methodology of (Warre...

Bayes for Rolling Mills: from Parameter Estimation to Decision Support

The paper shares experience gained in application of dynamic Bayesian approach to control problems in the field of metal rolling. The contribution introduces basic notions of theory applied and provides the algorithmic as well as application-oriented solutions developed. Specifically, the consistent use of the approach resulted in an advanced decision support system for operators of a reversing...

Reeling Mechanism for Wire Rod Rolling Mills

assessment of indoor airborne pollutants of beam rolling mills factory

air pollutants from iron and steel making operations have historically been an environmental concern. the factory located at ahwaz, iran, has two production lines namely, 630 and 650, which produce iron parallel edge. the objective of the study is to determine indoor respiratory particulate matter (rpm) and feo concentrations and their comparison with niosh standards. this is a cross–sectiona...

Neural Network Control for Rolling Mills

Worldwide, steel and aluminum production and manufacturing is still one of the major basic industries with a huge amount of material and energy consumption. Hence, optimization of the various process control schemes which are involved can lead to signiicant savings. Artiicial Neural Networks are a new information processing technique which provides a novel approach to process control problems a...