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In this paper, an advanced temperature control for the high carbon steel is proposed to obtain the desirable temperature and property of a steel on the run-out table (ROT) process. The temperature model based on the nonlinear heat transfer equation is described to predict the temperature of the steel at each position of the ROT. A cooling stop temperature (CST) concept is proposed to increase the volume fraction of the transformed phase for the high carbon steel. The concept is derived from a time-temperature transformation (TTT) diagram which is measured from the dilatometric experiment. The simulator using the temperature model is developed to achieve the desired temperature, and the effectiveness of the proposed control is also analyzed from the simulation. It is shown through the field test of the hot strip mill of POSCO that the performance with respect to the temperature and the property of the steel is greatly improved by the proposed control technology.

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In this paper, a width control system is proposed to obtain the desirable width margin of a strip in the rolling process of the hot strip mill. A simplified FEM (Finite Element Method) based width prediction model (WPM) is developed to compute the width spread at each stand. A neural network based error correction model (ECM) is also introduced to compensate for modelling errors from the simplified FEM based WPM. Input variables for the neural network model are chosen by using the hypothesis testing. In addition, the width control scheme using the simplified FEM based WPM and the neural network based ECM is proposed to achieve the desired width margin in the finishing mill. It is shown through the field test of the Pohang no. 1 hot strip mill of POSCO that the performance with respect to the width margin is greatly improved by the proposed width control scheme based on two models.

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