• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.229-232
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them..

• Transactions of Materials Processing
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• v.16 no.4 s.94
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• pp.250-253
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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• pp.59-67
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• 2013

This paper presents a neural net type process model for enhancing learning compensation function in hot strip finishing rolling mill. Adequate input and output variables of process model are chosen, the proposed model was designed as single layer neural net. Equivalent carbon content, strip thickness and rolling speed are suggested as input variables, and looper's manipulation variable is proposed as output variable. According to simulation result using process data to show the validity of the proposed process model, neural net type process model's outputs give almost similar data to process output under same input conditions.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.155-156
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• 2007

This paper presents the vision-based camber and optimal cutting line detection algorithm for hot-rolling process. It is important to measure the camber of head and tail part of strips because many problems are caused by the camber in the hot-rolling process. The hot-rolling process has time constraints. The camber detection algorithm of head and tail parts requires fast and less complex for satisfying time constraints. The proposed algorithm consists of two parts: measurement of the camber in the head and tail part of strips and decision part of the optimal cutting line of hot-rolled strip. First, we obtain the camber value of the strip from the difference between the real center line and the center line of head, tail part. Second, the head and tail part of strips isn't suitable for strips connections. Therefore, the cutting process is needed in the hot-rolling process. The optimal cutting line is determined by the head and tail images obtained from cameras. The algorithm is applied into the vision system with two area cameras, Matrox image processing board and host PC for verification.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.56-59
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• 1988

The main purpose of Set-up control of hot strip mill plant is to obtain the most regular thickness. Then the learning or adaptive computer control in hot strip rolling mill has been developed. But it is very difficult to keep the inter-stands load distribution ratio uniform; so that the deviation of strip flatness is not avoidable. This leads to the degradation of quality of the products. In this report, an improved method base on the steepest descent method including the computation of optimum step size. This method is applied to the off-line simulation. In consequence, the better balances of inter-stands load distribution is achieved in addition to improvements of output thickness of hot strip mill in POSCO.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1597-1603
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• 1995

A prediction model on forward slip has been developed for presetting rolling speed of each finish mill stand in the continuous hot strip roduction. Those factors such as neutral point, friction coefficient, volume fractions undergoing width spread, shape of deformation zone at each side of entry and delivery of the rolls were taken into account. To reduce the speed unbalance between adjacent stands a refining method of adjusting friction coefficient has also been developed. On-line application of the model showed a good agreement in rolling speeds between the predictions and the actual measurements, and gave an outstanding improvement in the travelling stability of strip passing through the finishing mill train.

• Transactions of Materials Processing
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• v.18 no.5
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• pp.377-384
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• 2009

The shape of edge cracking in rolling process generally occurred "V" shape. This cracking is successively generated at width edge of strip. The edge cracking is developed to center of strip during rolling process. In the results, the strip is occurred fracture, and the productivity is gone down because of the extensive production time. Accordingly, we need to control crack propagation during rolling process. But, the control of cracking is very difficult in rolling process. Previously the studies of edge cracking were mainly performed on hot rolling process. In this paper, the shape of the edge cracking in rolling was estimated according to process conditions such as initial edge crack size, reduction ratio and tension using FE-simulation and the simplicity experiments on cold rolling process.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.04a
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• pp.97-102
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• 2009

In hot strip rolling, sound prediction of the temperature of the strip is vital for achieving the desired finishing mill draft temperature (FDT). In this paper, a precision on-line model for the prediction of temperature distributions along the thickness of the strip in the finishing mill is presented. The model consists of an analytic model for the prediction of temperature distributions in the inter-stand zone, and a semi-analytic model for the prediction of temperature distributions in the bite zone in which thermal boundary conditions as well as heat generation due to deformation are predicted by finite element-based, approximate models. The prediction accuracy of the proposed model is examined through comparison with predictions from a finite element process model.

• Transactions of Materials Processing
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• v.14 no.9 s.81
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• pp.791-797
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• 2005

Extensive width reduction of slabs is an important technology for achieving continuous production between the steelmaking and hot rolling processes. However, the vertical horizontal rolling process has many disadvantages, e.g., large width deviations and less efficient width reduction. This study was carried out to investigate the deformation of slab by sizing press with two steps die. To do it, dog-bone and camber are discussed in width sizing process considering the deformation behavior according to the deviation of anvil velocity and the deviation of initial slab temperature. In this paper, the various causes of the sizing press phenomena are mentioned for the purpose of understanding of rolling conditions. As a result, the optimal anvil shape having a minimum-forming load is obtained by FE-simulation and ANN.