• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.7 s.166
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• pp.1196-1204
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• 1999

adaption of the model predictions is highly desirable. In general, the width deviation at the head and tail ends of strip may be different from that of the steady state region. Therefore, the dynamic edger corrections can be used to compensate the width deviations which would otherwise occur. For the precise width control, the effect of edger roll gap and rolling conditions on the width deviation of head and tail ends of strip has been investigated and the effective method to decrease width deviation has been proposed. On-line application of dynamic edger control method in this study shows about 50% width compensation at the head end of the strip, and near perfect compensation at the tail end of strip.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.544-548
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• 2007

In general, final width of hot strip should be accomplished in this stage because width reduction of strip hardly appears during typical finishing mill. However, it is difficult to control the width of strip in the roughing mill process as the horizontal rolling of strip is subsequently performed after the vertical rolling. It is therefore important to obtain the deformation rolling direction on strip width to minimize the width spread of strip during horizontal rolling after vertical rolling. Generally there is Sizing press type and Edger-roll type. The width reduction process in sizing press has small amount of width spread compared with the edger. However, productivity by the sizing press process is much lower than those of the edger. In this study, sizing press and Edger-roll process parameters in a sheet rolling mill were set at specified values and the effect of the change in these parameters on product quality and process performance were evaluated.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.438-446
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• 1999

Crop minimization of the top and bottom ends of hot rolled plate, in a plate, in a plate mill, has been investigated. The existing model to determine the edging pattern at the finishing rolling pass was not reasonable to get high width accuracy and rolling yields. New models including width prediction have been formulated by using neural network model of back propagation learning algorithm and statistical analysis based on the actual production rolling data to give the optimal pattern for minimizing trimming loss. Using these models, at a given rolling condition of broadside pass and finishing pass and the permissible condition of width variation, it was possible to minimize crip at the top and bottom ends according to optimum procedure in plate mill. An application to improve the plan view pattern reduced width variation by 23% and crop length by 30% on average with an effective fishtail crop shape.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.991-997
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• 2013

In this paper, we propose a CFWC (CCD and fuzzy PID based width control) scheme to obtain the desired delivery width margin of a vertical rolling mill in hot strip process. A WMS(width measurement system) is composed of two line scan cameras, an edge detection algorithm, a glitch filter, and so on. A dynamic model of the mill is derived from a gauge meter equation in order to design the fuzzy PID controller. The controller is a self-learning structure to select the PID gains from the error and error rate of the width margin. The effectiveness of the proposed CFWC is verified from simulation results under a width disturbance of the entry in the mill. Using a field test, we show that the performance of the width control is improved by the proposed control scheme.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.429-437
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• 1999

Width variation of the top and bottom ends of steel at finishing rolling in a plate, has been investigated. It was found that width variation after finishing rolling is affected by edging, broadside rolling ratio, longitudinal rolling ratio, width shape after broadside rolling, temperature, width-to-thickness ratio, and so on. A neural network modelling of back propagation has been conducted on the width variation during rolling. Based on these prediction models, a width control system, by which the roll opening and closing of the hydraulic AWC edger can be adjusted during edge rolling in finishing rolling passes, has been developed. Compared to conventional width model, the neural network model is much accurate in a model. The width control system is applied to a newly built production mill.

• Transactions of Materials Processing
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• v.8 no.2
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• pp.200-207
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• 1999

To increase dimensional accuracy of strip width, model to compensate width spread during roughing mill has been developed. To measure the amount of width spread during the production rolling more precisely, special roughing rolling procedures for the horizontal rolling and dog-bone rolling were designed in the actual production mill. From the operational data analysis, it is known that the prime factors influencing on the width spread were strip width, strip thickness, edging amount, number of pass and type of edger roll etc., Based upon the statistical analysis of rolling data, new models which can predict width spread during horizontal rolling and dog-bone rolling were developed and tested on the actual processing conditions for the reliability. The application test showed that newly developed model gave fairly accurate predictions on the width spread during roughing passes.

• Transactions of Materials Processing
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• v.21 no.1
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• pp.24-29
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• 2012

Precision control of the width of slabs is vital for product quality and production economy in steel rolling mills. However, the formation of so called 'dog-bone' at the edge of the slab would affect the final width during the horizontal rolling that follows. Therefore, it is essential to predict and control the dog-bone shape. In this paper, a model is derived by using a number of finite element simulations for edge rolling and a least square regression analysis. The prediction accuracy of the proposed model is examined by comparing the predictions from finite element simulation with experiment results in the literature.