• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.125-128
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• 2001

A finite element-based, integrated process model is presented for coupled analysis of the thermal and metallurgical behavior of the strip occurring on the run-out-table in hot strip rolling. The validity of the proposed model is examined through comparison with measurements. The models capability of revealing the effect of cooling pattern on strip temperatures and the optimal cooling pattern are demonstrated through a series of process simulation. In order to improve strip shape and control temperature history of thickness direction for strip during ROT cooling.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.869-874
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• 2015

We developed an LSDC (Load Shift and Load Distribution Control) technology in order to improve coil quality and productivity by reducing tension fluctuation especially for the tail of the strip in the down coiler in hot strip mills. To adapt the new controller, the torque and speed distribution between the zero pinch roll, pinch roll, and mandrel are needed. The proposed controller is a combination of an LSC to share the tension between the mill stand and the mandrel, and an LDC to shift the torque load from the zero pinch roll to the pinch roll. From the simulation, the proposed controller is verified under the torque disturbance. Using a field test, the torque deviation decreased by nearly 50% through utilization of the LSDC control.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.184-187
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• 2003

The simulation program is developed to get the target strip crown of high strength steel in the continuous hot strip rolling. The developed program consists of several sub-program, which contains work roll shifting pattern, roll wear profile, roll thermal expanded profile and strip profile. Also, the variation of strip profile is investigated according to roll deflection and flattening. The results are compared with the values observed from the actual hot rolling of high strength steel. And effect of bender force on the strip profile is studied. The strip crown is shown to decrease with increasing bender force.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.176-179
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• 2003

The mean temperature prediction of strip is very important in hot strip finishing mill because of affecting on product quality and shape. Also, temperature can be used by basic information in other on-line control models with affecting control accuracy in factory. So, FE based on-line temperature model was developed for predicting strip mean temperature accurately in various process conditions and factory environments. There are many variables in affecting strip mean temperature in on-line states of factory. But some problems are occurred in considering all variables for making temperature model because of the bad efficiency of regression or fitting analysis. In this report, we have adopted dimensional analysis for solving these problems. We have many variables with dimensions affecting strip temperature but we are able to make non-dimensional variables less than dimensional variables from the combination of dimensional variables caused by PI-Theorem in fluid mechanics. The developed models are divided by two parts. The one is interstand temperature prediction model. The other is roll gap temperature model.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.10a
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• pp.13-16
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• 2000

In the hot strip mill, a bad threading and shape of strip strip in the finishing mill was caused by asymmetric rolling In roughing min. Mathematical analysis for camber control of roughing mill in hot strip rolling has been developed. Each equation in the camber control model was derived from geometrical characteristics of camber mechanism. The model can predict variables such as wedge, side slippage and roll force difference etc. from a measured camber value and then find an optimum roll gap condition for minimizing camber in the next pass.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.257-266
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• 1993

Computer Simulation based of divided element method was done to predict strip shape in20-high Sendzimir Mill and has been used to find a way for preventing quarter waves occurring in the wide and thin gaged strip rolling. The simulation showed that it was difficult to prevent quarter waves by the existing methods of controlling actuators such as the shifting of the first intermediate roll and the profile control of As-U-Roll in back up roll. It was, however, confirmed analytically and experimentally that quarter waves could be effectively reduce by changing taper mode at the barrel-end taper radius of the first intermediate roll.

• 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.

• Transactions of Materials Processing
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• v.10 no.2
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• pp.130-136
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• 2001

The mathematical set-up model was developed to reduce the mechanical property deviation in annealed and slightly rolled steel strip. The mechanical peculiarities of skin pass rolling process, such as high friction value and non-circular contact arc, low reduction and non-negligible entry and exit elastic zones as well as central restricted deformation zone are all taken into account. The deformation of work rolls is calculated with the influence function method and arbitrary contact arc shape is permitted. The strip deformation is modeled by slab method and the entry and exit elastic deformation zones are included. The strip restricted deformation zone near the neutral point is also considered. It was revealed that the new model has better accuracy than present regression model by statistical analysis with actual mill rolling data.

• International Journal of CAD/CAM
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• v.12 no.1
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• pp.9-19
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• 2012

Generation of optimum planar B-spline curve in terms of minimum deviation and required fairness to approximate a target shape defined by a strip-shaped unorganized 2D point cloud is studied. It is proposed to use the location of control points as variables within the geometric optimization framework of point distance minimization. An adaptive simulated annealing heuristic optimization algorithm is developed to iteratively update an initial approximate curve towards the target shape. The new implementation comprises an adaptive cooling procedure in which the temperature change is adaptively dependent on the objective function evolution. It is shown that the proposed method results in an improved convergence speed when compared to the standard simulated annealing method. A couple of examples are included to show the applicability of the proposed method in the surface model reconstruction directly from point cloud data.