• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1296-1302
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• 2002

A mathematical model for cold rolling and temper rolling process of thin steel strip has been developed using the influence function method. By solving the equations describing roll gap phenomena in a unique procedure and considering more influence factors, the model offers significant improvements in accuracy, robustness and generality of the solution for the thin strip cold and temper rolling conditions. The relationship between the shape of the roll profile and the roll force is also discussed. Calculation results show that any change increasing the roll force may result in or enlarge the central flat region in the deformation zone. Applied to the temper rolling process, the model can well predict not only the rolling load but also the large forward slip. Therefore, the measured forward slip, together with the measured roll force, was used to calibrate the model. The model was installed in tile setup computer of a temper rolling mill to make parallel setup calculations. The calculation results show good agreement with the measured data and the validity and precision of the model are proven.

• Transactions of Materials Processing
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• v.28 no.4
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• pp.190-196
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• 2019

The capability of accurately predicting the roll force profile across a strip in the bite zone in cold rolling process is vital for the calculation of strip profile. This paper presents a derivation of a precision mathematical model for predicting variations in the roll force across a strip in cold rolling. While the derivation is based on an approximate 3-D theory of rolling, this mathematical model also considers plastic deformation in the pre-deformation region which is located close to the roll entrance before the strip enters the bite zone. Finally, the mathematical model is expressed as a boundary value problem, and it predicts the roll force profile and tension profile in addition to lateral plastic strain profile.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.271-277
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• 2013

Skin pass rolling is a very important process for applying a certain elongation to a strip in the cold rolling and annealing processes, which play an important role in preventing the stretching of the yield point when the material is processed. The exact prediction of the rolling force is essential for obtaining a given elongation with the steel grade and strip size. Unlike hot rolling and cold rolling, skin pass rolling is used to apply an elongation of within 2% to the strip. Under a small reduction, it is difficult to predict the rolling force because the elastic deformation behavior of the rolls is complicated and a model for predicting the rolling force has not yet been established. Nevertheless, the exact prediction of the rolling force in skin pass rolling has gained increasing importance in recent times with the rapid development of high-strength steels for use in automobiles. In this study, the possibility of predicting the rolling force in skin pass rolling for producing various steel grades was examined using foil rolling theory, which is known to have similar elastic deformation behavior of rolls in the roll bite. It was found that a noncircular arc model is more accurate than a circular model in predicting the roll force of high-strength steel below TS 980 MPa in skin pass rolling.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.3
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• pp.116-126
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• 2010

The Korean rolling stock safety regulation stipulates that the collision deceleration of a car body should be maintained under average 5g and maximum 7.5g during train collisions. One-dimensional dynamic model of a full rake train, which is made up of nonlinear springs/bars-dampers-masses, is often used to estimate the collision decelerations of car bodies in a basic design stage. By the way, the previous studies have often used some average force-deformation curve for energy absorbing structures in rolling stock. Through this study, we intended to analyse how much the collision deceleration levels are influenced by the initial peak force modeling in the one-dimensional force-deformation curve. The numerical results of the one-dimensional dynamic model for the Korean High-Speed Train show that the initial peak force modeling gives significant effect on the collision deceleration levels. Therefore the peak force modeling of the force-deformation curve should be considered in one-dimensional dynamic model of a full rake train to evaluate the article 16 of the domestic rolling stock safety regulations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.7
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• pp.1030-1041
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• 1997

The control model in the tandem cold rolling mill consists of many mathematical theories and is used to calculate the reference values such as the roll gap and the rolling speed for good operation of rolling mill. But, the control model used presently has a problem causing inaccurate prediction of the rolling force. By the parameter identification, it was found that the main factor causing inaccurate prediction of the rolling force was incorrect modeling of the friction coefficient and the flow stress. To get rid of the erroneous factor new adaptive schemes are suggested in this work. Those are a long-time adaptation by the iterative least-square method and a short-time adaptation by the recursive weighted least-square method respectively. The new equations for the friction coefficient and the flow stress are derived by applying the suggested adaptive algorithms. Through the on-line test in an actual mill, it is proved that the rolling force predicted by the new equations is more accurate than the one by the existing equations ever used.

• IE interfaces
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• v.9 no.3
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• pp.298-305
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• 1996

Cold rolling mill process in steel works uses stands of rolls to flatten a strip to a desired thickness. Most of rolling processes use mathematical models to predict rolling force which is very important to decide the resultant thickness of a coil. In general, these mathematical models are not flexible for variant coil types and cannot handle various elements which is practically important to decide accurate rolling force. A corrective neural network is proposed to improve the accuracy of rolling force prediction. Additional variables-composition of the coil, coiling temperature and working roll parameters-are fed to the network. The model uses an MLP with BP to predict a corrective coefficient. The test results using 1,586 process data collected at POSCO in early 1995 show that the proposed model reduced the prediction error by 30% on average.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.491-496
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• 2000

In the tandem cold rolling mill, the quality is very important and requirements for thickness accuracy become more strict. Howerver, the mathematical model for prediction of rolling force was not considered an elastic deformation at the entry and delivery side of the contacted area between the worked roll and rolling strip so that where was so difficult to control of the thickness. To overcome this problem, the mathematical model included an elastic deformation of strip has been developed and applied to the field in order to predict the rolling force. The simulated results showed that the effect of elastic recovery should be included the model, even f the effect of elastic compression was not important.

• Transactions of Materials Processing
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• v.20 no.8
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• pp.548-554
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• 2011

A Finite Element (FE)-based model is proposed for predicting the roll force in an edger. The model is developed on the basis of the hypothetical mode of rolling and the least-squares regression analysis from the result of the FE approach. This model reflects the effect of process variables affected by the roll force, and has three dimensionless parameters, I.e., shape factor, reduction ratio and width-to-thickness ratio. The model prediction compared satisfactorily with experiment observations.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.723-727
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• 2003

In this paper, two methods are discussed for good rolling force prediction in a plate mill. One is about the development of a long and a short learning scheme using a Neural Network for normal rolling and the other is about a mathematical model improvement by considering microstructural changes for controlled rolling. The research results are implemented in a on-line system of Pohang Works in POSCO and the field tests have showed that the prediction accuracies of rolling force are highly improved.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.162-165
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• 2001

In industrial practice, caliber design in shape rolling depends on the designer's experience, which in general is obtained through costly trial-and error process. on-line model which is relations of mean effective strain, roll force and area reduction is derived from finite element process simultion in bar rolling with three rolls.