• 소성∙가공
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• 제32권3호
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• pp.114-121
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• 2023

During rolling, rolling mill rolls endure wear when shaping metal billets into a desired form, such as bars, plates, and shapes. Such wear affects the lifespan of the rolls and product quality. Therefore, in addition to rigidity, wear performance is a key factor influencing the performance of rolling mill rolls. Conventional methods such as casting and forging have been used to manufacture rolling mill rolls. However, powder alloying methods are increasingly being adopted to enhance wear resistance. These powder manufacturing methods include atomization, canning to shape the powder, hot isostatic pressing to combine the powder alloy with conventional metals, and various wear performance tests on rolls prepared with powder alloys. In this study, numerical simulations and experimental tests were used to develop and elucidate the wear analysis mechanism of rolling mill rolls. The wear characteristics of the rolls under various rolling conditions were analyzed. In addition, experimental tests (wear and surface analysis tests) and wear theory (Archard wear model) were used to evaluate wear. These tests were performed on two different materials in various powder states to evaluate the different aspects of wear resistance. In particular, this study identifies the factors influencing the wear behavior of rolling mill rolls and proposes an analytical approach based on the actual production of products. The developed wear analysis mechanism can serve the future development of rolls with high wear resistance using new materials. Moreover, it can be applied in the mechanical and wear performance testing of new products.

• 한국소음진동공학회논문집
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• 제21권3호
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• pp.199-205
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• 2011

This paper proposes a framework to predict the mechanical fault of hot rolling mill system (HRMS). The optimum process of HRMS is usually identified by the rotating velocity of working roll. Therefore, observing the velocity of working roll is relevant to early know the HRMS condition. In this paper, we propose the framework which consists of two methods namely spectrum matrix which related to case-based fast Fourier transform(FFT) analysis, and three dimensional condition monitoring based on novel visualization. Validation of the proposed method has been conducted using vibration data acquired from HRMS by accelerometer sensors. The acquired data was also tested by developed software referred as hot rolling mill facility analysis module. The result is plausible and promising, and the developed software will be enhanced to be capable in prediction of remaining useful life of HRMS.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.24-30
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• 2008

A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.368-373
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• 2003

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analysis the performance of applied neural network, the comparison with the measured rolling force and the predicted results using two different neural networks - RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

• 한국공작기계학회논문집
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• 제13권6호
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• pp.29-33
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• 2004

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analyze the performance of applied neural network the comparison with the measured rolling force and the predicted results using two different neural networks-RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.403-407
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• 2005

This paper proposes a looperless tension control algorithm which is robust to disturbance and tensional variation in rolling process using SVR(Support Vector Regression). Hot rolling process which is global technology to coil steel after continuous finishing process for welded bars followed by roughing mill process, becomes hot issue. Finishing mill process not only makes it possible to produce ultra thin steel strip(0.8 mm) but enhance the quality of terminals of coil, which increases the productivity due to faster process. Constant tension control between stands in hot rolling process is essential to enhance the quality of steel. Sensorless tension control is under research by some advanced companies to replace the conventional tension control method because in continuous finishing mill process, it is impossible to install the looper used in conventional control system. Simulation results show the effectiveness of the proposed algorithm.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1996년도 제24회 춘계학술대회
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• pp.126-132
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• 1996

A laboratory scale hot strip rolling wear simulator(HRWS) was developed for the purpose of investigating the tribological phenomena occurred in production hot strip rolling mills. The HRWS' main parts are the electric heater, the mechanical descaler, tandem type 2-4Hi rolling mill stands, the cooling chamber, the tension controller and coiler. By simulating the tribelogical phenomena in rolling process at laboratory, wear patterns, cracks, cat-ear wear, black film, effect of hot rolling oil lubrication, etc. were reproduced, and discussed on the performace of simulator.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2004년도 제5회 압연심포지엄 신 시장 개척을 위한 압연기술
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• pp.349-358
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• 2004

The strip temperature history of finishing mill process is one of the most important factors to stabilize the facilities and to achieve the better product quality including a better prediction of roll force etc. The ultimate goal of this study is to improve scientific understanding of the finishing mill process in the view of heat transfer science. Finishing mill cooling facilities of KwangYang $\#3$ hot rolling are introduced and heat transfer analyses from FET to FDT are particularly focused in this study Three major tasks are successfully achieved as follows: 1) The temperature Prediction Models are developed. 2) The average absolute error is found to be less then 10 Celsius degree (about $8.5^{\circ}C$). 3) Prediction rate (less then $\bar{+}20$) are $10.2\%$ improved $(80.1\;\rightarrow\;90.3\%)$.

• 한국공작기계학회논문집
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• 제14권1호
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• pp.52-57
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• 2005

In the foe of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a mai or change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• 소성∙가공
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• 제12권7호
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• pp.668-674
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• 2003

Rigid-plastic finite element analyses on the deformation of slabs at various width reductions have been performed. By using commercial finite element code, dog-bone profile, crop profile and the longitudinal width profile after edging and Horizontal rolling have been analysed. The deformation behavior of slab for the heavy edger mill has also been compared with that for the sizing press. From the deformation analyses, it was found that the sizing press-horizontal rolling method is more efficient in width reduction than that of heavy edger mill-horizontal rolling. The results of finite element analyses fer the deformation of slab were well confirmed by the actual operational data. It was found that the amount of width variation after sizing and rolling is about 5∼10mm.