• Title/Summary/Keyword: rolling mill

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Development & Application of New Multi-Purpose Rolling Oil (일반강, SiliconSteel, StainlessSteel겸용 수용성 냉간압연유의 개발 및 적용)

  • SONG K. B.;KWOUN G. J.;KIM M. K.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2004.08a
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    • pp.261-267
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    • 2004
  • Current steel makers are trying to develop new manufacturing process to secure price competition and to improve productivity by testing a various kinds of rolling condition of several kinds of steel at TCM. Accordingly, Reverse Mill operation for Stainless steel is changing to TCM operation and furthermore, even general carbon steel and electric steel plate are requested to be worked at TCM simultaneously. By these changing of rolling condition, it become to be necessary to develop new water-soluble cold rolling oil that has a characteristics to be suitable for various working condition and in this report, we would like to mention lubrication condition to fulfill requested characteristics of each steels and development and applying result of multi-purpose water-soluble cold rolling oil which has such an lubrication property.

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Applied Facilities and Technologies of Modernization Project in No. 1 Cold Rolling Mill (1 냉연 신예화 적용설비 및 기술)

  • 여원구;이동섭;정철영;이시우
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 1999.08a
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    • pp.132-141
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    • 1999
  • No. 1 PL(Pickling Line) and No. 1 TCM(Tandem Cold Rolling Mill) at Pohang works started up in 1977 and have been operating successfully keeping high productivity for productivity thin gauge sheat such as BP, CR and silicon steel. On the other hand, customer's requirements of quality level are rasing higher continuously, so that Pohang works has combined and revamped No. 1 PL and No. 1 TCM in order to improve labor productivity, thickness accuracy and shape control capability, and so on in the period of 1977∼1999. This paper introduce the applied facilities, technologies and recent operations after revamping.

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Roll deformation and wear analysis of backup roll in heavy plate mill (후판압연의 백업롤 변형해석 및 마모특성 분석)

  • Seo, Jae-Hyung;Gho, Sung-Hyun;Moon, Chang-Ho;Chun, Myung-Sik;Park, Hae-Doo
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2009.04a
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    • pp.62-64
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    • 2009
  • Control of back-up roll deformation and wear profile in plate rolling is important not only for enhancement of the structural precision of mill, but also for improving the yield and rolling operation. in the heavy plate mill, there have been strong demands for upgrading back up roll operation technology. In order to satisfy these demands, it is essential to develop the backup roll deformation analysis models and wear profile prediction models. This paper gives a general description of the backup roll deformation and wear model, simulation result for deformation analysis and wear profile.

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Effect of Mn and S Contents on Edge Cracking of Low Carbon Steels in Mini-Mill Process (미니밀공정 중 저탄소강의 에지크랙에 미치는 Mn 및 S의 영향)

  • 곽재현;정진환;조경목
    • Transactions of Materials Processing
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    • v.9 no.1
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    • pp.66-71
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    • 2000
  • The present study tackles the metallurgical subjects involving the thin slab-direct hot rolling process, i.e. mini-mill process. In order to clarify the effect of chemical composition of steel and MnS precipitation behaviors on the development of edge cracking during hot rolling, the content of manganese and sulfur in low carbon steel was varied and the isothermal treatment prior to roughing was applied. Edge cracking during roughing in the hot-rolling process of mini-mill was effectively prevented by means of the isothermal treatment at 115$0^{\circ}C$ for 5 minutes in the 0.4% manganese steel containing sulfur lower than 0.013%. With the increase in manganese content in low carbon steel, coarser MnS developed. The edge cracking index which denotes the total length of edge crack per unit edge-length of rolled specimens was proposed in this paper. It was found that the edge cracking index linearly decreased with the increase in the ratio of MnS.

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Prediction for Rolling Force in Hot-rolling Mill Using On-line loaming Neural Network (On-line 학습 신경회로망을 이용한 열간 압연하중 예측)

  • 손준식;이덕만;김일수;최승갑
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.04a
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    • pp.124-129
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    • 2003
  • In the face of global competitor the requirements flor the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major 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 fir simulation and quantitative description of the industrial operations involved. In this paper, a 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.

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Prediction of Proper Horizontal Position of Work Roll in Backup Roll Driven-type Cold Rolling Mill (보강롤 구동 냉간압연기에서의 적정 작업롤 수평위치 설정기법 개발)

  • 변상민;이원호
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2003.05a
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    • pp.160-163
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    • 2003
  • For the purpose of rolling hard metals such as silicon steel and non-ferrous metals, the backup roll driven-type mill has been widely used in cold rolling industry. Since the backup roll drive results in horizontal bending of the work rolls and therefore exerted reciprocal action on the roll gap contour, the selection of slim work rolls is very restricted. In this paper, we present an analytic equation based scheme to determine a proper horizontal position of work roll minimizing the horizontal force subject to mechanical constraints.

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A Neural Net Type Process Model for Enhancing Learning Compensation Function in Hot Strip Finishing Rolling Mill (열연 마무리 압연기에서 압연속도 학습보상기능개선을 위한 신경망형 공정 모델)

  • Hong, Seong-Cheol;Lee, Haiyoung
    • 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.

Development and application of the new ASC system in No.2 cold rolling mill (2 냉연 신형상제어 시스템 개발 및 적용)

  • 박남수;심민석
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1068-1071
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    • 1996
  • Good shape on flat rolled product is necessary to meet today's customer quality requirement. To meet the increasing demand in quality of strip shape from downstream customers, POSCO has replaced the Automatic Shape Control(ASC) system with the existing one that had used noncontact type measuring system at No.2 Cold Rolling Mill, Pohang works in October, 1995. The strip shape is influenced by the profile, roll crown, bending control, skew control system, as well as work roll cooling system. We have used ASC to adjust those factors in Cold Rolling Mill that could get a satisfactory result, almost less than .+-.5 1-unit deviation from the target shape. However, the downstream customer(i.e. Continuos Annealing Line) wants a good shape not only at the moment of exit of roll bite, but after rolling without tension. In this investigation, the difference will be discussed and how deal with this problem.

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FEM Based Approach to Predict Rolling Force and Strip Thickness in 4-High Cold Rolling Mill Driven by Backup-Roll (유한요소법을 이용한 보강롤 구동 4단 냉간압연기에서의 압연하중 및 스트립 두께 예측)

  • Lee, Jae-Hyun;Byon, Sang-Min;Park, Heung-Slk
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.8 no.4
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    • pp.129-135
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    • 2009
  • In this paper, a finite element model is presented for the prediction of roll force and strip thickness in a backup-roll-drive mill. The proposed FE model is focused mainly on analyzing the elastic/plastic behavior between a work roll and a strip as well as the rigid/plastic behavior between a backup roll and a work roll. The capability of the proposed model is demonstrated through application to 4-high silicon steel rolling mill at POSCO. Results show that the predicted roll force and strip thickness rolled accurately agree with the measured them. It is also illustrated that the proper position of work roll displaced to one side from the vertical centerline of the backup-roll may be determined by minimizing the horizontal force of work roll.

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Development of High Precision Forward Slip Model By Using Roll Torque in Hot Strip Finishing Mill (압연롤 토크를 이용한 열연박판 마무리압연 선진율 예측 정밀도 개선연구)

  • 문영훈;김영환
    • Transactions of Materials Processing
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    • v.8 no.6
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    • pp.583-590
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    • 1999
  • New forward slip model has been developed for the precise prediction of rolling speed in the hot strip finishing mill. Besides those influential factors such as neutral point, work roll diameter, friction coefficient, bite angle and the thickness at each side of entry and delivery of the rolls, roll torque was specifically taken into account in this study. To consider the effect of width change on forward slip, calibration factors obtained from rolling torque has been added to new prediction model and refining method has also been developed to reduce the speed unbalance between adjacent stands. The application of the new model showed a good agreement in rolling speeds between the predictions and the actual measurements, and the standard deviation of prediction error has also been significantly reduced.

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