JP3470627B2 - Automatic extraction method of heating furnace in hot rolling - Google Patents
Automatic extraction method of heating furnace in hot rollingInfo
- Publication number
- JP3470627B2 JP3470627B2 JP00389699A JP389699A JP3470627B2 JP 3470627 B2 JP3470627 B2 JP 3470627B2 JP 00389699 A JP00389699 A JP 00389699A JP 389699 A JP389699 A JP 389699A JP 3470627 B2 JP3470627 B2 JP 3470627B2
- Authority
- JP
- Japan
- Prior art keywords
- time
- rolling
- heating furnace
- mill
- extraction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Landscapes
- Control Of Metal Rolling (AREA)
Description
【発明の詳細な説明】
【0001】
【発明の属する技術分野】本発明は、熱間圧延における
加熱炉の自動抽出方法に係り、特に、加熱炉在炉中に、
材料の抽出時点から各設備を通過するまでの時間を予測
計算し、先行材と後行材との干渉が生じないように材料
の抽出時刻を決定して、加熱炉から材料を自動的に抽出
する方法に関する。
【0002】
【従来の技術】熱間圧延において、材料の加熱炉からの
抽出タイミングを適切に決定することは、圧延能率及び
エネルギ効率の観点から重要である。抽出タイミングが
早過ぎれば、律速工程で先行材との干渉が起き、材料の
衝突、圧延機械の破損、ミルライン上での待ち時間によ
るエネルギ損失等の問題が生じ、逆に、抽出タイミング
が遅過ぎれば、材料を搬送する無駄時間が生じ、圧延能
率が低下する。
【0003】一般に、加熱炉から材料を抽出するタイミ
ングは、特開昭61−259818に記述されるよう
に、圧延スケジュールに基づいて、各設備の通過時間を
予測計算し、決定する方法が用いられている。
【0004】又、圧延時間の実績値が予測計算値と異な
り、誤差を生じた場合、特開昭62−30812に記述
されているように、先行する材料の各設備通過時刻の実
績を用いて、予測値との差により、次抽出材の抽出時刻
を修正する方法がある。これにより、設備の突発的故障
や、オペレータの手動介入による圧延時間の変動に対し
て、自動的に抽出タイミングを適正化することができ
る。
【0005】
【発明が解決しようとする課題】しかしながら、噛み込
み性、品質(形状・寸法)の向上を目的に、圧延速度・
加減速率・パス数等を調整すると、それまでに作成した
圧延時間予測式が合わなくなり、圧延時間予測値と実績
値との間に誤差が生じる問題がある。
【0006】従来の特開昭62−30812の方法のよ
うに、実績時間と予測時間の差で次材の抽出タイミング
を修正したのでは、このような要因で発生した圧延時間
予測誤差の平均値を小さくすることはできるが、ばらつ
きを示す分散は小さくすることができないという問題点
を有していた。
【0007】予測誤差の大きさは、一般に、二乗平均誤
差で評価される。
【0008】N個のデータが収集できたとして、
【0009】
【外1】
【0010】とし、予測誤差eiを次式で定義する。
【0011】
【数1】
【0012】すると、二乗平均誤差MSEは、次式で定
義される。
【0013】
【数2】
【0014】予測誤差の平均値を
【0015】
【外2】
と定義すると、二乗平均誤差MSEは、次式のように変
形できる。
【0016】
【数3】
【0017】(4)式右辺の第一項は分散(平均値から
のばらつき)を表わし、第二項は平均値の2乗を表わ
す。即ち、予測誤差の大きさを表わす二乗平均誤差は、
分散と平均値の2乗の和で表現される。従って、予測誤
差を小さくするためには、誤差の平均値を0に近付ける
と共に、分散を小さくする必要がある。
【0018】本発明は、前記従来の問題点を解決するべ
くなされたもので、圧延時間予測誤差の平均値のみなら
ず、分散も小さくし、加熱炉からの抽出タイミングを適
正化することを課題とする。
【0019】
【課題を解決するための手段】本発明は、前記課題を解
決するために、材料の抽出時点から各設備通過までの時
間を予測計算するための各設備通過時間予測式を、パス
数と圧延長の関数で記述し、先行材の各設備通過時間実
績値に基づき、オンライン同定法を用いて予測式を修正
し、次材の加熱炉抽出時刻を決定して、加熱炉から自動
的に材料を抽出するようにしたものである。
【0020】圧延時間に代表される各設備通過時間は、
パス数と圧延長に相関があり、この特性は圧延速度や加
減速率に変動があっても変化しない。よって、各設備通
過時間の実績値をパス数と圧延長で重回帰を行い、各設
備通過時間予測式を逐次修正すれば、圧延速度や加減速
率の変動により生じる各設備通過時間予測誤差の平均値
と分散を共に小さくして、加熱炉抽出タイミングを一層
適正化することができる。
【0021】
【発明の実施の形態】以下、図面を参照して、本発明を
形鋼圧延に適用した実施形態を詳細に説明する。
【0022】形鋼圧延ラインは、図1に示すように、加
熱炉10と、ブレークダウンミル12と、ユニバーサル
ミルU1及びエッジャE1を含む粗ミル14と、仕上ミ
ル(UF)16より構成され、この中で粗ミル14が律
速工程となることが多い。
【0023】本実施形態では、粗ミル14が律速工程と
なり、粗ミル14において先行材と後行材が干渉せず、
且つ、先行材が粗ミル14を通過してから後行材が粗ミ
ル14に進入するまでの時間を最小にするような、最適
な加熱炉抽出タイミングの決定方法を示す。ここでは、
説明の簡易化のため、ブレークダウンミル12において
は、常に同じ時間で圧延されると仮定する。即ち、材料
が加熱炉10から抽出されてから粗ミル14に到達する
までの時間は、常に一定であると仮定する。
【0024】本実施形態においては、粗ミル14での圧
延時間を予測するためのモデルとして、次式を用いる。
【0025】
圧延時間=a×パス数+b×圧延長+c …(5)
【0026】ここで、パス数とは粗ミル14での圧延回
数、圧延長とは粗ミル圧延終了後の材料長、a、b、c
は圧延時間予測モデルのパラルータである。これらのパ
ラメータa、b、cは、圧延成品である形鋼のウェブ高
さ、フランジ幅毎に分類され、実績圧延時間からオフラ
インで最小二乗法等の同定法を用いて決定する。
【0027】先行材を加熱炉10から抽出して、次材を
加熱炉10から抽出するまでの時間(以下抽出ピッチと
呼ぶ)は、次のようにして決定する。
【0028】
抽出ピッチ=先行材の粗ミル圧延時間+Bar to Bar時間 …(6)
【0029】ここで、先行材の粗ミル圧延時間とは、先
行材が粗ミル14に進入してから、粗ミル14から退出
するまでの時間である。これは、先行材の予定パス及び
予定圧延長をもとに、(5)式を用いて計算する。又、
Bar to Bar時間とは、先行材が粗ミル14から退出し
てから、次材が粗ミル14に進入可能になるまでの時間
(例えば、先行材が粗ミルを退出してから粗ミル付近の
設備を次材の圧延位置へ設定するまでの時間)であり、
定数で与える。
【0030】(6)式で計算した抽出ピッチをもとに、
材料を加熱炉10から抽出すれば、粗ミル14の圧延時
間予測モデルが合っていれば、最適な抽出タイミングを
実現できる。
【0031】図2に、あるサイズにおいて、オフライン
で最小二乗法により粗ミル圧延時間予測モデルを同定し
た結果を示す。このモデルを用いて抽出ピッチを決定す
るようにした。
【0032】図3に、半年経過した後の圧延時間予測値
と実績値の比較を示す。圧延時間予測誤差が増大してい
ることが分かる。これは、圧延速度、加減速率を調整し
たため、圧延時間予測モデルが合わなくなったからであ
る。このようなモデルを使用して、抽出ピッチを決定す
れば、圧延能率及びエネルギ効率の低下が起こる。
【0033】次に、オンライン同定法の一例として、逐
次型最小二乗法を示す。N本目の材料の粗ミル圧延時間
を、y(N)、パス数をp(N)、圧延長をq(N)と
表現する。又、N本目の材料までの実績をもとに計算し
た、圧延時間予測モデルのパラメータ・ベクトルを次式
で定義する。
【0034】
【数4】
【0035】N本目の材料までの圧延実績をもとに、圧
延時間予測モデルのパラメータを求める計算アルゴリズ
ムは、以下のように与える(逐次型最小二乗法)。
【0036】
【数5】
【0037】オンラインで同定した結果を用い、上式に
より材料が圧延される毎に圧延時間予測モデルのパラメ
ータを修正する。
【0038】図4に、本方法により圧延時間予測モデル
を修正した結果を示す。図3と比較して、圧延時間予測
誤差の平均値と分散が小さくなっていることが分かる。
【0039】これにより、材料1本当たりの抽出ピッチ
を平均4秒短縮することができ、圧延能率を向上するこ
とができた。又、分散が小さくなったことで、粗ミル前
での材料の待ち時間も小さくすることができ、エネルギ
ロスを低減することができた。
【0040】なお、図2〜4における○9、□11は、
前者が粗ミルでのトータルパス数が9パスの材料、後者
が11パスの材料を意味している。
【0041】前記実施形態においては、本発明が形鋼の
圧延時間の予測に適用されていたが、本発明の適用対象
はこれに限定されず、形鋼以外の圧延ラインの各設備通
過時間一般の予測に用いることができる。
【0042】
【発明の効果】本発明によれば、圧延時間に代表される
各設備通過時間の予測誤差の平均値及び分散を小さくす
ることができる。従って、材料の加熱炉からの抽出タイ
ミングを一層適正化して、抽出ピッチを短縮することが
でき、圧延能率を向上できる。又、材料が粗ミル等の律
速工程の前で待つことも少なくなり、エネルギロスを低
減することもできる。Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for automatically extracting a heating furnace in hot rolling, and more particularly, to a method for extracting a heating furnace in a heating furnace.
Predict and calculate the time from material extraction to passing through each facility, determine the material extraction time so that there is no interference between the preceding and succeeding materials, and automatically extract the material from the heating furnace On how to do it. [0002] In hot rolling, it is important to appropriately determine the timing of extracting a material from a heating furnace from the viewpoint of rolling efficiency and energy efficiency. If the extraction timing is too early, interference with the preceding material occurs in the rate-determining process, causing problems such as material collision, breakage of the rolling machine, energy loss due to waiting time on the mill line, and conversely, the extraction timing is too late If this is the case, waste time for transporting the material occurs, and the rolling efficiency decreases. [0003] Generally, as described in Japanese Patent Application Laid-Open No. 61-259818, a method of predicting and calculating the passage time of each facility based on a rolling schedule is used to determine the timing of extracting a material from a heating furnace. ing. If the actual value of the rolling time differs from the predicted calculated value and an error occurs, as described in Japanese Patent Application Laid-Open No. Sho 62-30812, the actual value of the preceding material at each facility passing time is used. There is a method of correcting the extraction time of the next extraction material based on the difference from the predicted value. Thereby, it is possible to automatically optimize the extraction timing with respect to a sudden failure of the equipment or a change in the rolling time due to manual intervention of an operator. [0005] However, in order to improve the biting property and the quality (shape and dimensions), the rolling speed and
If the acceleration / deceleration rate, the number of passes, and the like are adjusted, the rolling time prediction formulas created so far do not match, and there is a problem that an error occurs between the rolling time prediction value and the actual value. If the extraction timing of the next material is corrected based on the difference between the actual time and the predicted time as in the method of the conventional Japanese Patent Application Laid-Open No. Sho 62-30812, the average value of the rolling time prediction error generated due to such factors is considered. However, there is a problem that the variance showing the variation cannot be reduced. [0007] The magnitude of the prediction error is generally evaluated by a root mean square error. [0008] Assuming that N data can be collected, The prediction error ei is defined by the following equation. [0011] Then, the root mean square error MSE is defined by the following equation. [0013] The average value of the prediction error is given by Then, the root mean square error MSE can be transformed as the following equation. [Equation 3] The first term on the right side of equation (4) represents the variance (variation from the average value), and the second term represents the square of the average value. That is, the root mean square error representing the magnitude of the prediction error is
It is represented by the sum of the square of the variance and the average value. Therefore, in order to reduce the prediction error, it is necessary to make the average value of the error close to 0 and reduce the variance. SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned conventional problems, and it is an object of the present invention to reduce not only the average value of the rolling time prediction error but also the variance, and to optimize the extraction timing from the heating furnace. And According to the present invention, in order to solve the above-mentioned problems, each equipment passage time prediction formula for predicting and calculating the time from the time of material extraction to each equipment passage is defined by a pass-through equation. Described as a function of the number and extension of pressure, based on the actual passing time of each material of the preceding material, corrected the prediction formula using the online identification method, determined the heating furnace extraction time of the next material, and automatically In this method, the material is extracted. Each equipment passing time represented by the rolling time is as follows:
There is a correlation between the number of passes and the elongation of pressure, and this characteristic does not change even if the rolling speed or the acceleration / deceleration rate fluctuates. Therefore, by performing multiple regression on the actual value of each equipment transit time with the number of passes and pressure extension, and sequentially correcting each equipment transit time prediction formula, the average of each equipment transit time prediction error caused by fluctuations in rolling speed and acceleration / deceleration rate can be obtained. By reducing both the value and the variance, the heating furnace extraction timing can be further optimized. Embodiments of the present invention applied to rolled section steel will now be described in detail with reference to the drawings. As shown in FIG. 1, the section steel rolling line comprises a heating furnace 10, a breakdown mill 12, a rough mill 14 including a universal mill U1 and an edger E1, and a finishing mill (UF) 16, Of these, the roughing mill 14 is often the rate-determining step. In the present embodiment, the roughing mill 14 is a rate-determining step, and the preceding and succeeding materials do not interfere with each other in the roughing mill 14,
In addition, a method for determining an optimum heating furnace extraction timing so as to minimize the time from when the preceding material passes through the coarse mill 14 to when the following material enters the coarse mill 14 will be described. here,
For the sake of simplicity, it is assumed that the rolling is always performed at the same time in the breakdown mill 12. That is, it is assumed that the time from when the material is extracted from the heating furnace 10 to when it reaches the roughing mill 14 is always constant. In the present embodiment, the following equation is used as a model for predicting the rolling time in the rough mill 14. Rolling time = a × number of passes + b × pressure extension + c (5) where the number of passes is the number of times of rolling in the coarse mill 14, the pressure extension is the material length after the completion of the coarse mill rolling, a, b, c
Is a para router of the rolling time prediction model. These parameters a, b, and c are classified according to the web height and the flange width of the section steel as the rolled product, and are determined off-line from the actual rolling time using an identification method such as a least square method. The time required for extracting the preceding material from the heating furnace 10 and extracting the next material from the heating furnace 10 (hereinafter referred to as the extraction pitch) is determined as follows. Extraction pitch = coarse mill rolling time of the preceding material + Bar to Bar time (6) Here, the rough mill rolling time of the preceding material is defined as a rough time after the preceding material enters the rough mill 14. This is the time required to exit the mill 14. This is calculated using equation (5) based on the planned path and the planned pressure extension of the preceding material. or,
The Bar to Bar time is the time from when the preceding material exits the coarse mill 14 until the next material can enter the coarse mill 14 (for example, when the preceding material exits the coarse mill and Time to set the equipment to the next material rolling position)
Give as a constant. Based on the extracted pitch calculated by the equation (6),
If the material is extracted from the heating furnace 10, the optimum extraction timing can be realized if the rolling time prediction model of the rough mill 14 is suitable. FIG. 2 shows the result of identifying a rough mill rolling time prediction model at a certain size by an off-line least squares method. The extraction pitch was determined using this model. FIG. 3 shows a comparison between the predicted rolling time after a lapse of six months and the actual value. It can be seen that the rolling time prediction error has increased. This is because the rolling time and the acceleration / deceleration rate were adjusted, so that the rolling time prediction model did not fit. If the extraction pitch is determined using such a model, the rolling efficiency and the energy efficiency decrease. Next, a sequential least squares method will be described as an example of the online identification method. The rough mill rolling time of the Nth material is expressed as y (N), the number of passes is expressed as p (N), and the elongation is expressed as q (N). Also, a parameter vector of the rolling time prediction model calculated based on the results up to the N-th material is defined by the following equation. ## EQU4 ## A calculation algorithm for obtaining the parameters of the rolling time prediction model based on the results of rolling up to the Nth material is given as follows (sequential least squares method). (Equation 5) Using the results identified online, the parameters of the rolling time prediction model are corrected each time the material is rolled according to the above equation. FIG. 4 shows the result of modifying the rolling time prediction model by this method. It can be seen that the average value and the variance of the rolling time prediction error are smaller than those in FIG. As a result, the extraction pitch per material could be shortened by an average of 4 seconds, and the rolling efficiency could be improved. Further, since the dispersion is reduced, the waiting time of the material before the rough mill can be reduced, and the energy loss can be reduced. Note that 99 and □ 11 in FIGS.
The former means a material having a total number of passes of 9 in a coarse mill, and the latter means a material having an eleven passes. In the above embodiment, the present invention was applied to the prediction of the rolling time of a section steel. However, the application of the present invention is not limited to this. Can be used to predict According to the present invention, it is possible to reduce the average value and the variance of the prediction error of each equipment passing time represented by the rolling time. Therefore, the extraction timing of the material from the heating furnace can be further optimized, the extraction pitch can be shortened, and the rolling efficiency can be improved. In addition, it is less necessary for the material to wait before a rate-determining step such as a rough mill, so that energy loss can be reduced.
【図面の簡単な説明】
【図1】本発明の適用対象の一例である、形鋼工場圧延
ラインを示す工程図
【図2】粗ミル圧延時間予測モデルを、従来法によりオ
フラインで同定したときの圧延時間予測誤差の例を示す
線図
【図3】経年劣化により、図2で用いた圧延時間予測モ
デルが合わなくなったときの圧延時間予測誤差の例を示
す線図
【図4】本発明を適用したときの圧延時間予測誤差の例
を示す図
【符号の説明】
10…加熱炉
12…ブレークダウンミル
14…粗ミル
U1…ユニバーサルミル
E1…エッジャ
16…仕上ミル(UF)BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a process diagram showing a section steel mill rolling line, which is an example of an object to which the present invention is applied. FIG. 2 When a rough mill rolling time prediction model is identified offline by a conventional method. FIG. 3 is a diagram showing an example of a rolling time prediction error of FIG. 3. FIG. 3 is a diagram showing an example of a rolling time prediction error when the rolling time prediction model used in FIG. FIG. 1 shows an example of a rolling time prediction error when applying the equation [Description of References] 10 ... Heating furnace 12 ... Breakdown mill 14 ... Rough mill U1 ... Universal mill E1 ... Edger 16 ... Finishing mill (UF)
Claims (1)
備通過までの時間を予測計算し、先行材と後行材との干
渉が生じないように材料の抽出時刻を決定して、加熱炉
から自動的に材料を抽出する方法において、 各設備通過時間予測式を、パス数と圧延長の関数で記述
し、 先行材の各設備通過時間実績値に基づき、オンライン同
定法を用いて予測式を修正し、次材の加熱炉抽出時刻を
決定することを特徴とする、熱間圧延における加熱炉の
自動抽出方法。(57) [Claims] [Claim 1] Predicting and calculating the time from the time of material extraction to the passage of each equipment during the heating furnace in the furnace, so that interference between the preceding material and the succeeding material does not occur. In the method of automatically extracting the material from the heating furnace by determining the material extraction time, the equipment transit time prediction formula is described as a function of the number of passes and the pressure elongation, and the actual equipment transit time of the preceding material A method for automatically extracting a heating furnace in hot rolling, wherein a prediction formula is corrected using an online identification method based on a value, and a heating furnace extraction time of a next material is determined.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP00389699A JP3470627B2 (en) | 1999-01-11 | 1999-01-11 | Automatic extraction method of heating furnace in hot rolling |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP00389699A JP3470627B2 (en) | 1999-01-11 | 1999-01-11 | Automatic extraction method of heating furnace in hot rolling |
Publications (2)
Publication Number | Publication Date |
---|---|
JP2000202512A JP2000202512A (en) | 2000-07-25 |
JP3470627B2 true JP3470627B2 (en) | 2003-11-25 |
Family
ID=11569958
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Application Number | Title | Priority Date | Filing Date |
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JP00389699A Expired - Fee Related JP3470627B2 (en) | 1999-01-11 | 1999-01-11 | Automatic extraction method of heating furnace in hot rolling |
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JP (1) | JP3470627B2 (en) |
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JP5229069B2 (en) * | 2009-04-01 | 2013-07-03 | 新日鐵住金株式会社 | Method for determining rolling pass schedule of thick steel plate and method for manufacturing thick steel plate |
JP5903869B2 (en) * | 2011-12-19 | 2016-04-13 | Jfeスチール株式会社 | Mil pacing control method in hot rolling line |
JP6460004B2 (en) * | 2016-02-17 | 2019-01-30 | Jfeスチール株式会社 | Heating furnace extraction interval determination device, steel plate manufacturing apparatus, heating furnace extraction interval determination method, and steel plate manufacturing method |
CN109663815A (en) * | 2018-12-28 | 2019-04-23 | 宝钢湛江钢铁有限公司 | A kind of control method and system for taking out steel automatically during hot rolling |
JP7342891B2 (en) * | 2021-01-19 | 2023-09-12 | Jfeスチール株式会社 | Method for calculating rolling time of steel materials, automatic combustion control method for continuous heating furnace, and manufacturing method for steel materials |
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JPS55147409A (en) * | 1979-05-08 | 1980-11-17 | Nippon Kokan Kk <Nkk> | Extraction pitch control device in plate rolling |
JPH067823A (en) * | 1992-06-26 | 1994-01-18 | Kawasaki Steel Corp | Method for extracting rolled stock from heating furnace in hot rolling |
JPH07290127A (en) * | 1994-04-28 | 1995-11-07 | Kawasaki Steel Corp | Method for controlling mill pacing in hot rolling |
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