Surface crack prediction method, steel strip manufacturing method, and surface crack prediction device

Abstract

To provide a surface crack prediction method capable of predicting a surface crack of a steel strip after rolling.SOLUTION: A surface crack prediction method for predicting a surface crack of a steel strip manufactured by performing a furnace heating process and a rolling process on a slab cast by continuous casting, the method comprising: creating a surface crack database in which surface crack data indicating presence or absence of a surface crack for a steel strip manufactured in the past is recorded with respect to manufacturing condition sections obtained by dividing each of a component content of the slab, a heating temperature in the furnace heating process, and a strain rate in the rolling process into a plurality of sections; A surface crack of a steel strip to be manufactured is predicted by using a Cu content as a component content of a steel piece, specifying a manufacturing condition section including the component content, a heating temperature in a furnace heating process, and a strain rate in a rolling process for the steel strip to be manufactured, and referring to surface crack data recorded in the specified manufacturing condition section in a surface crack database.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a surface crack prediction method for predicting surface cracks in a steel strip caused by rolling, a surface crack prediction device, and a method for manufacturing a steel strip using the surface crack prediction method. [Background technology]

[0002] When scrap is used as the iron source for steelmaking, the Cu and Sn contained in the scrap become mixed into the steel. When the surface of the rolled material oxidizes during the furnace heating process in hot rolling, Cu concentrates at the interface between the scale (iron oxide) and the base steel, causing cracks on the surface during the hot rolling process after heating. Cu and Sn are called tramp elements and are difficult to remove through refining, so the amount of scrap used is limited due to the problem of surface cracks. In order to realize a recycling-oriented society, expanding the use of scrap is a major challenge for the steel industry.

[0003] Cu is less susceptible to oxidation than Fe, and its solid solubility in Fe is low (a few percent). For this reason, Cu precipitates as a metallic phase at the interface between the scale and the base steel during the scale formation process. Furthermore, the melting point of Cu is 1080°C, and because the material being rolled in typical hot rolling is heated to temperatures above this, the liquid phase of molten Cu penetrates the grain boundaries of the base steel, causing surface cracks during the width reduction and hot rolling processes, where large shear and tensile stresses are applied.

[0004] It is known that Sn reduces the solid solubility of Cu in steel, thereby promoting surface cracking caused by Cu. Conversely, Ni has the effect of increasing the solid solubility of Cu in steel. Non-Patent Document 1 discloses a technique for adding Ni to suppress surface cracking caused by Cu. However, using a large amount of Ni, which is a rare and expensive metal, increases the manufacturing cost.

[0005] In a hot rolling line, if a surface crack occurs in the width reduction process or hot rolling process on the upstream side, not only will the crack depth increase through the downstream processes, but scale will be pushed into the crack opening, causing surface defects due to poor descaling. For this reason, it is important to prevent surface cracks in all width reduction processes and hot rolling processes from upstream to downstream in a hot rolling line.

[0006] Patent Document 1 discloses a method for producing a hot-rolled steel sheet that does not generate surface defects by determining the boundary between the occurrence of surface defects during continuous casting and hot rolling using a relationship between the Cu content and the Sn content. Patent Document 2 discloses a method for preventing cracking in Cu- and Sn-containing steel by adding Si and setting the heating temperature to 1150°C or higher, thereby capturing the molten Cu and Sn precipitated at the interface between the scale and the base steel into the scale. Patent Document 3 proposes a hot rolling method for preventing surface cracking, in which the surface layer of the rolled material is cooled to a temperature below the crack initiation temperature just before it is bitten into the rolling rolls. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Patent No. 3180575 [Patent Document 2] Patent No. 3173914 [Patent Document 3] Patent No. 3025363 [Non-patent literature]

[0008] [Non-Patent Document 1] Steel Material Science of Tramp Elements: How to Deal Well with Scrap-Derived Impurity Elements, Iron and Steel Institute of Japan, March 1997 [Non-patent document 2] Theory and Practice of Plate Rolling (Revised Edition), Iron and Steel Institute of Japan, 2010, P165 Summary of the Invention [Problem to be solved by the invention]

[0009] However, in Patent Document 1, when steel containing 0.4 mass % Cu, which is considered to be in a range of components that does not cause surface cracks, is heated to 1100°C for production, the steel is processed in a state in which molten Cu penetrates grain boundaries, and in fact, surface cracks occur. Furthermore, there is no mention of width reduction or horizontal rolling conditions, which poses a problem in that it is not possible to set the reduction conditions in the reduction process so as to prevent surface cracks from occurring.

[0010] Patent Document 2 describes a technology for preventing the penetration of Cu into grain boundaries by adding Si, but it makes no mention of width reduction or horizontal rolling conditions, posing a problem in that it is not possible to set the reduction conditions in the reduction process so as to prevent surface cracks. Furthermore, the addition of Si makes the base steel interface uneven, which raises concerns about the occurrence of surface defects due to poor descaling.

[0011] Patent Document 3 is a technology that focuses on preventing surface cracks during the reduction process on a hot rolling line, but requires a cooling device. In the width reduction process using a sizing press, where slabs are transported intermittently, uneven cooling occurs in the surface temperature of the rolled material during processing, making it difficult to apply this technology to the width reduction process. Furthermore, lowering the temperature of the rolled material reduces the solid solubility of Cu in the steel, which could lead to Cu precipitation at the grain boundaries of the base steel, thereby potentially promoting surface cracks.

[0012] Furthermore, the techniques disclosed in Patent Documents 1 to 3 are techniques for preventing Cu-caused surface cracks during rolling, but do not disclose predicting such surface cracks. If Cu-caused surface cracks during rolling could be predicted, it would be possible to identify rolling conditions under which surface cracks are predicted not to occur, and by rolling under those rolling conditions, it may be possible to produce steel strips while suppressing the occurrence of surface cracks.

[0013] The present invention has been made in consideration of the problems of the prior art, and its object is to provide a surface crack prediction method and a surface crack prediction device that can predict surface cracks in a steel strip after rolling. Another object of the present invention is to provide a steel strip manufacturing method that uses the surface crack prediction method to identify a strain rate in the rolling process at which no surface cracks will occur in the steel strip, and to manufacture the steel strip at a strain rate equal to or lower than that strain rate. [Means for solving the problem]

[0014] The means for solving the above problems are as follows. [1] A surface crack prediction method for predicting surface cracks in a steel strip produced by subjecting a steel slab cast in a continuous casting process to a furnace heating process and a rolling process, the method comprising: creating a surface crack database in which surface crack data indicating the presence or absence of surface cracks for steel strips produced in the past is recorded for manufacturing condition classifications in which the component content of the steel slab, the heating temperature in the furnace heating process, and the strain rate in the rolling process are each classified into a plurality of categories; using the Cu content as the component content of the steel slab; identifying a manufacturing condition classification for the steel strip to be produced that includes the component content, the heating temperature, and the strain rate; and predicting surface cracks in the steel strip to be produced by referring to the surface crack data recorded in the identified manufacturing condition classification in the surface crack database. [2] The surface crack prediction method according to [1], further comprising using Ni content and / or Sn content as the component contents of the steel billet. [3] The surface crack prediction method described in [1] or [2], wherein the surface crack database further includes manufacturing condition classifications that classify the continuous casting conditions in the continuous casting process into multiple categories, and predicts surface cracks in the steel strip by identifying the manufacturing condition classification that includes the component content of the steel strip to be manufactured, the heating temperature in the furnace heating process, the strain rate in the rolling process, and the continuous casting conditions. [4] A method for manufacturing a steel strip using the surface crack prediction method described in [1] or [2], which specifies a strain rate at which no surface cracks are predicted to occur in a manufacturing condition category that includes the component content and heating temperature of the steel strip to be manufactured, and carries out the rolling process at a strain rate equal to or lower than the specified strain rate to manufacture the steel strip. [5] A method for manufacturing a steel strip using the surface crack prediction method described in [3], which specifies a strain rate at which no surface cracks are predicted to occur in a manufacturing condition category that includes the component content, heating temperature, and continuous casting conditions of the steel strip to be manufactured, and carries out the rolling process at a strain rate equal to or lower than the specified strain rate to manufacture the steel strip. [6] A method for manufacturing a steel strip using the surface crack prediction method described in [1] or [2], which includes identifying a range of manufacturing condition categories for strain rates in which surface crack data indicating the absence of surface cracks is recorded in a manufacturing condition category that includes the component content and heating temperature for the steel strip to be manufactured, and carrying out the rolling process at a strain rate that is equal to or lower than the fastest strain rate among the strain rates in the range of the identified manufacturing condition category to manufacture the steel strip. [7] A method for manufacturing a steel strip using the surface crack prediction method described in [3], which identifies a range of manufacturing condition categories for strain rates in which surface crack data indicating the absence of surface cracks is recorded in a manufacturing condition category that includes the component content, the heating temperature, and the continuous casting conditions for the steel strip to be manufactured, and carries out the rolling process at a strain rate that is equal to or lower than the fastest strain rate among the strain rates in the range of the identified manufacturing condition category to manufacture the steel strip. [8] A surface crack prediction device that uses a surface crack database to predict surface cracks in steel strips produced by subjecting steel billets cast in a continuous casting process to a furnace heating process and a rolling process, wherein the surface crack database is a database in which surface crack data indicating the presence or absence of surface cracks in steel strips produced in the past is recorded for manufacturing condition classifications that are divided into multiple categories for the component content of the steel billets, the heating temperature in the furnace heating process, and the strain rate in the rolling process, and the component content of the steel billets includes a Cu content, and the device has a surface crack prediction unit that identifies a manufacturing condition classification for the steel strip to be produced that includes the component content, the heating temperature, and the strain rate in the rolling process, and predicts surface cracks in the steel strip to be produced using the surface crack data recorded in the manufacturing condition classification identified in the surface crack database. [9] The surface crack prediction device according to [8], wherein the component contents of the steel billet further include a Ni content and / or a Sn content.

[10] The surface crack prediction device described in [8] or [9], wherein the surface crack database further includes manufacturing condition classifications that classify the continuous casting conditions in the continuous casting process into multiple categories, and the surface crack prediction unit identifies a manufacturing condition classification that includes the component content, the heating temperature, the strain rate, and the continuous casting conditions of the steel strip to be manufactured. [Effects of the Invention]

[0015] By using the surface crack prediction method according to the present invention, it becomes possible to predict surface cracks in a steel strip during a rolling process. In addition, by specifying a strain rate in the rolling process at which the surface cracks are predicted not to occur and producing the steel strip under production conditions that include a strain rate equal to or lower than the specified strain rate, it becomes possible to produce a steel strip while suppressing surface cracks. [Brief explanation of the drawings]

[0016] [Figure 1] FIG. 1 is a schematic diagram showing the state of a steel billet (slab) being rolled by horizontal rolling. [Figure 2] FIG. 2 is a top view showing the state of a slab being reduced in width reduction. [Figure 3] FIG. 3 is a schematic diagram showing an example of a steel strip manufacturing facility including a surface crack prediction device capable of implementing the surface crack prediction method according to this embodiment. [Figure 4] FIG. 4 is a schematic diagram showing an example of the configuration of a surface crack prediction device. [Figure 5] FIG. 5 is a schematic diagram showing a part of the surface crack database. [Figure 6] FIG. 6 is a flow diagram showing an example of the surface crack prediction method and steel strip manufacturing method according to this embodiment. [Figure 7] FIG. 7 is a surface crack database in which surface crack data is recorded for the manufacturing condition categories of Cu content and horizontal rolling strain rate, with the heating extraction temperature set to 1130°C. DETAILED DESCRIPTION OF THE INVENTION

[0017] FIG. 1 is a schematic diagram showing the state of a slab 22 being rolled by horizontal rolling. FIG. 1(a) is a cross-sectional view showing the state of the slab 22 being rolled by horizontal rolling, and FIG. 1(b) is a top view showing the state of the slab 22 being rolled by horizontal rolling (the upper work roll 20 is not shown). FIG. 2 is a top view showing the state of the slab 22 being reduced in width. The mechanism of surface cracking caused by tramp elements will be explained using FIG. 1 and FIG. 2, taking Cu as an example.

[0018] Cu is less susceptible to oxidation than Fe, and its solid solubility in Fe is low (a few percent). Therefore, during the scale formation process in a heating furnace, Cu precipitates as a metallic phase at the interface between the scale and the base steel. Furthermore, the melting point of Cu is 1080°C, and in hot rolling, the steel billet 22 being rolled is heated to temperatures of 1080°C or higher. For this reason, during hot rolling, the liquid phase of molten Cu penetrates the grain boundaries of the base steel. In this state, large shear stresses and tensile stresses are applied by width reduction and horizontal rolling, causing surface cracks.

[0019] In horizontal rolling of a slab 22 shown in Figure 1, large shear stress 24 occurs at the position where contact with the work roll 20 begins, causing surface cracks 26 to form at that position. Furthermore, at the width edges, the material spreads in the width direction, causing tensile stress 25 in the rolling direction, causing surface cracks 26 to form at those positions as well. In width reduction of a slab 22 using width reduction dies 28 shown in Figure 2, tensile stress 25 occurs at the width edges, causing surface cracks 26 to form at those width edges.

[0020] On the other hand, in hot rolling, as disclosed in Non-Patent Document 2, the yield stress increases as the strain rate in the rolling process increases, and the yield stress decreases as the strain rate decreases. Therefore, even with the same reduction amount, if the strain rate in horizontal rolling and width reduction is slowed, the shear stress 24 and tensile stress 25 decrease, and the occurrence of surface cracks may be suppressed. Therefore, it can be seen that the strain rate affects the presence or absence of surface cracks in rolling processes including horizontal rolling and width reduction.

[0021] In this embodiment, "strain" is the logarithm of the sheet thickness ratio before and after rolling, and "strain rate" is the value obtained by dividing the strain by the time it takes for the sheet to pass through the contact length with the work roll 20. Strictly speaking, the strain rate becomes large locally at the position where contact with the work roll 20 begins. The maximum strain rate during rolling may be determined using numerical calculations such as finite element analysis, and this value may be used as the strain rate for the rolling process. Furthermore, "strain" during width reduction is the logarithm of the sheet width ratio before and after width reduction, and "strain rate" is the value obtained by dividing the strain by the time it takes for the sheet to contact the width reduction die 28. The strain rate during width reduction may also be determined using numerical calculations such as finite element analysis, as in rolling.

[0022] Regarding the heating temperature in the heating furnace, the melting point of Cu is approximately 1080°C, so if the slab temperature in the heating furnace is 1080°C or below, the concentrated Cu becomes solid and does not infiltrate the grain boundaries of the base steel, so surface cracks do not occur. Also, if the slab temperature in the heating furnace is 1200°C or above, the solubility of Cu in the base steel increases, reducing the amount of concentrated Cu, making surface cracks less likely to occur.

[0023] On the other hand, the surface temperature of the slab 22 decreases during the rolling process after the slab 22 is extracted from the heating furnace, reducing the solubility of Cu in the base steel. This reduces the concentration of supersaturated Cu, which can lead to surface cracks. Furthermore, as the slab 22 remains in the heating furnace for a longer period of time, the amount of Cu concentrated increases, making surface cracks more likely to occur. Thus, it can be seen that the heating temperature and the duration of stay in the heating furnace also affect the presence or absence of surface cracks.

[0024] Regarding the component contents of the steel slab 22, as the content of Cu, which acts as a tramp element, increases, the amount of Cu concentrated during the scale formation process increases, making it more likely to infiltrate into grain boundaries. Therefore, as the Cu content of the steel slab 22 increases, surface cracks are more likely to occur. Thus, it can be seen that the Cu content of the steel slab 22 also affects the presence or absence of surface cracks.

[0025] Furthermore, Ni is an element that increases the solubility of Cu in the base steel, while Sn is an element that decreases the solubility of Cu in the base steel. Therefore, the higher the Ni content and the lower the Sn content, the less likely surface cracks will occur. Therefore, it can be seen that the Ni content and Sn content of the steel slab 22 also affect the presence or absence of surface cracks.

[0026] Based on this mechanism of occurrence of surface cracks, the surface crack prediction method and surface crack prediction device according to this embodiment predict surface cracks in a steel strip caused by Cu, which is a tramp element. Hereinafter, an example will be described in which a surface crack prediction device 18 capable of implementing the surface crack prediction method according to this embodiment is applied to a steel strip manufacturing facility 100 that constitutes a hot rolling line.

[0027] The surface crack prediction device 18 according to this embodiment can be applied not only to the steel strip manufacturing equipment 100 but also to a thick plate manufacturing equipment for manufacturing thick steel plates and a hot rolling line directly connected to a thin slab continuous casting machine. In other words, the equipment to which the surface crack prediction device 18 according to this embodiment can be applied is not limited to the thickness of the steel strip 23 and the connection layout between the continuous casting machine and the steel strip manufacturing equipment 100.

[0028] 3 is a schematic diagram showing an example of a steel strip manufacturing facility 100 including a surface crack prediction device 18 capable of implementing the surface crack prediction method according to this embodiment. In this embodiment, a steel strip 23 is manufactured through a continuous casting process, a furnace heating process, and a rolling process. Therefore, the steel strip manufacturing facility 100 includes a continuous casting device 10 that performs the continuous casting process, a heating furnace 12 that performs the furnace heating process, a rolling mill 14 that performs the rolling process, a process computer 16, and a surface crack prediction device 18.

[0029] The continuous casting apparatus 10 is an apparatus that cools molten steel in a mold to form a billet, and cuts the billet to a predetermined length to produce a billet 22. The continuous casting apparatus 10 has a gas scarfing device that scarifies and removes impurities on the surface of the billet 22 using fuel gas and oxygen.

[0030] The heating furnace 12 is a device that heats a billet 22 to a target temperature. The billet 22 heated to the target temperature is width-reduced by a width reduction device to a billet 22 of a predetermined width. The width reduction device includes a sizing press that forges the billet 22 in the width direction using a pair of left and right dies, and an edger that rolls the billet 22 in the width direction using a pair of left and right work rolls. The billet 22 that has been width-reduced to the predetermined width is rolled by a horizontal rolling mill to a steel strip 23 of a predetermined thickness. The horizontal rolling mill is a device that rolls in the thickness direction using a pair of upper and lower work rolls. The rolling mill 14 according to this embodiment includes a width reduction device that width-reduces the billet 22 to a predetermined width, and a horizontal rolling mill that rolls the billet 22 into a steel strip 23 of a predetermined thickness.

[0031] The process computer 16 is, for example, a general-purpose computer such as a workstation or a personal computer. The process computer 16 is connected to each device of the steel strip manufacturing facility 100 by wire or wirelessly, and controls the manufacturing process of the steel strip 23. The process computer 16 stores manufacturing conditions for operating the continuous casting apparatus 10, the heating furnace 12, and the rolling mill 14. The process computer 16 also collects and stores the elemental contents of the billet 22 manufactured by the continuous casting apparatus 10 and measurement values ​​measured during the operation of each device. The elemental contents of the billet 22 stored in the process computer 16 may be the elemental contents of molten steel measured in the steelmaking process.

[0032] In the steel strip 23 manufactured using such steel strip manufacturing equipment 100, surface cracks caused by Cu as described above may occur after rolling. These surface cracks occur when the liquid phase of molten Cu penetrates into the grain boundaries of the base steel, and in this state, large shear stresses and tensile stresses act on the surface in the rolling device 14.

[0033] The presence or absence of surface cracks on the front and back sides of the steel strip 23 after rolling is determined over the entire width and length, and the determination results are stored as surface crack data in the process computer 16. Surface cracks on the steel strip 23 may be detected, for example, by an image recognition method using a two-dimensional area camera, or may be detected visually by an operator.

[0034] Surface cracks of the steel strip 23 may be detected by detecting the presence or absence of surface cracks, or by detecting whether the number of surface cracks or the size of the surface cracks exceeds an allowable value. In other words, the detection criteria for surface cracks of the steel strip 23 may be changed depending on the quality required for the steel strip 23 to be manufactured.

[0035] The surface crack prediction device 18 predicts surface cracks of a steel strip 23 to be manufactured using the steel strip manufacturing equipment 100. The surface crack prediction device 18 acquires the Cu content of the steel billet 22, the heating temperature in the furnace heating process, and the set value of the strain rate in the rolling process for the steel strip 23 to be manufactured from the process computer 16. The surface crack prediction device 18 refers to a surface crack database created in advance, and predicts surface cracks of the steel strip 23 by referring to surface crack data for the manufacturing condition category that includes the acquired set values ​​of the Cu content, heating temperature, and strain rate.

[0036] Furthermore, it is preferable that the surface crack prediction device 18 specifies a strain rate in the rolling process at which it is predicted that there will be no surface cracks in the produced steel strip 23. The surface crack prediction device 18 outputs a strain rate equal to or lower than the specified strain rate in the rolling process to the process computer 16 in order to set a strain rate equal to or lower than the specified strain rate as a production condition for the rolling process.

[0037] Next, we will explain the surface crack prediction device 18 that predicts surface cracks in the steel strip 23. Figure 4 is a schematic diagram showing an example configuration of the surface crack prediction device 18. The surface crack prediction device 18 is, for example, a general-purpose computer such as a workstation or a personal computer. The surface crack prediction device 18 has a control unit 30, an input unit 32, an output unit 34, and a storage unit 36. The control unit 30 is, for example, a CPU, and functions as an acquisition unit 38, a surface crack prediction unit 40, and a manufacturing condition identification unit 42 by executing a program stored in the storage unit 36.

[0038] The input unit 32 is, for example, a keyboard, a touch panel integrated with a display, etc. The output unit 34 is, for example, an LCD or CRT display, etc. The storage unit 36 ​​is, for example, an information recording medium such as an updatable flash memory, a built-in hard disk or a memory card connected via a data communication terminal, and a read / write device for the same.

[0039] The storage unit 36 ​​stores programs and data for realizing each function of the surface crack prediction device 18. The storage unit 36 ​​also stores a surface crack database 44. The surface crack database 44 is a database in which surface crack data of steel strips 23 manufactured in the past is recorded for manufacturing condition categories, which are divided into multiple categories for the Cu content of the steel billet 22, the heating temperature in the furnace heating process, and the strain rate in the rolling process. The surface crack data is binary data indicating the presence or absence of surface cracks in steel strips manufactured in the past (○: no surface cracks / ×: surface cracks present). The surface crack database 44 is created in advance and stored in the storage unit 36.

[0040] Here, the surface crack database 44 will be described. FIG. 5 is a schematic diagram showing a portion of the surface crack database 44. The surface crack database shown in FIG. 5(a) records surface crack data of steel strips 23 previously manufactured for the manufacturing condition categories of Cu content and heating temperature when the manufacturing condition category of strain rate is 8 to 10. In FIG. 5(a), the manufacturing condition of Cu content is divided into 0.05 mass% increments in the range of 0.10 to 0.35 mass%, and the manufacturing condition of heating temperature is divided into 50°C increments in the range of 950 to 1200°C. In the example shown in FIG. 5, the heating temperature is the surface temperature of the steel billet 22 extracted from the heating furnace 12 (hereinafter referred to as the heating furnace extraction temperature).

[0041] The surface crack database shown in Figure 5(b) contains surface crack data for steel strips 23 previously manufactured for the range of strain rates from 10 to 12, and for the manufacturing condition categories of Cu content and heating temperature. The manufacturing condition categories of Cu content and heating temperature are the same as those in Figure 5(a).

[0042] In addition, when there are multiple surface crack data included in the same manufacturing condition category and the results of the surface cracks are different, it may be marked as "○" if no surface cracks occurred for a predetermined N% or more. Also, when there are multiple surface crack data included in the same manufacturing condition category, it may be marked as "×" if there is even one surface crack data that indicates that a surface crack occurred.

[0043] The size of the division of each manufacturing condition in the surface crack database 44 may be changed depending on the manufacturing condition record of steel strips 23 manufactured in the past, and for example, the division of the manufacturing conditions may be narrowed so that there is one surface crack data for one manufacturing condition of the steel strip 23. In constructing the surface crack database 44, it is preferable to use 1,000 or more manufacturing examples of steel strips 23 manufactured in the past.

[0044] Next, the processing of the acquisition unit 38 and the surface crack prediction unit 40 will be described. To predict surface cracks in the steel strip 23, the acquisition unit 38 acquires information indicating the Cu content of the steel billet 22, the heating temperature in the furnace heating process, and the set value of the strain rate in the rolling process from the process computer 16. The heating temperature in the furnace heating process is, for example, the heating furnace extraction temperature.

[0045] The acquisition unit 38 outputs information indicating the Cu content of the steel billet 22, the heating temperature of the furnace heating process, and the set values ​​of the strain rate of the rolling process acquired from the process computer 16 to the surface crack prediction unit 40. Upon acquiring the information from the acquisition unit 38, the surface crack prediction unit 40 reads the surface crack database 44 from the storage unit 36 ​​and identifies a manufacturing condition category in the surface crack database 44 that includes the set values ​​of the Cu content, heating temperature, and strain rate. The surface crack prediction unit 40 predicts surface cracks in the steel strip 23 to be manufactured using the surface crack data recorded in the identified manufacturing condition category. The surface crack prediction unit 40 may also output the surface crack data recorded in the identified manufacturing condition category to the output unit 34 and display it on the output unit 34. This allows an operator to visually check the output unit 34 to confirm the presence or absence of surface cracks in the steel strip to be manufactured.

[0046] Next, the processing of the manufacturing condition specifying unit 42 will be described. The manufacturing condition specifying unit 42 specifies the manufacturing conditions under which the surface crack prediction unit 40 predicts that the steel strip will not have surface cracks. The manufacturing condition specifying unit 42 outputs the conditions to the process computer 16, thereby setting them as manufacturing conditions for the steel strip manufacturing equipment 100. Below, the processing by the manufacturing condition specifying unit 42 will be described using an example in which the manufacturing condition specifying unit 42 specifies the strain rate of the rolling device 14.

[0047] 6 is a flow diagram showing an example of the surface crack prediction method and steel strip manufacturing method according to this embodiment. The flow shown in FIG. 6 is started, for example, by receiving an input from an operator via the input unit 32 to start the processing.

[0048] First, the acquisition unit 38 acquires information indicating the Cu content of the steel billet 22, the heating temperature in the furnace heating process, and the set value of the strain rate in the rolling process for the steel strip 23 to be manufactured from the process computer 16 (step S101). The acquisition unit 38 outputs the acquired information to the surface crack prediction unit 40.

[0049] The surface crack prediction unit 40 reads the surface crack database 44 from the storage unit 36 ​​and identifies a manufacturing condition category that includes the set values ​​of the Cu content, heating temperature, and strain rate in the surface crack database 44. The surface crack prediction unit 40 predicts surface cracks in the steel strip 23 to be manufactured by referring to the surface crack data recorded in the identified manufacturing condition category (step S102). The surface crack prediction unit 40 outputs the surface crack prediction result to the manufacturing condition identification unit 42.

[0050] The manufacturing condition specifying unit 42 determines whether it is predicted that the steel strip 23 to be manufactured will have no surface cracks (step S103). If the acquired prediction result of surface cracks indicates that there will be no surface cracks (step S103: Yes), the manufacturing condition specifying unit 42 specifies the acquired set value of the strain rate for the rolling process as a strain rate that will not cause surface cracks to occur in the steel strip 23 (step S104).

[0051] Since the slower the strain rate, the less likely surface cracks are to occur, the manufacturing condition specification unit 42 outputs a strain rate equal to or lower than the specified strain rate for the rolling process to the process computer 16 (step S105). This allows the specified strain rate for the rolling process to be reflected in the manufacturing conditions of the steel strip manufacturing equipment 100. The steel strip 23 is then manufactured under manufacturing conditions that reflect the strain rate (step S106), and the flow shown in FIG. 6 ends. Note that if the determination of step S103: Yes is made the first time through the processing of step S103, the strain rate is not changed, and the processing of steps S104 to S106 may be skipped. By manufacturing the steel strip 23 in this manner, the steel strip 23 can be manufactured under manufacturing conditions that include a strain rate equal to or lower than the strain rate predicted to result in no surface cracks in the steel strip, thereby making it possible to manufacture the steel strip 23 while suppressing surface cracks.

[0052] On the other hand, if the acquired prediction result of surface cracks indicates the presence of surface cracks (step S103: No), the manufacturing condition identification unit 42 changes the set value of the strain rate in the direction of slowing the strain rate in the rolling process (step S107). The change of the strain rate is performed by changing the set value of the strain rate in the surface crack database 44 so that the manufacturing condition classification of the strain rate is slowed by one classification ("2" in the example shown in FIG. 5).

[0053] The surface crack prediction unit 40 and the manufacturing condition determination unit 42 execute the processes of steps S102 and S103 again using the changed strain rate setting value. This process is repeated until it is determined in the process of step S103 that there are no surface cracks. This allows the manufacturing condition determination unit 42 to determine the strain rate of the rolling process at which the steel strip 23 is predicted to have no surface cracks.

[0054] If the prediction result indicates that surface cracks will be present at all strain rates in the surface crack database 44, the manufacturing condition identification unit 42 may identify a strain rate obtained by multiplying the slowest strain rate among all strain rates by, for example, 0.9. Alternatively, if the prediction result indicates that surface cracks will be present at all strain rates in the surface crack database 44, the output unit 34 may display a message indicating that the strain rate cannot be identified or an error message. After performing such processing, the flow shown in FIG. 6 ends.

[0055] As explained above, by using the surface crack prediction device 18 and surface crack prediction method according to this embodiment, it becomes possible to predict surface cracks in a steel strip 23 after rolling. Furthermore, by specifying a strain rate at which no surface cracks are predicted using the surface crack prediction method and producing the steel strip 23 under operating conditions that include a strain rate equal to or lower than this strain rate, it becomes possible to produce the steel strip 23 while suppressing the occurrence of surface cracks.

[0056] The embodiments of the present invention are not limited to the above-described embodiments and may be modified in various ways. Fig. 5 shows an example of a surface crack database 44 in which surface crack data is recorded under manufacturing condition categories that are divided into multiple categories for strain rate, Cu content, and heating temperature, but the present invention is not limited to this. In addition to the above-described manufacturing condition categories, the surface crack database 44 may also include manufacturing condition categories that are divided into multiple categories for continuous casting conditions. The manufacturing condition categories for continuous casting conditions are, for example, manufacturing condition categories that are divided into multiple categories for whether or not the surface of the billet 22 is subjected to surface scrubbing by a gas scarfing device performed in the continuous casting apparatus 10, the scrubbing speed, and the surface temperature of the billet 22 at the start of scrubbing.

[0057] When the surface of the billet 22 is scalded by the gas scarfing device, the surface temperature of the billet 22 rises, making it easier for scale to form. The formation of this scale makes it easier for Cu to infiltrate into grain boundaries, which promotes surface cracking during the rolling process. In this way, whether or not the surface of the billet 22 is scalded by the gas scarfing device affects the presence or absence of surface cracks. For this reason, by adding two manufacturing condition categories corresponding to the presence or absence of surface scalding to the surface crack database 44, it becomes possible to predict surface cracks in the steel strip 23 with even greater accuracy.

[0058] If the cutting speed is slow, the surface temperature of the steel billet 22 after cutting becomes high, making it easier for scale to form. The formation of this scale makes it easier for Cu to infiltrate into grain boundaries, which promotes surface cracks during the rolling process. In this way, the cutting speed affects the presence or absence of surface cracks, so by adding manufacturing condition categories that divide the cutting speed into multiple categories to the surface crack database 44, it becomes possible to predict surface cracks in the steel strip 23 with even higher accuracy.

[0059] If the surface temperature of the steel billet 22 at the start of the laser cutting is high, it will be more likely to oxidize after the laser cutting. The formation of this scale makes it easier for Cu to infiltrate into grain boundaries, which promotes surface cracks during the rolling process. In this way, the surface temperature of the steel billet 22 at the start of the laser cutting affects the presence or absence of surface cracks. For this reason, by adding manufacturing condition classifications that divide the surface temperature of the steel billet 22 at the start of the laser cutting into multiple categories to the surface crack database 44, it will be possible to predict surface cracks in the steel strip 23 with even greater accuracy.

[0060] 5 shows an example of a surface crack database 44 in which surface crack data is recorded for manufacturing condition categories that are divided into multiple categories for strain rate, Cu content, and heating temperature, but the present invention is not limited to this. The surface crack database 44 may further include, in addition to the Cu content, the Ni content and / or the Sn content as the component contents of the steel billet 22.

[0061] As described above, Ni is an element that increases the solubility of Cu in the base steel, and Sn is an element that decreases the solubility of Cu in the base steel. Therefore, the contents of these elements also affect the presence or absence of surface cracks, so by adding manufacturing condition categories that divide the Ni content and / or Sn content into multiple categories to the surface crack database 44, it becomes possible to predict surface cracks in the steel strip 23 with even higher accuracy. Note that the crack component crack index calculated by the following formula (1) may be used as the component content of the steel billet 22.

[0062] Cracking component index = Cu content (mass%) + 10 × Sn content (mass%) - Ni content (mass%) (1)

[0063] 6, an example has been shown in which the presence or absence of surface cracks is predicted under the manufacturing conditions of the steel strip 23, and the strain rate in the rolling process at which no surface cracks are predicted is specified, but this is not limiting. In the processing of step S102, the surface crack prediction unit 40 may predict surface cracks for all strain rates in the manufacturing condition classification of Cu content and heating temperature for the steel strip 23 to be manufactured.

[0064] The manufacturing condition specifying unit 42 may then specify the fastest strain rate among all strain rates predicted to result in no surface cracks, and reflect strain rates equal to or lower than the specified strain rate in the manufacturing conditions of the steel strip 23. This makes it possible to suppress the occurrence of surface cracks while also improving the productivity of the steel strip 23.

[0065] Furthermore, when it is predicted that the steel strip 23 to be manufactured will not have surface cracks at all strain rates in the manufacturing condition category of Cu content and heating temperature, a strain rate may be specified that is the fastest strain rate among all strain rates multiplied by 1.1. By reflecting strain rates equal to or lower than the specified strain rate in the manufacturing conditions of the steel strip manufacturing equipment 100, the productivity of the steel strip 23 can be further improved.

[0066] In the description of this embodiment, the surface temperature of the billet 22 extracted from the heating furnace 12 is used as the heating temperature in the furnace heating process, but this is not limiting. Instead of or in addition to the surface temperature of the billet 22 extracted from the heating furnace 12, the residence time of the billet 22 in the heating furnace 12 or the reduction temperature may be acquired as the heating temperature in the furnace heating process. The reduction temperature is the surface temperature of the material in the rolling process. A lower reduction temperature increases stress during the rolling process even with the same reduction amount, making surface cracks more likely to occur. Therefore, the reduction temperature also affects the presence or absence of surface cracks.

[0067] In the description of this embodiment, an example has been shown in which the steel strip manufacturing equipment 100 has a process computer 16 and a surface crack prediction device 18, but this is not limited to this. For example, the process computer 16 may have the function of the surface crack prediction device 18, and these may be configured as a single device. Furthermore, the surface crack prediction device 18 may be directly connected to the continuous casting device 10, the heating furnace 12, and the rolling device 14 by wire or wirelessly, and the acquisition unit 38 may directly acquire the operating conditions from these devices.

[0068] In the description of this embodiment, an example has been shown in which the control unit 30 of the surface crack prediction device 18 shown in Figure 3 has an acquisition unit 38, a surface crack prediction unit 40, and a manufacturing condition identification unit 42, but this is not limited to this. For example, if information indicating the Cu content of the steel billet 22, the heating temperature in the furnace heating process, and the strain rate in the rolling process is stored in the storage unit 36, the control unit 30 may not have the acquisition unit 38, and the surface crack prediction unit 40 may read out the information from the storage unit 36. Furthermore, if the surface crack prediction device 18 predicts surface cracks in the steel strip 23 to be manufactured, the control unit 30 may not have the manufacturing condition identification unit 42. [Example]

[0069] Example 1 Next, Example 1 will be described, in which surface cracks were confirmed in a steel strip produced by heating a steel billet cast by a continuous casting machine in three heating furnaces and rolling it in a rolling mill having one width reduction device, three roughing mills, and seven finishing mills. In Example 1, 1,000 steel strips having the chemical composition shown in Table 1 below were produced under various production conditions, and the presence or absence of surface cracks in the produced steel strips was confirmed. Using these results, a surface crack database was created.

[0070] [Table 1]

[0071] In Example 1, the Cu content and the furnace extraction temperature were used as manufacturing conditions, and the relationship between these manufacturing conditions and surface cracking was confirmed. In Example 1, the Ni content was set to 0.10 to 0.12 mass%, the Sn content was set to 0.019 to 0.020 mass%, and the furnace time was set to 160 to 180 min, which were limited to manufacturing conditions within a range in which the influence on surface cracking was considered to be similar. In the surface crack database, the Cu content was divided into categories in increments of 0.05 mass%, and the furnace extraction temperature was divided into categories in increments of 50°C.

[0072] The surface crack database shown in Figures 5(a) and (b) is a part of the surface crack database of Example 1. The strain rates in Figures 5(a) and (b) are the set values ​​of the strain rate for horizontal rolling, and the set value of the strain rate for the first pass of the roughing mill was used. As shown in Figures 5(a) and (b), it can be seen that the area with surface cracks (area marked with an "x") varies depending on the Cu content, the heating furnace extraction temperature, and the strain rate. Specifically, it was confirmed that the higher the Cu content, the higher the heating furnace extraction temperature, and the faster the strain rate, the more likely surface cracks are to occur. It was confirmed that surface cracks can be predicted by using a database using these manufacturing conditions.

[0073] In addition, a database was constructed using the manufacturing results of the 1,000 steel strips shown above, with the heating furnace extraction temperature set to 1,130°C. Figure 7 shows the surface crack database in which surface crack data is recorded for the manufacturing condition categories of Cu content and horizontal rolling strain rate, with the heating extraction temperature set to 1,130°C.

[0074] When a steel strip was manufactured with a strain rate of 8, referring to the surface crack data for the manufacturing condition category with a Cu content of 0.22 mass%, no surface cracks occurred on the manufactured steel strip. On the other hand, when a steel strip was manufactured with a strain rate of 10, surface cracks occurred on the manufactured steel strip.

[0075] Furthermore, in the manufacturing condition category with a Cu content of 0.10 mass%, no surface cracks were observed at any strain rate. Therefore, when a steel strip was manufactured at a strain rate obtained by multiplying the fastest strain rate (11) of all strain rates in that manufacturing condition category by 1.1, no surface cracks were observed in the manufactured steel strip.

[0076] Furthermore, in the manufacturing condition category with a Cu content of 0.25 mass%, surface cracks were observed at all strain rates. Therefore, when a steel strip was manufactured using a strain rate obtained by multiplying the slowest strain rate (8) of all strain rates in that manufacturing condition category by 0.9, surface cracks occurred in the manufactured steel strip.

[0077] Using these results, the surface crack database was updated, and steel strips were again manufactured using a strain rate obtained by multiplying the slowest strain rate (7.2) in the manufacturing condition category for the same Cu content by 0.9.No surface cracks occurred in the manufactured steel strips.

[0078] Furthermore, when the strain rate for the manufacturing conditions of a heating furnace extraction temperature of 1180°C was set using the surface crack database for a heating furnace extraction temperature of 1130°C, surface cracks occurred in the manufactured steel strip. In contrast, when the strain rate for the manufacturing conditions of a heating furnace extraction temperature of 1180°C was set using the surface crack database for a heating furnace extraction temperature of 1180°C, no surface cracks occurred in the manufactured steel strip.

[0079] These results confirmed that it is possible to predict surface cracks in steel strips after rolling by using a surface crack database that records surface crack data for manufacturing condition categories divided into multiple categories for Cu content, heating furnace extraction temperature, and horizontal rolling strain rate. Furthermore, when the components listed in Table 1 were checked to see which have an effect on surface cracks, no effect on surface cracks was confirmed for components other than Cu, Ni, and Sn.

[0080] <Example 2> Next, Example 2 will be described in which steel strips having the chemical compositions shown in Table 2 below were produced under various production conditions using the same equipment as in Example 1, and the presence or absence of surface cracks in the produced steel strips was confirmed.

[0081] [Table 2]

[0082] In Example 2, the manufacturing conditions used were the time spent in the heating furnace, the heating furnace extraction temperature, the crack component index, and the set values ​​of the strain rate in the width reduction process, and the effects of these manufacturing conditions on surface cracks were confirmed. The manufacturing conditions of the steel strip and the results of the presence or absence of surface cracks are shown in Table 3 below. The crack component index in Table 3 is a value calculated using the following formula (1).

[0083] Cracking component index = Cu content (mass%) + 10 × Sn content (mass%) - Ni content (mass%) (1)

[0084] [Table 3]

[0085] As shown in Table 3, a comparison of Production Example No. 2 and Production Example No. 5 confirmed that the longer the residence time in the heating furnace, the more likely surface cracks were to occur. A comparison of Production Example No. 1 and Production Example No. 6 confirmed that the higher the extraction temperature from the heating furnace, the more likely surface cracks were to occur. These results confirmed that the use of the residence time and / or the extraction temperature from the heating furnace as the heating temperature in the furnace heating process can predict surface cracks in the steel strip after rolling.

[0086] Regarding the cracking component index, a comparison of Production Examples No. 1 to 4 confirmed that the larger the cracking component index, the more likely surface cracking occurs. From these results, it was confirmed that the surface cracking of steel strips after rolling can be predicted by using not only the Cu content but also the Cu, Ni, and Sn contents as the component contents of steel billets.

[0087] Regarding the strain rate (width reduction process), a comparison of Production Example No. 1 and Production Example No. 7, and Production Example No. 2 and Production Example No. 8 confirmed that the faster the strain rate in the width reduction process, the more likely surface cracks are to occur. From these results, it was confirmed that the set value of the strain rate in the width reduction process, as well as the strain rate in the horizontal rolling, can be used as the strain rate in the rolling process, and that this makes it possible to predict surface cracks in the steel strip after rolling. [Explanation of symbols]

[0088] 10 Continuous casting equipment 12 Furnace 14 Rolling mill 16 Process Computer 18 Surface crack prediction device 20 Work Rolls 22 Steel billet 23 Steel strip 24 Shear Stress 25 Tensile stress 26 Surface cracks 28 Width reduction die 30 Control Unit 32 Input section 34 Output section 36 Storage area 38 Acquisition Department 40 Surface crack prediction section 42 Manufacturing condition specification department 44 Surface Crack Database

Claims

1. A surface crack prediction method for predicting surface cracks in a steel strip produced by subjecting a steel slab cast in a continuous casting process to a furnace heating process and a rolling process, comprising: a surface crack database is created in which surface crack data indicating the presence or absence of surface cracks for steel strips previously manufactured is recorded for each of a plurality of manufacturing condition categories, which are obtained by dividing the component contents of the steel billet, the heating temperature in the furnace heating step, and the strain rate in the rolling step into a plurality of categories; The content of Cu is used as the component content of the steel slab, A surface crack prediction method that identifies a manufacturing condition category for a steel strip to be manufactured that includes the component content, the heating temperature, and the strain rate, and predicts surface cracks in the steel strip to be manufactured by referring to surface crack data recorded in the identified manufacturing condition category in the surface crack database.

2. 2. The method for predicting surface cracks according to claim 1, further comprising using a Ni content and / or a Sn content as the component contents of the steel billet.

3. The surface crack database further includes manufacturing condition classifications into which continuous casting conditions in the continuous casting process are classified into a plurality of categories, 3. A surface crack prediction method according to claim 1, wherein a manufacturing condition category including the component content of the steel strip to be manufactured, the heating temperature in the furnace heating process, the strain rate in the rolling process, and the continuous casting conditions is identified to predict surface cracks in the steel strip.

4. A method for manufacturing a steel strip using the surface crack prediction method according to claim 1 or 2, A method for manufacturing a steel strip, comprising: specifying a strain rate at which no surface cracks are predicted to occur in a manufacturing condition category that includes the component contents and heating temperatures of the steel strip to be manufactured; and carrying out the rolling process at a strain rate equal to or lower than the specified strain rate to manufacture the steel strip.

5. A method for manufacturing a steel strip using the surface crack prediction method according to claim 3, A method for manufacturing a steel strip, comprising: specifying a strain rate at which no surface cracks are predicted to occur in a manufacturing condition category including the component contents, the heating temperature, and the continuous casting conditions for the steel strip to be manufactured; and carrying out the rolling process at a strain rate equal to or lower than the specified strain rate to manufacture the steel strip.

6. A method for manufacturing a steel strip using the surface crack prediction method according to claim 1 or 2, A method for manufacturing a steel strip, comprising: identifying a range of manufacturing condition categories for strain rates in which surface crack data indicating the absence of surface cracks is recorded in a manufacturing condition category that includes the component contents and heating temperatures for the steel strip to be manufactured; and carrying out the rolling process at a strain rate that is equal to or lower than the fastest strain rate among the strain rates in the range of the identified manufacturing condition category to manufacture the steel strip.

7. A method for manufacturing a steel strip using the surface crack prediction method according to claim 3, A method for manufacturing a steel strip, comprising: identifying a range of manufacturing condition categories for strain rates in which surface crack data indicating the absence of surface cracks is recorded in a manufacturing condition category that includes the component contents, the heating temperature, and the continuous casting conditions for the steel strip to be manufactured; and carrying out the rolling process at a strain rate that is equal to or lower than the fastest strain rate among the strain rates in the range of the identified manufacturing condition category to manufacture the steel strip.

8. A surface crack prediction device that uses a surface crack database to predict surface cracks in a steel strip that is produced by subjecting a steel slab cast in a continuous casting process to a furnace heating process and a rolling process, the surface crack database is a database in which surface crack data indicating the presence or absence of surface cracks in steel strips manufactured in the past is recorded for manufacturing condition classifications in which the component contents of the steel billet, the heating temperature in the furnace heating process, and the strain rate in the rolling process are classified into a plurality of classifications, and The component contents of the steel billet include a Cu content, A surface crack prediction device having a surface crack prediction unit that identifies a manufacturing condition category for the steel strip to be manufactured that includes the component content, the heating temperature, and the strain rate of the rolling process, and predicts surface cracks in the steel strip to be manufactured using the surface crack data recorded in the identified manufacturing condition category in the surface crack database.

9. The surface crack prediction device according to claim 8 , wherein the component contents of the steel billet further include a Ni content and / or a Sn content.

10. The surface crack database further includes manufacturing condition classifications into which continuous casting conditions in the continuous casting process are classified into a plurality of categories, The surface crack prediction device according to claim 8 or claim 9, wherein the surface crack prediction unit identifies a manufacturing condition category that includes the component content, the heating temperature, the strain rate, and the continuous casting conditions of the steel strip to be manufactured.

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