Dimensional change characteristic prediction method for steel material, steel ingot manufacturing method and hot working material manufacturing method

Abstract

To provide a dimensional change characteristic prediction method capable of predicting dimensional change characteristics in a stage of steel ingot even without hardening / tempering of a steel material.SOLUTION: A dimensional change characteristic prediction method for steel includes: a dimensional change characteristic acquisition step of collecting a sample from a steel material obtained by subjecting hardening / tempering to a hot working material obtained by subjecting hot working to steel ingot, to measure dimensional change characteristics; an element mapping data collection step of measuring the sample collected from an internal texture of the steel ingot with an X-ray analyzer to obtain element mapping data of a matrix composition; and a segregation ratio derivation step of deriving a segregation ratio of each element in the steel ingot from the element mapping data. In the segregation ratio derivation step, the segregation ratio is derived from a segmentation maximum value / a segmentation minimum value in a solidified cell, which is derived from a diagram combining detection intensity and a detection frequency for the element, to evaluate correlation between the segmentation ratio and the dimensional change characteristics.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a method for predicting dimensional change characteristics of a steel material, a method for manufacturing a steel ingot, and a method for manufacturing a hot-worked material. [Background technology]

[0002] Die steel used in the bending, drawing, and punching of plate materials is generally manufactured by annealing, cutting, quenching, and tempering. Dimensional change (variation) is known to be an issue that occurs during this quenching and tempering process, and since large dimensional change leads to an increase in the number of processing steps after heat treatment, various studies have been conducted to suppress dimensional change.

[0003] Patent Document 1 discloses that heat treatment dimensional deformation that occurs after quenching and tempering can also be suppressed by reducing segregation, and employs a "segregation index K" that combines the solid / liquid phase concentration distribution rate of each element and the change in specific gravity, and optimally adjusts this value to reduce segregation and suppress dimensional deformation.

[0004] Patent Document 2 describes a cold die steel with excellent dimensional change controllability, which has been developed by reducing primary carbides and adding appropriate amounts of Ni, Al, and Cu to a chemical composition that can suppress dimensional change as much as possible within a range that satisfies various properties. According to the invention of Patent Document 2, Ni and Al form intermetallic compounds that precipitate during tempering (aging) in the secondary hardening region of the tool steel, thereby suppressing dimensional change in the contraction direction and offsetting expansion during heat treatment.

[0005] Furthermore, Patent Document 3 proposes a technique using Ms point distribution as a method for evaluating dimensional change characteristics. Specifically, the method disclosed includes the steps of measuring the surface of a mold steel with an electron beam microanalyzer to obtain mapping data of the matrix composition, obtaining mapping data of Ms points from the mapping data of the matrix composition, binarizing the mapping data of the Ms points, and performing principal component analysis on the binarized mapping data of the Ms points to obtain the dimensional change characteristics of the steel surface from images of the obtained first and second principal components, thereby evaluating the relationship between the first and second principal components.

[0006] Furthermore, Non-Patent Document 1 reports an example of an evaluation of the segregation ratio by analyzing carbon (C) through line analysis by the electron probe method in the as-cast structure of 1 mass% C-1.5 mass% Cr steel, and Non-Patent Document 2 discloses a scatter plot (variance analysis) based on the intensity of a composition image taken by EPMA. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-152356 [Patent Document 2] Japanese Patent Application Laid-Open No. 2006-169624 [Patent Document 3] International Publication No. 2023 / 181435 [Non-patent literature]

[0008] [Non-Patent Document 1] RDDoherty,DAMelford:SOLIDIFICATION AND MICROSEGREGATION IN KILLED STEEL INGOTS WITH PARTICULAR REFERENCE TO 1 PER CENT C, 1 1 / 2 PER CENT CR STEEL,IRON STEEL INSTITUTE Journal, 1966, 204: 1131-1143. [Non-patent document 2] R. Smith: Microsegregation measurement: methods and applications. Metallurgical and Materials Transactions B, 2018, 49.6: 3258-3279. Summary of the Invention [Problem to be solved by the invention]

[0009] As described in Patent Documents 1 and 2, dimensional deformation characteristics can be resolved by suppressing elemental segregation. However, variations in dimensional deformation characteristics can be observed even with the same alloy composition. This is partly due to the fact that each element has a different impact on dimensional deformation, and it took time to determine which elemental species should be focused on to improve segregation. Furthermore, when evaluating heat treatment dimensional deformation, it was necessary to actually quench and temper forged steel material, evaluate the rectangular parallelepiped dimensions (thickness, width, length) equivalent to the mold after quenching and tempering, and select the optimal alloy steel composition, which required a lot of work.

[0010] The evaluation method described in Patent Document 3 is an excellent invention that can accurately evaluate dimensional change characteristics using a new index called the Ms point distribution. However, this characteristic can only be determined by evaluating the anisotropy of dimensional change during heat treatment after quenching and tempering, after forging a steel block (slab, ingot) with a pre-adjusted alloy.

[0011] The evaluation method described in Non-Patent Document 1 performs line analysis within the range of measurement variation, and this evaluation method requires a lot of labor. Furthermore, the method described in Non-Patent Document 2 states that it is useful for identifying trends in separation behavior and identifying complex factors such as second phases and phase transformations during solidification, but does not disclose the specific method. Therefore, an object of the present invention is to provide a method for predicting dimensional change characteristics that can predict dimensional change characteristics at the steel ingot stage without quenching and tempering the steel material. [Means for solving the problem]

[0012] The present invention has been made in view of the above-mentioned problems. That is, one aspect of the present invention is a method for predicting the dimensional change characteristics of steel, comprising: a dimensional change characteristic acquisition step of collecting a sample from a steel material obtained by hot working a steel ingot or by quenching and tempering the hot-worked material, and measuring the dimensional change characteristics; an elemental mapping data acquisition step of measuring a sample collected from the internal structure of the steel ingot using an X-ray analyzer to obtain elemental mapping data of the matrix composition; and a segregation ratio derivation step of deriving the segregation ratio of each element in the steel ingot from the elemental mapping data, wherein the segregation ratio derivation step derives the segregation ratio from the maximum segregation value / minimum segregation value in a solidification cell, which is derived from a diagram combining the detection intensity and frequency of elements, and evaluates the correlation between the segregation ratio and the dimensional change characteristics. Another aspect of the present invention is a method for producing a steel ingot, in which the segregation ratio of the steel ingot is controlled based on the results of the dimensional change characteristic prediction. Another aspect of the present invention is a method for producing a hot-worked material, comprising a hot-working step of hot-working the steel ingot. [Effects of the Invention]

[0013] According to the present invention, it is possible to predict the dimensional change characteristics at the steel ingot stage without quenching and tempering the steel material. [Brief explanation of the drawings]

[0014] [Figure 1]FIG. 1 is a diagram showing a method for estimating the minimum and maximum values ​​of segregation. [Figure 2] FIG. 1 is a graph showing the relationship between the Mo content and dimensional change during heat treatment. [Figure 3] FIG. 1 is a graph showing the relationship between the Cr content and dimensional change during heat treatment. [Figure 4] FIG. 1 is a graph showing the relationship between the Si content and dimensional change during heat treatment. [Figure 5] FIG. 1 is a diagram showing the measurement results of the segregation ratio for samples Std, CrL, and CrH, and three times the standard specimen deviation of the dimensional change rate. [Figure 6] FIG. 1 shows the measurement results of the segregation ratio for all samples and three times the standard specimen deviation of the dimensional change rate. DETAILED DESCRIPTION OF THE INVENTION

[0015] Hereinafter, an embodiment of the present invention will be described. <Dimensional change characteristics acquisition process> The prediction method of this embodiment includes a dimensional change characteristic acquisition step of manufacturing a hot-worked material, collecting a sample, quenching and tempering the sample, and measuring the dimensional change characteristic. Note that in this embodiment, "hot-worked material" refers to a material obtained by hot forging and annealing a steel ingot obtained by a melting step, and "steel" refers to a material obtained by quenching and tempering the hot-worked material. The hot-worked materials prepared here include hot-worked materials having standard compositions (target compositions) among the steels of interest, as well as multiple hot-worked materials in which the element contents are intentionally adjusted to be higher or lower than the target composition, for example, within a range of ±10% to ±50%. The elements whose contents are adjusted to be higher or lower than the target composition are selected from the main constituent elements of the hot-worked material. Elements with large fluctuations in dimensional deformation characteristics may be narrowed down in advance through preliminary experiments or simulations, and the contents of these elements may be adjusted to be higher or lower than the target composition. The steel types to which the present invention can be applied are not particularly limited, and the present invention can be applied to, for example, cold die steels and hot die steels in which heat treatment dimensional deformation is likely to be a problem.

[0016] Next, characteristic evaluation samples are taken from the resulting hot-worked material, and the dimensional change characteristics of each sample are measured. In this embodiment, the dimensional change characteristics are measured by cutting a rectangular or cuboid sample from the hot-worked material after the sample's temperature has cooled to room temperature or after annealing, and measuring the lengths of each side (L, W, and T directions). The sample is then quenched and tempered, and after the sample temperature has cooled to room temperature, the lengths of each side are measured again, and the dimensional change rate is calculated from the sample lengths before and after quenching and tempering. Here, the dimensional change rate can be calculated as (LB - LA) / LA, where LA is the sample length before quenching and tempering, and LB is the sample length after quenching and tempering. After calculating the dimensional change rates of the three sides in the length (L), width (W), and thickness (T) directions, the average value and sample standard deviation are calculated to obtain the dimensional change characteristics in this embodiment. In other words, if the sample standard deviation mentioned above is small, the dimensional change rates in the three directions are uniform, making it possible to evaluate that the material is close to isotropy or has little anisotropy. Conversely, if this standard sample deviation is large, the dimensional change rates in the three directions are uneven, making it possible to evaluate that there is anisotropy in the dimensional change rate directions. Evaluating dimensional change characteristics in this way makes it possible to understand the anisotropy and deformation characteristics of the material, providing important information for material design and quality control.

[0017] <Element concentration data acquisition process> Next, in this embodiment, an element concentration data acquisition step is carried out, in which the internal structure of the steel ingot to be measured is measured using an X-ray analyzer to acquire element concentration data (element mapping data). Specifically, a sample is taken from any location including the internal structure of the steel ingot, mirror-polished, and then the element concentration data is acquired using the X-ray analyzer. Note that the X-ray analyzer used in the present invention may be any analyzer equipped with an energy dispersive (EDX) or wavelength dispersive (WDX) type, but it is preferable to select an electron probe microanalyzer (EPMA) equipped with a WDX, which has high quantitative analysis accuracy. In particular, a field emission electron probe microanalyzer (FE-EPMA) is preferably used.

[0018] <Segregation ratio derivation process> In this embodiment, the segregation ratio is derived from the maximum value of segregation / minimum value of segregation in the solidification cell, which is derived from a diagram combining the detection intensity and frequency of the elements. The derivation method will be explained in more detail below with reference to FIG. 1. In FIG. 1, when the target element is C, the intensity is shown on the horizontal axis and the frequency is shown on the vertical axis. The minimum and maximum values ​​of segregation are the ends of the half-width of the C intensity at half the value of the frequency peak. The minimum value (C EP1 ), maximum value (C EP2 ) respectively reflect the minimum and maximum values ​​of the composition in the segregation, and the C intensity was read. EP2 / C EP1 was used as the segregation ratio in this embodiment. Using this segregation ratio makes it possible to process large amounts of data efficiently. Furthermore, a larger segregation ratio indicates a greater degree of segregation, while a smaller value indicates less segregation and a more uniform structure. In the above example, the analysis area was 857.1429 μm × 857.1429 μm, and the FE-EPMA intensity was collected numerically on a 300 × 300 grid. In this embodiment, the dimensional change characteristics are evaluated based on the correlation between the dimensional change characteristics and the segregation ratio. That is, the phenomenon in which the dimensional change rates in the three directions, i.e., the length (L), width (W), and thickness (T), vary is thought to be due to the structure being nonuniform in the three directions, and this nonuniformity is thought to be correlated with the segregation ratio of the internal structure (as-cast structure) of the steel ingot. The present invention has discovered that when the segregation ratio of the as-cast structure is large, the structure of the steel material becomes nonuniform in the three directions. [Example]

[0019] Eight types of samples were prepared with the compositions shown in Table 1. Each sample is distinguished by the sample symbol shown on the left side of Table 2. "Std" indicates steel with standard properties among mass-produced steels. "MoL" indicates steel with a lower molybdenum (Mo) content than "Std". "MoH" indicates steel with a higher molybdenum content than "Std". "CrL" indicates steel with a lower chromium (Cr) content than "Std". "CrH" indicates steel with a higher chromium content than "Std". "SiL" indicates steel with a lower silicon (Si) content than "Std".

[0020] [Table 1]

[0021] Six rectangular specimens were prepared for each sample listed in Table 1. Each specimen was cut from a single steel material so that the length direction was the direction in which the steel material expands during hot working, the thickness direction was the direction in which the steel material compresses, and the width direction was the direction perpendicular to both the length direction and the thickness direction. Each specimen was then quenched and tempered, and the heat treatment dimensional change rate was measured. The heat treatment dimensional change rate was calculated as (LB-LA) / LA, where LA is the sample length before quenching and tempering, and LB is the sample length after quenching and tempering. The quenching conditions were the same for all specimens. The specimens were quenched from 1020°C for 10 minutes by semi-cooling. The semi-cooling number indicates the time required to cool the specimen to half the temperature of 1020°C (510°C). Tempering was performed under five different tempering conditions: 485°C, 500°C, 515°C, 530°C, and 545°C. Tempering was carried out twice at each temperature.

[0022] Figure 2 shows the heat treatment dimensional change rates of steels with different Mo contents. Figure 2 shows three graphs arranged horizontally with a common vertical axis. (a) on the far left shows the heat treatment dimensional change rate for "MoL," (b) in the center shows the heat treatment dimensional change rate for "Std," and (c) on the far right shows the heat treatment dimensional change rate for "MoH." The horizontal axis of the graph shows the tempering temperature, and the vertical axis shows the heat treatment dimensional change rate. The heat treatment dimensional change rate on the vertical axis is calculated by measuring the sample dimensions before and after heat treatment, and then dividing the dimensional change before and after heat treatment by the dimensions before heat treatment. Positive values ​​on the vertical axis indicate expansion due to heat treatment, and negative values ​​on the vertical axis indicate contraction due to heat treatment. "As(Q)" on the horizontal axis indicates samples that were only quenched. The black circles on the graph indicate the heat treatment dimensional change rate in the length direction (L). The black diamonds indicate the heat treatment dimensional change rate in the width direction (W). The black triangles indicate the heat treatment dimensional change rate in the thickness direction (T). For each temperature, the average value ave and sample standard deviation s of the three heat treatment dimensional change rates in the length direction, width direction, and thickness direction were calculated, and the range of ave ± 3s is shown in gray.

[0023] Figure 3 shows the heat treatment dimensional change rates of steels with different Cr contents side by side. Like Figure 2, Figure 3 also has three graphs arranged horizontally with a common vertical axis. (a) on the far left shows the heat treatment dimensional change rate of "CrL", (b) in the middle shows the heat treatment dimensional change rate of "Std", and (c) on the far right shows the heat treatment dimensional change rate of "CrH". The vertical and horizontal axes and plot symbols are the same as in Figure 2, so explanations will be omitted. Also, (b) of Figure 2 and (b) of Figure 3 are the same graph.

[0024] Figure 4 shows the heat treatment dimensional change rates of steels with different Si contents side by side. Like Figures 2 and 3, Figure 4 also shows two graphs with a common vertical axis arranged side by side. (a) on the left shows the heat treatment dimensional change rate of "SiL", and (b) on the right shows the heat treatment dimensional change rate of "Std". The vertical and horizontal axes and plot symbols are the same as in Figure 2, so an explanation will be omitted. Also, Figure 2(b), Figure 3(b), and Figure 4(b) are the same graph.

[0025] When processing steel with large anisotropy in heat treatment dimensional change, differences in shape occur due to dimensional change caused by heat treatment after machining, which increases the machining cost and processing man-hours required to correct the shape. Therefore, it is desirable for the steel material's characteristics to have small anisotropy in the heat treatment dimensional change rate for each steel material, that is, a narrow range of ave ±3s shown in gray in the graphs of Figures 2 to 4. Furthermore, it is difficult to consider dimensional changes caused by heat treatment because the temperature for heat treatment, such as tempering, is appropriately selected depending on the equipment used and the mechanical properties of the machine parts to be manufactured. Therefore, it is desirable that the difference in dimensional changes caused by heat treatment due to the tempering temperature be small, that is, that there be little change in the vertical direction in the graphs of Figures 2 to 4.

[0026] Figure 5 shows the measurement results of the segregation ratio of the as-cast steel ingot obtained using the method shown in Figure 1, along with the tripled sample standard deviation (s) (3s) of the dimensional change ratio in three directions (L, W, T). The samples shown are Sample Std, CrL, and CrH. The values ​​of 3s are shown at 485, 500, 515, 530, and 545°C, with four significant digits. It was confirmed that as the Cr segregation ratio (segregation ratio) calculated based on the Cr concentration in the as-cast steel ingot increased, the tripled sample standard deviation (3s) of the dimensional change ratio also increased. Furthermore, Table 2 and Figure 6 show the results for all samples shown in Figure 5. Table 2 and Figure 6 confirm that the dimensional change ratio variability (3s) tends to increase as the Cr segregation ratio increases. These results confirm that, for the steels used in this example, reducing the Cr segregation ratio in the as-cast steel ingot is an effective factor controlling the dimensional change ratio variability. 6, when samples of alloy compositions such as Std, MoL, MoH, CrH, and SiL are forged to give a Cr segregation ratio of 2.4 or less in the as-cast structure of a certain steel ingot, the dimensional change after heat treatment following quenching and tempering of the forged steel shows smaller variation in dimensional change in three directions than sample CrL, which has a Cr segregation ratio of 2.58. Therefore, the anisotropy of dimensional change characteristics can be predicted from the evaluation of the Cr segregation ratio of the as-cast structure. In the steel of this example, by adjusting the composition to lower the Cr segregation ratio or by selecting a steel ingot or a portion of a steel ingot with a low Cr segregation ratio, it is possible to industrially obtain steel with isotropic dimensional change characteristics.

[0027] [Table 2]

Claims

1. a dimensional change characteristic acquisition step of taking a sample from a steel material obtained by quenching and tempering the hot-worked material obtained by hot-working a steel ingot, and measuring the dimensional change characteristic; an elemental mapping data acquisition step of measuring a sample taken from the internal structure of the steel ingot using an X-ray analyzer to obtain elemental mapping data of the matrix composition; a segregation ratio deriving step of deriving a segregation ratio of each element in a steel ingot from the element mapping data, the segregation ratio deriving step derives a segregation ratio from a maximum value of segregation / a minimum value of segregation in a solidification cell, the maximum value being derived from a diagram combining the detection intensity and frequency of elements; A method for predicting dimensional change characteristics of steel, comprising evaluating the correlation between the segregation ratio and the dimensional change characteristics.

2. A method for producing a steel ingot, comprising controlling the segregation ratio of the steel ingot based on the results of the dimensional change characteristic prediction according to claim 1.

3. A method for producing a hot-worked material, comprising a hot working step of hot working the steel ingot of claim 2.

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