Method and program for predicting hot working conditions

Abstract

The present invention provides a prediction method capable of more accurately predicting hot working conditions for generating cracks and suppressing generation of cracks during actual hot working. A hot working condition prediction method for predicting hot working conditions of a material to be hot-worked having a decarburized layer on a surface layer, the method comprising: a hot working characteristic acquisition step for acquiring hot working characteristics of a portion that becomes a ferrite-austenite two-phase region in the decarburized layer formed on the surface layer of the material to be hot-worked; a first analysis step for performing plastic deformation analysis on the basis of a simulation using the acquired hot working characteristics as an input value, and deriving a failure threshold value; a second analysis step for performing plastic working analysis based on a simulation in which actual hot working is simulated, and deriving a failure parameter corresponding to the amount of work of the material to be hot-worked; and a working condition deriving step for deriving a working condition threshold value during hot working in an actual device on the basis of the failure threshold value and the failure parameter.

Description

Technical Field

[0001] This invention relates to methods and procedures for predicting hot working conditions. Background Technology

[0002] Hot forging is a known method of steel processing, but the cracking defects that occur in the forged billets and finished steel have long been a problem to be solved. If these cracks form, surface grinding or finishing processes must be performed to repair them, which is a major cause of decreased yield and increased costs. One reason for cracking during forging is that the amount of processing applied during hot working exceeds the hot working characteristics of the material. Generally, the ease with which cracks form varies depending on the material; furthermore, even for the same material, differences in heating or cooling temperatures during the forging process can affect crack formation. To suppress these forging cracks, it is effective to predict potential crack-causing processing conditions in advance and set appropriate processing conditions.

[0003] A known method for predicting cracks involves calculating an evaluation index for failure using the finite element method and comparing it to a threshold. For example, in Patent Document 1, failure parameters of the forged material are calculated from the stress and strain of the forged material using a failure condition formula by analyzing the thermally coupled deformation of the forged material during hot free forging. Furthermore, a method is disclosed whereby the occurrence of forging cracks in the forged material is predicted by comparing these failure parameters with a failure threshold. In Patent Document 2, the applicant proposes a failure prediction method that determines the inherent failure threshold of the workpiece as the object of plastic processing, compares the cumulative failure effect based on the processing temperature and strain rate during plastic processing with the inherent failure threshold, determines whether the workpiece fails during plastic processing, and predicts the location of the failure.

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 2010-131621

[0007] Patent Document 2: Japanese Patent Application Publication No. 2022-41548 Summary of the Invention

[0008] The problem the invention aims to solve

[0009] Patent Documents 1 and 2 are effective inventions capable of predicting the failure of processed materials. However, in Patent Documents 1 and 2, the internal hot working characteristics of the material are obtained through high-temperature tensile tests. Since cracks are generated on the surface of the material in actual manufacturing processes, it is effective to consider the surface microstructure that may become the initiation point of cracks when setting forging conditions in order to more accurately predict surface cracks during forging. Therefore, there is room for improvement.

[0010] Therefore, the problem to be solved by the present invention is to provide a prediction method that can more accurately predict the hot working conditions that will cause cracks and suppress the generation of cracks in actual hot working.

[0011] Solution for solving the problem

[0012] The present invention was made in view of the above-mentioned problems.

[0013] That is, the present invention is a method for predicting hot working conditions, which predicts the hot working conditions of a material to be hot-worked with a decarburized layer on its surface, including: a hot working characteristic acquisition step, which acquires the hot working characteristics of the portion of the decarburized layer formed on the surface of the material to be hot-worked that is a ferrite + austenite two-phase region; a first analysis step, which performs simulation-based plastic deformation analysis and derives a failure threshold, wherein the simulation uses the acquired hot working characteristics as input values; a second analysis step, which performs simulation-based plastic working analysis and derives failure parameters corresponding to the amount of processing of the material to be hot-worked, wherein the simulation simulates actual hot working; and a processing condition derivation step, which derives the processing condition threshold for hot working in actual equipment based on the failure threshold and the failure parameters.

[0014] Invention Effects

[0015] According to the present invention, the hot working conditions for crack initiation can be predicted more accurately, and the initiation of cracks during actual hot working can be suppressed. Attached Figure Description

[0016] Figure 1 These are photographs used to illustrate cracks that appear in steel after hot working.

[0017] Figure 2 This is a flowchart illustrating the prediction method of the present invention.

[0018] Figure 3 This is a diagram showing the shape of a tensile test specimen.

[0019] Figure 4 This is a diagram showing the analytical model for simulating plastic processing.

[0020] Figure 5This is a graph showing the relationship between the failure parameter D calculated through plastic processing simulation and the reduction.

[0021] Figure 6 This is a graph showing the surface temperature and processing condition thresholds.

[0022] Figure 7 This is an explanatory diagram illustrating the structure of the processing condition prediction system.

[0023] Figure 8 This is an explanatory diagram showing the sampling location for the test pieces in the instruction manual.

[0024] Figure 9 This is an example of the results of plastic deformation analysis.

[0025] Figure 10 This is an explanatory diagram illustrating the prediction method for processing conditions.

[0026] Figure 11 It is a flowchart illustrating the processing flow of the program.

[0027] Figure 12 It is a flowchart illustrating the processing flow of the subroutine that predetermines the processing conditions.

[0028] Figure 13 This is an explanatory diagram illustrating the simulation results of the hot working of the modified example.

[0029] Figure 14 From Figure 13 An example of a curve plotted from data extracted when the reduction is 150 mm. Detailed Implementation

[0030] [Implementation Method 1]

[0031] The present invention will now be described in detail. It should be noted that the present invention is not limited to the embodiments listed herein, and appropriate combinations and improvements can be made without departing from the technical concept of the invention. Figure 2 A flowchart of the prediction method of the present invention is shown.

[0032] It should be noted that this invention is particularly preferred for carbon steel and alloy steels containing the following steel grades: steels that, when heated in air to a hot working temperature of 700–1200°C, produce a surface layer with a ferrite + austenite two-phase microstructure due to decarburization during the transformation of the matrix microstructure into the austenite phase. Examples include hot tool steels such as SKD61. Furthermore, hot working methods include free forging, die forging, and hot rolling. In this embodiment, the improved SKD61 material is selected as the material to be hot-worked, and hot free forging is selected as the hot working method.

[0033] <Process for Obtaining Heat Treatment Characteristics>

[0034] First, in this embodiment, the hot working characteristics of the portion of the decarburized layer formed on the surface of the material to be hot-worked are obtained (hot working characteristic acquisition step). The material to be hot-worked includes steel ingots manufactured by casting and steel billets (slabs, large billets, small billets) obtained by roughing the steel ingots. In this embodiment, steel billets are used as the material to be hot-worked.

[0035] In this embodiment, the "hot working characteristics" refer to the tensile properties (high-temperature tensile properties) of the material to be hot-worked under hot working conditions (e.g., 700–1200°C in the case of SKD61). Specifically, the ductility under high-temperature conditions, i.e., elongation at break or compression characteristics, is obtained using a test piece taken from the surface of the material to be hot-worked. Alternatively, the displacement of the test piece at the point of fracture in a tensile test (fracture displacement) can also be obtained as a high-temperature tensile characteristic. This test piece can be a tensile test piece with a prism shape in the parallel section or a plate-shaped tensile test piece. Since the tensile properties of the material to be hot-worked vary with the hot working temperature and compression rate, it is preferable to change the test temperature and strain rate conditions to obtain multiple tensile properties. In addition, to obtain the deformation resistance, which is one of the hot working characteristics, a cylindrical compression test piece can be used, and multiple deformation resistances can be obtained by changing the test temperature and strain rate conditions. Thus, in the processing condition derivation process of the present invention described later, a processing condition threshold combining the processing temperature and compression rate can be derived. In this embodiment, the heating mechanism of the test piece uses high-frequency induction heating, but electrical heating can also be used. It should be noted that, in addition to the above-mentioned measurements, the high-temperature tensile properties can also be obtained using simulation or other methods. In this invention, "surface layer" refers to the layer extending from the surface of the material to be heat-processed to a depth of 0.1 times the thickness of the material. Furthermore, in this invention, "decarburized layer" refers to the layer extending from the surface of the material to be heat-processed to a depth where, according to JIS G0558, the carbon content of the substrate microstructure is less than or equal to 95%.

[0036] In the hot workability acquisition process of this embodiment, hot workability is acquired, particularly for the ferrite + austenite two-phase region within the decarburized layer. This is one of the main features of the present invention (hereinafter, the ferrite phase is also referred to as the α phase, the austenite phase as the γ phase, and the ferrite + austenite two-phase region as the α+γ phase). Especially when carbon steel and alloy steel are heated in air to a hot workability temperature of 700–1200°C, decarburization results in a reduction of surface carbon content and the formation of an α+γ phase region on the surface. Since the hot workability of the α+γ phase is often lower than that of the γ phase, if the hot workability characteristics obtained from high-temperature tensile tests on the uniform microstructure within the material are used to derive the failure threshold described later, the accuracy of hot work crack prediction may decrease. Therefore, in this embodiment, it is necessary to measure the α+γ phase region within the decarburized layer on the surface of the steel billet to acquire hot workability.

[0037] To obtain the carbon concentration distribution from the decarburized layer on the surface of the steel billet, the carbon count can be measured using an electron beam microanalyzer (EPMA) on the cross-section of a test piece separated from the billet surface. The carbon concentration is then converted into a carbon concentration using a detection curve created using carbon steel with a known carbon concentration. Furthermore, to confirm the phase composition of the α-phase, γ-phase, and α+γ-phase, the test piece separated from the billet surface can be quenched, and the cross-section of the decarburized layer can be examined. The presence of martensitic phase transformation in the microstructure is then used to determine the composition.

[0038] <First Analysis Process>

[0039] Next, in this embodiment, plastic deformation analysis is performed based on a simulation with hot working characteristics as input values, and the failure threshold is derived (first analysis step). This simulation can use rigid-plastic analysis or elastoplastic analysis. By implementing this plastic deformation analysis, the temperature dependence of the failure threshold in the α+γ phase region is obtained. In addition, in this embodiment, the failure threshold is obtained as a function of temperature, but in addition to temperature, strain rate dependence can also be used. In the plastic deformation analysis, the same test conditions as those used in the hot working characteristics acquisition step are set, and the maximum principal stress σ_max_f, von Mises equivalent stress σ_eff_f, and equivalent plastic strain ε_f at the fracture site are determined when the fracture elongation, compression, or fracture displacement in the plastic deformation analysis are the same as the values ​​of the fracture elongation, compression, or fracture displacement of the test piece in the hot working characteristics acquisition step. The failure threshold D_f is obtained by the generalized Cockroft & Latham formula shown in Equation (1). Other commonly used failure condition formulas can also be used to obtain it, such as the Oyane formula.

[0040] Mathematical Formula 1

[0041]

[0042] <Second Analysis Process>

[0043] Next, based on the simulation of actual hot working, plastic working analysis is performed, and the failure parameters corresponding to the amount of processing of the material to be hot-processed are derived (second analysis step). The "failure parameters corresponding to the amount of processing" refer to the parameter D calculated by Equation (2) in the finite element method based on rigid-plastic analysis or elastic-plastic analysis, with the maximum principal stress σ_max, von Mises equivalent stress σ_eff, and equivalent plastic strain ε generated when processing with arbitrary processing amount as variables.

[0044] Mathematical formula 2

[0045]

[0046] In this plastic processing analysis, firstly, the shape of the material to be processed and the shape of the mold are imported as models into the analysis software. Then, the deformation resistance and thermophysical properties of the material to be processed are imported into the model of the material. The deformation resistance is preferably obtained from the material to be processed. More preferably, considering the formation of a decarburized layer on the surface of the material to be processed, elements simulating the decarburized layer are set on the surface of the model, and the deformation resistance obtained from the decarburized layer of the material to be processed is applied to the elements of the decarburized layer. Next, the hot processing conditions are input into the analysis software. For example, in the case of hot forging, the heating temperature of the material to be forged, the time from when the material is removed from the heating furnace to when it is placed on the forging press, the forging speed, and the amount of reduction are input as forging conditions into the analysis software. Then, the process of reducing the material to the same thickness from the beginning to the end along its length is considered as a stroke, and the failure parameter D of said stroke is derived. It should be noted that the shapes of the heat-processing material and the mold used in the plastic processing analysis of this embodiment are not particularly limited. For example, in this embodiment, a quarter-prism shape is used as the initial shape of the forging material, but it can also be a complete shape, a half-prism shape, or a cylindrical shape.

[0047] <Process Conditions for Deriving Operations>

[0048] In this embodiment, based on the damage threshold and damage parameters obtained in the first and second analysis steps, a processing condition threshold for hot working in the actual equipment is derived (processing condition derivation step). That is, by comparing the damage threshold and damage parameters of the α+γ phase region, a reduction amount (processing condition threshold) is determined that makes the damage parameters less than or equal to the damage threshold at any processing temperature or reduction rate. It should be noted that the processing temperature can also be calculated as the processing condition threshold so that the damage parameters at any reduction amount and reduction rate obtained in the second analysis step are less than or equal to the damage threshold obtained in the first analysis step. Similarly, the reduction rate can be calculated as the processing condition threshold based on any reduction amount and processing temperature. Alternatively, the relationship between reduction amount and processing temperature, and the relationship between reduction amount and reduction rate can be pre-calculated as processing condition thresholds, and these can be created as three-dimensional curves, allowing the processing condition threshold to be derived based on any two variables. In actual manufacturing, by setting processing conditions according to the derived processing condition threshold, cracks during hot working can be suppressed.

[0049] Example

[0050] (Example 1)

[0051] As a preliminary discussion before confirming the effectiveness of the present invention, in order to clarify the cause of cracks in the SKD61 modified material during forging, the morphology of its surface microstructure and its hot working characteristics were investigated. First, regarding the collected test pieces (parallel portion dimensions: A simulated hot forging hot tensile test was conducted, in which the collected test pieces contained a decarburized layer formed on the surface of the SKD61 modified material billet. Figure 1 The image shows the location of the cracks that formed inside the test piece. From... Figure 1 It can be seen that in the decarburized layer of the SKD61 modified material, large cracks were generated at the α / γ phase interface in the α+γ phase region. Therefore, the hot working characteristics of the α+γ phase region are lower than those of the undecarburized γ phase. The microstructure that causes cracks in the SKD61 modified material is likely the α+γ phase region formed in the decarburized layer on the surface of the billet.

[0052] (Example 2)

[0053] Secondly, experiments were conducted to confirm the effectiveness of the present invention. Firstly, as a process for obtaining hot working characteristics, samples were collected from different depths on the surface of the SKD61 modified steel billet where an α+γ phase region was formed. Figure 3The tensile test specimens shown are subjected to a process where the temperature was increased from room temperature to 1100°C and held at 1100°C for two hours. Afterwards, the temperature was decreased to the test temperature at a rate of -0.1°C / s, held at each temperature for 5 minutes, and tensile tests were conducted at a crosshead speed of 1.5 mm / s, assuming the average strain rate of forging. After fracture, the microstructure morphology during the test was determined by observing the longitudinal section of the parallel portion. Table 1 shows the fracture displacements of the α single-phase, α+γ phase region, and γ single-phase in the decarburized layer of the SKD61 modified material when all three phases were heated to 900°C. As can be seen from Table 1, the ductility of the α+γ phase region is significantly reduced compared to the α single-phase and γ single-phase.

[0054] Table 1

[0055] α single phase γ single phase α+γ two phases Fracture displacement 9.1mm 9.1mm 6.5mm

[0056] As the first analytical step, in order to derive the failure threshold based on the heat treatment characteristics obtained from the heat treatment characteristics acquisition step, the decarburized layer of the material to be heat-treated was analyzed using commercially available plastic deformation simulation software, taking into account the deformation resistance obtained in the temperature range of 700°C to 1200°C and the strain rate range of 0.01 / s to 1.0 / s. As part of the analysis, the test piece was deformed to the obtained fracture displacement in the α+γ phase region during the simulation, and the maximum principal stress σ_max_f, von Mises equivalent stress σ_eff_f, and equivalent plastic strain ε_f in the displacement of the test piece at fracture were determined. The failure threshold Df was then calculated using the generalized Cockroft & Latham formula.

[0057] In the second analytical process, by Figure 4 The simulation of forging a prism-shaped material to be heated on a frustum-shaped anvil is used to analyze plastic processing and derive the failure parameter D corresponding to the amount of material to be heated. Commercially available forging simulation software is used for forging analysis, performing only one stroke under various reduction amounts, and the maximum value of the failure parameter D, calculated using the maximum principal stress σ_max, the von Mises equivalent stress σ_eff, and the equivalent plastic strain ε as variables, is read. Then, through heat conduction analysis, the surface temperature change of the material with arbitrary cross-sectional dimensions is determined when it is naturally cooled in air from an arbitrary heating temperature. Figure 5 The relationship between the obtained failure parameter D and the reduction is shown. According to... Figure 5 It can be seen that the failure parameter D increases linearly relative to the reduction amount.

[0058] Next, in the processing condition derivation process, based on the damage threshold of the α+γ region obtained in the first analysis process and the relationship between the damage parameter D and the reduction amount obtained in the second analysis process, the reduction amount that makes the damage parameter D less than or equal to the damage threshold, i.e., the processing condition threshold, is determined. Figure 6 The relationship between surface temperature and the processing condition threshold is shown. It can be seen that by using a ratio... Figure 6 Forging with a small reduction (e.g., within 100 mm) as indicated by the dashed line can suppress cracks in the α+γ phase region on the surface of the material to be heat-processed.

[0059] (Example 3)

[0060] Under the processing condition threshold obtained in Example 2, i.e., a reduction of less than 100 mm, actual hot processing (hot forging) was performed and the effect was confirmed. Two SKD61 modified material steel ingots (approximately 10 tons) were prepared, and hot forging was performed at a processing temperature of 800–1050 °C, resulting in a cross-sectional area of ​​approximately 500,000 mm². 2 The hot-working materials of the present invention are described. The example hot-working material of the present invention is hot-working in such a way that the reduction in each stroke is less than 100 mm, while the comparative hot-working material is hot-working in such a way that the reduction in a portion of the hot-working stroke exceeds 100 mm. Next, penetrant testing based on JIS Z2343 was performed on the longitudinal sections of the obtained example and comparative hot-working materials of the present invention to measure the density of internal cracks (cracks caused by the α+γ phase region formed in the decarburized layer). As a result, 30 internal cracks were found per 1 m in the comparative sample, while 14 internal cracks were found per 1 m in the example sample of the present invention. Therefore, the number of internal cracks generated in the example of the present invention is reduced by half compared to the comparative sample, demonstrating that the processing condition threshold (reduction) derived using the prediction method of the present invention is effective in actual manufacturing.

[0061] [Implementation Method 2]

[0062] This embodiment relates to hardware and software for predicting hot working conditions. Details identical to those in Embodiment 1 will not be repeated.

[0063] Figure 7 This is an explanatory diagram illustrating the configuration of the processing condition prediction system 20. The processing condition prediction system 20 includes an information processing device 10 connected via a network, a test piece processing machine 25, and a heat treatment testing machine 26. The test piece processing machine 25 processes the test sample 40 (see...) Figure 8 A machine tool used to process test pieces to produce test pieces of a predetermined shape. The test piece is, for example, a... Figure 3 The shape shown.

[0064] In the following description, sample 40 is an example of a steel ingot or billet, or a portion cut from a steel ingot or billet.

[0065] The test piece processing machine 25 can also be configured by combining multiple automatic processing machines connected by a conveying device (not shown). Devices for processing materials into predetermined shapes are well-known and will not be described further here. The test piece processing machine 25 can be a general-purpose processing machine operated manually or semi-automatically by a skilled technician.

[0066] The hot working testing machine 26 is a testing machine that can be used for tensile tests, for example, conforming to JIS G0567:2020 (Japanese Industrial Standard - Method for High-Temperature Tensile Testing of Steel Materials and Heat-Resistant Alloys). Testing machines conforming to standards are well known and will not be described further.

[0067] Test piece 45 (see Figure 8 The test piece 45 is removed from the test piece processing machine 25 and installed onto the heat treatment testing machine 26 using a handling robot (not shown in the diagram). The test piece 45 is then tested using the aforementioned heat treatment testing machine 26. Removing the test piece 45 from the test piece processing machine 25, transferring the test piece 45 from the test piece processing machine 25 to the heat treatment testing machine 26, and installing the test piece onto the heat treatment testing machine 26 can be performed manually or semi-automatically.

[0068] The information processing device 10 includes a control unit 11, a main storage device 12, an auxiliary storage device 13, a communication unit 14, a display unit 15, an input unit 16, a reading unit 19, and a bus.

[0069] The control unit 11 is an arithmetic control device for executing the program of this embodiment. It uses one or more CPUs (Central Processing Units), GPUs (Graphics Processing Units), multi-core CPUs, etc. The control unit 11 is connected to the various hardware components constituting the information processing device 10 via a bus.

[0070] The main storage device 12 is a storage device such as SRAM (Static Random Access Memory), DRAM (Dynamic Random Access Memory), or flash memory. The main storage device 12 temporarily stores information required for the processing performed by the control unit 11, as well as the program being executed by the control unit 11.

[0071] The auxiliary storage device 13 is a storage device such as SRAM, flash memory, hard disk, or magnetic tape. The auxiliary storage device 13 stores software such as plastic deformation simulation software 31, hot working simulation software 32, and programs to be executed by the control unit 11, as well as various data required to execute each software.

[0072] The communication unit 14 is the interface for communication between the information processing device 10 and the network. The display unit 15 is, for example, a liquid crystal display panel or an organic EL (electro-Luminescence) panel. The input unit 16 is, for example, an input device such as a keyboard, mouse, or microphone. The display unit 15 and the input unit 16 can be stacked to form a touch panel.

[0073] The portable recording medium 96 is, for example, a USB (Universal Serial Bus) memory, a CD-ROM (CompactDisc Read Only Memory), a magneto-optical disk medium, other optical disk media, or an SD memory card. The portable recording medium 96 stores the program 97 described later.

[0074] The reading unit 19 is an interface that can connect to a portable recording medium 96, such as a USB connector, CD-ROM drive, or SD memory reader. The semiconductor memory 98 stores the program 97 and is a memory that can be installed inside the information processing device 10.

[0075] The information processing device 10 can be a general-purpose personal computer, tablet computer, mainframe computer, virtual machine running on a mainframe computer, or quantum computer. The information processing device 10 can also be composed of multiple personal computers or mainframe computers performing distributed processing. The information processing device 10 can also be a cloud computing system. Alternatively, the information processing device 10 can be composed of multiple personal computers or mainframe computers operating collaboratively.

[0076] Program 97 is recorded in portable recording medium 96. Control unit 11 reads program 97 via reading unit 19 and saves it to auxiliary storage device 13. Alternatively, control unit 11 can also read program 97 stored in semiconductor memory 98. Furthermore, control unit 11 can also download program 97 from another server computer (not shown) connected via communication unit 14 and a network (not shown) and save it to auxiliary storage device 13.

[0077] Program 97 is installed as a control program for the information processing device 10 and loaded into the main storage device 12 for execution. Program 97 in this embodiment is an example of a program product.

[0078] Plastic deformation simulation software 31 uses numerical analytical methods such as the finite element method to simulate the plastic deformation behavior of a material when stress is applied. Hot working simulation software 32 uses numerical analytical methods such as the finite element method to simulate the plastic deformation behavior of a material during hot working processes such as forging, where pressure is applied to the material placed on an anvil.

[0079] Both the plastic deformation simulation software 31 and the hot working simulation software 32 are well-known, so detailed processing will not be elaborated upon. The information input to and output to each simulation software will be explained later.

[0080] Plastic deformation simulation software 31 and hot working simulation software 32 can also be provided in the form of SaaS (Software as a Service) via a large computer or cloud service connected to the network and information processing device 10.

[0081] First, a summary of the processing performed in this embodiment will be given.

[0082] [Experimental film production]

[0083] Figure 8 This is an explanatory diagram illustrating the sampling location of test piece 45. As described above, the explanation will take a steel ingot or billet as an example for sample 40. Figure 8 The image schematically illustrates the state of sample 40 cut into cuboids. Figure 8 A decarburized layer is formed near the upper surface of the sample. This decarburized layer contains a portion of a ferrite + austenite two-phase region. Which part of the sample 40 constitutes the two-phase region can be detected by observing the cross-section of the sample 40 using methods such as EPMA, as described above.

[0084] The control unit 11 controls the test piece processing machine 25 to produce multiple two-phase region test pieces 41 from the two-phase region portion. The control unit 11 also controls the test piece processing machine 25 to produce multiple non-decarburized layer test pieces 42 from the non-decarburized layer, which is located further inside the decarburized layer. It should be noted that the production of test pieces 45 can also be performed by someone skilled in the art operating the test piece processing machine 25. In the following description, unless there is a need to distinguish between the two-phase region test pieces 41 and the non-decarburized layer test pieces 42, they will sometimes be referred to as test pieces 45.

[0085] Although Figure 8 The test piece 45 is simply illustrated as a cylinder, but the test piece 45 is... Figure 3 The shape of the tensile test piece is illustrated in the figure. The test piece 45 may also be the shape specified in Appendix A of JIS G0567:2000 or Appendix B to Appendix E of JIS Z2241:2022 (Japanese Industrial Standard for Metallic Materials, Tensile Testing). It should be noted that the deformation resistance and fracture displacement δf described later can be obtained separately. In obtaining the deformation resistance, the test piece 45 may be a cylindrical compression test piece.

[0086] [Data Collection]

[0087] The control unit 11 is capable of controlling the heat treatment testing machine 26 to measure the deformation resistance and fracture displacement δf of the test piece 45. It should be noted that the measurement is performed by a person skilled in the art operating the heat treatment testing machine 26, and the measurement data can be sent to the information processing device 10.

[0088] The control unit 11 controls the hot working testing machine 26 to measure the deformation resistance and fracture displacement δf of each of the two-phase region test piece 41 and the non-decarburized layer test piece 42 under various combinations of strain rates and temperatures. The strain rates used can be, for example, 0.01 / s and 1 / s, in addition to 0.1 / s. The temperatures used are, for example, from 700°C to 1100°C, in increments of 100°C. Furthermore, any combination of temperature and strain rate can be used.

[0089] The process of obtaining the fracture displacement δf of the two-phase test piece 41 using the hot working testing machine 26 is an example of the process of obtaining hot working characteristics.

[0090] The control unit 11 controls various measuring instruments (not shown) to measure the thermophysical properties of the test piece 45, such as its elastic properties (Young's modulus and Poisson's ratio), the temperature dependence of its coefficient of thermal expansion, and the temperature dependence of its thermal conductivity. These measurements can also be performed by those skilled in the art.

[0091] It should be noted that for data other than deformation resistance and fracture displacement δf, the data measured from either the two-phase region test piece 41 or the non-decarburized layer test piece 42 can be used as representative values. Alternatively, data other than deformation resistance and fracture displacement δf can also be measured in existing steels with similar properties. The deformation resistance of test piece 45 can also be obtained using simulation or other methods instead of actual measurement.

[0092] [Plastic Deformation Simulation]

[0093] Table 2 shows the data input to the plastic deformation simulation software 31.

[0094] Table 2

[0095]

[0096]

[0097] The control unit 11 inputs the data shown in Table 2 into the plastic deformation simulation software 31. When the two ends of the test piece model are separated by the fracture displacement δf, the plastic deformation simulation software 31 outputs the various stresses and strains generated inside the test piece model. The control unit 11 calculates the failure threshold D_f at temperature T according to equation (1). Then, the control unit 11 calculates the failure threshold D_f at multiple temperatures T respectively.

[0098] Figure 9 This is an example of the results of plastic deformation analysis. Figure 9 The horizontal axis represents temperature, T. The unit is degrees Celsius. Figure 9 The vertical axis represents the damage threshold D_f. The damage value D_f is a dimensionless quantity. It should be noted that... Figure 9 In Chinese, the subscript f is used instead of "_f".

[0099] Plastic deformation simulation software 31 is an example of software for performing simulation-based analysis of plastic deformation, where the simulation takes hot working characteristics as input values. The process using plastic deformation simulation software 31 is an example of the first analytical process for deriving the failure threshold D_f.

[0100] [Hot Working Simulation]

[0101] Table 3 shows the data input to the thermal processing simulation software 32. It should be noted that the Young's modulus and Poisson's ratio of the mold are measured in advance and stored in the auxiliary storage device 13.

[0102] Table 3

[0103]

[0104]

[0105] The control unit 11 inputs the data shown in Table 3 into the heat treatment simulation software 32. The heat treatment simulation software 32 outputs the various stresses and strains generated inside the material model to be heat-treated during processing with various parameters of the heat treatment conditions. The control unit 11 calculates the failure parameter D according to equation (2). The control unit 11 calculates each failure parameter D for multiple reduction amounts. The aforementioned Figure 5 Here is an example of the calculation result.

[0106] The hot working simulation software 32 is an example of software for performing simulation-based plastic working analysis, which simulates actual hot working. The process using the hot working simulation software 32 is an example of a second analytical process for deriving the failure parameter D.

[0107] [Prediction of Hot Working Conditions]

[0108] The explanation will take a target temperature of 900°C at the end of heat treatment as an example. The control unit 11 will be used according to... Figure 9 Based on the analytical results of plastic deformation, the failure threshold D_f at a temperature of 900℃ is calculated. Figure 9 In the example shown, the damage threshold D_f at 900℃ is approximately 0.25.

[0109] If no plastic deformation analysis is performed at the desired temperature, the control unit 11 will re-execute the plastic deformation analysis at that temperature and calculate the failure threshold D_f, or use any interpolation method to determine the failure threshold D_f at the desired temperature.

[0110] Figure 10 This is an explanatory diagram illustrating the prediction method for processing conditions. Figure 10 Is Figure 5 The diagram has been modified with dashed auxiliary lines. Figure 10 The horizontal axis represents the reduction amount during hot working, in mm. Figure 10 The vertical axis represents the failure parameter D. The failure parameter D is a dimensionless quantity.

[0111] Control unit 11 according to Figure 5 and Figure 10 The example illustrates the relationship between the reduction and the failure parameter D, calculating the reduction when the failure parameter D equals the failure threshold of 0.25. The calculated reduction is the maximum reduction that will not cause cracks in the material to be heat-processed, i.e., the threshold of the processing conditions. The process of calculating the reduction when the failure parameter D equals the failure threshold D_f is an example of deriving the processing condition threshold for heat processing in actual equipment.

[0112] Figure 11 This is a flowchart used to illustrate the process flow of a program. (Used...) Figure 11 The process flow of the control unit 11 when it automatically executes all processes is explained.

[0113] The control unit 11 controls the test piece processing machine 25 to produce multiple test pieces 45 (step S501). The control unit 11 controls a handling robot or the like to install the test pieces 45 onto the heat treatment testing machine 26. The control unit 11 controls the heat treatment testing machine 26 to perform a heat treatment test at a predetermined temperature and a predetermined strain rate (step S502). The heat treatment testing machine 26 measures and records the deformation resistance and the fracture displacement δf.

[0114] The control unit 11 determines whether the test at the predetermined strain rate has ended (step S503). If it determines that the test has not ended (no in step S503), the control unit 11 changes the strain rate of the test (step S504). It should be noted that the list of strain rates used for the test is stored in advance in the auxiliary storage device 13. The control unit 11 returns to step S502.

[0115] If it is determined that the test at the predetermined strain rate has ended (Yes in step S503), the control unit 11 determines whether the test at the predetermined temperature has ended (step S505). It should be noted that the list of test temperatures used for the tests is stored in advance in the auxiliary storage device 13. If it is determined that the test has not ended (No in step S505), the control unit 11 changes the test temperature (step S506). The control unit 11 returns to step S502.

[0116] If it is determined that the test at the predetermined temperature has ended (Yes in step S505), the control unit 11 controls various measuring instruments to measure the thermophysical properties of the test piece 45 (step S507). The control unit 11 inputs the deformation resistance and fracture displacement δf measured in step S507, as well as the thermophysical properties measured in step S507, into the plastic deformation simulation software 31, and performs plastic deformation simulation (step S508). The control unit 11 substitutes the data output by the plastic deformation simulation software 31 into equation (1) to calculate the failure threshold D_f at temperature T (step S509).

[0117] The control unit 11 inputs the deformation resistance and fracture displacement δf measured in step S507, as well as the thermophysical properties measured in step S507, into the hot working simulation software 32, and performs hot working simulation (step S510). The control unit 11 starts the subroutine for estimating processing conditions (step S511). The subroutine for estimating processing conditions is based on the use of... Figure 11 The steps described are a subroutine for estimating processing condition thresholds. Afterwards, the control unit 11 terminates the processing.

[0118] Figure 12 This is a flowchart illustrating the processing flow of the subroutine for estimating processing conditions. The control unit 11 acquires the target temperature at the end of the hot processing (step S521). The control unit 11 then... Figure 9 Based on the results of the plastic deformation simulation, the failure threshold D_f corresponding to the temperature obtained in step S521 is determined (step S522).

[0119] Control unit 11 if used Figure 11 As explained, based on the results of the thermal processing simulation, the amount of reduction corresponding to the damage threshold D_f determined in step S522 being equal to the damage parameter D is determined (step S523). The control unit 11 then ends the process.

[0120] According to this embodiment, a processing condition prediction system 20 can be realized, which can estimate the processing conditions under which cracks will not occur on the material to be heat-processed by automatic processing or semi-automatic processing of the processing and heat-processing test of the test piece 45 with the participation of those skilled in the art.

[0121] Because the process is automated or semi-automated, it is possible to predict suitable processing conditions for each steel ingot manufacturing batch. This helps to improve the yield of hot working processes.

[0122] [Variation Example]

[0123] This variation relates to a processing condition prediction system 20 that performs thermal processing simulation at multiple reduction speeds. The parts that are the same as in Embodiment 2 will not be described again.

[0124] Figure 13 This is an explanatory diagram illustrating the simulation results of the hot working of the modified example. (And...) Figure 6 Similarly, the horizontal axis represents the surface temperature at the end of the hot working process, in degrees Celsius. The vertical axis is used... Figure 10 The threshold values ​​for the processing conditions are specified.

[0125] The control unit 11 inputs multiple hot working conditions into the hot working simulation software 32 for calculation and use. Figure 5 and Figure 10 The relationship between the compression amount and the failure parameter D is explained by s. The control unit 11 operates at various temperatures T according to... Figure 10 The destruction threshold D_f is calculated in the order described in the text. Figure 13 The graphs shown are generated for compression speeds of S_LOW mm / s, S_MED mm / s, and S_HIGH mm / s. It should be noted that the graphs other than S_MED mm / s are only schematic and do not indicate the calculation location.

[0126] The graphs show the lower limit for heat treatment without cracking. Taking a reduction of 150 mm as an example, when the surface temperature of the material to be heat-treated is 930℃, the reduction rate at which cracks are not generated is S_MED mm / s. In other words, the threshold reduction rate for a reduction of 150 mm is S_MED mm / s.

[0127] Control unit 11 by Figure 13 The graph shown is displayed on the display unit 15, which can provide the user with information to select appropriate processing conditions.

[0128] Figure 14 From Figure 13 An example of a curve plotted from data extracted when the reduction is 150 mm. Figure 14 The graph is schematic and therefore does not show the location of the calculation. Figure 14 The horizontal axis represents the surface temperature at the end of the heat treatment, in degrees Celsius. Figure 14 The vertical axis represents the processing condition threshold expressed by the pressing speed.

[0129] exist Figure 13In the middle, the control unit 11 plots the surface temperature of each of the three curves when the pressing amount is 150mm as the horizontal axis and the pressing speed as the vertical axis. The control unit 11 will... Figure 14 The graph shown is displayed on the display unit 15. When the reduction is fixed at 150mm, the user can quickly grasp the relationship between the surface temperature of the material to be processed and the reduction speed threshold.

[0130] The vertical and horizontal axes of the graphs described above are for illustrative purposes only. Preferably, the control unit 11 can accept user commands to change the vertical and horizontal axes to display the corresponding graphs.

[0131] A program is an example of a program product.

[0132] Computer programs can be deployed on a single computer or at a single site, or they can be deployed across multiple sites and executed on multiple computers interconnected by a communication network.

[0133] The technical features (constituent elements) described in each embodiment can be combined with each other to form new technical features.

[0134] The embodiments disclosed herein are illustrative in all respects and should not be considered limiting. The scope of the invention is not limited by the foregoing meaning, but by the claims, and is intended to include all modifications within the same meaning and scope as the claims.

[0135] The independent and dependent claims described in the claims statement can be combined with each other in all combinations, regardless of their referencing form. Furthermore, the claims statement may use the form where one claim refers to two or more other claims (multiple claim form), but is not limited to this. It may also use the form where multiple claims refer to at least one multiple claim (multiple referencing multiple).

[0136] Explanation of reference numerals in the attached figures

[0137] 10. Information processing device

[0138] 11 Control Department

[0139] 12 Main storage devices

[0140] 13. Auxiliary storage device

[0141] 14 Ministry of Communications

[0142] 15 Display Section

[0143] 16 Input Section

[0144] 19 Reading Department

[0145] 20 Processing Condition Prediction System

[0146] 25 Test piece processing machine

[0147] 26. Heat treatment testing machine

[0148] 31 Plastic Deformation Simulation Software

[0149] 32. Thermal processing simulation software

[0150] 40 samples

[0151] 41 Two-phase region test piece

[0152] 42 Non-decarburized layer test piece

[0153] 45 test pieces

[0154] 96 Portable recording media

[0155] 97 Program

[0156] 98 Semiconductor memory

Claims

1. A method for predicting hot working conditions, characterized in that, include: The process of acquiring hot working characteristics is to acquire the hot working characteristics of the part of the ferrite + austenite two-phase region in the decarburized layer formed on the surface of the material to be hot worked. The first analytical step involves performing simulation-based analysis of plastic deformation and deriving the failure threshold, wherein the simulation uses the obtained hot working characteristics as input values. The second analytical step involves performing simulation-based plastic processing analysis and deriving failure parameters corresponding to the processing amount of the material to be heat-processed. This simulation approximates actual heat processing. The processing conditions are derived from the process, which derives the processing condition threshold for hot processing in actual equipment based on the damage threshold and the damage parameters.

2. The method for predicting hot working conditions according to claim 1, characterized in that, The method for predicting the hot working conditions includes the following steps: Multiple two-phase region test pieces were prepared from the portion that constituted the two-phase region. The thermal processing characteristics were obtained through thermal processing tests using the two-phase region test piece.

3. The method for predicting hot working conditions according to claim 2, characterized in that, The heat treatment characteristics are obtained for each combination of a test temperature selected from a plurality of test temperatures and a strain rate selected from a plurality of strain rates.

4. The method for predicting hot working conditions according to claim 1, characterized in that, The method for predicting the hot working conditions includes the following steps: Multiple two-phase region test pieces are prepared from the portion that constitutes the two-phase region; Multiple non-decarburized layer test pieces are prepared from the non-decarburized layer existing inside the decarburized layer; For each combination of a test temperature selected from multiple test temperatures and a strain rate selected from multiple strain rates, a heat treatment test is performed on the two-phase region test piece; as well as For each combination of a test temperature selected from multiple test temperatures and a strain rate selected from multiple strain rates, a heat treatment test is performed on the non-decarburized layer test piece. The simulation of the plastic processing analysis uses data obtained from the hot processing test of the two-phase region test piece and data obtained from the hot processing test of the non-decarburized layer test piece as input data.

5. A program, characterized in that, The computer will perform the following processing: To obtain the hot working characteristics of the ferrite + austenite two-phase region in the decarburized layer formed on the surface of the material to be hot-worked. The failure threshold is derived by performing simulation-based analysis of plastic deformation, where the obtained hot working characteristics are used as input values. Failure parameters corresponding to the processing amount of the material to be heat-processed were derived by performing simulation-based analysis of plastic processing, wherein the simulation was based on actual heat processing; and Based on the damage threshold and the damage parameter, the processing condition threshold for hot processing in actual equipment is derived.

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