Prediction method for predicting hardness at the time of quenching

The prediction method calculates austenite ratio and uses it to predict quenching hardness, addressing the unreliability and low accuracy of existing methods by eliminating the need for martensite ratio and simulation software, thereby improving prediction accuracy.

JP2025082427APending Publication Date: 2025-05-29TOYOTA JIDOSHA KK
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Patent Information

Application Number
JP2023195737
Authority / Receiving Office
JP · JP
Patent Type
Applications
Current Assignee / Owner
Filing Date
2023-11-17
Publication Date
2025-05-29

AI Technical Summary

Technical Problem

Existing methods for predicting hardness during quenching require simulation software and martensite ratio analysis, which are unreliable and reduce prediction accuracy.

Method used

A prediction method that calculates austenite ratio from heating temperature and added element coefficients, and then uses this ratio, cooling temperature, and base material hardness to predict quenching hardness without requiring martensite ratio or simulation software.

Benefits of technology

This method improves prediction accuracy by eliminating the need for martensite ratio analysis and simulation software, providing a reliable and efficient way to predict hardness during quenching.

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Abstract

To provide a prediction method for predicting hardness at the time of quenching capable of improving accuracy of a hardness prediction formula by dispensing with simulation software because of the prediction formula dispensing with a martensite ratio.SOLUTION: In a prediction method for predicting the hardness at the time of quenching, an austenite ratio is calculated from the heating temperature and the coefficient corresponding to additive elements (S11), and the hardness at the time of quenching is calculated from the austenite ratio, the cooling temperature, the coefficient corresponding to the additive elements and the hardness of a base metal (S12).SELECTED DRAWING: Figure 1
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Description

Technical Field

[0001] The present invention relates to a prediction method for predicting hardness during quenching.

Background Art

[0002] Patent Document 1 describes a method for calculating the hardness after quenching of a carburized and quenched part from the analysis results of carbon concentration and martensite ratio.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in Patent Document 1, it is necessary to obtain the martensite ratio in simulation, and phase transformation simulation software is required. Also, the reliability of the martensite ratio is unknown, and there is room for improvement in prediction accuracy.

Means for Solving the Problems

[0005] The prediction method for predicting the hardness during quenching according to the present embodiment calculates the austenite ratio from the heating temperature and the coefficient corresponding to the added element, and calculates the hardness during quenching from the austenite ratio, the cooling temperature, the coefficient corresponding to the added element, and the base material hardness.

Effects of the Invention

[0006] According to the prediction method for predicting the hardness during quenching of the present disclosure, since a prediction formula that does not require the martensite ratio is used, simulation software is not required. And the accuracy of the hardness prediction formula can be improved.

Brief Description of the Drawings

[0007]

Figure 1

Figure 2

Embodiments for Carrying Out the Invention

[0008] The present embodiment Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a flowchart showing an example of a prediction method for predicting the hardness during quenching according to the present embodiment.

[0009] First, in step S11, correlation data between the heating temperature and the austenite ratio of the part to be quenched is obtained (Formaster test). Then, the process proceeds to step S12.

[0010] Next, in step S12, the correlation between the heating temperature and the austenite ratio of the part to be quenched is formulated (logistic curve). For example, the correlation is formulated by the following formula (1). TIFF2025082427000002.tif20135 In formula (1), A and B are constants. A and B can change depending on the additive elements to the part to be quenched. Then, the process proceeds to step S13.

[0011] In step S13, correlation data between the austenite ratio, the cooling rate, and the hardness of the part to be quenched is obtained (hardness acquisition under each processing condition).

[0012] In step S14, the correlation between the austenite ratio, the cooling rate, and the hardness of the part to be quenched is formulated (logistic curve). For example, the correlation is formulated by the following formula (2). In Equation (2), C, D, and E are constants. C, D, and E can be changed by the additive elements to the parts to be quenched. Then the process ends.

[0013] Figure 2 is a graph showing an example of the relationship between the depth from the surface and the hardness. In Figure 2, the vertical axis indicates the hardness (HV), and the horizontal axis indicates the depth from the surface (mm). As shown in Figure 2, the predicted formula obtained from this embodiment and the measured values show a good agreement.

[0014] Thus, according to the prediction method for predicting the hardness during quenching in this embodiment, since the prediction formula does not require the martensite ratio, simulation software becomes unnecessary. And according to the prediction method for predicting the hardness during quenching in this embodiment, the accuracy of the hardness prediction formula can be improved.

[0015] Note that the present invention is not limited to the above embodiment, and can be appropriately changed without departing from the gist. For example, the hardness can be predicted based on either the measured temperature result or the temperature result of CAE (Computer Aided Engineering).

[0016] Also, each element described in the drawings as a functional block or flowchart that performs various processes can be configured hardware-wise by a CPU, memory, and other circuits, and software-wise by a program loaded into the memory or the like. Therefore, it is understood by those skilled in the art that these functional blocks can be realized in various forms by hardware, software, or a combination thereof, and are not limited to any one of them.

[0017] Also, the above-described program can be stored using various types of non-transitory computer-readable media and supplied to a computer. Non-transitory computer-readable media include various types of tangible recording media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, semiconductor memories (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)). Also, the program may be supplied to a computer by various types of transitory computer-readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. The transitory computer-readable media can supply the program to the computer via a wired communication path such as electric wires and optical fibers, or a wireless communication path.

Claims

【Claim 1】 Calculate the austenite ratio from the heating temperature and the coefficient corresponding to the added element, A prediction method for predicting the hardness during quenching, which calculates the hardness during quenching from the austenite ratio, the cooling temperature, the coefficient corresponding to the added element, and the base material hardness.

Citation Information

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