Tensile strength prediction method and manufacturing method of die-cast heat-treatment material

Abstract

To provide a tensile strength prediction method capable of predicting a tensile strength of an aluminum alloy die-cast material after a heat treatment.SOLUTION: A tensile strength prediction method measures a tensile strength Up1 of a test material before a heat-treatment, a solid-solution amount Dp1 of an element, a cavity volume Vp1, and a tensile strength Ua1 of the test material after the heat-treatment, a solid-solution amount Da1 of the element, and a cavity volume Va1, and assigns to an expression (1): (Ua1 / Up1)=A×(Da1 / Dp1)+B×(Va1 / Vp1)+C to obtain constant numbers A, B and C. Thereafter, a solid-solution amount Dp2 and a cavity volume Vp2 of the element in a target material before a heat-treatment and a solid-solution amount Da2 and a cavity volume Va2 of the element in the target material after the heat-treatment predicted at a prediction process, and the constant numbers A, B, and C are assigned to an expression (2): (Ua2 / Up2)=A×(Da2 / Dp2)+B×(Va2 / Vp2)+C, to predict a tensile strength (Ua2 / Up2) of the target material after the heat-treatment.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a tensile strength prediction method for predicting the tensile strength of an aluminum alloy die-cast material after heat treatment, and a method for producing heat-treated die-cast material using the tensile strength predicted by the tensile strength prediction method, which can easily produce a heat-treated die-cast material having a target tensile strength. [Background technology]

[0002] Die casting is a casting method that is suitable for mass production due to the fast filling speed of the molten metal, and can easily produce parts with complex shapes, resulting in excellent yields. However, because the molten metal is filled into the mold at high speed in die casting, gas is entrained within the mold, and the molten metal solidifies as it is, forming entrainment cavities. When this die-cast material is subjected to heat treatment (solution treatment) to improve its tensile strength, the entrainment cavities can expand. Furthermore, if the expanded entrainment cavities exist in areas where stress is concentrated, they can serve as the starting point for fracture of the heat-treated material, resulting in a significant decrease in mechanical strength.

[0003] As a heat treatment method for die-cast materials, for example, Patent Document 1 discloses a heat treatment method for an aluminum alloy die-cast member made of an Al-Si-Cu alloy, which can produce an aluminum alloy die-cast member free of blisters and having excellent strength. The heat treatment method described in Patent Document 1 includes a first step of heat treatment at a first heating temperature and for a time period that results in a volume expansion coefficient of 0.4% or less, and a second step, which is carried out subsequent to the first step, of heat treatment at a second heating temperature of 400°C or higher, higher than the first heating temperature, at which a desired amount of Cu is dissolved in the α-Al phase. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 4839264 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the technology described in Patent Document 1 is limited to the composition and type of aluminum alloy to be used, making it difficult to adapt the technology to various aluminum alloy materials. For example, suitable heat treatment methods for achieving high strength vary depending not only on the composition and type of the aluminum alloy material, but also on the shape and heat treatment conditions of the aluminum alloy material to be produced. Therefore, even if the heating temperature is specified within a predetermined range, it may not be possible to obtain a die-cast material with the desired strength. Furthermore, uniformly selecting heat treatment conditions may result in heating for longer than necessary, reducing production efficiency.

[0006] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a tensile strength prediction method that can predict the tensile strength of an aluminum alloy die-cast material after heat treatment, and a method for manufacturing heat-treated die-cast material that can use the prediction method to easily and efficiently manufacture heat-treated die-cast material having a target tensile strength. [Means for solving the problem]

[0007] The above object of the present invention is achieved by the following configuration [1] relating to a tensile strength prediction method.

[0008] [1] A tensile strength prediction method for predicting the tensile strength of a post-heat-treated target material made of an aluminum alloy die-cast material using a pre-heat-treatment test material made of an aluminum alloy die-cast material and a post-heat-treatment test material obtained by subjecting the aluminum alloy die-cast material to heat treatment under a plurality of heat treatment conditions, comprising: an element selection step of selecting elements that affect tensile strength according to the composition of the aluminum alloy die-cast material; a test material measuring step of measuring the amount of solid solution of the element, the volume of porosity and the tensile strength in the test material before the heat treatment, and measuring the amount of solid solution of the element, the volume of porosity and the tensile strength of a plurality of test materials after the heat treatment; a prediction formula deriving step of deriving a prediction formula for tensile strength so that the amount of solid solution of the element, the cavity volume, and the tensile strength have a common correlation in the pre-heat treatment test material and each of the post-heat treatment test materials; a target material solid solution amount prediction step of deriving a correlation regarding the solid solution amount of the element so that the plurality of heat treatment conditions and the solid solution amount of the element in the heat-treated test material have a predetermined relationship, and predicting the solid solution amount of the target material after the heat treatment; A target material cavity volume prediction step of deriving a correlation regarding the cavity volume so that the plurality of heat treatment conditions and the cavity volume of the heat-treated test material have a predetermined relationship, and predicting the cavity volume in the target material after the heat treatment; a tensile strength prediction step of predicting the tensile strength of the heat-treated target material by substituting the amount of solid solution of the element in the heat-treated target material predicted based on the target material solid solution amount prediction step and the cavity volume in the heat-treated target material predicted based on the target material cavity volume prediction step into the prediction formula derived in the prediction formula derivation step; A tensile strength prediction method comprising the steps of:

[0009] Furthermore, preferred embodiments of the present invention relating to the tensile strength prediction method relate to the following [2] to [9].

[0010] [2] The test material measurement step A pre-heat treatment test material measurement step of measuring the tensile strength Up1, the solid solution amount Dp1 of the element, and the porosity volume Vp1 of the pre-heat treatment test material; and a post-heat-treated test material measuring step of measuring a tensile strength Ua1, a solid solution amount Da1 of the element, and a porosity volume Va1 for each of the post-heat-treated test materials that have been heat-treated under the plurality of heat treatment conditions, at least some of which are different from each other, The prediction equation deriving step includes: a constant calculation step of calculating constants A, B, and C common to the following formula (1) by substituting the tensile strength Up1, the amount of solid solution of the element Dp1, and the cavity volume Vp1 of the pre-heat-treatment test material, and the tensile strength Ua1, the amount of solid solution of the element Da1, and the cavity volume Va1 of each of the post-heat-treatment test materials into the following formula (1), Formula (1): (Ua1 / Up1)=A×(Da1 / Dp1)+B×(Va1 / Vp1)+C The target material solid solution amount prediction step includes: a solid solution amount deriving step of deriving a correlation between the solid solution amount Dp1 of the element in the pre-heat-treatment test material and the solid solution amount Da1 of the element in each of the post-heat-treatment test materials; a target material solid solution amount calculation step of calculating a solid solution amount Da2 of the element in the target material after the heat treatment under predetermined heat treatment conditions from the solid solution amount Dp2 of the element in the target material before the heat treatment based on the correlation of the solid solution amount derived in the solid solution amount derivation step, The target cavity volume prediction step includes: A porosity volume derivation step of deriving a correlation between the porosity volume Vp1 in the pre-heat-treatment test material and the porosity volume Va1 in the post-heat-treatment test material; and a target material cavity volume calculation step of calculating a cavity volume Va2 in the target material after the heat treatment under the predetermined heat treatment conditions from a cavity volume Vp2 in the target material before the heat treatment based on the correlation of the cavity volume derived by the cavity volume derivation step, In the tensile strength prediction step, The tensile strength Up2, the amount of solid solution Dp2 of the element, and the cavity volume Vp2 of the target material before the heat treatment, and the amount of solid solution Da2 of the element and the cavity volume Va2 of the target material after the heat treatment, and the constants A, B, and C derived in the constant calculation step are substituted into the following formula (2), Formula (2): (Ua2 / Up2)=A×(Da2 / Dp2)+B×(Va2 / Vp2)+C The tensile strength prediction method according to [1], characterized in that it predicts the tensile strength (Ua2 / Up2) of the target material after the heat treatment.

[0011] [3] The test material measurement step includes: A pre-heat treatment test material measurement step of measuring the tensile strength Up1, the solid solution amount Dp1 of the element, and the porosity volume Vp1 of the pre-heat treatment test material; and a post-heat-treated test material measuring step of measuring a tensile strength Ua1, a solid solution amount Da1 of the element, and a porosity volume Va1 for each of the post-heat-treated test materials that have been heat-treated under the plurality of heat treatment conditions, at least some of which are different from each other, The prediction equation deriving step includes: a constant calculation step of substituting the tensile strength Up1, the amount of solid solution of the element Dp1, and the cavity volume Vp1 of the pre-heat-treatment test material, and the tensile strength Ua1, the amount of solid solution of the element Da1, and the cavity volume Va1 of each of the post-heat-treatment test materials into the following formulas (3) and (4), to calculate constants A, B, and C common to the following formulas (3) and (4), Formula (3): Up1=A×Dp1+B×Vp1+C Formula (4): Ua1=A×Da1+B×Va1+C The target material solid solution amount prediction step includes: a solid solution amount deriving step of deriving a correlation between the solid solution amount Dp1 of the element in the pre-heat-treatment test material and the solid solution amount Da1 of the element in each of the post-heat-treatment test materials; a target material solid solution amount calculation step of calculating a solid solution amount Da2 of the element in the target material after the heat treatment under predetermined heat treatment conditions from the solid solution amount Dp2 of the element in the target material before the heat treatment based on the correlation of the solid solution amount derived in the solid solution amount derivation step, The target cavity volume prediction step includes: A porosity volume derivation step of deriving a correlation between the porosity volume Vp1 in the pre-heat-treatment test material and the porosity volume Va1 in the post-heat-treatment test material; and a target material cavity volume calculation step of calculating a cavity volume Va2 in the target material after the heat treatment under the predetermined heat treatment conditions from a cavity volume Vp2 in the target material before the heat treatment based on the correlation of the cavity volume derived by the cavity volume derivation step, In the tensile strength prediction step, The amount Da2 of the solid solution of the element in the heat-treated target material and the cavity volume Va2, and the constants A, B, and C derived in the constant calculation step are substituted into the following formula (5), Formula (5): Ua2=A×Da2+B×Va2+C The tensile strength prediction method according to [1], characterized in that it predicts the tensile strength Ua2 of the target material after the heat treatment.

[0012] [4] Further, an adjustment step is performed after the tensile strength prediction step, The adjusting step includes: A strength measurement step of measuring the tensile strength Ua3 of the target material after the heat treatment; a confirmation process of comparing the tensile strength Ua2 of the heat-treated target material predicted in the tensile strength prediction process with the tensile strength Ua3 actually measured in the strength actual measurement process to confirm whether an error has occurred; a re-prediction step of repeating the test material measurement step, the prediction formula deriving step, the target material solid solution amount prediction step, the target material cavity volume prediction step, and the tensile strength prediction step, when an error of a predetermined value or more occurs in the confirmation step, by performing a heat treatment on the aluminum alloy die-cast material under a plurality of heat treatment conditions other than the heat treatment conditions used in the test material measurement step.

[0013] [5] A tensile strength prediction method according to any one of [1] to [4], characterized in that in the element selection step, the amount of solid solution of a plurality of elements contained in the pre-heat treatment test material and the tensile strength Up1 of the pre-heat treatment test material are compared with the amount of solid solution of the plurality of elements contained in each of the post-heat treatment test materials after heat treatment under the plurality of heat treatment conditions and the tensile strength Ua1 of each of the post-heat treatment test materials, and elements from the plurality of elements that have a high correlation with the tensile strength Up1 and the tensile strength Ua1 are selected.

[0014] [6] The plurality of heat treatment conditions are heat treatment conditions in which at least some of the heat treatments are performed at different test temperatures T1 and test times H1, The solid solution amount deriving step includes: A calorific value quantification step is included in which a constant X is calculated so that a Larson-Miller parameter LMP1 calculated by the following formula (6) based on the test temperature T1 and the test time H1 and a solid solution amount Da1 of the element in the post-heat-treatment test material after performing heat treatment under the plurality of heat treatment conditions have a high correlation. Equation (6): LMP1=T1×(X+Log(H1)) In the step of calculating the amount of solid solution of the target material, The constant X calculated in the heat quantity quantification step, and the temperature T2 and time H2 of the heat treatment performed on the pre-heat treatment target material are substituted into the following formula (7), Equation (7): LMP2=T2×(X+Log(H2)) The tensile strength prediction method according to [2] or [3], characterized in that the amount of solid solution Da2 of the element in the target material after the heat treatment is calculated based on the obtained Larson-Miller parameter LMP2.

[0015] [7] In the solid solution amount derivation step, if there is a heat treatment condition among the plurality of heat treatment conditions under which the effect of the solid solution amount Da1 of the element in the heat-treated test material on the tensile strength Ua1 of the heat-treated test material is saturated, The tensile strength prediction method according to [2] or [3], characterized in that a correlation is derived between the amount of solid solution Dp1 of the element in the test material before heat treatment and the amount of solid solution Da1 of the element in the test material after heat treatment, except for the heat treatment conditions under which the tensile strength Ua1 is saturated.

[0016] [8] The test material measurement step includes: The porosity volume Vp1 in the test material before the heat treatment and the porosity volume Va1 in the test material after the heat treatment were measured by CT, In the cavity volume derivation step, The tensile strength prediction method according to [2] or [3], characterized in that the correlation between the porosity volume Vp1 in the test material before heat treatment and the porosity volume Va1 in the test material after heat treatment is derived by organizing the porosity volume Vp1 and the porosity volume Va1 using Weibull analysis.

[0017] [9] The aluminum alloy die-cast material is an Al-Si-Cu alloy material represented by alloy symbol ADC12 specified in JIS H 5302:2006, The tensile strength prediction method according to any one of [1] to [8], wherein the element that affects the tensile strength is Cu.

[0018] The above object of the present invention is also achieved by the following configuration

[10] relating to a method for manufacturing a heat-treated die-cast material.

[0019]

[10] A method for producing a die-cast heat-treated material, comprising a step including the tensile strength prediction method according to any one of [1] to [9], a solution treatment step of subjecting the pre-heat treatment target material made of the aluminum alloy die-cast material to solution treatment; a quenching step of rapidly cooling the heat-treated material after the solution treatment step; an artificial age hardening treatment step of performing an artificial age hardening treatment on the quenched target material after the quenching step, a heat treatment condition for the solution treatment is selected in the solution treatment step so that the tensile strength of the target material after the heat treatment predicted by the tensile strength prediction method falls within a target range. [Effects of the Invention]

[0020] According to the tensile strength prediction method of the present invention, the tensile strength of an aluminum alloy die-cast material after heat treatment can be easily predicted. Also, according to the manufacturing method of heat-treated die-cast material of the present invention, the prediction method can be used to easily manufacture heat-treated die-cast material having a target tensile strength with high production efficiency. [Brief explanation of the drawings]

[0021] [Figure 1] FIG. 1 is a graph showing the temperature change during the T6 treatment of a typical aluminum alloy casting material, with the vertical axis representing temperature and the horizontal axis representing time. [Figure 2]FIG. 2 is a schematic diagram showing the effect of heat treatment on entrapment porosity in die-cast material. [Figure 3] FIG. 3 is a perspective view showing an example of the shape of a column housing as a die-cast product for test material. [Figure 4A] FIG. 4A is a schematic diagram showing the position from which a test piece for a tensile test is taken in the direction of an arrow 5A with respect to the column housing shown in FIG. [Figure 4B] FIG. 4B is a schematic diagram showing the position from which a test piece for a tensile test is taken in the direction of an arrow 5B with respect to the column housing shown in FIG. [Figure 4C] FIG. 4C is a schematic diagram showing the position from which a test piece for a tensile test is taken in the direction of an arrow 5C with respect to the column housing shown in FIG. [Figure 4D] FIG. 4D is a schematic diagram showing the position from which a test piece for a tensile test is taken in the direction of an arrow 5D relative to the column housing shown in FIG. [Figure 5] FIG. 5 is a schematic diagram showing the shape of a test piece for a tensile test. [Figure 6] FIG. 6 is a graph showing the relationship between tensile strength and the amount of solid solution of Cu, with the vertical axis representing tensile strength (Ua1 / Up1) and the horizontal axis representing the amount of solid solution of Cu (Da1 / Dp1). [Figure 7] FIG. 7 is a graph showing the relationship between tensile strength and the amount of solid solution of Cu (Da1 / Dp1) using only specific data, with the vertical axis representing tensile strength (Ua1 / Up1) and the horizontal axis representing the amount of solid solution of Cu (Da1 / Dp1). [Figure 8] FIG. 8 is a graph showing the relationship between the amount of solid solution of Cu (Da1 / Dp1) and the Larson-Miller parameter LMP1, with the vertical axis representing the amount of solid solution of Cu (Da1 / Dp1) and the horizontal axis representing the Larson-Miller parameter LMP1. [Figure 9] FIG. 9 is a graph showing the porosity volumes in the test materials before and after the heat treatment, with the vertical axis representing cumulative probability (%) and the horizontal axis representing voxels. [Figure 10A] FIG. 10A is a graph showing the relationship between the defect volume expansion coefficient and the heat treatment time, with the vertical axis representing the defect volume expansion coefficient and the horizontal axis representing the heat treatment time. [Figure 10B] FIG. 10B is a graph showing the relationship between the defect volume expansion coefficient and the heat treatment temperature, with the vertical axis representing the defect volume expansion coefficient and the horizontal axis representing the heat treatment temperature. [Figure 11] FIG. 11 is a graph showing the range in which a desired tensile strength is obtained, with the vertical axis representing the heat treatment temperature and the horizontal axis representing the heat treatment time. DETAILED DESCRIPTION OF THE INVENTION

[0022] The present inventors have conducted extensive research to solve the above problems. As a result, they have found that the tensile strength of a die-cast material after heat treatment, which is initiated by porosity, is significantly affected by the amount of a predetermined element dissolved in the die-cast material after heat treatment and the volume expansion coefficient of the defect. First, the relationship between the amount of an element dissolved in the die-cast material and the tensile strength will be described below.

[0023] FIG. 1 is a graph showing the temperature change during the T6 treatment of a typical aluminum alloy cast material, with the vertical axis representing temperature and the horizontal axis representing time. After the high-temperature molten metal is cooled in the mold, it is subjected to a solution treatment (heat treatment), followed by quenching and artificial aging hardening. The present inventors focused on the relationship between the temperature and time of the solution treatment and the amount of solid solution of a predetermined element. They measured the amount of solid solution of Cu in the aluminum alloy material before and after the heat treatment by spectroscopic analysis and found that the amount of solid solution of Cu after the heat treatment was increased compared to before the heat treatment. The present inventors also found that the greater the amount of solid solution of Cu, the greater the strength of the matrix structure, i.e., the strength of the cast material when there are no defects such as porosity.

[0024] Next, the inventors of the present application focused on the relationship between the temperature and time of solution treatment and defects such as porosity in the cast material. Figure 2 is a schematic diagram showing the effect of heat treatment on entrapment porosity in a die-cast material. As shown in Figure 2, entrapment porosity 2 is inevitably present in the die-cast material 1. When the die-cast material 1 is subjected to heat treatment, the entrapment porosity 2 present in the die-cast material 1 expands, as described above. Furthermore, when subsequent heat treatment is performed, the entrapment porosity 2 on the surface of the die-cast material 1 expands further, and those near the surface may become blisters 3. Thus, when the die-cast material 1 is subjected to heat treatment, the expansion of the entrapment porosity 2 inside the die-cast material 1 and the formation of blisters 3 significantly reduce the tensile strength of the die-cast material 1 after heat treatment.

[0025] Therefore, the present inventors discovered that it is important to select heat treatment conditions that can increase the amount of Cu in solid solution, which is a benefit of heat treatment, while suppressing the expansion of porosity, which is a disadvantage. They then derived a formula using the amount of solid solution of elements that affect strength and the volume of porosity, and found that this formula can be used to efficiently predict the tensile strength of die-cast materials after heat treatment. The present invention was made based on the above findings.

[0026] A tensile strength prediction method according to an embodiment of the present invention will be described below.

[0027] [Tensile strength prediction method] The tensile strength prediction method according to the present embodiment is a method for predicting the tensile strength of a post-heat-treated target material made of an aluminum alloy die-cast material, using a pre-heat-treatment target material made of an aluminum alloy die-cast material and post-heat-treatment test materials obtained by subjecting this aluminum alloy die-cast material to heat treatment under a plurality of heat treatment conditions. In the above tensile strength prediction method, it is preferable to carry out an adjustment step, which will be described later, as necessary.

[0028] [First embodiment] In the first embodiment, first, a test material having the same shape as the target product is prepared using the same material as the target product, and this test material is subjected to heat treatment under various conditions. Then, the ratios (relative values) of the amount of solid solution of elements that affect strength, tensile strength, and porosity volume are calculated for the test material before and after heat treatment, and correlations are derived. Each step is described in detail below.

[0029] <Preparation of test material> In this embodiment, an example will be described in which a column housing made of an Al-Si-Cu alloy (ADC12 material) is used as the product for predicting tensile strength. First, using the same aluminum alloy die-cast material (e.g., ADC12 material) as the target product (subject material), heated molten metal is injection molded while evacuating to create a die-cast product for testing. Injection molding while evacuating involves installing a vacuum valve above the die-cast cavity and using an external vacuum pump to suck the material. To achieve a higher vacuum, the die-cast mold, injection plunger, etc. may be sealed.

[0030] The range of components of the alloy ADC12 material specified in JIS H 5302:2006 and the like is shown in Table 1. Table 1 also shows the composition of the column housing (die-cast product for test material) used in this embodiment, measured by spectroscopic analysis.

[0031] [Table 1]

[0032] 3 is a perspective view showing an example of the shape of a column housing as a die-cast product for test material. The roughly cylindrical column housing 10 rotatably supports a steering shaft (not shown) on its inner diameter side via a bearing (not shown). The column housing 10 is also provided with a key lock hole 12, a pair of key lock unit mounting bosses 13 each having a bolt hole 14, and the like.

[0033] <Element selection process> In the element selection step, elements that affect the tensile strength of the heat-treated target material are selected according to the composition of the aluminum alloy die-cast material used. For example, elements that are present in large amounts in the aluminum alloy die-cast material and are known to exhibit age hardening upon heat treatment can be selected. Alternatively, the following selection method can be used. For example, an energy dispersive X-ray fluorescence analyzer (EDX) is used to compare the amounts of solid solution of multiple elements contained in the pre-heat-treatment test material and the tensile strength Up1 of the pre-heat-treatment test material with the amounts of solid solution of multiple elements contained in each heat-treated test material and the tensile strength Ua1 of the post-heat-treatment test material after heat treatment under multiple heat treatment conditions. Then, it is possible to select elements from the multiple elements that have a high correlation with the tensile strength Up1 and the tensile strength Ua1.

[0034] This element selection step may be performed in the test material measurement step described below, during which the solid solution amounts of multiple elements and the tensile strength of the pre-heat-treatment test material and the post-heat-treatment test material are measured. More specifically, based on the measured tensile strength and literature, etc., components that are likely to affect the tensile strength or that are likely to provide a high heat treatment effect can be selected, and the element (Cu) that is thought to have the highest correlation can be selected. If two elements have a high correlation with the tensile strength of the post-heat-treatment test material, these two elements can also be selected.

[0035] In this embodiment, for example, Cu is selected as an element that affects the tensile strength. Cu is contained in large amounts in ADC12 material, is an element that can dissolve into the matrix by heat treatment, and is known to affect the strength of the member after heat treatment, so it is preferable to select Cu.

[0036] <Test material measurement process> The test material measurement step includes a pre-heat treatment test material measurement step and a post-heat treatment test material measurement step. In the pre-heat treatment test material measurement step, the solid solution amount Dp1 of the selected element (Cu), the cavity volume Vp1, and the tensile strength Up1 of the pre-heat treatment test material are measured. In the post-heat treatment test material measurement step, the solid solution amount Da1 of the selected element (Cu), the cavity volume Va1, and the tensile strength Ua1 of the post-heat treatment test material that has been heat-treated under a plurality of conditions are measured. In this test material measurement step, it is preferable to also measure the tensile strength Up1 of the pre-heat treatment test material. By measuring the tensile strength Up1 of the pre-heat treatment test material and the tensile strength Ua1 of the post-heat treatment test material described below, the degree of the heat treatment effect can be confirmed.

[0037] In this specification, the tensile strength, amount of solid solution of elements, and cavity volume of the test material before or after heat treatment are represented by letters and numbers. Specifically, the first letters U, D, and V represent tensile strength, amount of solid solution, and cavity volume, respectively, and the second letters p and a represent before and after heat treatment, respectively. Furthermore, the third letters 1 and 2 represent whether the material is a test material or a material whose tensile strength is actually being predicted, respectively.

[0038] (Measurement of tensile strength) The tensile strength prediction method according to this embodiment is a method for predicting the tensile strength of a post-heat-treated target material after heat treatment (solution treatment) of a pre-heat-treated target material. Therefore, to confirm the tensile strength before and after heat treatment, a column housing without heat treatment (pre-heat-treated test material) and a column housing heat-treated under a plurality of heat treatment conditions, at least some of which are different from each other (post-heat-treated test material) are prepared, and the tensile strengths of these test materials are measured. As the heat treatment conditions, at least three conditions, some of which are different from each other, are sufficient, but the more types of heat treatment conditions there are, the more accurate the prediction. Table 2 below shows examples of heat treatment conditions for the column housing 10. In Table 2 below, heat treatment numbers N7 and N8 are examples in which a two-stage heat treatment was performed. That is, after a heat treatment at 410°C for 3 hours, a further heat treatment at 460°C for 1 hour or 0.25 hours was performed.

[0039] [Table 2]

[0040] Test pieces for measuring tensile strength are taken from multiple locations on the test material that has undergone the heat treatment shown in Table 2 above. FIGS. 4A to 4D are schematic diagrams showing the positions from which test pieces for tensile testing are taken from the directions of arrows 5A to 5D, respectively, relative to the column housing shown in FIG. 3. In this embodiment, for example, 12 test pieces are taken for one column housing 10, and therefore, measurements are performed on 24 test pieces for one condition. Specifically, as shown in FIGS. 4A to 4D, test pieces 11a to 11c, each having a long side parallel to the axial direction of the column housing 10, are taken from the same circumferential region as the position where the key lock unit mounting boss 13 is provided. Furthermore, test pieces 11d to 11j, each having a long side parallel to the axial direction of the column housing 10, are taken rearward of test pieces 11a to 11c. Furthermore, test pieces 11k and 11m, each having a long side parallel to the axial direction of the column housing 10, are taken rearward of test pieces 11d to 11j.

[0041] Although the number of test pieces for each condition is not particularly limited, if the die-cast product used as the test material has a complex shape or a shape that causes differences in heat transfer time, it is preferable to collect test pieces from multiple different locations. Furthermore, if the stress concentration area is limited and there are a sufficient number of samples (column housings in this embodiment), it is also preferable to collect many test pieces so that the stress concentration area is located in the center of the tensile test piece. Even if it is difficult to collect test pieces so that the stress concentration area is located exactly in the center of the test piece, collecting many test pieces makes it possible to check the variation in the heat treatment state and the influence of defects depending on the location.

[0042] FIG. 5 is a schematic diagram showing the shape of a test piece for a tensile test. As shown in FIG. 5, the test piece 20 is thinner in the longitudinal center than at both ends, with a longitudinal length of 35 mm to 50 mm, a parallel portion 21 of the thin portion having a length of 12±0.1 mm, and both end portions 22 having a width of 10.0±0.1 mm, and the parallel portion 21 having a width of 5±0.1 mm. The test piece is formed so as to gradually narrow from both end portions 22 to the parallel portion 21, with a curvature radius R of 5 mm. The tensile test is performed, for example, using a precision universal testing machine (AUTOGRAPH AG-X 100 kN, manufactured by Shimadzu Corporation) at a strain rate of, for example, 5.0×10 -4 The above can be measured by a known method, but the test conditions and test equipment are not particularly limited.

[0043] In this embodiment, the tensile strength Up1 and tensile strength Ua1 are measured for each test piece taken from the test materials with the heat treatment numbers N1 to N12. At this time, it is preferable to observe the fracture surface to confirm the effect of porosity on the tensile strength, and to select only those specimens in which the fracture originated from a porosity and those without any clear defects. The average, maximum, minimum, and average -3σ values ​​of the tensile strengths of the selected test pieces are shown in Table 3 below. The values ​​shown in Table 3 below are expressed as 1.00, based on the average value without heat treatment, i.e., the average value of the tensile strength for heat treatment number N1. The average, maximum, minimum, and average -3σ values ​​of the tensile strengths of the test materials after heat treatment (heat treatment numbers N2 to N12) are expressed as a ratio to heat treatment number N1 (relative value: Ua1 / Up1).

[0044] [Table 3]

[0045] (Measurement of the amount of solid solution of elements) In this step, the amount of solid solution of elements is measured for the test material before and after heat treatment. To measure the amount of solid solution of the element (Cu), first, a test piece for measuring the amount of solid solution is taken from a predetermined location for the test material before and after heat treatment under the conditions of heat treatment numbers N1 to N12 shown in Table 2 above, and then embedded in resin. Next, the amount of Cu dissolved in the Al matrix is ​​measured at five positions: 50 μm, 100 μm, 200 μm, 300 μm, and 500 μm from the surface of the test piece. Six points at each position are measured for a total of 30 points, and the average value for each test material is calculated. The amount of solid solution of Cu can be measured, for example, by analysis using an energy dispersive X-ray fluorescence analyzer (JEOL Ltd.: JSM-IT300LV). The measurement results for the amount of solid solution of the element (Cu) in the test material before and after heat treatment are shown in Table 4 below. The amount of Cu dissolved in solid solution shown in Table 4 below is expressed as 1.00, based on the average value of the amount of Cu dissolved in solid solution (Dp1) in the case without heat treatment, i.e., heat treatment number N1, and the amount of dissolved element Da1 in the test material after heat treatment (heat treatment numbers N2 to N12) is also expressed as an average value and as a ratio to heat treatment number N1 (relative value: Da1 / Dp1).

[0046] [Table 4]

[0047] (Measurement of nest volume) Two column housings were prepared for each condition: one without heat treatment (pre-heat treatment test material) and two column housings heat-treated under some of the heat treatment conditions listed in Table 2 (post-heat treatment test material). The volume of the entrapment cavities (cavity volume) formed in these test materials was measured. The cavities volume can be measured by performing a CT scan at a resolution of, for example, 80 μm using an X-ray CT scanner (manufactured by Carl Zeiss) on the vicinity of the key lock hole 12 of the column housing 10 shown in FIG. 5 . Defect analysis software such as Volume Graphic Version 3.5 (software manufactured by Volume Graphics, Inc.) can be used. While the measurement position for the cavities volume is not particularly limited, shrinkage cavities are likely to form inside portions with thick or unstable wall thicknesses. Therefore, in this embodiment, it is preferable to perform a CT scan on a portion with a relatively thin and uniform wall thickness to avoid portions where shrinkage cavities and entrapment cavities are mixed, i.e., to measure portions with as many entrapment cavities as possible.

[0048] Table 5 below shows the heat treatment conditions for the column housing 10 for some test materials, and the defect volume expansion coefficients actually measured under each heat treatment condition. The defect volume expansion coefficient represents the ratio of the porosity volume Va1 of the test material after heat treatment to the porosity volume Vp1 of the test material without heat treatment, i.e., heat treatment number N1 (test material before heat treatment). Note that the defect volume expansion coefficients shown in Table 5 below are expressed as 1.00 when the heat treatment conditions are 450°C x 5 hours, i.e., the defect volume expansion coefficient for heat treatment number N5, is used as the reference, and the defect volume expansion coefficients of the other test materials are expressed as ratios to heat treatment number N5.

[0049] [Table 5]

[0050] <Prediction formula derivation process> The prediction formula deriving step is a step of deriving a prediction formula for tensile strength so that the amount of solid solution of elements, the volume of porosity, and the tensile strength have a common correlation in the pre-heat-treatment test material and each post-heat-treatment test material. As described above, based on the knowledge that the tensile strength of the post-heat-treatment test material is affected by the amount of solid solution of Cu and the volume expansion coefficient, the tensile strength prediction formula is derived based on the values ​​measured under the above-mentioned multiple heat treatment conditions.

[0051] (Constant calculation process) In this embodiment, the prediction formula deriving step includes a constant calculation step. Specifically, in the constant calculation step, the tensile strength Up1 of the pre-heat treatment test material, the amount of solid solution of the element (Cu) in the pre-heat treatment test material Dp1, and the porosity volume Vp1 of the pre-heat treatment test material, as well as the tensile strength Ua1 of the post-heat treatment test material, the amount of solid solution of the element (Cu) in the post-heat treatment test material Da1, and the porosity volume Va1 of the post-heat treatment test material are substituted into the following formula (1) to calculate constants A, B, and C common to the following formula (1). Note that when multiple elements are selected as elements that affect the tensile strength after heat treatment, the solid solution amounts of these multiple elements before and after heat treatment may be used to calculate the constants according to the following formula (1). Formula (1): Ua1 / Up1=A×(Da1 / Dp1)+B×(Va1 / Vp1)+C

[0052] Specifically, the process of calculating the constants can be performed by using regression analysis to reflect values ​​measured under multiple heat treatment conditions in the above formula (1). For example, first, for the heat treatment numbers N3, N5, N6, N9, N10, and N11, the tensile strength Ua1, porosity volume Vp1, and solid solution amount Dp1 of the element (Cu) of the test material after heat treatment are measured and summarized. The measured values ​​under each heat treatment condition are shown in Table 6 below.

[0053] [Table 6]

[0054] Next, by substituting the tensile strength, the amount of Cu in solid solution, and the defect volume expansion coefficient shown in Table 6 above into the above formula (1) and performing a regression analysis, the intercept in the above formula (1), the constant A for the amount of Cu in solid solution, and the constant B for the defect volume expansion coefficient are calculated as follows. Intercept (constant C): 0.243045568 Coefficient of Cu solid solubility (constant A): 0.376949916 Coefficient of defect volume expansion rate (constant B): -0.034374237 Furthermore, when multiple heat treatments are performed, the constants A, B, and C can be calculated more accurately by performing regression analysis again taking these values ​​into consideration.

[0055] <Process for predicting the amount of solid solution in the target material> The target material solid solution amount prediction step is a step of deriving a correlation regarding the solid solution amount of an element so that the plurality of heat treatment conditions and the solid solution amount of the element in the heat-treated test material have a predetermined relationship, and predicting the solid solution amount of the target material after the heat treatment. The target material solid solution amount prediction step preferably includes a solid solution amount derivation step and a target material solid solution amount calculation step.

[0056] (Solid solution amount derivation process) The solid solution amount deriving step is a step of deriving the correlation between the solid solution amount Dp1 of an element in the pre-heat-treated test material and the solid solution amount Da1 of the element in each post-heat-treatment test material. First, the correlation between the tensile strength Ua1 of the post-heat-treatment test material and the solid solution amount Da1 of the above element in the post-heat-treatment test material under the multiple heat treatment conditions shown in Table 2 above will be explained.

[0057] By performing heat treatment on the pre-heat-treated test material, AlCu does not precipitate after quenching from the α-phase solid solution state, and the α-phase becomes supersaturated with Cu, which affects strength. As mentioned above, the higher the heat treatment temperature, the greater the solid solubility limit of Cu in the Al matrix. Furthermore, the greater the amount of Cu dissolved in the matrix (the amount of Cu solid solution), the higher the tensile strength. Note that this tendency is observed when the aluminum alloy die-cast material for which tensile strength is predicted is, for example, Al-4%Cu material. However, a similar tendency is also expected to be observed in materials such as ADC12, which contain nearly 2% Cu.

[0058] Figure 6 is a graph showing the relationship between tensile strength and the amount of Cu solid solution, with the vertical axis representing tensile strength (Ua1 / Up1) and the horizontal axis representing the amount of Cu solid solution (Da1 / Dp1). The tensile strength (Ua1 / Up1) shown in Figure 6 is the maximum value among the tensile strengths listed in Table 3. This is because selecting the maximum value of tensile strength allows the tensile strength to be considered close to that of the test material in which the influence of porosity is small and the heat treatment effect of only the matrix structure is achieved. As shown in Figure 6, when the influence of porosity is not considered, a high correlation is observed between tensile strength (Ua1 / Up1) and the amount of Cu solid solution (Da1 / Dp1). However, in the region where the relative value of the amount of Cu solid solution is approximately 2.7 or higher, variability in tensile strength occurs. This is thought to be because when the relative value of the amount of Cu solid solution exceeds a certain value, it becomes supersaturated and no longer affects the strength. That is, among the above heat treatment conditions, it is presumed that the heat treatment numbers N5 to N12, in which the relative value of the amount of solid solution of Cu is 2.70 or more, are excessively effective.

[0059] Here, for heat treatment numbers N2 to N4, where the heat treatment effect is not excessive, comparing the maximum tensile strength with the element solid solution amount Da1 reveals an even stronger correlation. Furthermore, even if the heat treatment effect is excessive, if there are test specimens that have been heat treated at the same heat treatment temperature, test specimens with shorter heat treatment times under the same treatment conditions may also be used for comparison. Table 7 below shows data extracted from heat treatment conditions that are considered to have a high correlation between tensile strength Ua1 and element solid solution amount Da1.

[0060] [Table 7]

[0061] 7 is a graph showing the relationship between tensile strength and the amount of solid solution of Cu (Da1 / Dp1) using only specific data, with the vertical axis representing tensile strength (Ua1 / Up1) and the horizontal axis representing the amount of solid solution of Cu (Da1 / Dp1). As shown in Fig. 7, if there is a heat treatment condition among multiple heat treatment conditions under which the effect of the amount of solid solution of elements (Da1 / Dp1) in the heat-treated test material on the tensile strength (Ua1 / Up1) of the heat-treated test material becomes saturated, the correlation between the amount of solid solution of elements (Dp1) in the test material before heat treatment and the amount of solid solution of elements (Da1) in the heat-treated test material can be derived, excluding the heat treatment condition under which the tensile strength (Ua1 / Up1) becomes saturated, and the correlation between the two can be further improved.

[0062] From the above comparison, it can be seen that the tensile strength (Ua1 / Up1) of the heat-treated test material is significantly affected by the solid solution amount (Da1 / Dp1) of the above elements in the heat-treated test material. Therefore, in the solid solution amount derivation process, a correlation is derived between the solid solution amount Dp1 of the elements in the test material before heat treatment and the solid solution amount Da1 of the elements in the heat-treated test material under multiple heat treatment conditions. In other words, by deriving the above correlation, the solid solution amount Dp1 of the elements in the heat-treated test material can be derived based on the solid solution amount Dp1 of the elements in the test material before heat treatment and the heat treatment conditions.

[0063] (Calorie quantification process) The solid solution amount deriving step preferably includes a heat quantity quantification step. To quantitatively express the amount of heat, the Larson-Miller parameter (LMP), which is a formula between temperature and time, may be used. LMP is an evaluation method using various temperatures and times as parameters, and is a concept for equivalently evaluating the thermal energy received in experiments where the temperature and time are changed. If the above-mentioned multiple heat treatment conditions are at least partially heat treatment conditions performed at different test temperatures T1 and test times H1, the heat quantity quantification step is a step of calculating a constant X based on the test temperature T1 and test time H1 using the following formula (6) so that there is a high correlation between the Larson-Miller parameter LMP1 and the solid solution amount Da1 of the element in the post-heat-treated test material after heat treatment under the multiple heat treatment conditions. The multiple heat treatment conditions can be expressed by the Larson-Miller parameter LMP1 in the following formula (6), where X is a constant. Equation (6): LMP1=T1×(X+Log(H1))

[0064] The effect of heat treatment on improving tensile strength is considered to be correlated with LMP1, expressed by the above formula (6). The relationship between LMP1 and the amount of solid solution Cu (Da1 / Dp1) was analyzed under the heat treatment conditions shown in Table 7, which are conditions immediately before the effect of the amount of solid solution Cu in the heat-treated test material (Da1 / Dp1) reaches saturation. Specifically, the heat treatment conditions shown in Table 7, excluding the conditions under which the effect of the amount of solid solution Cu on tensile strength is considered to reach saturation, are designated as the test temperature T1 and test time H1. A graph was then created between the Larson-Miller parameter LMP1 calculated from the test temperature T1 and test time H1 and the amount of solid solution Cu in the heat-treated test material (Da1 / Dp1), and the constant X was calculated so that the two have the highest correlation.

[0065] For example, when calculating the constant X for the five levels shown in Table 7 above, any integer is substituted for X to calculate the Larson-Miller parameter LMP1 for the five levels, and the amount of Cu solid solution (Da1 / Dp1) and the Larson-Miller parameter LMP1 for each value of X are also calculated. When a value from 10 to 200 is substituted for X, for example, as shown in Table 8 below, when X=165, the correlation coefficient between Da1 and LMP1 is closest to 1, so X=165 can be used.

[0066] [Table 8]

[0067] Thus, each condition determined by the temperature and time of the solution treatment is determined by the Larson-Miller parameter LMP1, which quantitatively represents the amount of heat. As described above, it can be seen that, for the above five levels, when the constant X is set to 165, the Larson-Miller parameter LMP1 has a high correlation with the amount of Cu in solid solution. Next, the calculated constant X, the heat treatment temperature, and the time are substituted into the above formula (6) to calculate the Larson-Miller parameter LMP1, and the relationship between LMP1 and the amount of Cu in solid solution (Da1 / Dp1) is graphed.

[0068] 8 is a graph showing the relationship between the amount of Cu in solid solution (Da1 / Dp1) and the Larson-Miller parameter LMP1, with the vertical axis representing the amount of Cu in solid solution (Da1 / Dp1) and the horizontal axis representing the Larson-Miller parameter LMP1. As shown in FIG. 8, the amount of Cu in solid solution (Da1 / Dp1) and LMP1 have a proportional relationship as shown in the following formula (8). Formula (8):y=0.0000595855x-4.3889962129 Therefore, by using the above formula (8), the amount of solid solution Cu Da1 in the test material after heat treatment can be derived from the amount of solid solution Cu Dp1 in the test material before heat treatment.

[0069] In this embodiment, the value of X is calculated until the correlation coefficient between the amount of solid solution of Cu (Da1 / Dp1) and LMP1 becomes 0.996531, but in reality, a correlation coefficient lower than this value does not pose any particular problem. The value of X can be calculated within a range in which the correlation is considered to be high. Furthermore, in this embodiment, the Larson-Miller parameter is used as a parameter that quantitatively indicates the amount of heat, but the present invention is not limited to this. Any formula can be used as long as it can be organized in terms of time and temperature and has a correlation with the amount of solid solution of an element.

[0070] (Process for calculating the amount of solid solution of the target material) In the target material solid solution amount calculation step, the solid solution amount Da2 of the element in the target material after heat treatment, which is obtained by performing a predetermined heat treatment under predetermined conditions, is calculated from the solid solution amount Dp2 of the element in the target material before heat treatment based on the correlation of the solid solution amount derived in the solid solution amount derivation step. For example, the Larson-Miller parameter LMP2 is calculated by substituting the constant X calculated in the heat amount quantification step and the temperature T2 and time H2 performed on the target material into the following equation (7). Equation (7): LMP2=T2×(X+Log(H2))

[0071] Then, based on the obtained Larson-Miller parameter LMP2, the amount of solid solution of elements Da2 in the post-heat-treatment target material can be calculated from the amount of solid solution of elements Dp2 in the pre-heat-treatment target material. Note that, because the pre-heat-treatment test material is made of the same raw materials and manufactured using the same method as the pre-heat-treatment target material, the amount of solid solution of elements Dp2 in the pre-heat-treatment target material may be considered to be equal to the amount of solid solution of elements Dp1 in the pre-heat-treatment test material. However, it is preferable to also measure the amount of solid solution of elements Dp2 in the pre-heat-treatment target material.

[0072] <Target cavity volume prediction process> The tensile strength Ua1 of the heat-treated test material is also significantly affected by the defect volume expansion coefficient in the heat-treated test material. Therefore, in the target material cavity volume prediction process, a correlation regarding the cavity volume is derived so that a plurality of heat treatment conditions and the cavity volume after the heat treatment have a predetermined relationship, and the cavity volume in the target material after the heat treatment is predicted. The target material cavity volume prediction process preferably includes a cavity volume derivation process and a target material cavity volume calculation process.

[0073] (Nest volume derivation process) In the porosity volume derivation step, the correlation between the porosity volume Vp1 in the pre-heat-treatment test material and the porosity volume Va1 in the post-heat-treatment test material is derived. When deriving the correlation of porosity volumes, it is preferable to use, for example, Weibull analysis. First, in order to understand the extent to which each porosity expanded due to the heat treatment, the porosity volumes in the pre-heat-treatment test material are sorted in descending order. The post-heat-treatment test material is also sorted in descending order of porosity volume, and then the number of porosity detected in the pre-heat-treatment test material is extracted. Then, the porosity volume Vp1 in the pre-heat-treatment test material and the porosity volume Va1 in the post-heat-treatment test material are sorted using Weibull analysis, whereby the correlation between the porosity volume Vp1 and the porosity volume Va1 can be derived.

[0074] FIG. 9 is a graph showing the porosity volumes in the test material before and after heat treatment, with the vertical axis representing cumulative probability (%) and the horizontal axis representing voxels. By performing a Weibull analysis on the test material before heat treatment, it is possible to predict the maximum porosity volume that may occur with a 99.9% cumulative probability. Similarly, it is also possible to predict the maximum porosity volume that may occur with a 99.9% cumulative probability for the test material after heat treatment. By comparing and organizing these results, it is possible to calculate the defect volume expansion rate due to each heat treatment, i.e., the value of (porosity volume Va1 in the test material after heat treatment) / (porosity volume Vp1 in the test material before heat treatment).

[0075] It is also preferable to confirm the tendency of the defect volume expansion coefficient for each heat treatment condition using the defect volume expansion coefficient (Va1 / Vp1) obtained as described above for each heat treatment condition. Specifically, first, based on Table 6 above, the defect volume expansion coefficient (Va1 / Vp1) that changes depending on the heat treatment time and heat treatment temperature is organized as shown in Table 9 below.

[0076] [Table 9]

[0077] In practice, it is preferable to collect all data so that the table is complete, but when organizing based on Table 6, data for (Note 1) to (Note 5) in Table 9 above will be insufficient. Therefore, for the areas where data is insufficient, data will be predicted and added, assuming that there will be similar trends to other temperatures. Note that the more results there are of changing the temperature and time parameters in the experiment, the more the prediction rate can be improved.

[0078] For example, in Table 9, (Note 1) is the value calculated by applying the ratio of the defect volume expansion coefficient after heat treatment at 470°C for 1 minute to the defect volume expansion coefficient after heat treatment at 470°C for 0.6 hours to heat treatments at 450°C for 1 minute and 0.6 hours. (Note 2) is the value calculated by applying the ratio of the defect volume expansion coefficient after heat treatment at 450°C for 1 minute to the defect volume expansion coefficient after heat treatment at 450°C for 5 hours to heat treatments at 430°C for 1 minute and 5 hours. (Note 3) is the value calculated by applying the ratio of the defect volume expansion coefficient after heat treatment at 450°C for 0.6 hours to the defect volume expansion coefficient after heat treatment at 450°C for 5 hours to heat treatments at 430°C for 0.6 hours and 5 hours. (Note 4) is a value calculated by applying the ratio of the defect volume expansion rate after heat treatment at 470°C for 1 minute to the defect volume expansion rate after heat treatment at 470°C for 0.6 hours to the relationship between heat treatment at 500°C for 1 minute and 0.6 hours. (Note 5) is a value calculated by applying the ratio of the defect volume expansion rate after heat treatment at 450°C for 0.6 hours to the relationship between heat treatment at 450°C for 5 hours and 0.6 hours to the relationship between heat treatment at 470°C for 5 hours.

[0079] Next, based on the data obtained in Table 9, the relationship between time and the expansion coefficient at each temperature is plotted in a graph. Figure 10A is a graph showing the relationship between the defect volume expansion coefficient and heat treatment time, with the vertical axis representing the defect volume expansion coefficient and the horizontal axis representing the heat treatment time. As shown in Figure 10A, for example, when the heat treatment time is in the range of 1 hour or longer, the increase rate of the defect volume expansion coefficient is gradual. In Figure 10A, the defect volume expansion coefficient increases sharply between 0 hours and 1 minute. This is thought to be because the expansion had progressed by the time the heat treatment temperature reached 1 minute. As also shown in Table 5 above, even when a short heat treatment at 470°C for 1 minute (heat treatment number N12) was performed, the defect volume expansion coefficient was higher than, for example, a heat treatment at 430°C for 5 hours (heat treatment number N3) or a heat treatment at 450°C for 0.6 hours (heat treatment number N9). This result suggests that the temperature increase during the heat treatment process also affects the expansion of porosity.

[0080] That is, in this embodiment, data is collected using a furnace, but because it takes time to reach the target temperature, expansion may already be progressing when the heat treatment time is measured after the specified temperature is reached. Note that if the correlation is observed for a heat treatment time of 0.6 hours or more, it is not necessary to consider the time during the temperature rise. However, if the time during the temperature rise can be quantitatively added to the graph shown in FIG. 10A using a specified method, it may be added and then the correlation may be confirmed.

[0081] Based on the obtained data shown in Table 9, the relationship between temperature and expansion coefficient at each time is plotted in a graph. FIG. 10B is a graph showing the relationship between the defect volume expansion coefficient and heat treatment temperature, with the vertical axis representing the defect volume expansion coefficient and the horizontal axis representing the heat treatment temperature. As shown in FIG. 10B, for example, the higher the heat treatment temperature, the greater the effect of the heat treatment time on the defect volume expansion coefficient. In this way, by plotting the defect volume expansion coefficient against each heat treatment time or heat treatment temperature, the defect volume expansion coefficient under desired heat treatment conditions can be derived. Note that if an equation can be created that has a high correlation between the heat treatment time or heat treatment temperature and the defect volume expansion coefficient, an appropriate equation may be used for approximation.

[0082] (Target nest volume calculation process) In the target material cavity volume calculation step, the cavity volume Va2 in the target material after heat treatment, which is obtained by carrying out the above-mentioned predetermined heat treatment conditions, is calculated from the cavity volume Vp2 in the target material before heat treatment based on the correlation of the cavity volumes derived in the cavity volume derivation step. Note that the cavity volume Vp2 in the target material before heat treatment can also be considered to be equal to the cavity volume Vp1 in the test material before heat treatment. However, since there is variation in cavity volume in die-cast materials, it is preferable to measure the cavity volume Vp2 of the target material before heat treatment in advance using CT.

[0083] <Tensile strength prediction process> Next, the amount of solid solution of the element in the target material after the heat treatment predicted based on the target material solid solution amount prediction step and the cavity volume in the target material after the heat treatment predicted based on the target material cavity volume prediction step are substituted into the prediction formula derived in the prediction formula derivation step to predict the tensile strength of the target material after the heat treatment. More specifically, the tensile strength Up2 of the target material before the heat treatment, the amount of solid solution of the element Dp2 and the cavity volume Vp2, and the amount of solid solution of the element Da2 and the cavity volume Va2 of the target material after the heat treatment, and the constants A, B, and C derived in the constant calculation step are substituted into the following formula (2) to predict the tensile strength (Ua2 / Up2) of the target material after the heat treatment. Formula (2): (Ua2 / Up2)=A×(Da2 / Dp2)+B×(Va2 / Vp2)+C

[0084] For example, using the above formula (2), the tensile strength of target material I that has been heat treated at a temperature of 430°C for 0.6 hours and the tensile strength of target material II that has been heat treated at a temperature of 480°C for 5 hours are predicted.

[0085] [Table 10]

[0086] As shown in Table 10, first, the Larson-Miller parameter LMP2 is calculated by the above formula (7) using the temperature T2 and time H2 of the heat treatment assumed to be performed on the target material I and the target material II. Note that X uses the value (X = 165) calculated in the above (heat quantity quantification step).

[0087] Next, using the relationship between LMP1 and the solid solution amount Da1 obtained from the graph shown in Figure 8, the Cu solid solution amount Da2 of the heat-treated target material is calculated from the Cu solid solution amount Dp2 of the target material before heat treatment, and the Cu solid solution amount of the heat-treated target material relative to the Cu solid solution amount of the target material before heat treatment (Da2 / Dp2) is obtained. However, since the effect of the Cu solid solution amount on the increase in tensile strength decreases once the Cu solid solution amount exceeds a certain level, for target material II, whose Cu solid solution amount exceeds the upper limit that affects tensile strength, the Cu solid solution amount (Da2 / Dp2) is adjusted to 2.7. The defect volume expansion coefficient (Va2 / Vp2) is also calculated from the relationship between the heat treatment temperature and the defect volume expansion coefficient, and the relationship between the heat treatment time and the defect volume expansion coefficient. Then, by substituting the adjusted Cu solid solution amount (Da2 / Dp2) and the calculated defect volume expansion coefficient (Va2 / Vp2) into the above formula (2), the tensile strength (Ua2 / Up2) value can be predicted. Furthermore, since the tensile strength Up2 value is known, the above method can also be used to predict the tensile strength Ua2 (absolute value) of the target material after heat treatment.

[0088] In this embodiment, the Cu solid solution amount (Da2 / Dp2) was adjusted to 2.7 when the Cu solid solution amount exceeded 2.7, which affects tensile strength, based on the relationship between the Cu solid solution amount and tensile strength shown in Figure 6. However, the present invention is not limited to this value. If another element is selected as an element that affects the tensile strength of the target material after heat treatment, the solid solution amount can be selected based on the relationship between the solid solution amount and tensile strength, as shown in Figure 6, so that the effect on tensile strength is reduced when the solid solution amount of the element exceeds a certain level. Even when Cu is selected, the solid solution amount at which the effect on tensile strength is reduced varies depending on the composition of the aluminum alloy die-cast material, so it is preferable to select it appropriately.

[0089] According to the tensile strength prediction method of this embodiment, it is possible to easily predict the tensile strength (Ua2 / Up2) of a post-heat-treated target material (aluminum alloy die-cast material) after solution treatment (heat treatment) under certain conditions, based on the amount of solid solution Cu in the target material before heat treatment, Dp2, and the porosity volume, Vp2, in the target material before heat treatment.

[0090] In the above embodiment, measurements are performed on a large number of test materials, and the solid solution amount deriving step and the porosity volume deriving step are performed based on these measurements. However, in the present invention, the test material measurement step may be performed first on a small number of test materials. In this case, it is preferable to apply significantly different heat treatment conditions. Then, after determining the trends in the changes in the solid solution amount and the porosity volume, the following adjustment step may be performed.

[0091] <Adjustment process> The adjustment step preferably includes a strength measurement step and a confirmation step. (Strength measurement process) After the tensile strength prediction step, the tensile strength Ua3 of the post-heat treatment target material whose tensile strength has been predicted is actually measured.

[0092] (Confirmation process) The tensile strength (Ua2 / Up2) of the target material after heat treatment predicted in the tensile strength prediction process is compared with the ratio (Ua3 / Up2) of the tensile strength of the target material before heat treatment actually measured in the strength measurement process to check whether an error has occurred.

[0093] (Reforediction process) If an error of a predetermined value or more occurs in the confirmation step, a re-prediction step is carried out. The re-prediction step is a step in which heat treatment is performed on the aluminum alloy die-cast material under a plurality of heat treatment conditions other than the heat treatment conditions used in the test material measurement step, and the test material measurement step, prediction formula derivation step, target material solid solution amount prediction step, target material cavity volume prediction step, and tensile strength prediction step are repeated. This allows for improved prediction accuracy of tensile strength.

[0094] Second Embodiment In the first embodiment, the correlation was derived from the ratios (relative values) of the amount of solid solution of elements that affect strength, tensile strength, and porosity volume between the pre-heat-treatment test material and the post-heat-treatment test material. However, the present invention does not necessarily require the use of ratios (relative values). That is, in the first embodiment, the amount of solid solution of elements (Da1 / Dp1), defect volume expansion coefficient (Va1 / Vp1), and tensile strength (Ua1 / Up1) of the post-heat-treatment test material, and the amount of solid solution of elements (Da2 / Dp2), defect volume expansion coefficient (Va2 / Vp2), and tensile strength (Ua2 / Up2) of the post-heat-treatment target material can all be interpreted as the amount of solid solution of elements (absolute value) Da1, porosity volume (absolute value) Va1, and tensile strength (absolute value) Ua1 of the post-heat-treatment test material, respectively. A tensile strength prediction method for predicting tensile strength using an absolute value will be briefly described below as a second embodiment.

[0095] <Element selection process> The element selection step is the same as in the first embodiment, and therefore a description thereof will be omitted.

[0096] <Test material measurement process> The test material measurement process includes a pre-heat treatment test material measurement process for measuring the tensile strength Up1, the amount of solid solution of elements Dp1, and the porosity volume Vp1 of the pre-heat treatment test material, and a post-heat treatment test material measurement process for measuring the tensile strength Ua1, the amount of solid solution of elements Da1, and the porosity volume Va1 of each post-heat treatment test material that has been heat-treated under multiple heat treatment conditions, at least some of which are different from each other.

[0097] <Prediction formula derivation process> The prediction formula derivation process includes a constant calculation process in which the tensile strength Up1, the amount of solid solution of elements Dp1, and the cavity volume Vp1 of the test material before heat treatment, and the tensile strength Ua1, the amount of solid solution of elements Da1, and the cavity volume Va1 of each test material after heat treatment are substituted into the following formulas (3) and (4) to calculate constants A, B, and C common to formulas (3) and (4).

[0098] Formula (3): Up1=A×Dp1+B×Vp1+C Formula (4): Ua1=A×Da1+B×Va1+C

[0099] <Process for predicting the amount of solid solution in the target material> The target material solid solution amount prediction step includes a solid solution amount derivation step and a target material solid solution amount calculation step.

[0100] (Solid solution amount derivation process) In the solid solution amount deriving step, the correlation between the solid solution amount Dp1 of the element in the test material before the heat treatment and the solid solution amount Da1 of the element in each of the test materials after the heat treatment is derived.

[0101] (Process for calculating the amount of solid solution of the target material) In the target material solid solution amount calculation process, the solid solution amount Da2 of the element in the target material after heat treatment under specified heat treatment conditions is calculated from the solid solution amount Dp2 of the element in the target material before heat treatment based on the correlation of the solid solution amount derived in the above solid solution amount derivation process.

[0102] <Target cavity volume prediction process> The target material cavity volume prediction process includes a cavity volume derivation process and a target material cavity volume calculation process.

[0103] (Nest volume derivation process) In the porosity volume deriving step, the correlation between the porosity volume Vp1 in the test material before the heat treatment and the porosity volume Va1 in the test material after the heat treatment is derived.

[0104] (Target nest volume calculation process) In the target material cavity volume calculation process, the cavity volume Va2 in the target material after heat treatment under specified heat treatment conditions is calculated from the cavity volume Vp2 in the target material before heat treatment based on the correlation of the cavity volumes derived in the above-mentioned cavity volume derivation process.

[0105] <Tensile strength prediction process> In the tensile strength prediction process, the amount of solid solution Da2 of the elements of the target material after heat treatment and the cavity volume Va2, and the constants A, B, and C derived in the constant calculation process are substituted into the following formula (5) to predict the tensile strength Ua2 of the target material after heat treatment. Formula (5): Ua2=A×Da2+B×Va2+C

[0106] The details of each step are the same as those in the first embodiment, and therefore detailed explanations will be omitted.

[0107] In the tensile strength prediction method according to the second embodiment, the tensile strength Ua2 of the target material after heat treatment can also be easily predicted based on the amount of Cu in solid solution Dp2 in the target material before heat treatment and the porosity volume Vp2 in the target material before heat treatment. Note that, in the second embodiment as well, it is preferable to carry out the above-mentioned adjustment step.

[0108] [Manufacturing method for heat-treated die-cast materials] The manufacturing method of the heat-treated die-cast material according to this embodiment includes a process including the above-described method for predicting tensile strength. The manufacturing method of the heat-treated die-cast material according to this embodiment will be described below.

[0109] <Solution treatment process> A pre-heat-treated target material made of an aluminum alloy die-cast material after casting is subjected to a solution treatment (heat treatment). In this solution treatment step, the heat treatment conditions for the solution treatment are selected so that the tensile strength of the post-heat-treated target material predicted by the tensile strength prediction method falls within a target range.

[0110] <Quenching process> Next, the heat-treated target material after the solution treatment step is quenched.

[0111] <Artificial aging hardening treatment process> Thereafter, the quenched target material after the quenching process is subjected to artificial age hardening treatment.

[0112] In the solution treatment process, to ensure that the target material has the desired tensile strength after heat treatment, first, a tentative heat treatment temperature and time are set as heat treatment conditions, and the amount of Cu solid solution Da2 and the defect volume expansion coefficient (Va2 / Vp2) in the target material after heat treatment obtained under these heat treatment conditions are predicted. The amount of Cu solid solution Dp2 in the target material before heat treatment, the predicted amount of Cu solid solution Da2, and the defect volume expansion coefficient (Va2 / Vp2) are then substituted into the above formula (2) to predict the tensile strength (Ua2 / Up2) of the target material after heat treatment. By repeating this process multiple times, heat treatment conditions can be obtained that result in a tensile strength (Ua2 / Up2) in the desired range.

[0113] Fig. 11 is a graph showing the range in which a desired tensile strength is obtained, with the heat treatment temperature on the vertical axis and the heat treatment time on the horizontal axis. As shown by the diagonal lines in Fig. 11, the tensile strength (Ua2 / Up2) may be predicted under various conditions in which the heat treatment temperature and heat treatment time are changed, and a map showing the range in which the desired tensile strength is obtained may be created.

[0114] According to the manufacturing method of the heat-treated die-cast material of the present embodiment, by using the tensile strength prediction method of the present embodiment, it is possible to easily manufacture heat-treated die-cast material having a target tensile strength with high production efficiency. Note that in the manufacturing method of the heat-treated die-cast material of the present embodiment, the amount of solid solution of elements, the cavity volume, and the tensile strength are described as relative values, but they may also be expressed as absolute values, as in the second embodiment.

[0115] Furthermore, the present invention is not limited to the above-described embodiments, and modifications, improvements, etc. are possible as appropriate. In the above-described embodiments, a column housing has been described as an example, but any die-cast product manufactured from ADC12 and subjected to solution treatment may be used. In other words, the tensile strength prediction method and the manufacturing method for heat-treated die-cast materials of the present invention can be applied to other steering products and other products. [Example]

[0116] Using the tensile strength prediction method of the present invention, the predicted tensile strength was compared with the actual measured value. First, according to the above (tensile strength prediction step), the Larson-Miller parameter LMP2 was calculated for Example 1 using equation (7) with the temperature T2 set to 440°C and the time H2 set to 5 hours. The value X (X = 165) calculated in the above (calorie quantification step) was used. Equation (7): LMP2=T2×(X+Log(H2))

[0117] Next, using the relationship between LMP1 and the solid solution amount Da1 obtained from the graph shown in Figure 8, the Cu solid solution amount Da2 of the target material after heat treatment was calculated from the Cu solid solution amount Dp2 of the target material before heat treatment.Furthermore, the Cu solid solution amount of the target material after heat treatment relative to the Cu solid solution amount of the target material before heat treatment (Da2 / Dp2) was calculated.Since the obtained Cu solid solution amount (Da2 / Dp2) was less than 2.7, the Cu solid solution amount after adjustment (Da2 / Dp2) was also set to the calculated value.In addition, the defect volume expansion coefficient (Va2 / Vp2) was also calculated from the cavity volumes of the target material before and after heat treatment calculated by the method described above in the <cavity volume derivation process>. The tensile strength (Ua2 / Up2) was then predicted by substituting the adjusted Cu solid solution amount (Da2 / Dp2) and the calculated defect volume expansion coefficient (Va2 / Vp2) into the above formula (2). The calculated values, predicted values, and measured values ​​of tensile strength are shown in Table 11 below.

[0118] [Table 11]

[0119] As shown in Table 11 above, the tensile strength (predicted value) predicted using the tensile strength prediction method of the present invention was approximately 1.213, and the tensile strength (measured value) measured for the target material actually obtained was 1.20. This shows that the predicted value and the measured value are extremely close, and that accurate prediction is possible. [Explanation of symbols]

[0120] 1. Die-casting materials 2. Nest 3 Blisters 10 Column housing 11a,11b,11c,11d,11e,11f,11g,11h,11i,11j,11k,11m,20 test piece 12 Key lock hole

Claims

1. A tensile strength prediction method for predicting the tensile strength of a post-heat-treated target material made of an aluminum alloy die-cast material, using a pre-heat-treatment test material made of the aluminum alloy die-cast material and a post-heat-treatment test material obtained by subjecting the aluminum alloy die-cast material to heat treatment under a plurality of heat treatment conditions, comprising: an element selection step of selecting elements that affect tensile strength according to the composition of the aluminum alloy die-cast material; a test material measuring step of measuring the amount of solid solution of the element, the volume of porosity and the tensile strength in the test material before the heat treatment, and measuring the amount of solid solution of the element, the volume of porosity and the tensile strength of a plurality of test materials after the heat treatment; a prediction formula deriving step of deriving a prediction formula for tensile strength so that the amount of solid solution of the element, the cavity volume, and the tensile strength have a common correlation in the pre-heat treatment test material and each of the post-heat treatment test materials; a target material solid solution amount prediction step of deriving a correlation regarding the solid solution amount of the element so that the plurality of heat treatment conditions and the solid solution amount of the element in the heat-treated test material have a predetermined relationship, and predicting the solid solution amount of the target material after the heat treatment; A target material cavity volume prediction step of deriving a correlation regarding the cavity volume so that the plurality of heat treatment conditions and the cavity volume of the heat-treated test material have a predetermined relationship, and predicting the cavity volume in the target material after the heat treatment; a tensile strength prediction step of predicting the tensile strength of the heat-treated target material by substituting the amount of solid solution of the element in the heat-treated target material predicted based on the target material solid solution amount prediction step and the cavity volume in the heat-treated target material predicted based on the target material cavity volume prediction step into the prediction formula derived in the prediction formula derivation step; A tensile strength prediction method comprising the steps of:

2. The test material measurement step includes: a pre-heat treatment test material measuring step of measuring a tensile strength Up1, a solid solution amount Dp1 of the element, and a void volume Vp1 of the pre-heat treatment test material; and a post-heat-treated test material measuring step of measuring a tensile strength Ua1, a solid solution amount Da1 of the element, and a porosity volume Va1 for each of the post-heat-treated test materials that have been heat-treated under the plurality of heat treatment conditions, at least some of which are different from each other, The prediction equation deriving step includes: a constant calculation step of calculating constants A, B, and C common to the following formula (1) by substituting the tensile strength Up1, the amount of solid solution of the element Dp1, and the cavity volume Vp1 of the pre-heat-treatment test material, and the tensile strength Ua1, the amount of solid solution of the element Da1, and the cavity volume Va1 of each of the post-heat-treatment test materials into the following formula (1), Formula (1): (Ua1 / Up1)=A×(Da1 / Dp1)+B×(Va1 / Vp1)+C The target material solid solution amount prediction step includes: a solid solution amount deriving step of deriving a correlation between the solid solution amount Dp1 of the element in the pre-heat treatment test material and the solid solution amount Da1 of the element in each of the post-heat treatment test materials; a target material solid solution amount calculation step of calculating a solid solution amount Da2 of the element in the target material after the heat treatment under predetermined heat treatment conditions from the solid solution amount Dp2 of the element in the target material before the heat treatment based on the correlation of the solid solution amount derived in the solid solution amount derivation step, The target cavity volume prediction step includes: A porosity volume derivation step of deriving a correlation between the porosity volume Vp1 in the pre-heat treatment test material and the porosity volume Va1 in the post-heat treatment test material; and a target material cavity volume calculation step of calculating a cavity volume Va2 in the target material after the heat treatment under the predetermined heat treatment conditions from a cavity volume Vp2 in the target material before the heat treatment based on the correlation of the cavity volume derived by the cavity volume derivation step, In the tensile strength prediction step, The tensile strength Up2, the amount of solid solution Dp2 of the element, and the cavity volume Vp2 of the target material before the heat treatment, and the amount of solid solution Da2 of the element and the cavity volume Va2 of the target material after the heat treatment, and the constants A, B, and C derived in the constant calculation step are substituted into the following formula (2), Formula (2): (Ua2 / Up2)=A×(Da2 / Dp2)+B×(Va2 / Vp2)+C The tensile strength prediction method according to claim 1, characterized in that the tensile strength (Ua2 / Up2) of the target material after the heat treatment is predicted.

3. The test material measurement step includes: a pre-heat treatment test material measuring step of measuring a tensile strength Up1, a solid solution amount Dp1 of the element, and a void volume Vp1 of the pre-heat treatment test material; and a post-heat-treated test material measuring step of measuring a tensile strength Ua1, a solid solution amount Da1 of the element, and a porosity volume Va1 for each of the post-heat-treated test materials that have been heat-treated under the plurality of heat treatment conditions, at least some of which are different from each other, The prediction equation deriving step includes: a constant calculation step of substituting the tensile strength Up1, the amount of solid solution of the element Dp1, and the cavity volume Vp1 of the pre-heat-treatment test material, and the tensile strength Ua1, the amount of solid solution of the element Da1, and the cavity volume Va1 of each post-heat-treatment test material into the following formulas (3) and (4), to calculate constants A, B, and C common to the following formulas (3) and (4), Formula (3): Up1=A×Dp1+B×Vp1+C Formula (4): Ua1=A×Da1+B×Va1+C The target material solid solution amount prediction step includes: a solid solution amount deriving step of deriving a correlation between the solid solution amount Dp1 of the element in the pre-heat treatment test material and the solid solution amount Da1 of the element in each of the post-heat treatment test materials; a target material solid solution amount calculation step of calculating a solid solution amount Da2 of the element in the target material after the heat treatment under predetermined heat treatment conditions from the solid solution amount Dp2 of the element in the target material before the heat treatment based on the correlation of the solid solution amount derived in the solid solution amount derivation step, The target cavity volume prediction step includes: A porosity volume derivation step of deriving a correlation between the porosity volume Vp1 in the pre-heat treatment test material and the porosity volume Va1 in the post-heat treatment test material; and a target material cavity volume calculation step of calculating a cavity volume Va2 in the target material after the heat treatment under the predetermined heat treatment conditions from a cavity volume Vp2 in the target material before the heat treatment based on the correlation of the cavity volume derived by the cavity volume derivation step, In the tensile strength prediction step, The amount of solid solution Da2 of the element in the heat-treated target material and the cavity volume Va2, and the constants A, B, and C derived in the constant calculation step are substituted into the following formula (5), Formula (5): Ua2=A×Da2+B×Va2+C The tensile strength prediction method according to claim 1, wherein the tensile strength Ua2 of the target material after the heat treatment is predicted.

4. Further, an adjustment step is performed after the tensile strength prediction step, The adjusting step includes: a strength measurement step of measuring a tensile strength Ua3 of the target material after the heat treatment; a confirmation step of comparing the tensile strength Ua2 of the post-heat-treated target material predicted in the tensile strength prediction step with the tensile strength Ua3 actually measured in the strength actual measurement step to confirm whether an error has occurred; 4. The tensile strength prediction method according to claim 1, further comprising: a re-prediction step in which, if an error equal to or greater than a predetermined value occurs in the confirmation step, heat treatment is performed on the aluminum alloy die-cast material under a plurality of heat treatment conditions other than the heat treatment conditions used in the test material measurement step, and the test material measurement step, the prediction formula deriving step, the target material solid solution amount prediction step, the target material cavity volume prediction step, and the tensile strength prediction step are repeated.

5. 4. The tensile strength prediction method according to claim 1, wherein in the element selection step, the amount of solid solution of a plurality of elements contained in the pre-heat treatment test material and the tensile strength Up1 of the pre-heat treatment test material are compared with the amount of solid solution of the plurality of elements contained in each of the post-heat treatment test materials after heat treatment under the plurality of heat treatment conditions and the tensile strength Ua1 of each of the post-heat treatment test materials, and an element from among the plurality of elements that has a high correlation with the tensile strength Up1 and the tensile strength Ua1 is selected.

6. At least some of the plurality of heat treatment conditions are heat treatment conditions performed at different test temperatures T1 and test times H1, The solid solution amount deriving step includes: A calorific value quantification step is included in which a constant X is calculated so that a Larson-Miller parameter LMP1 calculated by the following formula (6) based on the test temperature T1 and the test time H1 and a solid solution amount Da1 of the element in the post-heat-treatment test material after performing heat treatment under the plurality of heat treatment conditions have a high correlation. Formula (6): LMP1=T1×(X+Log(H1)) In the step of calculating the amount of solid solution of the target material, The constant X calculated in the heat quantity quantification step and the temperature T2 and time H2 of the heat treatment performed on the pre-heat treatment target material are substituted into the following formula (7): Formula (7): LMP2=T2×(X+Log(H2)) 4. The tensile strength prediction method according to claim 2, further comprising: calculating a solid solution amount Da2 of the element in the target material after the heat treatment based on the obtained Larson-Miller parameter LMP2.

7. In the solid solution amount derivation step, when there is a heat treatment condition among the plurality of heat treatment conditions under which the effect of the solid solution amount Da1 of the element in the heat-treated test material on the tensile strength Ua1 of the heat-treated test material is saturated, 4. The tensile strength prediction method according to claim 2, wherein a correlation is derived between the amount of solid solution Dp1 of the element in the test material before heat treatment and the amount of solid solution Da1 of the element in the test material after heat treatment, except for heat treatment conditions under which the tensile strength Ua1 is saturated.

8. The test material measurement step includes: The porosity volume Vp1 in the test material before the heat treatment and the porosity volume Va1 in the test material after the heat treatment were measured by CT, In the cavity volume derivation step, 4. The tensile strength prediction method according to claim 2, wherein the correlation between the porosity volume Vp1 and the porosity volume Va1 in the test material before the heat treatment and the porosity volume Va1 in the test material after the heat treatment is derived by organizing the porosity volume Vp1 and the porosity volume Va1 using Weibull analysis.

9. The aluminum alloy die-cast material is an Al-Si-Cu alloy material represented by alloy symbol ADC12 specified in JIS H 5302:2006, 4. The tensile strength prediction method according to claim 1, wherein the element that affects the tensile strength is Cu.

10. A method for manufacturing a heat-treated die-cast material, comprising a step including the tensile strength prediction method according to any one of claims 1 to 3, a solution treatment step of subjecting the pre-heat treatment target material made of the aluminum alloy die-cast material to solution treatment; a quenching step of rapidly cooling the heat-treated material after the solution treatment step; an artificial age hardening treatment step of performing an artificial age hardening treatment on the quenched target material after the quenching step, a heat treatment condition for the solution treatment is selected in the solution treatment step so that the tensile strength of the target material after the heat treatment predicted by the tensile strength prediction method falls within a target range.

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