Mold seizure prediction method, mold seizure prediction device, and program

Abstract

Accurately predicting mold seizure. [Solution] The mold seizure prediction method according to this disclosure calculates the target energy using the sum of the stored energy accumulated in the mold before the flow of molten aluminum, the heat transfer energy due to heat transfer caused by the flow of molten aluminum, and the collision energy when the molten aluminum collides with the mold. In the temperature plot of one cycle of injection casting of molten aluminum, the area value S of the region where the mold temperature T is above a predetermined temperature T0 is calculated by S = ∫(T-T0)dt. A first region is identified in which the target energy is determined to be greater than the critical value for aluminum adhesion, and a second region is identified in which the area value S is determined to be greater than a predetermined value. The frictional force between the first region and the mold, and between the second region and the mold is calculated, and it is determined that aluminum adheres to the mold when the frictional force is greater than the tensile strength of the product when the product is moved in the direction of removing it from the mold.

Description

[Technical Field]

[0001] This disclosure relates to a mold seizure prediction method, a mold seizure prediction apparatus, and a program. [Background technology]

[0002] Patent Document 1 discloses a method for predicting mold seizure in aluminum casting using molten aluminum. The method described in Patent Document 1 involves selecting a region in the temperature plot of one cycle of injection casting of molten aluminum in which the mold temperature T is equal to or greater than a predetermined temperature T0, and calculating the area value S of the selected region using the formula S = ∫(T-T0)dt, where t is the time in one cycle. This method determines that a violent reaction occurs between the molten aluminum and the mold when the area value S is greater than a predetermined value S0. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2024-068861 [Overview of the project] [Problems that the invention aims to solve]

[0004] During casting, the product shrinks due to the solidification of the molten metal, causing friction between the mold and the product. As a result, surface galling may occur on the product when it is demolded. The method described in Patent Document 1 does not take into account the friction between the mold and the product when predicting mold seizure.

[0005] This disclosure has been made to solve such problems, and its purpose is to provide a mold seizure prediction method, a mold seizure prediction device, and a program that can accurately predict mold seizure. [Means for solving the problem]

[0006] The mold seizure prediction method according to this disclosure is a mold seizure prediction method for predicting seizure of a product cast using molten aluminum to a mold, and includes the steps of: calculating a target energy using the sum of the stored energy stored in the mold before the flow of the molten aluminum, the heat transfer energy which is the energy due to heat transfer caused by the flow of the molten aluminum, and the collision energy when the molten aluminum collides with the mold; calculating the area value S of the region in a temperature plot of one cycle of injection casting of molten aluminum in which the temperature T of the mold is greater than or equal to a predetermined temperature T0 using S = ∫(T-T0)dt (where t is the time in the one cycle); identifying a first region in which the target energy is determined to be greater than the critical value for aluminum adhesion and a second region in which the area value S is determined to be greater than a predetermined value; calculating the frictional force between the first region and the mold, and between the second region and the mold; and determining that aluminum adheres to the mold when the frictional force is greater than the tensile strength of the product when the product is moved in the direction of removing it from the mold.

[0007] In the above prediction method, the step of calculating the friction force is: The steps include: analyzing the solidification state of the molten aluminum in the mold and calculating the compressive stress σ based on the mold constraint due to the solidification shrinkage of the molten aluminum; The friction force F is calculated using the following formula. f The steps to calculate, F f =μ × σ × S (μ represents the coefficient of friction of each part of the product, and S represents the area of ​​each part of the product.) Includes.

[0008] The mold seizure prediction device according to this disclosure is a mold seizure prediction device that predicts seizure of a product cast using molten aluminum onto a mold, comprising: a determination target energy calculation unit that calculates a determination target energy using the sum of the stored energy stored in the mold before the flow of the molten aluminum, the heat transfer energy which is the energy due to heat transfer caused by the flow of the molten aluminum, and the collision energy when the molten aluminum collides with the mold; and an area value S of the region in a temperature plot of one cycle of injection casting of molten aluminum where the temperature T of the mold is ≥ a predetermined temperature T0. The device includes: an area value calculation unit that calculates an area value using the formula =∫(T-T0)dt (where t is the time in the cycle); a identification unit that identifies a first region where the energy to be determined is determined to be greater than the critical value for aluminum adhesion and a second region where the area value S is determined to be greater than a predetermined value; a friction force calculation unit that calculates the friction force between the first region and the mold, and between the second region and the mold; and a determination unit that determines that aluminum adheres to the mold when the friction force is greater than the tensile strength of the product when the product is moved in the direction of removing it from the mold.

[0009] The program relating to this disclosure is a program that causes a computer to perform a process to predict the adhesion of a product cast using molten aluminum to a mold, and includes the steps of: calculating a target energy using the sum of the stored energy stored in the mold before the flow of the molten aluminum, the heat transfer energy which is the energy due to heat transfer caused by the flow of the molten aluminum, and the collision energy when the molten aluminum collides with the mold; calculating the area value S of the region in a temperature plot of one cycle of injection casting of molten aluminum in which the temperature T of the mold is greater than or equal to a predetermined temperature T0, using S = ∫(T-T0)dt (where t is the time in the one cycle); identifying a first region in which the target energy is determined to be greater than the critical value for aluminum adhesion, and a second region in which the area value S is determined to be greater than a predetermined value; calculating the frictional force between the first region and the mold, and between the second region and the mold; and determining that aluminum adheres to the mold when the frictional force is greater than the tensile strength of the product when the product is moved in the direction of removing it from the mold. [Effects of the Invention]

[0010] This disclosure makes it possible to accurately predict mold seizure. [Brief explanation of the drawing]

[0011] [Figure 1] This is a flowchart illustrating an example of a mold seizure prediction method according to an embodiment. [Figure 2] Figure 1 is a conceptual diagram illustrating the mold seizure prediction method. [Figure 3] Figure 1 is a schematic graph showing an example of a temperature plot used to explain the mold seizure prediction method. [Figure 4] This diagram illustrates the seized areas and compressive stresses that occur when aluminum casting is performed by pouring molten aluminum into a mold consisting of a fixed mold and a movable mold. [Figure 5] This diagram shows the frictional force at the baked-on portion of the product when the mold is opened. [Figure 6] It is a block diagram showing a configuration example of a mold seizure prediction device according to an embodiment.

Mode for Carrying Out the Invention

[0012] Hereinafter, the present invention will be described through embodiments of the invention, but the invention according to the claims is not limited to the following embodiments. Also, not all of the configurations described in the embodiments are essential as means for solving the problems.

[0013] (Embodiment) An example of a mold seizure prediction method according to the present embodiment will be described while referring to the drawings. FIG. 1 is a flowchart for explaining an example of the mold seizure prediction method according to the embodiment. FIG. 2 is a conceptual diagram for explaining the mold seizure prediction method of FIG. 1. FIG. 3 is a schematic graph showing an example of a temperature plot for explaining the mold seizure prediction method of FIG. 1.

[0014] The mold seizure prediction method according to the embodiment is a method for predicting the seizure of a mold in aluminum casting using molten aluminum. The mold seizure prediction method according to the present embodiment includes steps S1 to S5 described later. In step S1, a casting analysis is performed. The casting analysis includes a first region identification step (steps S10, S11) and a second region identification step (steps S20, S21) for respectively identifying a first region and a second region where seizure is predicted to occur, and a product stress calculation step (S30).

[0015] (1) First Region Identification Step Focusing on the fact that mold seizure (aluminum adhesion to the mold) is likely to occur where the mold temperature before aluminum filling is high, the flow velocity during aluminum flow is large, and the aluminum collides with the mold during aluminum flow, the first region is identified by determining whether mold seizure occurs from an energy perspective.

[0016] The first region identification step includes a determination target energy calculation step (S10) and a first determination step (S11). Specifically, the method disclosed in Japanese Patent Application Publication No. 2024-68860 is applied to the identification of the first region. The determination energy is calculated by analyzing the flow of molten aluminum within the mold and performing the calculation for each part of the mold corresponding to each mesh (cell) of the three-dimensional data (three-dimensional mesh model) of the designed mold.

[0017] This method is explained by assuming a simplified model as shown in Figure 2. For convenience, molten aluminum is shown as aluminum 21 in Figure 2. In Figure 2, the velocity and temperature of aluminum 21 before filling (before reaching the mold 20) are represented as Vi and Ti, respectively, and the velocity and temperature of aluminum 21 after filling (at the point of impact with the mold 20) are represented as V and T, respectively.

[0018] In the determination target energy calculation step (S10), the stored energy E1 accumulated in the mold 20 before the flow of molten aluminum is considered. Therefore, the determination target energy calculation step calculates the stored energy E1 by utilizing the fact that the stored energy E1 is proportional to the temperature Ti in the mold 20 before aluminum filling, that is, the relationship E1 = α·Ti (where α is the proportionality constant (coefficient)). The specific method for calculating the stored energy E1 can be any method that utilizes the relationship E1 = α·Ti. If the stored energy E1 has different temperature distributions depending on the part of the mold, for example, it can be calculated using that temperature distribution.

[0019] Furthermore, the step for calculating the energy to be determined takes into account the heat transfer energy E2, which is the energy generated by heat transfer due to the flow of molten aluminum (aluminum 21). Therefore, the step for calculating the energy to be determined utilizes the fact that the heat transfer energy E2 is proportional to the temperature change value (T-Ti) from the temperature Ti of the mold 20 before the flow of molten aluminum (i.e., before filling) to the temperature T of the mold 20 after the flow (i.e., after filling). The proportionality constant in this case can also be α. Thus, the heat transfer energy E2 can be expressed using (T-Ti), and in particular, it can be expressed as α·(T-Ti). However, the proportionality constant used in the calculation of heat transfer energy E2 may be a different value from the proportionality constant used in the calculation of heat storage energy E1.

[0020] Furthermore, the step for calculating the energy to be determined takes into account the collision energy E3 of the molten aluminum (aluminum 21) colliding with the mold 20. Therefore, the step for calculating the energy to be determined calculates the collision energy E3. Specifically, the collision energy E3 is proportional to the square of the normal velocity V near the surface of the mold 20, that is, E3 = β·V 2 The collision energy E3 is calculated by utilizing the relationship between the two. Here, β is the proportionality constant (coefficient). Of course, other parameters can also be taken into consideration when calculating the collision energy E3. In this way, the collision energy E3 of aluminum 21 colliding with mold 20 is calculated as a value weighted by the velocity V in the direction of the normal vector of the mold surface.

[0021] The specific method for calculating the collision energy E3 is E3 = β·V 2 Any method that utilizes this relationship is acceptable. In particular, the collision energy E3 can be calculated by determining the sum of the squares of the normal velocity V while the molten aluminum is in contact with the mold 20, and taking the value proportional to that sum. That is, the collision energy E3 can be calculated by the following formula. E3 = β·∫(V 2 )dt

[0022] The energy to be determined, E, is calculated using the sum of the stored energy E1, the heat transfer energy E2, and the collision energy E3. For example, the energy to be determined, E, can be E1 + E2 + E3.

[0023] In the first determination step (S11), it is determined whether the target energy E is greater than the critical value El for aluminum adhesion. In step S11, the region in which the target energy E is greater than the critical value El for aluminum adhesion is identified as the first region in which aluminum adhesion occurs due to overheating of the flow rate. The critical value for aluminum adhesion may be a value set based on the results of experiments conducted to see whether aluminum actually adheres to the mold by changing the flow rate of molten aluminum.

[0024] (2) Second domain identification step Rather than simply identifying areas where the reaction layer frequently occurs at high mold temperatures, the second region is identified by focusing on areas where the mold temperature exceeds a certain level and where the mold temperature receives significant energy from the aluminum, and where particularly intense reaction layers are more likely to occur.

[0025] The second region identification step includes a mold temperature calculation step (S20) and a second determination step (S21). Specifically, the method disclosed in Japanese Patent Application Publication No. 2024-068861 is applied to the identification of the second region. The mold temperature calculation is performed for each part of the mold corresponding to each mesh (cell) of the three-dimensional data (three-dimensional mesh model) of the designed mold by analyzing the flow of molten aluminum within the mold.

[0026] In the mold temperature calculation step (S20), a region is selected from the temperature plot of one cycle in which molten aluminum is injected and cast, in which the mold temperature T is equal to or greater than a predetermined temperature T0. This temperature plot is shown, for example, in Figure 3. The region selected here is the combined region shown by the upward-sloping diagonal line and the downward-sloping diagonal line in Figure 3.

[0027] In the mold temperature calculation step, the area value S of the selected region in the temperature plot for one cycle of injection casting of molten aluminum is calculated by the following formula. In the following formula, t is the time during one cycle. S = ∫(T-T0)dt

[0028] In the second determination step (S21), it is determined whether the area value S is greater than a predetermined value S0. If the area value S is greater than the predetermined value S0 (S > S0), it is identified as a second region where a violent reaction occurs between the molten aluminum and the mold, i.e., a violent reaction layer is formed. The area where a violent reaction layer occurs can refer to the region where the mold vigorously melts with the molten aluminum. The degree of melting required to be determined as a violent reaction layer can be determined by the predetermined value S0.

[0029] The identified first and second regions are mapped as areas where mold seizure is likely to occur (referred to as seizure areas). Figure 4 illustrates the seizure areas and compressive stress when aluminum casting is performed by injecting molten aluminum (indicated as Al in Figure 4) into a mold consisting of a fixed mold and a movable mold. As shown in the upper part of Figure 4, the seizure areas are mapped onto the three-dimensional data of the mold. The coefficient of friction between the mold and the product in the seizure areas is denoted as μ.

[0030] (3) Product stress calculation step The product stress calculation step (S30) is a step in which the solidification state of the molten aluminum in the mold is analyzed and the compressive stress σ based on the mold constraint due to the solidification shrinkage of the molten aluminum is calculated. The compressive stress σ can be calculated using, for example, CAE (Computer Aided Engineering). A wide variety of numerical analysis methods can be used for the calculation method. For example, various methods such as the finite volume method, finite difference method, finite element method, and particle method can be used. Multiple types of numerical analysis methods may be used in combination as needed. As shown in the lower part of Figure 4, it can be seen that a compressive stress σ acts on the mold in the direction constrained by the product.

[0031] After the casting analysis (step S1), the frictional force of the fused area (at least one of the two areas, the first region and the mold, and the second region and the mold) is calculated when the product is moved in the direction of removal from the mold (step S2). Frictional force F f It is calculated using the compressive stress σ by the following formula. F f =μ × σ × S Here, μ represents the coefficient of friction of each part of the product, and S represents the area of ​​each part of the product.

[0032] Figure 5 shows the frictional force at the baked-on portion of the product when the mold is opened. In Figure 5, the frictional force is indicated by arrows on the 3D data (3D mesh model) of the product surface.

[0033] Subsequently, it is determined whether the calculated frictional force is greater than or equal to the tensile strength of the product (step S3). The tensile strength of a product is known to be temperature-dependent, decreasing as the product temperature increases. The tensile strength compared with the calculated frictional force may be determined by considering the temperature of the product when it is removed from the mold.

[0034] If the calculated frictional force is greater than the tensile strength of the product (Step S3, YES), it is predicted that when the cast product is removed from the mold, instead of the interface between the mold and the product separating, the material constituting the product will fracture and aluminum will adhere to the mold. In this case, it is determined that galling will occur on the surface of the product (Step S4).

[0035] On the other hand, if the calculated frictional force is less than or equal to the tensile strength of the product (step S3, NO), it is predicted that when the cast product is removed from the mold, the interface between the mold and the product will separate without aluminum adhering to the mold. In this case, it is determined that no galling will occur on the surface of the product (step S5). The determination results in step S4 and step S5 can be output by a display device or an audio output device (step S6).

[0036] Thus, in this embodiment, a first region is identified in which aluminum adhesion is predicted considering flow rate overheating, and a second region is identified in which aluminum adhesion is predicted considering the region of the product of mold temperature and contact time of aluminum with the mold. Furthermore, in this embodiment, a determination is added that takes into account the temperature-dependent strength of the product for these first and second regions. This makes it possible to more accurately determine aluminum adhesion due to mold seizure. In addition, according to this embodiment, it is possible to predict the risk of galling occurring as well.

[0037] If seizing or galling is detected, the design can be reviewed, and the same process can be repeated to determine if seizing occurs. This review and evaluation process can be repeated until a mold is produced that does not seize.

[0038] Figure 6 is a block diagram showing an example configuration of a mold seizure prediction device according to an embodiment. As shown in Figure 6, the mold seizure prediction device 10 includes a determination target energy calculation unit 11, an area value calculation unit 12, a specification unit 13, a friction force calculation unit 14, and a determination unit 15.

[0039] The determination target energy calculation unit 11 calculates the determination target energy by using the sum of the stored energy accumulated in the mold before the flow of molten aluminum, the heat transfer energy which is the energy generated by heat transfer due to the flow of molten aluminum, and the collision energy when the molten aluminum collides with the mold.

[0040] As described above, the stored energy E1 accumulated in the mold before the molten aluminum flows is calculated by utilizing the fact that the stored energy E1 is proportional to the temperature of the mold, i.e., E1 = α·Ti. The heat transfer energy E2 generated by the flow of the molten aluminum is calculated by utilizing the fact that the heat transfer energy E2 is proportional to the change in temperature from the mold temperature before flow to the mold temperature after flow. The collision energy E3 when the molten aluminum collides with the mold is calculated by utilizing the fact that the collision energy E3 is proportional to the square of the normal velocity V near the surface of the mold, i.e., E3 = β·V 2 It is calculated by utilizing the relationship between these two factors.

[0041] During one cycle of temperature plotting for injecting and casting molten aluminum, the area value calculation unit 12 calculates the area value S of the region where the temperature T of the mold is equal to or higher than a predetermined temperature T0 by S = ∫(T - T0)dt (t is the time during the one cycle). Specifically, the area value calculation unit 12 selects the region where the temperature T of the mold is equal to or higher than the predetermined temperature T0 during one cycle of temperature plotting for injecting and casting molten aluminum. Then, the area value calculation unit 12 can calculate the area value S of the region selected in step S1 in the temperature plot by the above formula.

[0042] The specific part 13 identifies a first region where the determination target energy is determined to be greater than the aluminum adhesion generation critical value, and a second region where the area value S is determined to be greater than a predetermined value. The first region is a region where aluminum adhesion due to flow velocity overheating is predicted to occur. The second region is a region where a violent reaction between the molten aluminum and the mold is predicted to occur.

[0043] The frictional force calculation unit 14 calculates the frictional force between at least one of the first region and the mold and the second region and the mold. For example, the frictional force calculation unit 14 analyzes the solidification state of the molten aluminum in the mold and calculates the compressive stress σ based on the mold restraint due to the solidification shrinkage of the molten aluminum. Then, using the formula F f = μ×σ×S (μ is the friction coefficient of each part of the product, S is the area of each part of the product), the frictional force of the seizure part when the product is moved in the direction of removing it from the mold is calculated. The determination unit 15 determines that aluminum adheres to the mold when the frictional force is greater than the tensile strength of the product when the product is moved in the direction of removing it from the mold.

[0044] The mold seizure prediction device 10 can be equipped with each of the parts 11 to 15 as a control unit. This control unit can be implemented, for example, by an integrated circuit, and can be implemented by a processor such as an MPU (Micro Processor Unit) or CPU (Central Processing Unit), working memory, and a non-volatile storage device. A control program executed by the processor is stored in this storage device, and the processor reads the program into the working memory and executes it, thereby enabling each of the parts 11 to 15 to perform its function.

[0045] The mold seizure prediction device 10 can be configured with a computer, and as is clear from the example of the control unit described above, it can also be configured to include a computer. Therefore, the above program can be said to be a program that causes the computer to execute the processing shown in the mold seizure prediction method described above. In addition, the mold seizure prediction device 10 can also be configured by distributing its functions among multiple devices.

[0046] Thus, by considering the relationship between tensile strength and frictional force at the product temperature during demolding, it becomes possible to more accurately predict the occurrence of aluminum adhesion and surface galling of the product when predicting mold seizure.

[0047] Although the shape of the mold was not specifically described in the above embodiment, it can be applied to molds of any shape. Furthermore, in the above embodiment, mold seizure can also be determined by using various other parameters, such as parameters related to the composition of the molten aluminum and the material of the mold.

[0048] The program described above, when loaded into a computer, includes a set of instructions (or software code) for causing the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include electrical, optical, acoustic or other forms of propagating signals.

[0049] It should be noted that the present invention is not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of the invention. [Explanation of symbols]

[0050] 10. Mold seizure prediction device 11. Energy calculation unit for determination 12 Area Value Calculation Unit 13 Specific section 14 Friction force calculation section 15 Judgment section

Claims

1. A mold seizure prediction method for predicting the seizure of a product cast using molten aluminum onto a mold, A step of calculating the target energy using the sum of the stored energy accumulated in the mold before the flow of the molten aluminum, the heat transfer energy which is the energy generated by heat transfer due to the flow of the molten aluminum, and the collision energy when the molten aluminum collides with the mold, In a temperature plot of one cycle of injection casting of molten aluminum, the area value S of the region where the temperature T of the mold is above a predetermined temperature T0 is calculated by S = ∫(T - T0) dt (where t is the time in the one cycle), The steps include identifying a first region in which the target energy for determination is determined to be greater than the critical value for aluminum deposition, and a second region in which the area value S is determined to be greater than a predetermined value, A step of calculating the frictional force between the first region and the mold, and between the second region and the mold, The step of determining that aluminum adheres to the mold when the product is moved in the direction of removal from the mold and the frictional force is greater than the tensile strength of the product, including, A method for predicting mold seizure.

2. The step of calculating the frictional force is: The steps include: analyzing the solidification state of the molten aluminum in the mold and calculating the compressive stress σ based on the mold constraint due to the solidification shrinkage of the molten aluminum; The friction force F is calculated using the following formula. ｆ The steps to calculate, F ｆ =μ×σ×S (μ represents the coefficient of friction of each part of the product, and S represents the area of ​​each part of the product.) including, The mold seizure prediction method according to claim 1.

3. A mold seizure prediction device that predicts the seizure of a product cast using molten aluminum onto a mold, A determination target energy calculation unit calculates the determination target energy by using the sum of the stored energy accumulated in the mold before the flow of the molten aluminum, the heat transfer energy which is the energy generated by heat transfer due to the flow of the molten aluminum, and the collision energy when the molten aluminum collides with the mold. An area value calculation unit calculates the area value S of the region where the temperature T of the mold is above a predetermined temperature T0 in a temperature plot of one cycle of injection casting of molten aluminum, using the formula S = ∫(T - T0) dt (where t is the time in the one cycle), A identifying unit that identifies a first region in which the target energy for determination is determined to be greater than the critical value for aluminum deposition, and a second region in which the area value S is determined to be greater than a predetermined value, A friction force calculation unit that calculates the friction force between the first region and the mold, and between the second region and the mold, A determination unit that determines that aluminum adheres to the mold when the frictional force is greater than the tensile strength of the product when the product is moved in the direction of removal from the mold, including, Mold seizure prediction device.

4. A program that causes a computer to perform a process to predict whether a product cast using molten aluminum will stick to the mold, A step of calculating the target energy using the sum of the stored energy accumulated in the mold before the flow of the molten aluminum, the heat transfer energy which is the energy generated by heat transfer due to the flow of the molten aluminum, and the collision energy when the molten aluminum collides with the mold, In a temperature plot of one cycle of injection casting of molten aluminum, the area value S of the region where the temperature T of the mold is above a predetermined temperature T0 is calculated by S = ∫(T - T0) dt (where t is the time in the one cycle), The steps include identifying a first region in which the target energy for determination is determined to be greater than the critical value for aluminum deposition, and a second region in which the area value S is determined to be greater than a predetermined value, A step of calculating the frictional force between the first region and the mold, and between the second region and the mold, The step of determining that aluminum adheres to the mold when the product is moved in the direction of removal from the mold and the frictional force is greater than the tensile strength of the product, including, program.

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