Analysis apparatus, analysis method, and computer program

Abstract

To reduce the number of machining operations of a real mold.SOLUTION: An analysis apparatus extracts difference vectors between respective points of first analysis result data, which is three-dimensional point cloud data generated by simulation and indicative of a predicted shape of a first press-formed article obtained using a first mold, and respective points of second analysis result data, which is three-dimensional point cloud data generated by simulation and indicative of a predicted shape of a second press-formed article obtained using a second mold, and generates, on the basis of the difference vectors and three-dimensional measurement data, virtual formed article data as three-dimensional point cloud data representing a corrected predicted shape of the second press-formed article obtained using the second mold.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to an analysis device. [Background technology]

[0002] When press-forming metal sheets, the press-formed product, once released from the die load after forming, experiences springback, which is a reaction force that causes the press-formed product to return to its original shape. This springback is one of the causes of deviations between the press-formed product and the target shape. To improve the precision of press-formed products, it is necessary to create dies that take springback into consideration.

[0003] A known technique for improving the accuracy of press-formed products is an analysis method using CAE (Computer Aided Engineering). CAE is a tool that performs simulations on a computer and can verify the accuracy of press-formed products. For example, Patent Document 1 discloses a technique for identifying a portion of a press-formed product that causes a discrepancy between the springback amount of an actual panel press-formed product and the springback amount analyzed by CAE. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2020-179409 Summary of the Invention [Problem to be solved by the invention]

[0005] In the prior art disclosed in Patent Document 1, in order to improve the accuracy of a press-formed product, it is necessary to repeat a cycle of checking the deviation of the press-formed product from a target shape, modifying the die according to the deviation, performing press-forming again using the modified die, and then checking again the deviation of the obtained press-formed product from the target shape. Therefore, in order to improve the accuracy of the press-formed product, it is necessary to repeatedly re-machine the actual die.

[0006] One aspect of the present disclosure is to reduce the number of times that the actual mold is machined. [Means for solving the problem]

[0007] One aspect of the present disclosure is an analysis device including a first analysis result acquisition unit, a second analysis result acquisition unit, a three-dimensional measurement data acquisition unit, a difference extraction unit, and a generation unit. The first analysis result acquisition unit is configured to acquire first analysis result data, which is three-dimensional point cloud data generated by performing a simulation related to press forming, including springback analysis, using first mold surface data representing the three-dimensional shape of the first mold, and which is three-dimensional point cloud data representing the expected shape of the first press-formed product obtained by press forming using the first mold.

[0008] The second analysis result acquisition unit is configured to acquire second analysis result data, which is three-dimensional point cloud data generated by performing a simulation using second mold surface data representing the three-dimensional shape of the second mold, and which is three-dimensional point cloud data representing the expected shape of a second press-molded product obtained by press molding using the second mold.

[0009] The three-dimensional measurement data acquisition unit is configured to acquire three-dimensional measurement data generated by measuring the shape of the first press-formed product, which is three-dimensional point cloud data representing the shape of the first press-formed product.

[0010] The difference extracting unit is configured to extract a difference vector representing the difference between each point of the first analysis result data and each point of the second analysis result data. The generation unit is configured to generate virtual molded product data as three-dimensional point cloud data representing a corrected expected shape of a second press-molded product obtained by press molding using the second mold based on the difference vector and the three-dimensional measurement data.

[0011] According to this configuration, it is possible to obtain virtual press-formed product data for the second press-formed product, which has a higher accuracy of the expected shape than the second analysis result data based on the simulation. The virtual press-formed product data is generated without processing the actual second mold. This reduces the number of times the actual mold is processed.

[0012] In one embodiment of the present disclosure, the second mold surface data may be data obtained by correcting the first mold surface data based on the three-dimensional measurement data. One aspect of the present disclosure may further include a corrected mold surface data acquisition unit.

[0013] The corrected mold surface data acquisition unit is configured to acquire corrected mold surface data obtained by correcting the second mold surface data when the virtual molded product data does not satisfy a predetermined standard. The second analysis result acquisition unit may be configured to further acquire, as the modified analysis result data, three-dimensional point cloud data generated by a simulation using the modified die surface data.

[0014] The difference extracting unit may be configured to further extract a corrected difference vector representing the difference between each point of the first analysis result data and each point of the corrected analysis result data. The generating unit may be configured to further generate corrected virtual molded article data as data obtained by correcting the virtual molded article data, based on the corrected difference vector and the three-dimensional measurement data.

[0015] As described above, the virtual product data represents a highly accurate expected shape of the second press-formed product, taking into account the three-dimensional measurement data, as the expected shape of the second press-formed product based on the second mold. Similarly, the corrected virtual product data based on the corrected mold surface data represents a highly accurate expected shape of the second press-formed product based on the corrected second mold. The corrected virtual product data can be obtained without actually modifying the actual second mold.

[0016] Therefore, with the above-described analysis device, it is possible to modify the die surface data without modifying the actual die, thereby making the second press-formed product closer to the target shape, thereby reducing the number of times the actual die is processed.

[0017] One aspect of the present disclosure is an analysis method including: acquiring first analysis result data, which is three-dimensional point cloud data generated by performing a simulation related to press forming, including a springback analysis, using first die surface data representing the three-dimensional shape of a first die, and which represents an expected shape of a first press-formed product obtained by press forming using the first die; acquiring second analysis result data, which is three-dimensional point cloud data generated by performing the simulation using second die surface data representing the three-dimensional shape of a second die, and which represents an expected shape of a second press-formed product obtained by press forming using the second die; acquiring three-dimensional measurement data, which is three-dimensional measurement data generated by measuring the shape of the first press-formed product, and which is the three-dimensional point cloud data representing the shape of the first press-formed product; extracting difference vectors representing the differences between each point of the first analysis result data and each point of the second analysis result data; and generating virtual press-formed product data as three-dimensional point cloud data representing a corrected expected shape of the second press-formed product based on the difference vectors and the three-dimensional measurement data.

[0018] According to this method, as with the above-mentioned analysis device, highly accurate virtual product data can be obtained regarding the expected shape of the press-formed product, thereby reducing the number of times that the actual mold is processed.

[0019] One aspect of the present disclosure is a computer program that causes a computer to execute the following steps: acquire first analysis result data, which is three-dimensional point cloud data generated by performing a simulation related to press forming, including a springback analysis, using first die surface data representing the three-dimensional shape of a first die, and which represents an expected shape of a first press-formed product obtained by press forming using the first die; acquire second analysis result data, which is three-dimensional point cloud data generated by performing the simulation using second die surface data representing the three-dimensional shape of a second die, and which represents an expected shape of a second press-formed product obtained by press forming using the second die; acquire three-dimensional measurement data, which is three-dimensional measurement data generated by measuring the shape of the first press-formed product, and which is the three-dimensional point cloud data representing the shape of the first press-formed product; extract difference vectors representing the differences between each point of the first analysis result data and each point of the second analysis result data; and generate virtual press-formed product data as three-dimensional point cloud data representing a corrected expected shape of the second press-formed product based on the difference vectors and the three-dimensional measurement data.

[0020] According to this configuration, the computer program can obtain highly accurate virtual product data regarding the expected shape of the press-molded product, similar to the above-mentioned analysis device, thereby providing a computer program that can reduce the number of times the actual mold is machined. [Brief explanation of the drawings]

[0021] [Figure 1] FIG. 2 is a block diagram of an analysis device. [Figure 2] 10 is a flowchart of an analysis process executed by the analysis device. [Figure 3] FIG. 2 is a diagram illustrating the relationship between various data in the analysis process. [Figure 4] 1 is an exemplary flowchart of a multi-step press forming process. DETAILED DESCRIPTION OF THE INVENTION

[0022] Hereinafter, exemplary embodiments of the present disclosure will be described with reference to the drawings. [1. First embodiment] [1-1.Configuration] The analysis device 1 shown in Fig. 1 is a device for reducing deviations from a target shape of a press-formed product based on the results of press forming using a die and CAE analysis of die surface data representing the three-dimensional shape of the die (hereinafter referred to as CAE analysis). The CAE analysis includes execution of simulations related to press forming. The simulations include springback analysis.

[0023] The analysis device 1 includes a processor 11 , a memory 12 , a storage 13 , a user interface 14 , and a communication interface 15 . The processor 11 is configured to execute processing in accordance with a computer program recorded in the storage 13 .

[0024] The memory 12 is used as a work area when the processor 11 executes processing. An example of the memory 12 is a RAM. The storage 13 stores various data as well as computer programs executed by the processor 11. Examples of the storage 13 include a hard disk drive (HDD) and a solid state drive (SSD).

[0025] The user interface 14 is an interface configured to receive input from a user and to output to a user. Examples of the user interface 14 include a mouse, a keyboard, a touch panel, a display, and the like.

[0026] The communication interface 15 is an interface configured to enable communication with an external device of the analysis device 1. 1, in the analysis device 1, the processor 11 executes a computer program to function as a first analysis result acquisition unit 111, a second analysis result acquisition unit 112, a three-dimensional measurement data acquisition unit 113, a determination unit 114, a corrected mold surface data acquisition unit 115, a difference extraction unit 116, and a generation unit 117. That is, the analysis device 1 includes the first analysis result acquisition unit 111, the second analysis result acquisition unit 112, the three-dimensional measurement data acquisition unit 113, the determination unit 114, the corrected mold surface data acquisition unit 115, the difference extraction unit 116, and the generation unit 117 as virtual components realized by software.

[0027] The first analysis result acquisition unit 111 and the second analysis result acquisition unit 112 are configured to perform CAE analysis on the input mold surface data. The mold surface data is, for example, data in IGES format. IGES is known as a file format for computer-aided design (CAD). The first analysis result acquisition unit 111 and the second analysis result acquisition unit 112 acquire analysis result data, which is three-dimensional point cloud data representing the expected shape of a press-molded product obtained by press molding using a mold. The analysis result data is, for example, data in STL format. STL is a well-known file format for storing data representing three-dimensional shapes and is widely used as a triangular mesh solid representation file format. The three-dimensional point cloud data includes at least the three-dimensional position coordinates of each point in the three-dimensional point cloud and may further include surface information including mesh normal vectors. The three-dimensional position coordinates are, for example, three-dimensional coordinate values of length, width, and height.

[0028] The three-dimensional measurement data acquisition unit 113 is configured to acquire three-dimensional measurement data, which is three-dimensional point cloud data representing the shape of the press-formed product. The three-dimensional measurement data is generated, for example, by measuring the three-dimensional position coordinates of the press-formed product using a three-dimensional measuring machine. The three-dimensional measurement data acquisition unit 113 outputs the three-dimensional measurement data, which is point cloud data of three-dimensional coordinates, as the measurement result. The three-dimensional measurement data is, for example, data in STL format.

[0029] The determination unit 114 is configured to acquire the result of a user's determination as to whether or not the virtual product data, which is three-dimensional point cloud data obtained by correcting the expected shape of the press-molded product, satisfies a predetermined standard.

[0030] An example of the predetermined criterion is the deviation rate between the virtual product data and the target shape of the press-formed product. The deviation rate is the percentage of points in the point cloud of the virtual product data whose distance from each point of the target shape of the press-formed product exceeds a predetermined threshold.

[0031] As another example, the points of agreement between the virtual molded product data and the target shape may be plotted on the virtual molded product data, and the user may visually check the degree of agreement plotted on the virtual molded product data to determine whether the criteria expected by the user are met.

[0032] In this embodiment, whether or not the virtual article data satisfies the predetermined criteria is determined by the user using a comparison tool or the like provided outside the analysis device 1. However, whether or not the virtual article data satisfies the predetermined criteria may be determined by the determination unit 114 instead of the user.

[0033] The corrected die surface data acquisition unit 115 is configured to acquire corrected die surface data obtained by correcting die surface data. The corrected die surface data may be die surface data corrected by a user or may be die surface data corrected by a computer. The user may generate corrected die surface data by correcting the die surface data held by the analysis device 1 via the user interface 14. The correction of the die surface data is performed for the purpose of reducing deviation from the target shape of the press-molded product.

[0034] The difference extraction unit 116 is configured to extract difference vectors that represent the differences between each point of the first analysis result data and each point of the second analysis result data, which are two pieces of analysis result data. Specifically, the difference extraction unit 116 converts the input first analysis result data and second analysis result data into polygons, and extracts, as differences, portions that do not match when the first analysis result data and the second analysis result data are superimposed. The difference vectors are a collection of vectors that represent the direction and amount of movement of each point of the second analysis result data relative to each point of the first analysis result data.

[0035] According to one example, the difference vector is a set of vectors for each mesh. That is, the difference vector can be a set of vectors connecting the center of gravity of each mesh in the three-dimensional point cloud identified from the first analysis result data with the center of gravity of the corresponding mesh in the three-dimensional point cloud identified from the second analysis result data. For example, the center of gravity of the mesh corresponding to the center of gravity of each mesh in the three-dimensional point cloud identified from the first analysis result data is the center of gravity of the closest mesh among the meshes in the three-dimensional point cloud identified from the second analysis result data.

[0036] According to one example, the difference vector may be a set of vectors for each point of all or part of the three-dimensional point cloud. That is, the difference vector may be a set of vectors connecting each point of the three-dimensional point cloud identified from the first analysis result data with a corresponding point of the three-dimensional point cloud identified from the second analysis result data. For example, the point corresponding to each point of the three-dimensional point cloud identified from the first analysis result data is the closest point in the three-dimensional point cloud identified from the second analysis result data.

[0037] The generation unit 117 is configured to generate the aforementioned virtual molded article data based on the difference vector and the three-dimensional measurement data. Specifically, the generation unit 117 generates virtual molded article data by correcting the three-dimensional measurement data by adding the difference vector to the three-dimensional measurement data. The virtual molded article data is, for example, data in STL format. There are various methods for adding the difference vector to the three-dimensional measurement data. In a simple example, adding the difference vector to the three-dimensional measurement data includes adding the difference vector of a corresponding point to the coordinates of each point in the three-dimensional measurement data to calculate the corrected coordinates of the corresponding point. The virtual molded article data can be generated by calculating the corrected coordinates of each point.

[0038] [1-2. Processing] The analysis process executed by the processor 11 of the analysis device 1 will be described using the flowchart in Fig. 2. The relationships between various pieces of data in the analysis process are shown in Fig. 3. The step numbers in Fig. 3 indicate the relationships corresponding to the step numbers in Fig. 2.

[0039] First, in S100, the processor 11 acquires first mold surface data 22 as mold surface data representing the three-dimensional shape of the first mold 21. The processor 11 may acquire the first mold surface data 22 that has been stored in the storage 13 in advance, or may acquire the first mold surface data 22 from outside the analysis device 1 via the communication interface 15.

[0040] Next, in S102, the processor 11 performs CAE analysis using the first die surface data 22 to acquire first analysis result data 23. The first analysis result data 23 is analysis result data that is three-dimensional point cloud data that represents the expected shape of a first press-molded product 24 obtained by press molding using the first die 21. The CAE analysis may be performed inside the analysis device 1 or outside the analysis device 1. The processing of S102 corresponds to processing as a first analysis result acquisition unit 111.

[0041] Next, in S104, the processor 11 acquires three-dimensional measurement data 25, which is three-dimensional point cloud data representing the shape of the first press-formed product 24. The first press-formed product 24 is an actual molded product, and is obtained by press molding using the first mold 21. The three-dimensional measurement data 25 is generated by measuring the shape of the first press-formed product 24. For example, the three-dimensional measurement data 25 can be acquired by applying a three-dimensional measuring machine to the first press-formed product 24 and measuring the three-dimensional coordinate values of the first press-formed product 24. The processing of S104 corresponds to processing as the three-dimensional measurement data acquisition unit 113.

[0042] Next, in S106, the processor 11 obtains the result of determining whether the three-dimensional measurement data 25 satisfies a predetermined criterion. Whether the three-dimensional measurement data 25 satisfies the predetermined criterion is determined by comparing the three-dimensional measurement data 25 with the target shape of the press-formed product. The predetermined criterion may be, for example, that the three-dimensional measurement data 25 is below the deviation rate described above. The processing of S106 corresponds to the processing of the determination unit 114.

[0043] If the determination result acquired in S106 satisfies the predetermined standard, the processor 11 ends the analysis process of FIG. On the other hand, if the judgment result acquired in S106 does not satisfy the predetermined standard, the processor 11 proceeds to S108. In S108, the processor 11 acquires second mold surface data 32 obtained by correcting the first mold surface data 22. The second mold surface data 32 is mold surface data obtained by correcting the first mold surface data 22 by the user based on the three-dimensional measurement data 25. The processing of S108 corresponds to the processing of the corrected mold surface data acquisition unit 115.

[0044] Next, in S110, the processor 11 performs CAE analysis on the second mold surface data 32 to acquire second analysis result data 33. The second analysis result data 33 is analysis result data that is three-dimensional point cloud data that represents the expected shape of a second press-molded product 34 obtained by press molding using the second mold 31. The second mold 31 is a mold whose three-dimensional shape is represented by the second mold surface data 32. The processing of S110 corresponds to processing as the second analysis result acquisition unit 112.

[0045] Subsequently, in S112, the processor 11 extracts difference vectors 43 representing the differences between each point of the first analysis result data 23 and each point of the second analysis result data 33. The processing of S112 corresponds to the processing performed by the difference extraction unit 116.

[0046] Subsequently, in S114, the processor 11 generates virtual molded article data 35 by adding the difference vector 43 to the three-dimensional measurement data 25. The processing of S114 corresponds to the processing performed by the generation unit 117.

[0047] Next, in S116, the processor 11 acquires the result of determining whether or not the virtual product data 35 satisfies a predetermined criterion. Whether or not the virtual product data 35 satisfies the predetermined criterion is determined by comparing the virtual product data 35 with the target shape of the press-molded product. The predetermined criterion is, for example, that the virtual product data 35 is below the deviation rate described above. The processing of S116 corresponds to the processing of the determination unit 114.

[0048] If the determination result acquired in S116 satisfies the predetermined standard, the processor 11 ends the analysis process of FIG. On the other hand, if the determination result obtained in S116 does not satisfy the predetermined standard, the processor 11 returns to S108.

[0049] In S108, the processor 11 acquires corrected mold surface data 32a obtained by correcting the initially used second mold surface data 32. The corrected mold surface data 32a is mold surface data obtained by the user correcting the second mold surface data 32 based on the three-dimensional measurement data 25. The processing of S108 corresponds to the processing performed by the corrected mold surface data acquisition unit 115.

[0050] The subsequent processing is the same as that described above. That is, in S110, the processor 11 performs CAE analysis on the corrected die surface data 32a to obtain corrected analysis result data 33a as analysis result data.

[0051] In S112, the processor 11 extracts, as a difference vector, a corrected difference vector 43a that represents the difference between each point of the first analysis result data 23 and each point of the corrected analysis result data 33a. In S114, the processor 11 generates corrected virtual molded article data 35a as the virtual molded article data 35 by adding the corrected difference vector 43a to the three-dimensional measurement data 25.

[0052] In S116, the processor 11 acquires the result of determining whether the corrected virtual product data 35a satisfies a predetermined criterion. Whether the corrected virtual product data 35a satisfies the predetermined criterion is determined by comparing the corrected virtual product data 35a with the target shape of the press-molded product. The predetermined criterion may be, for example, that the corrected virtual product data 35a is below the deviation rate described above.

[0053] If the determination result acquired in S116 satisfies the predetermined standard, the processor 11 ends the analysis process of FIG. On the other hand, if the determination result obtained in S116 does not satisfy the predetermined standard, the processor 11 returns to S108.

[0054] In this way, the processor 11 generates virtual molded product data 35 based on the difference vector 43 and the three-dimensional measurement data 25. If the virtual molded product data 35 does not satisfy the predetermined criteria, the processor 11 repeats the generation of corrected mold surface data 32a, acquisition of corrected analysis result data 33a, extraction of the corrected difference vector 43a, and generation of corrected virtual molded product data 35a until the corrected virtual molded product data 35a satisfies the predetermined criteria. Through these processes, the processor 11 generates virtual molded product data 35 or corrected virtual molded product data 35a with the same accuracy as the second press-molded product 34.

[0055] After the analysis process is completed, the user molds the second mold 31 based on the second mold surface data 32 or the corrected mold surface data 32a corresponding to the finally obtained virtual molded product data 35 or the corrected virtual molded product data 35a. Thereafter, the user molds a second press-molded product 34 using a press molding mechanism based on the second mold 31. The second press-molded product 34 obtained at this time is formed into a press-molded product with the same accuracy as the finally obtained virtual molded product data 35 (in other words, the virtual molded product data 35 or the corrected virtual molded product data 35a that meets predetermined standards).

[0056] [1-3.Effects] According to the embodiment described above in detail, the following effects can be obtained. (1a) The processor 11 of the analysis device 1 generates virtual molded product data 35 based on the difference vector 43 and the three-dimensional measurement data 25. If the virtual molded product data 35 does not satisfy a predetermined standard, the processor 11 repeats the steps of generating corrected mold surface data 32a, acquiring corrected analysis result data 33a, extracting the corrected difference vector 43a, and generating corrected virtual molded product data 35a until the corrected virtual molded product data 35a satisfies the predetermined standard. The second mold 31 is molded based on the second mold surface data 32 or corrected mold surface data 32a that corresponds to the finally obtained virtual molded product data 35 or corrected virtual molded product data 35a that satisfies the predetermined standard.

[0057] According to this process, the user does not need to process the actual second mold 31 until the virtual molded product data 35 or the corrected virtual molded product data 35a that meets the predetermined criteria is obtained, which reduces the number of times the actual mold is processed.

[0058] (1b) The processor 11 of the analysis device 1 does not identify portions that do not satisfy the predetermined criteria and does not modify those portions individually until the virtual molded article data 35 or the modified virtual molded article data 35a satisfy the predetermined criteria. This reduces the number of steps required to obtain the virtual molded article data 35 or the modified virtual molded article data 35a that satisfy the predetermined criteria.

[0059] (1c) The virtual molded product data 35 or the corrected virtual molded product data 35a is generated by adding a difference vector 43 or a corrected difference vector 43a to the three-dimensional measurement data 25. The difference vector 43 or the corrected difference vector 43a is generated based on the first analysis result data 23 and the second analysis result data 33 or the corrected analysis result data 33a. The second analysis result data 33 and the corrected analysis result data 33a are generated based on the second mold surface data 32 or the corrected mold surface data 32a. In other words, the virtual molded product data 35 or the corrected virtual molded product data 35a is generated based on the second mold surface data 32 or the corrected mold surface data 32a.

[0060] According to this processing, the virtual molded article data 35 and the corrected virtual molded article data 35a are generated based on the second mold surface data 32 or the corrected mold surface data 32a without creating an actual mold.

[0061] Therefore, for a press-molded product that is formed in multiple processes, once the second mold surface data 32 or modified mold surface data 32a is generated, virtual molded product data 35 or modified virtual molded product data 35a can be obtained even in a process that does not involve modifying the mold surface data.

[0062] As an example, in press molding, which is performed in the order of the first step S201, the second step S202, the third step S203, the fourth step S204, and the fifth step S205, as shown in Figure 4, if second mold surface data 32 is acquired in the third step S203, virtual molded product data 35 can be acquired based on the second mold surface data 32 in both the subsequent fourth step S204 and the fifth step S205.

[0063] 2. Other Embodiments Although the embodiments of the present disclosure have been described above, it goes without saying that the present disclosure is not limited to the above-described embodiments and can take on various forms.

[0064] (2a) In the above embodiment, in S108, the processor 11 acquires second mold surface data 32 obtained by correcting the first mold surface data 22. The second mold surface data 32 is mold surface data obtained by the user correcting the first mold surface data 22 based on the three-dimensional measurement data 25. However, the second mold surface data 32 does not have to be generated based on the three-dimensional measurement data 25. For example, the processor 11 may acquire second mold surface data 32 that has been stored in advance in the storage 13, or may acquire second mold surface data 32 that has been input by the user via the user interface 14.

[0065] (2b) Multiple functions of one component in the above embodiments may be realized by multiple components, or one function of one component may be realized by multiple components. Also, multiple functions of multiple components may be realized by one component, or one function realized by multiple components may be realized by one component. Also, part of the configuration of the above embodiments may be omitted. Also, at least part of the configuration of the above embodiments may be added to or substituted for the configuration of another of the above embodiments. [Explanation of symbols]

[0066] 1...analysis device, 11...processor, 111...first analysis result acquisition unit, 112...second analysis result acquisition unit, 113...three-dimensional measurement data acquisition unit, 116...difference extraction unit, 117...generation unit, 21...first mold, 22...first mold surface data, 23...first analysis result data, 24...first press-molded product, 25...three-dimensional measurement data, 31...second mold, 32...second mold surface data, 33...second analysis result data, 34...second press-molded product, 35...virtual molded product data, 43...difference vector.

Claims

1. An analysis device, comprising: a first analysis result acquisition unit configured to acquire first analysis result data, which is three-dimensional point cloud data generated by performing a simulation related to press forming, including a springback analysis, using first die surface data representing the three-dimensional shape of a first die, and which is three-dimensional point cloud data representing an expected shape of a first press-formed product obtained by press forming using the first die; a second analysis result acquisition unit configured to acquire second analysis result data, which is three-dimensional point cloud data generated by performing the simulation using second die surface data representing a three-dimensional shape of a second die, and which is three-dimensional point cloud data representing an expected shape of a second press-molded product obtained by press molding using the second die; a three-dimensional measurement data acquisition unit configured to acquire three-dimensional measurement data generated by measuring a shape of the first press-formed product, the three-dimensional measurement data being three-dimensional point cloud data representing the shape of the first press-formed product; and a difference extraction unit configured to extract a difference vector representing a difference between each point of the first analysis result data and each point of the second analysis result data; a generation unit configured to generate virtual product data as three-dimensional point cloud data representing a corrected prospective shape of the second press-formed product based on the difference vector and the three-dimensional measurement data; An analysis device comprising:

2. The analysis device according to claim 1 , The second mold surface data is data obtained by correcting the first mold surface data based on the three-dimensional measurement data. Analysis device.

3. 3. The analysis device according to claim 1 or 2, Further provided is a corrected mold surface data acquisition unit configured to acquire corrected mold surface data obtained by correcting the second mold surface data when the virtual molded product data does not satisfy a predetermined standard, the second analysis result acquisition unit is configured to further acquire, as modified analysis result data, three-dimensional point cloud data generated by the simulation using the modified die surface data, the difference extraction unit is configured to further extract a corrected difference vector representing a difference between each point of the first analysis result data and each point of the corrected analysis result data; the generation unit is configured to further generate corrected virtual molded product data as data obtained by correcting the virtual molded product data, based on the corrected difference vector and the three-dimensional measurement data. Analysis device.

4. 1. A method of analysis comprising: Acquiring first analysis result data, which is three-dimensional point cloud data generated by performing a simulation related to press forming, including a springback analysis, using first die surface data representing the three-dimensional shape of a first die, and which is three-dimensional point cloud data representing the expected shape of a first press-formed product obtained by press forming using the first die; Acquiring second analysis result data, which is three-dimensional point cloud data generated by performing the simulation using second die surface data representing the three-dimensional shape of the second die, and which is three-dimensional point cloud data representing the expected shape of a second press-molded product obtained by press molding using the second die; and acquiring three-dimensional measurement data generated by measuring a shape of the first press-formed product, the three-dimensional measurement data being three-dimensional point cloud data representing the shape of the first press-formed product; extracting a difference vector representing a difference between each point of the first analysis result data and each point of the second analysis result data; generating virtual product data as three-dimensional point cloud data representing a corrected prospective shape of the second press-formed product based on the difference vector and the three-dimensional measurement data; An analysis method including:

5. A computer program comprising: Acquiring first analysis result data, which is three-dimensional point cloud data generated by performing a simulation related to press forming, including a springback analysis, using first die surface data representing the three-dimensional shape of a first die, and which is three-dimensional point cloud data representing the expected shape of a first press-formed product obtained by press forming using the first die; Acquiring second analysis result data, which is three-dimensional point cloud data generated by performing the simulation using second die surface data representing the three-dimensional shape of the second die, and which is three-dimensional point cloud data representing the expected shape of a second press-molded product obtained by press molding using the second die; and acquiring three-dimensional measurement data generated by measuring a shape of the first press-formed product, the three-dimensional measurement data being three-dimensional point cloud data representing the shape of the first press-formed product; extracting a difference vector representing a difference between each point of the first analysis result data and each point of the second analysis result data; generating virtual product data as three-dimensional point cloud data representing a corrected prospective shape of the second press-formed product based on the difference vector and the three-dimensional measurement data; A computer program for causing a computer to execute the above.

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