Control devices, production systems, extraction methods, and programs

Abstract

To provide a device, system, method and program, in which a structure that is out of a permissible range can be effectively used without discarding the same.SOLUTION: There is provided a management device 15 that is a device for managing a plurality of structures including at least a modeled object modeled by a modeling device, and that comprises extracting means 41 for extracting a combination of two or more structures from a plurality of structures modeled by the modeling device based on shape information of the structures. The management device 15 also comprises acquisition means 40 for acquiring measurement results of a measuring device as shape information from the measuring device for measuring a plurality of modeled structures.SELECTED DRAWING: Figure 14

Description

Technical Field

[0001] The present invention relates to a management device for managing structures shaped by a shaping apparatus, a production system including the management device, a method for extracting a combination of two or more structures, and a program for causing a computer to execute the extraction process. Background Art

[0002] As a shaping apparatus, a 3D printer can shape structures having various three-dimensional shapes. However, not all of the plurality of shaped structures have shapes and dimensions as designed.

[0003] For the purpose of more faithfully reproducing a shaped article as a structure, there is known a system that reads information on the surface shape of the shaped article and retrieves shaped article information including information on the internal structure based on the read surface shape information (see, for example, Patent Document 1). Summary of the Invention Problems to be Solved by the Invention

[0004] Conventional systems can reduce the number of structures that fall outside the allowable range by reproducing more faithfully, but there has been a problem that structures that fall outside the allowable range have to be discarded.

[0005] The present invention solves the above-described problems, and an object of the present invention is to provide an apparatus, a system, and a method that enable effective utilization of structures that are out of an allowable range without discarding them. Means for Solving the Problems

[0006] According to the present invention, there is provided a management device that manages a plurality of structures including at least a shaped article shaped by a shaping apparatus, extraction means for extracting a combination of two or more structures from among the plurality of structures based on shape information of the structures A management device is provided including [Effects of the Invention]

[0007] According to the present invention, even structures that fall outside the acceptable range can be effectively utilized instead of being discarded. [Brief explanation of the drawing]

[0008] [Figure 1] A diagram showing an example of a production system configuration. [Figure 2] A diagram showing an example of connecting a measuring device and a control device. [Figure 3] A diagram illustrating an example of a workflow for manufacturing products using a production system. [Figure 4] A diagram explaining how to change the build area. [Figure 5] A flowchart showing the process for changing the build area. [Figure 6] A diagram illustrating the execution of maintenance due to a change in the build area. [Figure 7] A flowchart illustrating the process of performing maintenance due to a change in the build area. [Figure 8] This diagram illustrates the process for determining areas where highly accurate structures will be created. [Figure 9] A flowchart illustrating the process for determining areas where highly accurate structures will be created. [Figure 10] A diagram illustrating the process of obtaining quality data from unnecessary structures. [Figure 11] A flowchart illustrating the process for acquiring quality data from unnecessary structures. [Figure 12] A diagram illustrating an example of manufacturing a product by combining two conventional structures. [Figure 13] A diagram showing an example of the hardware configuration of the management device. [Figure 14] A block diagram showing an example of the functional configuration of a control device. [Figure 15] A block diagram showing an example configuration of the calculation means provided by the management device. [Figure 16]Flowchart showing an example of processing executed by a management device. [Figure 17] Diagram showing a first example of extracting a combination of two structures with a management device and manufacturing a product based on the extracted combination. [Figure 18] Diagram showing a second example of extracting a combination of two structures with a management device and manufacturing a product based on the extracted combination. [Figure 19] Diagram showing a third example of extracting a combination of two structures with a management device and manufacturing a product based on the extracted combination. [Figure 20] Diagram illustrating processing in which a management device optimizes parameters of each device. [Figure 21] Diagram illustrating processing in which a management device optimizes modeling data. [Figure 22] Diagram illustrating processing for optimizing modeling data using measurement results before and after sintering. [Figure 23] Diagram showing a fourth example of extracting a combination of two structures with a management device and manufacturing a product based on the extracted combination. [Figure 24] Diagram showing a fifth example of extracting a combination of two structures with a management device and manufacturing a product based on the extracted combination. [Figure 25] Diagram illustrating a first method for extracting a combination of two structures. [Figure 26] Diagram illustrating output of a result of a combination of two structures. [Figure 27] Diagram illustrating a second method for extracting a combination of two structures. [Figure 28] Diagram illustrating a third method for extracting a combination of two structures. [Figure 29] Diagram illustrating a first method for determining a product manufactured as a fastening structure, in which one of two structures related to the combination is a lattice structure, in accordance with a structure to be fastened. [Figure 30] Diagram illustrating a blind rivet as a fastening structure. [Figure 31] This diagram shows how blind rivets are fastened to a plate with holes, where a portion of the blind rivets is made up of a lattice structure. [Figure 32] This diagram shows how a spring-loaded screw, acting as a fastening structure, is fastened to a plate, which is the structure to be fastened. [Figure 33] This diagram illustrates a second method for determining the product to be manufactured as a fastening structure, where one of the two structures involved in the combination is a lattice structure, and the product to be manufactured as a fastening structure is determined according to the structure to be fastened. [Modes for carrying out the invention]

[0009] The present invention will be described below with reference to embodiments, but the present invention is not limited to the embodiments described later.

[0010] Figure 1 is a diagram showing an example of the configuration of a production system. The production system in Figure 1 includes at least a molding device 10, an information processing device 11, a drying device 12, an excess powder removal device 13, a degreasing and sintering device 14, a control device 15, a measuring device 16, and a network 17. The production system shown in Figure 1 is a system in which, at least the molding device 10 molds an object as a structure, extracts combinations of two or more structures from among a plurality of structures including the molded object based on the shape information of the structures, and manufactures a product by combining two or more structures based on the extracted combinations. Here, the structure is a structure having a three-dimensional shape molded by the production system, and as an example, it includes structures at any of the stages of molding, after drying, after excess powder removal, after degreasing, and after sintering in the molding device. The molded structure is, for example, some kind of part, and the product is described as being manufactured by combining two or more structures of different types.

[0011] The production system includes a molding device 10 that fabricates structures as two or more types of molded objects to be combined to manufacture a product, and an information processing device 11 that creates data for fabricating each structure for the molding device 10. The information processing device 11 implements a design tool as software and creates data as three-dimensional shape data. The design tool allows input of design conditions such as the type of powder and molding fluid to be used, and can create data based on the input design conditions. The design tool can be any software that can create data.

[0012] The molding device 10 communicates with the information processing device 11 and molds multiple structures based on the data received from the information processing device 11. The multiple structures molded at once based on a single data set may be multiple structures of one type, or they may be two or more types of structures combined.

[0013] As the 3D printing device 10, a 3D printer can be used that employs methods such as SLS (Selective Laser Sintering), which selectively irradiates with a laser; EBM (Electron Beam Melting), which irradiates with an electron beam; or BJ (Binder Jetting), which applies a printing fluid. Figure 1 illustrates an example using a BJ-type 3D printing device 10, but other methods besides the BJ method can also be applied to the 3D printing device 10.

[0014] In the BJ-type molding apparatus 10, one layer containing powder of a predetermined thickness is formed, and the molding liquid is repeatedly discharged from the discharge nozzle to a predetermined position on the surface of the layer, thereby forming a laminate with multiple layers stacked on top of each other. The laminate is formed into a solid by drying. Excess powder adheres to the solid, and this excess powder is removed from the solid. The solid is a state in which the molding liquid is interposed in the gaps between the powder particles, and the powder particles are simply bonded together by the molding liquid, and is called a green body. Since the green body has low strength, the strength is improved by reducing the distance between the powder particles and making them denser by volatilizing and removing the resin component of the molding liquid, and then baking it.

[0015] Therefore, the production system includes a drying device 12 for drying the laminate, an excess powder removal device 13 for removing excess powder, and a degreasing and sintering device 14 for volatilizing and removing the resin components of the molding liquid and then baking it. The drying device 12 and the degreasing and sintering device 14 include heating means such as heaters. The excess powder removal device 13 may use any method that can remove excess powder, such as using a sieve, brushing it off with a brush, or using centrifugal separation.

[0016] The management device 15 extracts combinations of two or more structures based on the shape information of the fabricated structures, stores information related to those combinations, and manages the structures. The measuring device 16 measures various dimensions of the fabricated structures in order to acquire shape information of the structures. The measuring device 16 includes cameras, 3D scanners, calipers, height gauges, rulers, surface roughness meters, three-dimensional measuring machines, ultrasonic measuring devices, CT (Computed tomography), X-ray devices, density meters, etc. The shape information measured by the measuring device 16 includes images, two-dimensional and three-dimensional coordinates of the object, mesh information, point clouds, surface roughness, internal defects, density, etc.

[0017] As an example, let's explain 3D scanners. 3D scanners come in two types: contact-type and non-contact-type. Contact-type scanners use sensors or probes to make contact with a structure and obtain the coordinates of the contact point. They can acquire highly accurate shape information.

[0018] Non-contact scanning methods include pattern projection and laser beam methods. The pattern projection method projects a pattern onto the structure. It then recognizes the distortion of the pattern due to the structure's irregularities, measures the distance from the scanner to the structure, and obtains coordinates. Because it can scan a large area at once, it reduces the overall scanning time. Furthermore, it can acquire shape information with relatively little noise.

[0019] The laser beam method projects a laser beam onto the structure. Methods for obtaining coordinates include trigonometry, time-of-flight, and phase difference.

[0020] Trigonometry uses a sensor to identify the reflected light from a laser beam shining on a structure. The distance is then calculated using trigonometry to obtain the coordinates. Time-of-flight method calculates the distance and obtains coordinates from the time it takes for the reflected laser light from the structure to reach the sensor. Phase difference method shines laser beams of different wavelengths onto the structure and calculates the distance and obtains coordinates from the phase difference of the reflected light. Laser beam scanning is possible regardless of the size of the object.

[0021] The control device 15 extracts combinations of two or more structures based on the measurement results measured by the measuring device 16.

[0022] The control device 15 monitors each structure from fabrication to sintering in order to identify each of the multiple structures fabricated at once. Each structure is assigned identification information (such as an ID). The identification information only needs to be unique enough to identify the structure, and the method of assignment is not limited. For example, the identification information can be attached to the data so that it is formed on the surface of the structure. This allows each structure to be identified by the identification information of the structure's surface, which is captured by a camera or the like, from fabrication to sintering. Alternatively, each structure may be identified by its position within the device from fabrication until excess powder is removed, and after the excess powder is removed, identification information may be attached to the surface of the structure by handwriting or attaching a label to identify each structure.

[0023] The management device 15 manages the information related to the extracted combinations using the assigned identification information. By assembling two or more structures using the information related to the combinations, it is possible to manufacture products that meet certain quality standards. In the example shown in Figure 1, two types of structures are manufactured, and the other structure is inserted into one of the structures to manufacture the product.

[0024] The management device 15 is connected to the network 17 along with the information processing device 11 and the measuring device 16, and can communicate with the information processing device 11 and the measuring device 16. This allows the management device 15 to receive measurement results from the measuring device 16 via the network 17, and, if a simulation is performed, to transmit the simulation results to the information processing device 11. The network 17 may be wired or wireless, and may be a LAN (Local Area Network), WAN (Wide Area Network), or the Internet. The molding device 10 may also be connected to the network 17.

[0025] Figure 1 illustrates an example where two or more structures are fabricated using a single fabrication device 10, but two or more structures may also be fabricated using multiple fabrication devices 10. In this case, the multiple fabrication devices 10 may each use the same method, or they may be a combination of different methods.

[0026] Furthermore, two or more structures may be manufactured by combining the molding device 10 with other devices. Other devices refer to devices other than the molding device 10, such as molds. Similar to the molding device 10, the other devices are connected to the information processing device 11, the management device 15, and the measuring device 16 via the network 17. Structures manufactured by the other devices are processed, managed, and measured, respectively, by the information processing device 11, the management device 15, and the measuring device 16, which are connected via the network 17. The other devices communicate with the information processing device 11 and manufacture multiple structures based on the data received from the information processing device 11. Note that the other devices do not necessarily have to be connected to the network 17. The management device 15 assigns identification information to the structures manufactured by the other devices for management. The measuring device 16 measures the dimensions of the manufactured structures in order to acquire shape information of the structures.

[0027] The management device 15 extracts combinations of two or more structures based on the measurement results measured by the measuring device 16. In addition to structures fabricated by the molding device 10, it can also extract combinations of structures fabricated by the molding device 10 and structures manufactured by other devices. It can also extract combinations from structures manufactured by other devices. This allows, for example, when transporting structures manufactured by other devices located at a different site from the molding device 10, all structures can be traced, enabling the production of products that meet a certain quality standard.

[0028] The measurement results obtained by the measuring device 16 may be managed by a management device 15 connected to the measuring device 16 via a network, as shown in Figure 2(a). Alternatively, as shown in Figure 2(b), the measurement results may be initially processed by a processing device 18 connected to the measuring device 16, and the necessary shape information etc. may be sent to the management device 15 for management. By performing the initial processing on the processing device 18 as an edge computer and reducing the amount of information transmitted, it is possible to reduce communication costs without straining the bandwidth.

[0029] Figure 3 shows an example of a workflow in which the molding device 10 manufactures a product using the production system. Starting from step 100, in step 101, the information processing device 11 creates data. Based on the data, if a structure to be molded is to be molded, the information processing device 11 sends the created data to the molding device 10. In step 102, the molding device 10 molds the structure based on the received data.

[0030] The structure, formed as a laminate by the molding device 10, is sent to the drying device 12 and dried in step 103. After drying, it is sent to the excess powder removal device 13 and the excess powder is removed in step 104. In step 105, the structure, now a green body from which the excess powder has been removed, is degreased and sintered. In step 106, the dimensions of the structure are measured by the measuring device 16. In step 107, the control device 15 extracts combinations of two or more structures from among the multiple structures formed, based on the measurement results from the measuring device 16. In step 108, the combination of structures is determined based on the extracted combinations, and the work is completed in step 109.

[0031] Depending on the type of molding apparatus 10, steps 103, 104, and 105 may be omitted as appropriate. Here, we have described the case in which a structure is manufactured using the molding apparatus 10, but structures manufactured using other devices may also be measured and managed. In this case, in step 106, the dimensions of the structure manufactured using the other device are measured.

[0032] When referring to the measurement results of various dimensions of the structure, it may be found that there are build areas with low build accuracy where the quality does not meet the specified standards. If a structure is manufactured in a build area with low build accuracy, the structure that does not meet the quality standards will be discarded, resulting in wasted material. It is desirable to change the build area so that material cannot be placed in such areas during the next build. Here, we specify the next build, but it may also be for subsequent builds. If it is for subsequent builds, and the build environment changes due to part replacement, etc., the build area can be changed and build in the entire area again.

[0033] Figure 4 is a diagram illustrating the change of the build area after step 106 shown in Figure 3. The measurement results of each dimension obtained in step 106 are stored and accumulated in the data storage unit 70 of the management device 15 or a data storage device. The judgment unit 71 of the management device 15, etc., determines whether the build quality for the build area meets a predetermined standard, that is, whether it is above a certain level of accuracy and therefore passes, based on the accumulated measurement results, because the build accuracy differs depending on the build area. For example, if it is determined that it passes if the difference between the diameter dimension actually built and measured and the diameter dimension at the time of design is 0.5 mm or less, in the example shown in Figure 3, the structure in the area that is largest in the X direction and smallest in the Y direction among the measurement results (measurement data) exceeds 0.5 mm and is judged to be a failure (NG).

[0034] The judgment unit 71 sends the judgment result to the CAM (Computer Aided Manufacturing) / CAD (Computer Aided Design) 72 and reflects it as build area data. CAD is a system that creates shape data for three-dimensional shapes, and CAM is a system that creates machining data from the shape data created by CAD. Once the judgment result is reflected, the CAM / CAD 72 will not be able to place material in the areas that failed the judgment result during the next build.

[0035] Furthermore, the determination unit 71 transmits the determination result to the manufacturing unit 73, such as the molding device 10, as molding area data for the next molding process. As a result, the determination unit 71 instructs the user interface (UI) 74, which is the display unit of the manufacturing unit 73, to display information about the molding area that has been newly excluded from the molding area data and to exclude it from the molding process.

[0036] The build area information displayed in UI74 is shown in a way that distinguishes it from other build areas that meet quality standards, such as by using color coding or displaying measurement results (numerical values). Therefore, it is not limited to color coding or numerical display, as long as it can be displayed in a way that distinguishes it from other build areas.

[0037] Figure 5 is a flowchart showing the process for changing the build area. After measuring the dimensions of the structure in step 106, the process proceeds to step 106_1A, where the measurement results are stored and accumulated in the data storage unit 70. In step 106_2A, it is determined whether the measurement results have been stored for all the built structures. If not, the process returns to step 106; if stored, the process proceeds to step 106_3A.

[0038] In step 106_3A, the build quality of the structures created in each area is determined to be acceptable. If all are acceptable, the process proceeds to step 106_7A and ends. On the other hand, if there are any unacceptable structures, the process proceeds to step 106_4A, where the build area is changed and the area where the unacceptable structures were created is instructed to be excluded from the build area. In step 106_5A, the change in the build area is reflected in CAM / CAD72, the system that creates the build data, and in step 106_6A, the change in the build area is reflected in the manufacturing unit 73. Here, the reflection to CAM / CAD72 is performed followed by the reflection to the manufacturing unit 73, but this order is not limited; the reflection to the manufacturing unit 73 may be performed first, or the reflection to CAM / CAD72 and the reflection to the manufacturing unit 73 may be performed in parallel. Once the changes have been reflected, the process proceeds to step 106_7A and ends.

[0039] Figure 6 illustrates the execution of maintenance due to a change in the build area. The manufacturing unit 73 is equipped with a fan 75 and a heater 76 for drying the layered material and sintering the green body. When the build area is changed, there is a high possibility that differences will occur in the build environment due to the time-series deterioration of the fan 75 and heater 76 and changes in the condition of various drive components. Therefore, when changing the build area, maintenance such as adjustments and parts replacement can be performed.

[0040] Figure 7 is a flowchart showing the flow of maintenance performed by changing the build area. Steps 106 to 106_3B are the same as the processes from steps 106 to 106_3A shown in Figure 5, so their explanation is omitted here.

[0041] If a defective structure is determined in step 106_3B, the process proceeds to step 106_4B, where an abnormality is found and maintenance of the manufacturing unit 73 is performed. In step 106_5B, maintenance of the fan 75 is performed, and in step 106_6B, maintenance of the heater 76 is performed. Note that maintenance is not limited to the fan 75 and heater 76, but can also be performed on other devices and parts involved in molding. Furthermore, the order of maintenance is not limited to fan 75 then heater 76; it may be heater 76 then fan 75, or fan 75 and heater 76 may be performed in parallel. After maintenance, the process ends in step 106_7B.

[0042] By referring to the measurement results of various dimensions of the structure, it is possible to identify areas where the fabrication quality meets the prescribed standards and where highly accurate structures are fabricated. Highly accurate structures are those where the dimensions during design are nearly identical to the dimensions during actual fabrication. Such highly accurate structures can be given added value and offered as premium products.

[0043] Figure 8 illustrates the process for determining the area where a highly accurate structure is fabricated. The measuring unit 77, such as the measuring device 16, measures characteristic points of fastening parts, shear force, tensile force, etc., as information necessary for the fabrication quality of the fabrication area. The measurement results are stored in the data holding unit 70.

[0044] The determination unit 71 determines the area where a highly accurate structure has been fabricated based on the stored measurement results. The determination unit 71 transmits the determination result to the manufacturing unit 73 and instructs the manufacturing unit 73 to display the structure on its UI 74, etc., by changing the color of the structure.

[0045] In the example shown in Figure 8, areas where the difference between the diameter dimension at the time of design and the measured diameter dimension is less than 0.05 mm, and where the difference is rounded to 0.0 mm (after rounding to two decimal places), are circled as areas of high-precision structures. Here, the determination is made based only on the diameter dimension, but this is not the only method; other elements such as length may also be used for determination, or multiple elements including other elements may be used for determination.

[0046] Figure 9 is a flowchart showing the process for determining the area where a highly accurate structure will be fabricated. After measuring the dimensions of the structure in step 106, the process proceeds to step 106_1C to determine the fabrication quality for the fabrication area. In step 106_2C, the determined fabrication quality information is stored in the data storage unit 70. In step 106_3C, it is determined whether N pieces of fabrication quality information have been secured. N is an integer greater than or equal to 1. If not, the process returns to step 106.

[0047] If information on the build quality of N is obtained in step 106_3C, the process proceeds to step 106_4C to determine whether there are areas of high-precision structures. If there are areas of high-precision structures, the process proceeds to step 106_5C, where the measurement results and information indicating which areas should be displayed in a different color are sent to the manufacturing unit 73, etc., and the UI 74, etc. in the manufacturing unit 73 is instructed to display that information. Then, the process proceeds to step 106_6C to end. On the other hand, if there are no areas of high-precision structures, the process proceeds directly to step 106_6C to end.

[0048] The determination unit 71 makes a determination based on the measurement results to remove areas where structures that do not meet predetermined criteria have been fabricated from the fabrication area. In this determination, structures that do not meet the predetermined criteria become unnecessary structures. In addition, even if a structure meets the predetermined criteria, if there are not the same number of counterpart structures to combine it with, the excess amount becomes a surplus and becomes an unnecessary structure.

[0049] The performance of a structure can be evaluated based on characteristics of fastening points, shear force, tensile force, etc. Even if a structure is deemed unnecessary, discarding it without evaluating its performance, when parts that can be evaluated still exist, leads to waste of materials. In some cases, unnecessary structures can be combined to manufacture products of satisfactory quality. Therefore, it is desirable to acquire as much quality data as possible for parts that can be evaluated, so that this data can be used when combining structures.

[0050] Figure 10 illustrates the process of obtaining quality data from unnecessary structures. The determination unit 71 determines which structures are unnecessary based on the measurement results. As shown in the table in Figure 10, the determined unnecessary structures are classified as follows: shape NG, width (e.g., width or diameter) NG, length NG, and excess. The performance of a hollow cylindrical structure into which a cylindrical structure is inserted can be evaluated by the characteristic points of the fastening part, shear force, and tensile force. As shown in the table in Figure 10, shear force is a force that displaces the internal surface of the structure in the direction indicated by the arrow. As shown in the table in Figure 10, tensile force is a force that pulls the structure in the direction indicated by the arrow.

[0051] The parts that can be evaluated for performance vary depending on the classification. If the shape or width is NG, the length is almost the same as the design length, so the tensile force is the part that can be evaluated for performance. If the length is NG, the shape and diameter are almost the same as the design shape and diameter, so the characteristic points of the fastening part and the shear force are the parts that can be evaluated for performance. In the case of excess, in addition to the shape and diameter, the length is also almost the same as the design shape, etc., so the characteristic points of the fastening part, the shear force and the tensile force are all parts that can be evaluated for performance.

[0052] The measuring unit 77 performs measurements on parts of an unnecessary structure that can be evaluated for performance. For example, if the part of an unnecessary structure that can be evaluated for performance is its length, the measuring unit measures that length.

[0053] The quality data processing unit 78 of the control device 15 acquires the measurement results of the parts that can be evaluated for performance as quality data, associates the acquired quality data with the identification information assigned to each structure, and transmits it to the data holding unit 70 for storage (storage).

[0054] Figure 11 is a flowchart showing the process for obtaining quality data from unnecessary structures. Steps 106 to 106_3D shown in Figure 11(a) are the same as steps 106 to 106_3C shown in Figure 9, so their explanation is omitted here.

[0055] If the N-number of molding quality information is obtained in step 106_3D, proceed to step 110, where measurements are taken on parts that can be evaluated for performance using unnecessary structures. Specifically, as shown in Figure 11(b), in step 110_1, the shape and dimensions of the characteristic points of the fastening part are measured, in step 110_2, the shear force is measured, and in step 110_3, the tensile force is measured. This is an example of measuring all characteristic points, shear force, and tensile force. For example, if the shape or lateral aspect is unacceptable, only the tensile force in step 110_3 can be measured, as shown in the table in Figure 10.

[0056] Referring again to Figure 11(a), in step 111, the measurement results are acquired as quality data, in step 112, the quality data is stored in the data holding unit 70, and in step 113, the process is terminated. The quality data is associated with and stored the identification information assigned to the structure.

[0057] Referring again to Figure 3, in step 107, one or more combinations of structures are extracted from the structures fabricated by the molding device 10 and the structures manufactured by other devices. Then, in step 108, the combination of structures is determined based on the extracted combinations.

[0058] The information related to combinations is used when manufacturing a product by combining two or more structures. Furthermore, the information related to combinations can be used in the information processing device 11 to simulate how deformation will occur and what kind of structure will be created based on the data used.

[0059] When multiple structures are fabricated simultaneously using a powder-based fabrication apparatus 10, it is difficult to maintain a consistent thickness and uniform density of the powder layer throughout the entire structure. The way the fabrication fluid penetrates varies depending on the fabrication location, and the way heat is transferred differs depending on the arrangement of each device, such as the drying apparatus 12. As a result, not all of the fabricated structures will have the exact shape and dimensions of the design. Therefore, conventionally, tolerances have been set, and those within the tolerance range are used in the product as meeting the specified standards, while those outside the tolerance range are discarded.

[0060] In the example shown in Figure 12, two or more structures are fabricated: a hollow cylindrical structure A and a cylindrical structure B that is inserted into the hollow portion of structure A. The product is then manufactured by inserting structure B into structure A. As shown in Figure 12(a), when structures A and B are fabricated in the shape specified in the design, both have a nearly circular cross-section, and the diameter of the hollow portion of structure A is slightly larger than the diameter of structure B, allowing the product to be manufactured by inserting structure B into structure A.

[0061] On the other hand, as shown in deformations A', A'', B', and B'' in Figure 12(b), if the deformation exceeds the specified tolerance and is outside the allowable range, the deformed structure becomes unusable. Tolerance is the difference between the maximum and minimum values ​​of the allowable range. The combination of structures is basically subject to strict tolerances, and if it falls outside the tolerance, it cannot be used in the product, and the unusable structure is discarded.

[0062] In Figure 12(b), in deformations A' and A'', the difference between the length in the major axis direction and the minor axis direction of the elliptical cross-section of the hollow portion exceeds the tolerance, and in deformations B' and B'', the difference between the length in the major axis direction and the minor axis direction of the elliptical cross-section exceeds the tolerance.

[0063] Comparing deformations A' and B', and A'' and B'' in Figure 12(b), we see that the elliptical cross-sections of the hollow portions deform in the same direction, and the amount of deformation is almost the same. Therefore, it is possible to insert deformation B' into deformation A', and it is possible to insert deformation B into deformation A''. If these meet the required conditions such as insertion length and insertion pressure necessary for providing them as products, discarding them would be a waste of materials, as there would be no quality issues.

[0064] Therefore, even if the structures are to be discarded, the management device 15 is configured to measure the dimensions of the combined deformations A' and B', and deformations A'' and B'', and based on the measurement results, extract combinations of these two structures that can be used to manufacture products that are of acceptable quality.

[0065] Figure 13 shows an example of the hardware configuration of a management device 15 that manages structures created by extracting combinations of two structures and storing information related to those combinations. The management device 15 is equipped with a CPU (Central Processing Unit) 20, ROM (Read Only Memory) 21, RAM (Random Access Memory) 22, HD (Hard Disk) 23, and HDD (Hard Disk Drive) controller 24, similar to a general computer. The management device 15 also includes a display 25, an external device connection I / F (Interface) 26, a network I / F 27, a data bus 28, a keyboard 29, a pointing device 30, a DVD-RW (Digital Versatile Disk Rewritable) drive 31, and a media I / F 32.

[0066] The CPU 20 controls the operation of the entire management device 15. The ROM 21 stores programs used to drive the CPU 20, such as the IPL (Initial Program Loader). The RAM 22 provides a workspace for the CPU 20. The HD 24 stores various data, such as programs. The HDD controller 24 controls the reading and writing of various data to the HD 24 according to the control of the CPU 20. Here, an HDD is used as the storage device for storing various data, but it is not limited to this, and an SSD (Solid State Drive) or the like may also be used.

[0067] The display 25 displays various information such as cursors, menus, windows, text, or images. The external device connection interface 26 is an interface for connecting various external devices. In this case, external devices include, for example, USB (Universal Serial Bus) memory and printers. The network interface 27 is an interface for data communication using a communication network. The data bus 28 is an address bus and data bus for electrically connecting various components such as the CPU 20.

[0068] The keyboard 29 is a type of input means equipped with multiple keys for inputting characters, numbers, and various instructions. The pointing device 30 is a type of input means for selecting and executing various instructions, selecting processing targets, moving the cursor, etc. The DVD-RW drive 31 controls the reading or writing of various data to a DVD-RW 33, which is an example of a removable recording medium. Note that it is not limited to DVD-RW, but may also be DVD-R, etc. The media I / F 32 controls the reading or writing of data to a recording medium 34 such as flash memory.

[0069] Figure 14 is a block diagram showing an example of the functional configuration of the management device 15. The management device 15 includes acquisition means 40, extraction means 41, data holding means 42, identification means 43, calculation means 44, and input receiving means 45. These functional means can be realized by one or more processing circuits. Here, processing circuits include processors programmed to execute each function by software, such as processors implemented by electronic circuits, and devices such as ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), FPGAs (Field Programmable Gate Arrays), and conventional circuit modules designed to execute each function.

[0070] The acquisition means 40 acquires measurement results measured by the measuring device 16 as shape information of structures fabricated by the molding device 10. It also acquires measurement results measured by the measuring device 16 as shape information of structures manufactured by other devices. Based on the measurement results acquired by the acquisition means 40, the extraction means 41 extracts combinations of two or more structures from among multiple structures that, when combined, satisfy the quality of the product. If the quality of the product is satisfied, in addition to structures A and B as designed as shown in Figure 11(b), it becomes possible to extract combinations of structures such as deformed A' and deformed B', and deformed A'' and deformed B'', which would conventionally have been subject to disposal.

[0071] The measurement results include information on one or more feature points. When combining a first structure and a second structure, the extraction means 41 can extract combinations of first and second structures that meet predetermined conditions based on the information on one or more feature points included in the measurement results of each of the multiple first structures and multiple second structures that have been fabricated.

[0072] Furthermore, it is possible that any combination of structure 1, structure 2, or structure 3 may meet the specified conditions and satisfy the product quality requirements. In such cases, the structure that provides better quality (e.g., structure 2) can be selected from among structure 2 and structure 3, and structure 1 and structure 2 can be extracted as the optimal combination. This is just one example; for example, in comparison with structure 1, the structure that is initially determined to satisfy the product quality requirements may be selected.

[0073] The data holding means 42 holds the measurement results acquired by the acquisition means 40. The data holding means 42 holds multiple fastening information items, which associate measurement results of multiple structures, measurement results of fastening structures as products, measurement results of fastening target structures to which fastening structures are fastened, and measurement results such as fastening strength.

[0074] The identification means 43 identifies each structure from the start of molding by the molding apparatus 10 to the completion of degreasing and sintering by the degreasing and sintering apparatus 14, based on images acquired from an imaging device such as a camera. The identification means 43 also identifies each structure from the start to the end of manufacturing by other devices, based on images acquired from an imaging device such as a camera. The identification means 43 identifies each structure by its position and arrangement within each device, and identifies each structure by identification information applied to its surface, etc. The acquisition means 40 can acquire the measurement results of the structures identified by the identification means 43 measured by the measuring device 16, along with the identification information used to identify those structures.

[0075] The calculation means 44 performs simulations of the formation of multiple structures. The data holding means 42 holds measurement results of multiple structures after excess powder has been removed and measurement results of multiple structures after sintering. Based on the measurement results collected by the data holding means 42, the calculation means 44 performs simulations to predict the dimensions of the structures after sintering from the measurement results after excess powder has been removed. The calculation means 44 also determines the fastening structure to be fastened to the fastening target structure based on the multiple fastening information held by the data holding means 42 and the measurement results of one or more feature points of the fastening locations of the input fastening target structure. In addition to the multiple fastening information and measurement results of the fastening locations, the calculation means 44 can also determine the fastening structure based on the fastening conditions of the fastening structure to the input fastening target structure. The input receiving means 45 receives input such as fastening conditions that the calculation means 44 uses for calculations.

[0076] The calculation means 44 may further implement a machine learning program. The calculation means 44 can perform an optimal simulation using machine learning based on data for shaping the structure and measurement results. The machine learning program can function as a data storage means 80, a learning means 81, and an estimation means 82, as shown in Figure 15. The data storage means 80 receives data for shaping the structure, measurement results, and simulation results, and stores them as data. The learning means 81 extracts features from the data stored in the data storage means 80 and learns their relationships. The estimation means 82 estimates the shape changes of the structure based on the results learned by the learning means 81, and performs a simulation based on this estimation.

[0077] The management device 15 includes at least an extraction means 41, and other acquisition means 40, data holding means 42, etc., may be provided as needed. The management device 15 may also include a determination means corresponding to a determination unit 71 and a quality data processing means corresponding to a quality data processing unit 78.

[0078] Figure 16 is a flowchart showing an example of a process performed by the control device 15. The control device 15 performs this process after two or more structures have been fabricated by the molding device 10, etc., and before combining the various structures to manufacture a product. Two or more structures may be fabricated by the molding device 10 alone, or two or more structures may be manufactured by the molding device 10 and other devices. Starting from step 200, in step 201, the dimensions of the fabricated structures are measured by the measuring device 16, and the measurement results are obtained from the measuring device 16. In step 202, the measurement results are stored.

[0079] Step 203 involves selecting one structure. Step 204 involves comparing the measurement results of the selected structure with those of other structures. Step 205 involves extracting structures to combine with the selected structure. This results in the combination of the selected structure and the extracted structures becoming the combination of structures to be extracted.

[0080] The measurement results of the selected structure and structures of different types are compared. If the selected structure is within the specified tolerance, the measurement results of other types of structures within the specified tolerance are extracted as structures to combine with it.

[0081] If the selected structure exceeds the specified tolerance, a structure of a different type from the selected structure, whose measurement results exceed the specified tolerance, is insertable into the selected structure, and meets predetermined conditions such as insertion length and insertion pressure, will be extracted as a structure to be combined with. If the selected structure is the structure to be inserted, a structure that is insertable into the selected structure and meets predetermined conditions will be extracted as a structure to be combined with.

[0082] In step 206, information relating to the combination of the selected structure and the extracted structure is stored. The information stored is, for example, information that associates the identification information of the selected structure with the identification information of the extracted structure.

[0083] In step 207, it is determined whether there are any structures left to select. If there are still some, the process returns to step 203 and extracts the combinations. If there are no more, the process proceeds to step 208 and ends.

[0084] The following will provide a detailed explanation using specific examples. Figure 17 shows a first example in which a control device 15 extracts combinations of two structures and a product is manufactured based on the extracted combinations. When multiple structures A and multiple structures B that are combined with each other are manufactured in the same production system, as mentioned above, the density of the powder, the penetration of the molding fluid, the way heat is applied, etc. differ depending on the position in each device, so it is not possible to manufacture structures A and B that are all the same size.

[0085] Therefore, in addition to structures A and B having the characteristic C and C' of having a circular cross-section within the tolerance as shown in Figure 17, structures A and B having the characteristic D, D', E and E' of having an elliptical cross-section exceeding the tolerance are manufactured.

[0086] When assembling a product by inserting structure B into structure A, the quality of the assembled product can be kept consistent by selecting a structure B that is suitable for the shape of a given structure A from among several structures and inserting the selected structure B. A structure B that is suitable for the shape of structure A would be, for example, a structure B with feature C' for structure A which has feature C, a structure B with feature D' for structure A which has feature D, and a structure B with feature E' for structure A which has feature E. This means that even if structure A is deformed, a structure B that matches its shape can be assigned to assemble a product of consistent quality. By using such deformed structures to manufacture products, the number of discarded structures can be reduced, leading to improved yield and cost reduction. This effect can be obtained even more effectively by applying it to 3D printers, which are generally said to have large deformations during the manufacturing process.

[0087] In the example shown in Figure 17, we explained how combinations are extracted based on the shape information (features) of each structure. However, by measuring not only features but also dimensions and shape in detail and using the measurement results, it is possible to extract combinations of structures more appropriately.

[0088] Figure 18 shows a second example in which a control device 15 extracts combinations of two structures and a product is manufactured based on the extracted combinations.

[0089] The example shown in Figure 18 includes a measuring device 16 for measuring dimensions, shape, etc. When assembling a product by combining structure A and structure B, the dimensions, shape, characteristics, etc. of each joint where structure A and structure B come into contact are obtained as measurement results for all manufactured structures using the measuring device 16. For example, the dimensions of the joint of structure A are the inner diameter, length in the longitudinal direction, etc., and the shape is cylindrical, etc. The dimensions of the joint of structure B are the outer diameter, length in the longitudinal direction, etc., and the shape is cylindrical, etc. Characteristics include the cross-sectional shape such as a perfect circle or ellipse, and the surface condition such as surface roughness, etc.

[0090] By using information such as the dimensions of the joints and the shape of the structure, in addition to features such as the cross-section being a perfect circle or ellipse, it is possible to determine whether structure B can be inserted into structure A, what the insertion length will be if inserted, and whether the insertion pressure is appropriate. This makes it possible to determine and extract the most suitable structure B from among multiple structures B for a given structure A. Whether a structure is optimal can be determined by whether it meets predetermined conditions. If there are multiple structures that meet the predetermined conditions, any of the multiple suitable structures may be adopted, and the structure that would produce the best quality when manufactured or the structure that was initially determined to meet the predetermined conditions can be selected.

[0091] In the example shown in Figure 18, the extraction of combinations was explained using the measurement results measured by the measuring device 16. However, by storing the measurement results and comparing them, combinations can be easily extracted. Figure 19 shows a third example in which the management device 15 extracts combinations of two structures and a product is manufactured based on the extracted combinations.

[0092] In the example shown in Figure 19, a data storage means 42 is provided to hold the measurement results measured by the measuring device 16, making it possible to access all measurement results. The data storage means 42 may be a non-volatile storage area such as an HDD or SSD provided by the management device 15, a USB memory connected to the management device 15, or a standalone data storage device such as a NAS (Network Attached Storage).

[0093] Since the data holding means 42 holds the measurement results of all structures A and B, the extraction means 41 can use the measurement results held by the data holding means 42 to extract appropriate combinations of structures A and B. The optimal combination of structures A and B can be determined by comparing the dimensional differences of the joints (assembly target parts) of the structures A and B to be combined, or by the similarity ratio of the shapes of structures A and B. Furthermore, the optimal combination for assembly may be determined by comparing the surface roughness.

[0094] If structure A is fabricated, the distribution of feature points is calculated from the measurement results, and structure B is fabricated to be optimal for the calculated distribution, then it becomes possible to minimize waste and efficiently combine structures.

[0095] Figure 20 illustrates the process by which the control device 15 optimizes the parameters of each device. The manufacturing unit 73 produces a finished product of structure A, and the measurement unit 77 performs measurements. The distribution calculation means 46 of the control device 15 calculates the distribution of one or more feature points of structure A based on the measurement results from the measurement unit 77. The parameter determination means 47 of the control device 15 optimizes the parameters such as molding conditions, drying conditions, and sintering conditions used to manufacture structure B by determining (calculating) them so that the distribution of one or more feature points of structure B matches the calculated distribution, and sets these parameters in each device, including the molding device 10 that constitutes the manufacturing unit 73.

[0096] The manufacturing unit 73 manufactures structure B using the set parameters. The measurement unit 77 measures the finished product of structure B. The distribution of the measurement results at this time will be close to the distribution that matches the distribution of structure A, so they can be efficiently combined in a way that minimizes excess between them.

[0097] Figure 21 illustrates the process by which the management device 15 optimizes the molding data. In the example shown in Figure 20, the parameters of each device were optimized, but it is also possible to manufacture structure B with a distribution that matches the distribution of structure A by modifying the molding data. For this reason, after the distribution is calculated by the distribution calculation means 46, the calculation means 44 can modify and optimize the molding data used to manufacture structure B so that the distribution of one or more feature points of structure B matches the distribution of structure A. The calculation means 44 can optimize the molding data by using a machine learning program and making it function as each means shown in Figure 15. Note that this is just one example, and the method of optimizing the molding data is not limited to the method using a machine learning program.

[0098] The manufacturing unit 73 manufactures structure B using optimized molding data. The measurement unit 77 measures the finished product of structure B. The distribution of the measurement results at this time will be close to the distribution that matches the distribution of structure A, so they can be efficiently combined in a way that minimizes excess.

[0099] In the examples shown in Figures 20 and 21, the distribution is calculated using the measurement results after sintering of structure A. If the correlation between deformation before and after sintering is well understood, the distribution may be estimated using measurement results measured after fabrication, but after the excess powder from before sintering has been removed, rather than using the measurement results after sintering. In Figure 22, the distribution calculation means 46 estimates the distribution using the measurement results measured after the excess powder has been removed, and during the time it takes for structure A to sinter, the calculation means 44 modifies the fabrication data of structure B to match the calculated distribution. In this case as well, the fabrication data can be modified using the machine learning program described above, but the method of optimizing the fabrication data is not limited to the method using the machine learning program.

[0100] By modifying the molding data during the sintering time, the manufacturing of structure B can be started earlier, resulting in more efficient production time, and the parts can be assembled more efficiently with minimal waste.

[0101] After manufacturing structures A and B, in order to extract combinations of structures A and B, it is necessary to identify the individual structures A and B involved in the combination from among multiple structures. Figure 23 shows a fourth example in which the control device 15 extracts combinations of two structures and manufactures products based on the extracted combinations.

[0102] In the example shown in Figure 23, an identification means 43 is provided to monitor which structure is where from the start to the end of the fabrication process, and to identify each structure. This allows for the association of each structure with the measurement results.

[0103] A camera is attached to the molding device 10, etc., as an imaging device, and the identification means 43 identifies each structure from images or videos captured by the camera. To enable the identification of each structure, each structure can be uniquely identified before the start of molding, and identification information (identification symbol data) that appears on the surface as a result of the molding of each structure can be assigned to the data. As long as each structure can be identified, this is not the only option; at the end of molding, labels or the like with identification symbols that uniquely identify the structure while associating it with its position within the device may be attached.

[0104] In the example shown in Figure 23, monitoring is performed until the completion of molding. However, if degreasing and sintering are performed after the completion of molding, monitoring can be performed until after degreasing and sintering. Figure 24 shows a fifth example in which the control device 15 extracts combinations of two structures and manufactures a product based on the extracted combinations.

[0105] In the example shown in Figure 24, the camera monitors the inside of the degreasing and sintering apparatus 14, and even after measuring each structure after the fabrication is complete, all structures can still be identified. Degreasing and sintering can then be performed in the degreasing and sintering apparatus 14, and after sintering, each structure can be measured again, and the measurement results can be correlated.

[0106] When identification symbols are assigned to each structure by attaching labels, there is a possibility that they will be burned off during degreasing and sintering. Therefore, before placing the structures into the degreasing and sintering apparatus 14, the positions within the apparatus 14 and the identification symbols on the labels are recorded in correspondence, and after sintering is complete, labels with the corresponding identification symbols can be attached to the structures at each position. This makes it possible to understand the quality of all structures from the start of fabrication to the measurement results after sintering.

[0107] Next, we will describe in detail the method for extracting combinations of two structures. Figure 25 is a diagram illustrating the first method for extracting combinations of two structures. The extraction means 41 compares the data of one or more feature points included in the measurement results of the sintered first structure and the data of one or more feature points included in the measurement results of the sintered second structure, obtained from the measurement device 16, and extracts the combination that is best suited for assembly.

[0108] As shown in Figure 25, in the case of a product assembled by inserting the lower part of structure B into the upper part of structure A, the inner shape of the cylindrical upper part into which structure B is inserted is used as a characteristic point in structure A, and its dimensions are measured. Similarly, in structure B, the outer shape of the cylindrical lower part that serves as the insertion part is used as a characteristic point, and its dimensions are measured.

[0109] The measurement results may be stored in the data storage means 42, and the data of each stored feature point can be compared to extract the optimal combination for assembly. This makes it possible to reduce the waste of structures and ensure a certain level of assembly quality.

[0110] The results of combining two structures can be output as a report, as shown in Figure 26. The report can be printed using, for example, a printer. In addition to printing on paper, the report may also be displayed on a display unit, projected onto a wall or screen, etc. In these cases, a display device or projection device can be used as the output device. By outputting such a report, it becomes possible to present the results of the combination, and the resulting quality and performance, to users without requiring any intervention from quality control personnel.

[0111] In the example shown in Figure 25, the optimal combination is extracted using measurement results taken after sintering. However, by also obtaining measurement results taken after fabrication but before degreasing and sintering, it becomes possible to correlate the measurement results after fabrication with those after sintering, and extract the optimal combination based on the measurement results after fabrication, without relying on the measurement results after sintering. Figure 27 illustrates a second method for extracting combinations of two structures.

[0112] Figure 27 shows that, in addition to measurement results of one or more feature points of the structure after sintering in the degreasing and sintering apparatus 14, measurement results of one or more feature points of the structure after molding before degreasing and sintering are continuously acquired. This allows for a correlation between the measurement results after molding and the measurement results after sintering. In other words, it becomes possible to understand how changes in the measurement results after molding will affect the measurement results after sintering, and to predict the shape after sintering from the shape after molding. Then, it becomes possible to determine from the measurement results after molding which structures will form the optimal combination, and to prioritize feeding the structures involved in the combination into the degreasing and sintering apparatus 14, thereby enabling efficient structure manufacturing.

[0113] Figure 27 simply correlates the measurement results before and after degreasing and sintering; therefore, without obtaining the measurement results before degreasing and sintering, it is not possible to predict the measurement results after degreasing and sintering. However, by collecting measurement results according to data, molding conditions, drying conditions, molding position, etc., it is possible to construct estimation formulas to estimate the measurement results after sintering. Then, by inputting the data and molding conditions for molding, it is possible to run a simulation to predict the data of the structure after molding and the data of the structure after sintering. This makes it possible to extract the optimal combination from before molding and facilitates the planning of manufacturing structures that take assembly into consideration.

[0114] Figure 28 illustrates a third method for extracting combinations of two structures. In the example shown in Figure 28, the calculation means 44 predicts the deformation of structure A through simulation, predicts the deformation of structure B through simulation, and performs a combination simulation using the results of each simulation. The extraction means 41 extracts the optimal combination based on the combination simulation results.

[0115] The deformation of structures A and B can be predicted by performing structural simulations, sintering simulations, etc. Note that one simulation may be performed, or a combination of simulations may be performed. The simulations can be executed using estimation models, such as estimation formulas, created using previously measured results. Combination simulations include cases where assembly is impossible, such as when structure B cannot fit inside structure A, or when there are gaps preventing assembly and joining. The simulations then analyze insertion length, insertion pressure, etc., to extract combinations that meet the predetermined conditions, such as allowable insertion length and insertion pressure.

[0116] Since structural deformation occurs during fabrication, degreasing, and sintering, etc., by measuring the dimensions of the resulting structure after each process and collecting as many measurement results as possible, an estimation model for use in simulations can be constructed. Furthermore, the estimation model can be modified each time measurement results are collected to improve the accuracy of the simulation.

[0117] Estimation models can be created for deformation simulations from fabrication to sintering. From these estimated deformation simulation models, models can be created for combination simulations, where structures are combined to determine whether they meet predetermined conditions. This allows for continuous updates of each model after its creation, enabling continuous improvement of simulation accuracy.

[0118] Furthermore, simulations allow for accurate prediction of the resulting structure's shape before actual fabrication, enabling the precise extraction of the optimal combination of structures.

[0119] Up to this point, we have explained how to manufacture a product by combining two or more structures. This involves extracting the optimal combination of two or more structures, storing and managing information related to that combination, and then manufacturing the product by combining the two or more structures based on the managed information. The manufactured product may be a fastening structure such as a blind rivet or a spring-loaded screw, which is fastened to a plate or other structure that is to be fastened.

[0120] When fastening a fastening structure to a target structure, the fastening structure is passed through a hole provided in the target structure. For example, when fastening a screw to a plate, the screw can be inserted perpendicular to the surface of the plate to achieve the desired fastening force. However, the screw may be inserted at an angle to the surface of the plate, in which case the desired fastening force cannot be obtained. Also, the holes provided in the plate are not always formed perpendicular to the surface of the plate, but may be formed at an angle. In this case as well, the desired fastening force cannot be obtained.

[0121] Therefore, by making the fastening parts that each fastening structure comes into contact with a target structure into a lattice structure, it is possible to create a structure that conforms easily to the target structure while ensuring strength where necessary and preventing excessive deformation. A lattice structure is a grid-like structure that is used in 3D printing to improve strength and reduce weight when manufacturing metal products. Complex shapes like lattice structures can only be manufactured with 3D printers and are called DfAM (Design for Additive Manufacturing) shapes.

[0122] In order to fasten a fastening structure to a target structure and obtain a predetermined strength, the shape of the fastening structure having a DfAM shape must be suitable for the fastening conditions, such as the characteristic points and strength of the fastening part of the target structure.

[0123] Figure 29 illustrates a first method for determining a product manufactured as a fastening structure having a lattice structure at the fastening point, according to the structure to be fastened. A fastening structure having a DfAM shape at the fastening point, manufactured using a production system and having its characteristic points measured, is fastened with a structure to be fastened, whose characteristic points at the fastening point have been measured by a measuring device 16 of the production system. The strength and other properties after fastening are measured and retained as fastening data. Multiple fastening data sets are obtained by fastening fastening structures with different shapes, etc., to structure to be fastened with structures with different shapes, etc., at the fastening points, and measuring the strength and other properties. The fastening data may include data such as characteristic points at the fastening point, the force required at fastening, shear force, tensile force, etc.

[0124] The extraction means 41 can determine the shape of a fastening structure suitable for fastening to the target structure based on the characteristic points and fastening conditions such as strength of the fastening part of the target structure. The determined shape of the fastening structure is used to create data for fabricating each structure that makes up the fastening structure in order to manufacture such a fastening structure.

[0125] For fastening structures having a DfAM shape at the fastening portion, the dimensions and shape of characteristic points such as outer diameter, length, and roundness are measured by the measuring device 16. For the fastening structure and the structure to be fastened, the dimensions and shape of characteristic points such as plate thickness and hole shape at the fastening location are measured by the measuring device 16. After measuring each, the fastening structure is fastened to the structure to be fastened, and the fastening performance such as the force required at fastening, the shear force after fastening, and the tensile force after fastening is measured.

[0126] By repeatedly performing such measurements and fastenings, it is possible to establish a correlation between the characteristic features of the fastening structure and the structure to be fastened and the fastening performance. This correlation is stored along with the data for creating the fastening structure, and by inputting the fastening conditions (fastening performance) for fastening with the structure to be fastened, it is possible to extract a fastening structure suitable for the structure to be fastened from the stored correlation. As a result, even if the fastening point of the structure to be fastened is irregularly shaped, for example, not a perfect circle but deformed, it is possible to create a fastening structure that can adapt to that condition without discarding the structure.

[0127] Here, referring to Figure 30, we will describe a blind rivet, which is an example of a fastening structure. As shown in Figures 30(a) and (b), a hole 51 is made in the metal plate 50 to be fastened using a drill 52 or the like. The size of the drilled hole 51 and the thickness of the metal plate 50 are measured. The rivet diameter and length are determined from the size of the hole 51 and the thickness of the metal plate 50. The rivet 53 has a flange 54 and a shaft 55.

[0128] As shown in Figure 30(c), when fastening by inserting a rivet into a hole 51 made in a metal plate 50, a rivet 53 having a rivet diameter suitable for the hole 51 is selected, and the selected rivet 53 is inserted into the hole 51. As shown in Figure 30(d), the shaft 55 of the rivet 53 inserted into the hole 51 is pulled out by the riveter 56. As a result of this pulling out, as shown in Figure 30(e), the head 57 of the shaft 55 enters the cylindrical structure 58 surrounding it, the cylindrical body 58 expands in the outward direction, and the shaft 55 is cut and pulled out, leaving the head 57 inside the cylindrical body 58.

[0129] Figure 31 shows a blind rivet with a fastening portion 59 manufactured in a DfAM shape, fastened to a metal plate 50. Figure 31(a) shows the state when a normal rivet is fastened, and Figures 31(b) and (c) show the state when a rivet with a DfAM shape is fastened to a deformed hole. The rivet 53 is inserted diagonally into the hole 51, but the fastening portion 59 with a DfAM shape deforms to conform to the shape of the hole 51, and fastens in accordance with the fastening conditions. If the fastening portion 59 is not in a DfAM shape, it would not be possible to fasten it with a strength greater than the predetermined strength required for fastening. However, by making the fastening portion 59 in a DfAM shape, it can deform to match the shape of the hole 51 and fasten it in close contact with the hole 51, making it possible to obtain a fastening force greater than the predetermined strength.

[0130] Figure 32 illustrates a spring-loaded screw as another example of a fastening structure. The spring-loaded screw 60 shown in Figure 32 has an expanded head 61 and a rod-shaped insertion part 62. The insertion part 62 of the screw is inserted into a coiled spring 63, and the screw head 61 and spring 63 are integrated. The spring-loaded screw 60 is fastened to the plate 64, which is the structure to be fastened, by inserting the insertion part 62 so that the sharp tip of the insertion part 62 pierces the plate 64.

[0131] The spring 63 of the spring-loaded screw provides a reaction force between the screw and the plate 64 to prevent the screw from loosening. When fastening the spring-loaded screw to the plate, the joint between the screw head 61 and the spring 63 breaks, and the spring separates. The spring 63 then provides a reaction force in the direction that pulls the screw head 61 and the plate 64 apart, preventing the screw from loosening.

[0132] These blind rivets and spring-loaded screws can be designed by inputting necessary parameters such as the hole diameter and plate thickness of the structure to be fastened into the design tool, and then creating optimal data based on previously obtained measurement results.

[0133] Figure 33 illustrates a second method for determining which fastening structures have a lattice structure at the fastening portion, depending on the structure to be fastened. In the first method shown in Figure 29, the fastening structure is determined based on measurement results. It would be ideal if there were fastening structures with the same measurement results among the accumulated measurement results, but if not, it is not possible to determine the optimal fastening structure for fastening to that structure.

[0134] Therefore, by creating an estimation model from the correlation of accumulated measurement results, and using the created estimation model to accept input fastening conditions and run a simulation, it is possible to determine a fastening structure that conforms to the input fastening conditions. By running such a simulation, it becomes possible to propose a fastening structure that can also handle new fastening conditions, even if there are no matching examples in the past.

[0135] As explained above, structures that fall outside the acceptable range are usually discarded, but those that can be combined to ensure product quality can be effectively reused. This reduces the amount of discarded structures, improves yield, and contributes to cost reduction. Furthermore, since combinations that meet the set conditions are extracted, a certain level of quality can be ensured.

[0136] Although one embodiment of the present invention has been described so far, the present invention is not limited to the embodiments described above. The components of this embodiment can be changed or deleted, or other components can be added to the components of this embodiment, to the extent that a person skilled in the art can conceive of such modifications. Any embodiment that achieves the effects of the present invention is included within the scope of the present invention. [Explanation of Symbols]

[0137] 10... Molding device 11…Information Processing Devices 12...Drying device 13… Excess powder removal device 14…Degreasing and sintering equipment 15…Management device 16… Measuring device 17…Network 18… Processing equipment 20…CPU 21…ROM 22...RAM 23…HD 24…HDD controller 25…Display 26…External device connection interface 27…Network Interface 28...Data bus 29... Keyboard 30…Pointing device 31…DVD-RW drive 32…Media I / F 33…DVD-RW 34…Recording media 40…Acquisition method 41...Extraction means 42...Data retention means 43... Identification means 44...Arithmetic means 45…Input reception means 46…Distribution calculation means 47…Parameter determination means 50...Metal plate 51… Hole 52... Drill 53... Rivet 54…Flange 55... Shaft 56... Riveter 57...Head 58…Cylindrical body 59…Fastening part 60...Spring-loaded screw 61...Head 62... Insertion part 63... Spring 64...board 70...Data storage unit 71…Judgment section 72…CAM / CAD 73…Manufacturing Department 74…UI 75…FAN 76... Heater 77...Measuring part 78…Quality Data Processing Section 80...Data storage means 81…Learning methods 82...Estimation means [Prior art documents] [Patent Documents]

[0138] [Patent Document 1] Japanese Patent Publication No. 2017-087718

Claims

1. A management device for managing a plurality of structures, including at least a first structure and a plurality of second structures formed by a molding device, The system includes an extraction means for extracting combinations of two or more structures from among the aforementioned plurality of structures based on the shape information of the structures, The extraction means is a control device that extracts from a plurality of second structures a second structure to be combined with the first structure to satisfy the quality of the product when manufacturing the product by combining the first structure and the second structure.

2. A management device for managing multiple structures, including at least one object created by a molding device, An extraction means for extracting combinations of two or more structures from among the aforementioned plurality of structures based on the shape information of the structures, From the measuring device that measures the structure, an acquisition means for acquiring the measurement results of the measuring device as shape information. A control device, including a management device.

3. Includes data holding means for holding the measurement results, The management device according to claim 2, wherein the extraction means extracts combinations of the two or more structures based on the measurement results held by the data holding means.

4. Includes identification means for identifying each of the aforementioned plurality of structures, The management device according to claim 2, wherein the acquisition means acquires the measurement results obtained by measuring the structure identified by the identification means using a measuring device, together with the identification information used to identify the structure.

5. The system includes a determination means for determining whether the structure meets predetermined standards based on the measurement results, The management device according to claim 4, wherein the determination means instructs a change in the molding area based on the accumulated determination results for each of the structures.

6. The management device according to claim 5, wherein the determination means instructs the system that creates the modeling data to exclude from the modeling area any modeling area in which a structure that the determination means has determined does not meet the predetermined criteria has been modeled.

7. The management device according to claim 5, wherein the determination means instructs the display unit of the molding device to display the molding area in which a structure that it has determined does not meet the predetermined criteria has been molded as being outside the molding area.

8. The system includes a determination means for determining whether the structure meets predetermined standards based on the measurement results, The management device according to claim 4, wherein the determination means determines whether or not to perform maintenance on the production system including the molding apparatus based on the accumulated determination results for each of the structures.

9. The system includes a determination means for determining whether the structure meets predetermined standards based on the measurement results, The management device according to claim 4, wherein the determination means determines an area in which a high-performance structure can be manufactured based on the accumulated determination results for each of the structures.

10. A determination means for determining whether the structure meets predetermined standards based on the measurement results, A quality data processing means for collecting measurement results as quality data for unnecessary structures that are determined not to meet the predetermined standards. The control device according to claim 4, including the following:

11. The management device according to claim 4, wherein the identification means identifies a structure that has been formed by the molding device and then sintered by the sintering device.

12. The management device according to claim 4, wherein the extraction means extracts combinations of first structures and second structures that meet predetermined conditions based on information of one or more feature points included in the measurement results of each of the plurality of first structures and plurality of second structures.

13. Distribution calculation means for calculating the distribution of one or more feature points included in the measurement results of the first structure among the plurality of structures, A parameter determination means for optimizing the parameters used by the production system, including the molding apparatus, to manufacture the structure, so as to fit the distribution of one or more feature points of the second structure to the calculated distribution. The control device according to claim 12, including the following:

14. The management device according to claim 13, wherein the distribution calculation means uses information of one or more feature points included in either the measurement result of measuring the first structure formed by the molding apparatus, or the measurement result of measuring the first structure that has been formed by the molding apparatus and then sintered by the sintering apparatus.

15. Distribution calculation means for calculating the distribution of one or more feature points included in the measurement results of the first structure among the plurality of structures, A calculation means for optimizing the modeling data used by the modeling apparatus to model the second structure so that the distribution of one or more feature points of the second structure is fitted to the calculated distribution, The control device according to claim 12, including the following:

16. The management device according to claim 15, wherein the distribution calculation means uses information of one or more feature points included in either the measurement result of measuring the first structure formed by the molding apparatus, or the measurement result of measuring the first structure that has been formed by the molding apparatus and then sintered by the sintering apparatus.

17. The management device according to claim 12, wherein the extraction means extracts the combination using information of one or more feature points included as the measurement result of measuring a structure fabricated by the fabrication device, or a structure fabricated by the fabrication device and then sintered by a sintering device.

18. Includes calculation means for performing a simulation of the molding process of the molding apparatus, The management device according to claim 2, wherein the extraction means extracts a combination of a first structure and a second structure that conforms to predetermined conditions based on the simulation results of the calculation means.

19. The management device according to claim 18, wherein the calculation means collects measurement results of a plurality of fabricated structures and measurement results of a plurality of structures that have been sintered after fabrication, and performs the simulation based on the collected measurement results.

20. When manufacturing a fastening structure as a product by combining the first structure and the second structure, at least a part of the fastening structure is made into a lattice structure, and a data holding means holds a plurality of fastening information that associates fastening structure measurement results obtained by measuring one or more characteristic points of the portion of the fastening structure having the lattice structure, fastening target structure measurement results obtained by measuring one or more characteristic points of the fastening location that abuts the portion of the fastening target structure having the lattice structure with the fastening structure, and fastening measurement results obtained by measuring at least the strength after fastening the fastening structure and the fastening target structure, A calculation means that determines which fastening structure to be fastened to the input fastening target structure based on the plurality of fastening information and the measurement results of one or more characteristic points of the fastening locations of the input fastening target structure. The control device according to claim 12, including the following:

21. The management device according to claim 20, wherein the calculation means determines a fastening structure to be fastened to the input fastening target structure based on the plurality of fastening information, the measurement results of one or more characteristic points of the fastening locations of the input fastening target structure, and the input fastening conditions.

22. A production system comprising a molding apparatus for molding objects, and a management apparatus according to any one of claims 1 to 21 for managing information relating to combinations of two or more structures among a plurality of structures, which include at least a first structure and a plurality of second structures, formed by the molding apparatus.

23. The production system according to claim 22, further comprising an output device that outputs information relating to the combination of the two or more structures managed by the management device.

24. A method for extracting combinations of two or more structures using a computer, A step of extracting combinations of two or more structures from among a plurality of structures, which include at least one first structure and a plurality of second structures fabricated by a molding device, based on the shape information of the structures. Includes, A method for extracting, in the extraction step, a second structure to be combined with the first structure to satisfy the quality of the product when the first structure and the second structure are combined to manufacture the product, from among the plurality of second structures.

25. A program for causing a computer to perform steps included in the method according to claim 24.

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