Product manufacturing method, manufacturing system and repair analysis device

Abstract

To allow used components to be appropriately combined, repaired, and used for re-manufacturing a product.SOLUTION: A method for manufacturing a product including a reproduced component obtained by combining at least two used components includes: a step of acquiring shape data of a plurality of used components: a combination selection step of selecting a combination satisfying a prescribed combination condition from the plurality of used components on the basis of the shape data of the plurality of used components; a first repair analysis step of, on the basis of shape data of a plurality of used components constituting the selected combination, specifying repair positions and repair amounts of the used components; and a repair instruction step of giving an instruction to repair the used components on the basis of the specified repair positions and repair amounts.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a product manufacturing method, a manufacturing system, and a repair analysis device. [Background technology]

[0002] Currently, in order to address the social challenges of reducing environmental impact, resource constraints, and labor shortages, the shift to a circular economy that promotes resource circulation is accelerating. In arterial industries (manufacturing and sales), business models are shifting from the traditional one-time sale model to a service model. In venous industries (collection and regeneration), in addition to traditional recycling, services such as remanufacturing, reuse, and repair, which have a lower environmental impact, are becoming more important, and there is a demand for effective use of limited resources.

[0003] Among the above-mentioned service initiatives in the venous industry, remanufacturing (hereafter referred to as "remanufacturing") poses challenges in ensuring the stable collection of parts to be used in remanufacturing and a stable supply to rebuilders. It is necessary to minimize the number of parts that are discarded after collection and not used for remanufacturing, and to use them for remanufacturing. Reasons why collected used parts are discarded include not meeting the specified number of times they can be used for remanufacturing, or not meeting the standards for new parts when repaired individually, and so are removed. To reduce waste, it is considered effective to consider the combination of parts to be assembled and select parts with good assembly conditions to assemble them, thereby ensuring final performance.

[0004] For example, Patent Document 1 discloses a method for manufacturing a product in which a first part and a second part to be put into product assembly are inspected to obtain information on the characteristics of each part, and inspection information for products that pass the product inspection is used to obtain information on the affinity of the characteristics between the parts, and the combination of the first part and the second part is determined using the information on affinity. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-217982 Summary of the Invention [Problem to be solved by the invention]

[0006] The method shown in Patent Document 1 is a manufacturing method or assembly method for a product using new parts, and does not take into consideration the repair of used parts, which is necessary when utilizing recovered products (i.e., used parts).

[0007] The present invention has been made in view of the above points, and has an object to make it possible to appropriately combine and repair used parts so that they can be used for the remanufacturing of products. [Means for solving the problem]

[0008] The present application includes a number of means for solving at least part of the above problems, examples of which are as follows.

[0009] One aspect of the present invention is a manufacturing method for a product including a recycled part that is a combination of at least two used parts, the method including: a step of acquiring shape data for a plurality of used parts; a combination selection step of selecting a combination that satisfies predetermined combination conditions from a plurality of used parts based on the shape data for the plurality of used parts; a first repair analysis step of identifying repair positions and repair amounts for the used parts based on the shape data for the plurality of used parts that make up the combination; and a repair instruction step of instructing repair of the used parts based on the identified repair positions and repair amounts.

[0010] Another aspect of the present invention is a manufacturing system for a product including a remanufactured part that is a combination of at least two used parts, the system comprising a computer that executes the steps of acquiring shape data for a plurality of used parts, a combination selection step of selecting a combination that satisfies predetermined combination conditions from a plurality of used parts based on the shape data for the plurality of used parts, a first repair analysis step of identifying the repair position and repair amount for the used parts based on the shape data for the plurality of used parts that make up the combination, and a repair instruction step of instructing repair of the used parts based on the identified repair position and repair amount.

[0011] Yet another aspect of the present invention is a repair analysis device for a product including a remanufactured part that is a combination of at least two used parts, the device comprising a processor, wherein the processor executes the following steps: acquiring shape data for a plurality of used parts; a combination selection step of selecting a combination that satisfies predetermined combination conditions from a plurality of used parts based on the shape data for the plurality of used parts; a first repair analysis step of identifying a repair position and repair amount for the used parts based on the shape data for the plurality of used parts that make up the combination; and a repair instruction step of instructing repair of the used parts based on the identified repair position and repair amount. [Effects of the Invention]

[0012] According to the present invention, used parts can be appropriately combined, repaired, and used to remanufacture products.

[0013] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0014] [Figure 1] 1A to 1C are schematic diagrams illustrating an example of a method for manufacturing a product according to an embodiment of the present invention. [Figure 2] 1 is a block diagram illustrating an example of a functional configuration of a repair analysis system according to an embodiment of the present invention. [Figure 3] FIG. 2 is a block diagram illustrating an example of a hardware configuration of a repair analysis system. [Figure 4] 10 is a flowchart illustrating an example of processing by the repair analysis system. [Figure 5] FIG. 10 is an explanatory diagram showing an example of the shape state of a used part. [Figure 6] FIG. 6 is an explanatory diagram showing an example in which each shape state shown in FIG. 5 is mapped onto a feature space. [Figure 7] FIG. 10 is an explanatory diagram showing an example of a combination selection of used parts and an analysis by virtual assembly. DETAILED DESCRIPTION OF THE INVENTION

[0015] An embodiment of the present invention will be described below with reference to the drawings. In all drawings used to describe the embodiment, the same components are generally designated by the same reference numerals, and repeated description thereof will be omitted where appropriate. It goes without saying that, in the following embodiments, the components (including element steps, etc.) are not necessarily essential unless otherwise specified or considered to be fundamentally essential. It goes without saying that, except when specifically specified to include only a particular element, other elements are not excluded. Similarly, in the following embodiments, when referring to the shape, positional relationship, etc. of a component, etc., it includes those that are substantially similar or similar to that shape, etc., unless otherwise specified or considered to be fundamentally essential.

[0016] FIG. 1 is a schematic diagram showing an example of a product manufacturing method (including a remanufacturing method) according to one embodiment of the present invention. Processes K101 to K106 in the upper row correspond to the flow of manufacturing a product using new parts. The combination of processes K107 to K111 in the lower row and processes K101 to K106 in the upper row corresponds to the flow of remanufacturing a product using reused parts. This embodiment can be applied to a manufacturing system that remanufactures a product that includes at least one recycled part that is made up of a combination of at least two used parts.

[0017] In the manufacture of a product, the parts that make up the product are processed according to the design drawings (process K101), the processed parts are inspected to see if their dimensions and other characteristics are within specifications (process K102), parts that pass inspection are sent to the product assembly process (process K103), two or more component parts are assembled into a product and adjusted (process K104), the product is inspected to see if it meets the performance specifications (process K105), and the product that meets the product specifications is shipped (process K106).

[0018] In product remanufacturing, shipped products are collected after use (step K107), the collected products are disassembled into their component parts (step K108), the shape of each component part (i.e., used parts) is inspected (step K109), the combination of used parts to be used in the product and repairs are analyzed (step K110), and the used parts are repaired according to the results of the repair analysis (step K111). The repaired used parts undergo part inspection (step K102) and are then input into the product assembly process (step K103), where the product is assembled according to the combination of parts selected based on the results of the analysis of the combination of used parts (step K110) (step K104).

[0019] Next, a repair analysis system according to one embodiment of the present invention will be described, which is used in the above-described lower steps K107 to K111. The repair analysis system is used to realize part of the above-described manufacturing method and manufacturing system.

[0020] 2 is a block diagram showing an example of the functional configuration of a repair analysis system according to one embodiment of the present invention. The repair analysis system 500 includes a three-dimensional shape measuring device 501, a data storage unit 502, a repair analysis unit 503 (second repair analysis unit), a part combination selection unit 504, a repair analysis unit 505 (first repair analysis unit), a performance prediction unit 506, a repair method selection unit 507, a repair instruction unit 508, and a repair device 509.

[0021] The three-dimensional shape measuring device 501 is, for example, a 3D scanner. In the inspection process (process K109), the three-dimensional shape measuring device 501 scans each used part to generate three-dimensional shape data (CAD data, etc.), and outputs inspection data including the shape data to the data storage unit 502.

[0022] Data storage unit 502 acquires and stores shape data of each used part output from three-dimensional shape measuring device 501 (part inspection data 527 in FIG. 3). Data storage unit 502 also acquires design data including three-dimensional shape data of each used part at the time of initial manufacturing from an external device such as a database and stores the data, or stores the data in advance (part design data 526 in FIG. 3).

[0023] The repair analysis unit 503 reads out the inspection data and design data for each used part from the data storage unit 502, and compares the three-dimensional shape data contained in these data to identify the shape differences as the repair position and repair amount.

[0024] The component combination selection unit 504 selects a combination that satisfies a predetermined combination condition from among a plurality of used parts based on the inspection data of each used part. For example, the component combination selection unit 504 classifies a plurality of used parts into a plurality of shape clusters based on their shape states, and selects a combination of used parts in accordance with a predetermined combination condition that indicates an appropriate combination of the plurality of shape clusters. The processing of the component combination selection unit 504 will be described in detail later (FIGS. 5 to 7).

[0025] The repair analysis unit 505 identifies the gap position and gap amount that will occur when each used part is combined with other used parts in the combination selected by the part combination selection unit 504. The repair analysis unit 505 also identifies the repair position and repair amount so that the gap amount at the identified gap position will satisfy a predetermined appropriate value (such as an appropriate dimensional range in the design data) after repair. Data regarding the appropriate value may be included in the design data. The repair analysis unit 505 may execute processing by software simulation (virtual assembly) using three-dimensional shape data. The processing of the repair analysis unit 505 will be described in detail later ( FIG. 7 ).

[0026] The performance prediction unit 506 executes performance prediction of a remanufactured part configured including the combination of used parts selected by the part combination selection unit 504, or a remanufactured product manufactured including the remanufactured parts. The performance prediction unit 506 executes processing by software simulation (virtual assembly, operation analysis) using three-dimensional shape data of each part. The processing of the performance prediction unit 506 will be described in detail later.

[0027] The repair method selection unit 507 determines whether or not each used part needs repair. For example, the repair method selection unit 507 determines whether or not the shape difference (repair position and repair amount) identified by the repair analysis unit 503, i.e., the current shape state, satisfies predetermined shape standards (such as appropriate dimensional ranges in design data). Data related to the standards may be included in the design data.

[0028] Furthermore, if the repair method selection unit 507 determines that the used part requires repair, it compares the repair amount identified by the repair analysis unit 503 with the repair amount identified by the repair analysis unit 505 to determine which is smaller. The repair method selection unit 507 selects the repair position and repair amount corresponding to the smaller repair amount as the repair method to be adopted for the used part.

[0029] The repair instruction unit 508 outputs, for each used part, a repair instruction based on the repair method selected by the repair method selection unit 507. The repair instruction unit 508 outputs, for example, the identification information of the used part, the repair position and the repair amount, together with the identification information of the used part, to the repair device 509, or to a display or terminal device used by the repair worker. For each used part, the repair instruction unit 508 may also output the identification information of other used parts that are combined with the used part, as well as the repair position and the repair amount.

[0030] The repair device 509 is, for example, one or more machine tools such as a welding device, a cutting device, a 3D printer, etc., for repairing portions that have been worn down due to wear or deformation. The repair device 509 repairs each used product according to the repair position and repair amount output from the repair instruction unit 508.

[0031] 3 is a block diagram showing an example of the hardware configuration of a repair analysis system. The repair analysis system 500 is realized using a general computer 510 (corresponding to a repair analysis device) such as a PC (Personal Computer). However, it may also be realized using multiple computers, a cloud system, or the like.

[0032] The computer 510 has a configuration in which a processor 511, a main memory device 512, an auxiliary memory I / F (Interface) 513, a network I / F 514, an input / output I / F 515, and the like are connected via a bus.

[0033] The processor 511 is a processor such as a CPU (Central Processing Unit), which controls each part of the repair analysis system 500 and executes each program read into the main memory device 512. The processor 511 is not limited to a CPU, and may be any other semiconductor device that executes predetermined processing. Examples of semiconductor devices include an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), and a CPLD (Complex Programmable Logic Device).

[0034] The main storage device 512 is typically configured with a volatile memory such as a RAM, and stores programs executed by the processor 511, data to be referenced, and data calculated by the processor 511.

[0035] The auxiliary storage I / F 513 is an interface for connecting an auxiliary storage device 519 such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The auxiliary storage device 519 has a large storage capacity and stores OS (Operating System) software, programs for executing this embodiment, such as a repair analysis program 520, a component combination selection program 521, a repair analysis program 522, a performance prediction program 523, a repair method selection program 524, and a repair instruction program 525, and information necessary for executing each program, such as component design data 526 and component inspection data 527.

[0036] The repair analysis program 520, the parts combination selection program 521, the repair analysis program 522, the performance prediction program 523, the repair method selection program 524, and the repair instruction program 525 are programs that respectively realize the functions of the repair analysis unit 503, the parts combination selection unit 504, the repair analysis unit 505, the performance prediction unit 506, the repair method selection unit 507, and the repair instruction unit 508 in Fig. 2. The data storage unit 502 is realized by at least one of the main memory device 512 and the auxiliary memory device 519.

[0037] Each program may be installed on the computer 510 from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server may include a processor and storage resources for storing the programs to be distributed, and the processor of the program distribution server may distribute the programs to be distributed to other computers. Furthermore, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0038] The network I / F 514 is an interface for connecting the computer 510 to external devices via a network. The computer 510 is connected to the three-dimensional shape measuring device 501 and the repair device 509 via a router / hub 516, either wired or wirelessly.

[0039] The input / output I / F 515 is an interface for connecting an input device 517 such as a keyboard or mouse for inputting input data to the computer 510 , and an output device 518 such as a display for outputting output data from the computer 510 .

[0040] Next, an example of the processing of the repair analysis system will be described.

[0041] Fig. 4 is a flowchart showing an example of processing by the repair analysis system. For easy understanding, Fig. 4 shows the processing (steps S201 to S208) executed by the repair analysis system 500, as well as the steps before and after these steps (K107 to K109 and K111; see Fig. 1). Steps S201 to S208 correspond to step K110 in Fig. 1.

[0042] The shipped products are collected after use (step K107), each collected product is disassembled into its component parts (step K108), and the shape state of each component part (i.e., used part) is inspected (step K109). The three-dimensional shape data of each used part acquired by the three-dimensional shape measuring device 501 during the inspection is stored in the data storage unit 502 as inspection data.

[0043] Next, the repair position and repair amount are calculated for each used part (step S201). Specifically, the repair analysis unit 503 reads and acquires the inspection data and design data for each used part from the data storage unit 502, and compares the three-dimensional shape data contained in these data to identify the difference in shape as the repair position and repair amount.

[0044] Next, it is determined whether each used part requires repair (step S202). Specifically, the repair method selection unit 507 determines whether the shape difference (repair position and repair amount) identified in step S201, i.e., the current shape state, satisfies predetermined shape standards (such as dimensional error from design data). For used parts that do not require repair (NO in step S202), the processing of this flowchart ends.

[0045] For each used part that requires repair (YES in step S202), classification is performed (step S203), and a combination is selected (step S204). Specifically, the part combination selection unit 504 classifies each used part into a plurality of shape clusters based on its shape state. The part combination selection unit 504 also selects a combination of each used part based on predetermined combination conditions that indicate an appropriate combination of the plurality of shape clusters.

[0046] Next, gap analysis is performed for each combined used part (step S205). Specifically, the repair analysis unit 505 uses virtual assembly to identify the position and amount of gaps that will occur when each used part is combined with other used parts in the combination selected in step S204.

[0047] Next, the repair position and repair amount are calculated for each used part (step S206). Specifically, the repair analysis unit 505 uses virtual assembly to identify the repair position and repair amount for each used part so that the gap amount at the gap position identified in step S205 satisfies a predetermined appropriate value (such as an appropriate dimensional range in the design data) after repair.

[0048] Next, for each used part, the repair amounts are compared and a repair method is selected (step S207). Specifically, for each used part, the repair method selection unit 507 compares the total repair amount identified in step S201 with the total repair amount identified in step S206 and determines which is smaller. Then, the repair method selection unit 507 selects the repair position and repair amount corresponding to the smaller repair amount as the repair method to be adopted for that used part.

[0049] Next, repair instructions for each used part are output (step S208). Specifically, the repair instruction unit 508 outputs repair instructions for each used part based on the repair method selected in step S207. The repair instruction unit 508, for example, outputs the identification information of the used part together with the repair position and repair amount to the repair device 509 or to a display or terminal device used by the repair worker. For each used part, the repair instruction unit 508 may also output the identification information of other used parts that are combined with the used part, as well as the repair position and repair amount.

[0050] In accordance with the repair instructions in step S208, each used part is repaired (step K111), and the processing of this flowchart ends.

[0051] In this embodiment, in step S207, the repair amount is compared to select the repair method with the least amount of repair, but it is also possible to omit the comparison of repair amount and select a repair method that takes combination into consideration (step S206). In this way, it is possible to always adopt a repair method that takes combination into consideration.

[0052] The processing of steps S203 to S206 will be described in detail with reference to FIGS. 5 to 7, taking a rotor part of a screw compressor as an example.

[0053] Fig. 5 is an explanatory diagram showing an example of the shape state of used parts. Fig. 6 is an explanatory diagram showing an example of mapping each shape state shown in Fig. 5 onto a feature space. Fig. 7 is an explanatory diagram showing an example of combination selection of used parts and analysis by virtual assembly.

[0054] A screw compressor is a machine that compresses gas by rotating a pair of spiral-shaped parts called male and female screw rotors (hereinafter referred to as "rotors") in contact with each other. Gas drawn in through the suction port is trapped between the tooth space of the pair of rotors and the casing, compressed to a predetermined pressure by the rotation of the intermeshing teeth of the pair of rotors, and then forced out through the discharge port. The pair of rotors undergo deformation due to wear (hereinafter simply referred to as deformation) as they rotate in contact with each other, and so are used parts that can be subject to repair when used in the remanufacturing of screw compressors.

[0055] Consider the case where the shapes of used rotors are broadly classified into tapered shapes 301 where the periphery of one end face is significantly deformed, convex shapes 302 where the peripheries of both end faces are significantly deformed, and concave shapes 303 where the center is significantly deformed, as shown in Figure 5. In this case, with the center position of the rotor as the origin, the following equation (1), which is a polynomial of degree 2, can be fitted to the tooth positions in the three-dimensional shape data of the inspection data for each rotor, and the parameter coefficients (a, b, and c) of the variables of each degree of fitting function 304 for each rotor can be calculated.

[0056]

number

[0057] The degree 2 polynomial can be transformed into the following equation (2). In this case, parameter coefficient A indicates the uneven state (indicating concave or convex) of the deformed part, which is the difference compared to the design shape, and the characteristics of the deformation amount of the uneven shape. Parameter coefficient B indicates the characteristics of the deviation amount of the position of the uneven shape in the rotor rotation axis direction. Parameter coefficient C indicates the characteristics of the deviation amount of the position of the uneven shape in the direction perpendicular to the rotor rotation axis.

[0058]

number

[0059] Each used rotor is mapped based on the feature quantities A to C in a three-dimensional feature quantity space with the parameter coefficients A to C as the axes (FIG. 6). A common data grouping (clustering) technique is then applied to each mapping data, allowing each used rotor to be classified into multiple clusters 305, 306, and 307 with similar shape conditions. While a degree-2 polynomial was used as the fitting function in the above description, feature quantities for more complex shapes can be calculated by increasing the degree of the polynomial. In this way, the component combination selection unit 504 can classify each used part into multiple shape clusters based on its shape condition. More simply, classification may be performed based on one- or two-dimensional feature quantities, which are less than three dimensions.

[0060] Furthermore, the component combination selection unit 504 searches for and selects a combination of used rotors from clusters 305, 306, and 307 that have good rotor meshing compatibility. For example, as shown in the right of FIG. 7, a rotor (concave shape) and a rotor (convex shape) have good meshing compatibility, and as shown in the left of FIG. 7, a rotor (tapered shape) has good meshing compatibility. By predefining the combination of clusters, it is possible to select a combination of used rotors that have good compatibility. In addition to or instead of the combination of clusters, a combination that is likely to have a better fit in the contour shape may be identified based on rotor features, such as the amount of deformation of the concave-convex shape or the amount of misalignment between the convex and concave shapes. For example, rotors with similar amounts of concave-convex deformation or similar amounts of misalignment between the convex and concave shapes have good meshing compatibility.

[0061] The repair analysis unit 505 performs virtual assembly for each used rotor using the three-dimensional shape data of the inspection data of that used rotor and the three-dimensional shape data of the inspection data of other used rotors selected to be paired with that rotor. Then, while rotating each rotor, the repair analysis unit 505 identifies the gap positions and gap amounts at the tooth meshing portion 400 ( FIG. 7 ) of the combined male and female rotors over the entire rotation angle. The repair analysis unit 505 also identifies the repair positions and repair amounts for each male and female rotor so that the gap amounts at the identified gap positions fall within a predetermined appropriate value range after repair over the entire rotation angle. This makes it possible to identify a repair method that will allow the used part to satisfy its performance specifications after repair.

[0062] The performance prediction unit 506 performs a fluid analysis of the gas to be compressed using, as parameters, the gap position and gap amount at the meshing portion of the male and female rotor teeth when repaired using the repair position and repair amount specified as above, thereby making a performance prediction regarding the amount of power converted into fluid energy, such as the discharge pressure and efficiency of a remanufactured part using the repaired male and female rotors or a screw compressor using the remanufactured part. The performance prediction unit 506 may output the performance prediction results for the used part to the output device 518 or another device. In this way, the results can be used as a reference, for example, when reusing the used product to manufacture a new product.

[0063] In step S207, the repair method selection unit 507 may obtain the performance prediction result for the used part by the performance prediction unit 506 and determine whether the performance prediction result satisfies predetermined performance specifications. If the performance specifications are not satisfied, the repair method selection unit 507 can exclude the used part from the repair target. In this way, used parts that may not satisfy the performance specifications of remanufactured products even if repaired and reused can be sent to another process, such as disposal, without being reused.

[0064] Although an example of a rotor part for a screw compressor has been described above, it goes without saying that this embodiment can be applied to machine element parts that function when combined with each other. In addition to rotors, other parts such as gears and screws can be considered. It goes without saying that this embodiment can also be applied to combinations of three or more parts, not limited to combinations of two parts.

[0065] An embodiment of the present invention has been described above. According to this embodiment, a compatible combination of used parts and the repair amount for that combination are determined. As a result, used parts can be appropriately combined and repaired so that they can be used to remanufacture products that meet required performance specifications. Furthermore, by selecting a repair method that requires less repair, repair costs can be reduced. By adopting the manufacturing method according to this embodiment, not only can the number of used parts that are discarded without repair be reduced, but energy consumption in remanufacturing can also be reduced, resulting in high efficiency and low costs.

[0066] The present invention is not limited to the above-described embodiments, and various modifications are possible. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with or add to the configuration of another embodiment. [Explanation of symbols]

[0067] 301 Tapered shape, 302 Convex shape, 303 Concave shape, 304 Fitting function, 305 Cluster, 306 Cluster, 307 Cluster, 400 Meshing portion, 500 Repair analysis system, 501 Three-dimensional shape measuring device, 502 Data storage unit, 503 Repair analysis unit, 504 Part combination selection unit, 505 Repair analysis unit, 506 Performance prediction unit, 507 Repair method selection unit, 508 Repair instruction unit, 509 Repair device, 510 Computer, 511 Processor, 512 Main memory device, 513 Auxiliary memory I / F, 514 Network I / F, 515 Input / output I / F, 516 Router / hub, 517 Input device, 518 Output device, 519 Auxiliary memory device, 520 Repair analysis program, 521 Part combination selection program, 522 Repair analysis program, 523 performance prediction program, 524 repair method selection program, 525 repair instruction program, 526 part design data, 527 part inspection data

Claims

1. A method for manufacturing a product including a remanufactured part that combines at least two used parts, comprising: acquiring shape data of a plurality of used parts; a combination selection step of selecting a combination that satisfies a predetermined combination condition from among the plurality of used parts based on the shape data of the plurality of used parts; a first repair analysis step of identifying a repair position and a repair amount of the used part based on shape data of the plurality of used parts that constitute the combination; a repair instruction step of instructing repair of the used part based on the identified repair position and repair amount; A method for manufacturing a product, including:

2. 10. A method for producing the product of claim 1, comprising: a second repair analysis step of identifying a repair position and a repair amount for each used part based on a difference between shape data of the used part and corresponding design data; a repair method selection step of comparing the repair amount identified in the first repair analysis step with the repair amount determined in the second repair analysis step, and selecting the repair position and the repair amount corresponding to the smaller one; The repair instruction step instructs repair of the used part based on the repair position and the repair amount selected in the repair method selection step. A method for manufacturing a product, including:

3. 10. A method for producing the product of claim 1, comprising: In the combination selection step, the plurality of used parts are classified into a plurality of shape clusters, and a combination of the used parts is selected based on the combination conditions indicating a combination of the plurality of shape clusters. How the product is manufactured.

4. A method for producing the product according to claim 3 In the combination selection step, the used parts are classified based on at least one of the characteristics of the deformation amount and the position of the deformed portion, which is a difference compared with the shape at the time of design. How the product is manufactured.

5. 10. A method for producing the product of claim 1, comprising: In the first repair analysis step, a plurality of the used parts constituting the combination are assembled by software simulation, and the repair position and the repair amount are identified based on the gap positions and gap amounts between the plurality of the used parts. How the product is manufactured.

6. A method for producing the product of claim 5, comprising the steps of: a performance prediction step of predicting the performance of a remanufactured part or a product using the remanufactured part, which is made using a combination of the used parts that have been repaired at the specified repair position and with the specified repair amount, by software simulation; A method for manufacturing a product, including:

7. A method for producing the product of claim 6, comprising the steps of: a repair method selection step of determining whether the performance predicted in the performance prediction step satisfies predetermined performance specifications, and if the performance does not satisfy the specifications, excluding the used part from the list of repair targets; A method for manufacturing a product, including:

8. A manufacturing system for a product including a remanufactured part that combines at least two used parts, acquiring shape data of a plurality of used parts; a combination selection step of selecting a combination that satisfies a predetermined combination condition from among the plurality of used parts based on the shape data of the plurality of used parts; a first repair analysis step of identifying a repair position and a repair amount of the used part based on shape data of the plurality of used parts that constitute the combination; a repair instruction step of instructing repair of the used part based on the identified repair position and repair amount; A product manufacturing system comprising a computer that executes the above.

9. 9. A system for manufacturing a product according to claim 8, The computer a second repair analysis step of identifying a repair position and a repair amount for each used part based on a difference between shape data of the used part and corresponding design data; a repair method selection step of comparing the repair amount identified in the first repair analysis step with the repair amount determined in the second repair analysis step, and selecting the repair position and the repair amount corresponding to the smaller one; In the repair instruction step, a repair of the used part is instructed based on the repair position and the repair amount selected in the repair method selection step. Product manufacturing system.

10. 9. A system for manufacturing a product according to claim 8, In the combination selection step, the used parts are classified into a plurality of shape clusters, and a combination of the used parts is selected based on the combination conditions indicating a combination of the plurality of shape clusters. Product manufacturing system.

11. A system for manufacturing a product according to claim 10, In the combination selection step, the used parts are classified based on at least one of the characteristics of the deformation amount and the position of the deformed portion, which is a difference compared with the shape at the time of design. Product manufacturing system.

12. 9. A system for manufacturing a product according to claim 8, In the first repair analysis step, a plurality of the used parts constituting the combination are assembled by software simulation, and the repair position and the repair amount are identified based on the gap positions and gap amounts between the plurality of the used parts. Product manufacturing system.

13. 13. A system for manufacturing a product according to claim 12, comprising: The computer a performance prediction step of predicting performance of a remanufactured part or a product using the remanufactured part, which uses a combination of the used parts repaired at the specified repair position and with the specified repair amount, by software simulation; A product manufacturing system that performs the above.

14. 14. A system for manufacturing a product according to claim 13, comprising: The computer a repair method selection step of determining whether the performance predicted in the performance prediction step satisfies predetermined performance specifications, and if the performance does not satisfy the specifications, excluding the used part from the list of repair targets; A product manufacturing system that performs the above.

15. A repair analysis device for a product including a remanufactured part that combines at least two used parts, the device comprising: a processor; The processor: acquiring shape data of a plurality of used parts; a combination selection step of selecting a combination that satisfies a predetermined combination condition from among the plurality of used parts based on the shape data of the plurality of used parts; a first repair analysis step of identifying a repair position and a repair amount of the used part based on shape data of the plurality of used parts that constitute the combination; a repair instruction step of instructing repair of the used part based on the identified repair position and repair amount; A repair analysis device that performs the following.

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