Selection support device and method, and program

Abstract

To provide a selection support device which can support a user to select an optimal processing method for a product.SOLUTION: A selection support device 2 comprises: a cutting estimation processing unit 253 which estimates a first manufacturing condition for a component which is an object of estimation, in cutting on the basis of design information data of a three-dimensional model of the component and data of information about the cutting; an additional manufacturing estimation processing unit 254 which estimates a second manufacturing condition for the component in additional manufacturing on the basis of the design information data of the three-dimensional model of the component and data of information about additional manufacturing; an estimation result comparison unit 255 which compares the first manufacturing condition with the second manufacturing condition to evaluate them; and a comparison result output unit 256 which outputs an evaluation result of the estimation result comparison unit 255 to present the same to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a selection assistance device, method, and program. [Background technology]

[0002] In recent years, the establishment of additive manufacturing technology, such as 3D printers, has enabled lower costs and shorter manufacturing times compared to machining, which removes unnecessary parts from materials. However, machining can achieve much higher precision in terms of product strength and surface accuracy than additive manufacturing. Therefore, it is desirable to use both methods appropriately depending on the product's intended use. One method for users to decide whether to manufacture a product using machining or additive manufacturing is to compare the manufacturing costs of both methods. For example, Patent Document 1 discloses a technology for calculating manufacturing costs based on design information read from data on a three-dimensional model created using three-dimensional computer-aided design (CAD). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-3698 Summary of the Invention [Problem to be solved by the invention]

[0004] However, because the technology disclosed in Patent Document 1 is intended to calculate manufacturing costs for cutting processes, it is difficult to accurately calculate manufacturing costs for additive manufacturing even if it is directly applied to additive manufacturing equipment. Furthermore, the technology disclosed in Patent Document 1 does not have a function for comparing multiple manufacturing costs using a unified comparison standard. Therefore, it is difficult for users to use the technology disclosed in Patent Document 1 to determine whether it is more appropriate to manufacture a product using cutting processes or additive manufacturing.

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a selection assistance device, method, and program that can assist users in selecting the optimal processing method for a product. [Means for solving the problem]

[0006] In order to achieve the above-mentioned object, the selection support device of the present disclosure includes a cutting processing estimation processing unit that estimates first manufacturing conditions for a part in cutting processing based on design information data of a three-dimensional model of the part to be estimated and information data related to cutting processing, an additive manufacturing estimation processing unit that estimates second manufacturing conditions for the part in additive manufacturing based on design information data of the three-dimensional model of the part and information data related to additive manufacturing, an estimation result comparison unit that compares and evaluates the first manufacturing conditions and the second manufacturing conditions, and a comparison result output unit that outputs the evaluation results evaluated by the estimation result comparison unit to present to a user. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to provide a selection support device that can estimate the manufacturing conditions for cutting and additive manufacturing from the design information data of a three-dimensional model and present the comparison results to the user, thereby assisting the user in selecting the optimal processing method for the product. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an overview of a selection support system including a selection support device according to an embodiment of the present disclosure. [Figure 2] FIG. 1 is a diagram showing an example of a hardware configuration of a selection support device according to an embodiment. [Figure 3A] FIG. 1 is a diagram showing an example of a three-dimensional model for cutting according to an embodiment; [Figure 3B] Cross-sectional view of the 3D model for cutting shown in Figure 3A. [Figure 3C] FIG. 1 illustrates an example of a three-dimensional model for additive manufacturing according to an embodiment. [Figure 3D] Cross-section of the 3D model for additive manufacturing shown in Figure 3C. [Figure 4A] FIG. 1 is a diagram showing a table of a cutting processing information database according to an embodiment. [Figure 4B] FIG. 1 shows a table of an additive manufacturing information database according to an embodiment. [Figure 5] FIG. 10 is a table showing comparison results according to an embodiment. [Figure 6A] Flowchart of selection support processing according to an embodiment [Figure 6B] Continuation of the selection support process shown in FIG. 6A [Figure 7] Flowchart of cutting work estimation process according to an embodiment [Figure 8] Flowchart of additive manufacturing estimation process according to an embodiment [Figure 9] Flowchart of quotation result comparison processing according to an embodiment DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, a selection support device 2 according to an embodiment of the present disclosure and a selection support system 100 including the selection support device 2 will be described with reference to the drawings. Note that the same or equivalent parts are denoted by the same reference numerals.

[0010] The selection support device 2 is a device that can estimate the manufacturing conditions for cutting and additive manufacturing, such as processing cost, delivery time, and difficulty, from the design information data of a three-dimensional model and present the comparison results to the user, thereby supporting the user in selecting the optimal processing method for the product. Furthermore, the selection support system 100 is a system that includes the selection support device 2. Note that, hereinafter, the additive manufacturing device will be described as a 3D printer.

[0011] 1 shows an overview of a selection support system 100. The selection support system 100 includes a three-dimensional model data storage unit 1 that stores design information data for parts to be manufactured, and a selection support device 2 that supports the selection of an optimal processing method for the parts to be manufactured. The three-dimensional model data storage unit 1 stores design information data for a three-dimensional model of the part that is the subject of an estimate.

[0012] The selection support device 2 includes a connection unit 21 for connecting external devices, an operation input unit 22 for receiving input from a user, a display unit 23 for displaying various data, a storage unit 24 for storing various data and programs, and a processing unit 25 for executing various processes. The connection unit 21 can connect to external devices, and in this embodiment, is connected to the three-dimensional model data storage unit 1. The operation input unit 22 inputs instructions and various data from the user. The display unit 23 displays the various data input by the user from the operation input unit 22, the contents of the instructions, the processing results processed by the processing unit 25, etc.

[0013] The storage unit 24 includes a selection support processing program 241 that executes processing to support the selection of the optimal processing method, a cutting processing information database 242 that stores information on cutting machines, and an additive manufacturing information database 243 that stores information on additive manufacturing devices. By executing the selection support processing program 241, it is possible to support the user in selecting the optimal processing method for the product. The cutting processing information database 242 stores information on all cutting machines that the user can use. The additive manufacturing information database 243 stores information on all additive manufacturing devices that the user can use.

[0014] The processing unit 25 executes various processes for supporting the user in selecting the optimal processing method for the product, which are executed by the selection support device 2. The processing unit 25 includes a data acquisition unit 251 that acquires various data, a design information processing unit 252 that processes design information data, a cutting processing estimate processing unit 253 that makes an estimate for cutting processing, an additive manufacturing estimate processing unit 254 that makes an estimate for additive manufacturing, an estimate result comparison unit 255 that compares estimate results, and a comparison result output unit 256 that outputs the comparison result to the display unit 23.

[0015] The data acquisition unit 251 acquires various data such as estimation conditions and information specified by the user, which are input from the operation input unit 22. The design information processing unit 252 acquires design information data of a three-dimensional model of a part that is the subject of an estimate from the three-dimensional model data storage unit 1 via the connection unit 21. The cutting work estimation processing unit 253 estimates the processing costs required for processing, estimates the delivery time until the target product is completed and delivered to the user, and determines the difficulty of the processing, based on the design information data of the three-dimensional model of the part that is the subject of an estimate acquired by the design information processing unit 252 and data on information related to cutting work stored in the cutting work information database 242.

[0016] The additive manufacturing estimate processing unit 254 estimates the processing costs required for processing, estimates the delivery time until the product is completed and delivered to the user, and determines the level of difficulty required for processing, based on the design information data of the three-dimensional model of the part that is the subject of the estimate obtained by the design information processing unit 252 and information about the additive manufacturing equipment stored in the additive manufacturing information database 243. The estimate result comparison unit 255 compares the estimate results from the cutting processing estimate processing unit 253 and the estimate results from the additive manufacturing estimate processing unit 254 to obtain a comparison result. The comparison result output unit 256 outputs the comparison result obtained by the estimate result comparison unit 255 to the display unit 23. This allows the user to check the comparison results and select the optimal processing method.

[0017] Each function of the processing unit 25 can be realized by executing a selection support processing program 241 stored in the storage unit 24. An example of a hardware configuration for executing the selection support processing program 241 will be described below with reference to FIG.

[0018] The selection support device 2 includes a storage device 301 that stores various programs and various data, a connection device 302 for connecting the three-dimensional model data storage unit 1, an operation input device 303 that accepts input of various data, a display device 304 that displays the various data, a display controller 305 that generates display data to be displayed on the display device 304, a memory 306 for expanding the various programs, and a processor 307 that executes the various programs. The storage device 301, connection device 302, operation input device 303, display controller 305, memory 306, and processor 307 are connected to one another via a data bus 308.

[0019] The storage device 301 stores various programs executed by the processor 307, various data for assisting in the selection of an optimal processing method, and display data such as images and characters to be displayed on the display device 304. The storage device 301 can be configured using a storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The storage device 301 also functions as the storage unit 24 shown in FIG. 1.

[0020] The connection device 302 is a device that can connect to the three-dimensional model data storage unit 1 and acquire design information data of a three-dimensional model of a part that is the subject of an estimate. The connection device 302 can be configured using various ports that allow data to be sent and received between devices, such as a wired or wireless LAN (Local Area Network) port, a USB (Universal Serial Bus) port, or an IEEE1394 port. The connection device 302 also functions as the connection unit 21 shown in FIG. 1.

[0021] The operation input device 303 is an input unit for inputting instructions and various data from the user. The operation input device 303 can be configured using, for example, a keyboard, a mouse, a touch panel, etc. The operation input device 303 also functions as the operation input unit 22 shown in FIG. 1. The display device 304 displays on a screen various data input by the user from the operation input unit 22 shown in FIG. 1 and various data output from the comparison result output unit 256 of the processing unit 25 shown in FIG. 1. The display device 304 can be configured using, for example, an LCD (Liquid Crystal Display), an organic EL (Electroluminescence) monitor, etc.

[0022] Display controller 305 is a controller that outputs a video signal to display display data including characters and images to display device 304. Display controller 305 can be configured using a video signal output device such as a video card, a GPU (Graphics Processing Unit), or a graphics board. Display device 304 and display controller 305 function as display unit 23 shown in FIG. 1 .

[0023] The memory 306 is a device for expanding the various programs stored in the storage device 301. The memory 306 can be configured using, for example, a storage element and a storage medium such as a random access memory (RAM) or a volatile or non-volatile semiconductor memory such as a flash memory. The processor 307 reads the various programs stored in the storage device 301, expands them in the memory 306, and executes them. The processor 307 can be configured using, for example, a processing device such as a central processing unit (CPU) or a micro-processing unit (MPU).

[0024] Next, an overview of the three-dimensional model for cutting of the product to be estimated will be explained below with reference to Figures 3A and 3B. First, Figure 3A shows the entire product 4 for cutting that is to be estimated. Hereinafter, an XYZ Cartesian coordinate system will be set up, with the width direction of the product 4 for cutting and the product 5 for additive manufacturing (described later) as the X-axis direction, the height direction as the Z-axis direction, and the direction perpendicular to the X-axis and Z-axis directions as the Y-axis direction, and explanations will be made with reference to this system as appropriate. Note that, below, the direction of the arrows on each coordinate axis will be referred to as the + direction, and the direction opposite to the arrow direction will be referred to as the - direction.

[0025] When viewed from the +Z-axis direction, the product for cutting work 4 shown in Figure 3A has an opening 42 in a housing 41. When the product for cutting work 4 is cut in the Z-axis direction along the line AA' shown by the dashed dotted line, it takes the shape shown in Figure 3B. Note that for ease of viewing, the cross-sectional area is not hatched. As shown in Figure 3B, two levels are formed inside the opening 42: a stepped first cutting bottom surface 411 and a second cutting bottom surface 412.

[0026] Using the first bottom cutting surface 411 of the product for cutting work 4 and the dotted auxiliary line s as reference points, the space surrounded by the side surfaces in the +Z-axis direction is defined as a first cutting process area 421. Furthermore, the space surrounded by the side surfaces in the +Z-axis direction from the second bottom cutting surface 412 of the product for cutting work 4 to the dotted auxiliary line s is defined as a second cutting process area 422. When manufacturing the product for cutting work 4 using a cutting machine, the first cutting process area 421 is cut from a rectangular parallelepiped product material, and then the second cutting process area 422 is cut.

[0027] Next, an overview of the three-dimensional additive manufacturing model of the product for which an estimate is being made will be described below with reference to Figures 3C and 3D. First, Figure 3C shows the entire additive manufacturing product 5 for which an estimate is being made. When viewed from the +Z-axis direction, the additive manufacturing product 5 shown in Figure 3C has an opening 52 in a housing 51. When the additive manufacturing product 5 is cut in the Z-axis direction along the dashed line BB', it takes the shape shown in Figure 3D. Note that for ease of viewing, the cross-sectional area is not hatched.

[0028] As shown in FIG. 3D , two layers are formed inside the opening 52: a stepped first additively manufactured bottom surface 511 and a second additively manufactured bottom surface 512. In additive manufacturing, additive manufacturing materials such as plastic and metal are layered in the +Z axis direction from the bottom surface to form the additively manufactured product 5. For this reason, the layer formed on the surface on the +Z axis direction side of the second additively manufactured bottom surface 512 is referred to as the first additively manufactured layer 521. The layer layered on the +Z axis direction side of the first additively manufactured layer 521 from the second additively manufactured bottom surface 512 to the auxiliary line s shown by the dotted line is referred to as the second additively manufactured layer 522. The surface on the +Z axis direction side of the second additively manufactured layer 522 is the first additively manufactured bottom surface 511.

[0029] Using the first additive manufacturing bottom surface 511 and the dotted auxiliary line s as reference points, the layer formed on the +Z axis direction side of the second additive manufacturing layer 522 is the third additive manufacturing layer 523. The first additive manufacturing layer 521 is the first additive manufacturing region 531, the second additive manufacturing layer 522 is the second additive manufacturing region 532, and the third additive manufacturing layer 523 is the third additive manufacturing region 533. When manufacturing an additive manufacturing product 5 using an additive manufacturing device, first the first additive manufacturing region 531 is formed, and then the second additive manufacturing region 532 is formed on the +Z axis direction side of the first additive manufacturing region 531. Then, the third additive manufacturing region 533 is formed on the +Z axis direction side of the second additive manufacturing region 532.

[0030] As shown in FIG. 3D , the second additive manufacturing area 532 and the third additive manufacturing area 533 are hollow inside to form the opening 52. In this case, a support material is placed in the hollow area to support the second additive manufacturing area 532 and the third additive manufacturing area 533 so that they do not collapse. The area where the support material is placed is referred to as a support material area 534. Here, the support material area 534 has the same area as the opening 52.

[0031] Next, the tables of the cutting information database 242 and the additive manufacturing information database 243 will be described below with reference to FIGS. 4A and 4B. FIG. 4A is a table of the cutting information database 242. The cutting information database 242 is a database that stores information about cutting devices that perform cutting, and stores the blade used for cutting, the cutting speed, the length and width of the available machining area, etc., in association with the device name. For example, as shown in FIG. 4A, the device name "AA" is associated with the blade "circular (diameter) 20" mm, the machining speed "100" mm / sec, the length and width of the available machining area "20" cm, etc. From this information, the machining time for each cutting device can be determined, allowing the machining cost to be calculated.

[0032] 4B shows a table of the additive manufacturing information database 243. The additive manufacturing information database 243 is a database that stores information about additive manufacturing equipment that performs additive manufacturing, and stores the material used for additive manufacturing, the layering pitch of the material, the length and width of the available layering area, etc., in association with the equipment name. For example, as shown in FIG. 4B, the equipment name "DD" is associated with the material "Resin 1," the layering pitch "0.1" mm / sec, the length and width of the available layering area "30" cm, etc. From this information, the additive manufacturing time for each additive manufacturing equipment can be determined, allowing the processing cost to be calculated.

[0033] Next, the contents of the comparison results output from the comparison result output unit 256 of the selection support device 2 shown in Fig. 1 to the display unit 23 will be described. Fig. 5 shows a table of the comparison results. The comparison result table includes, in the column direction, the items of the user's desired value, the estimate results and evaluation value for cutting processing, and the estimate results and evaluation value for additive manufacturing. The comparison result table also includes, in the row direction, the items of the processing cost required to process the target product, the delivery date until the target product is completed and delivered to the user, and the difficulty of processing.

[0034] The column-wise user desired value items are set in correspondence with the processing cost and delivery date input by the user via the operation input unit 22 of the selection support device 2 shown in FIG. 1. The estimate results and evaluation values ​​for cutting processing are set with the estimate results and evaluation values ​​for the processing cost, delivery date, and difficulty level of cutting processing executed by the cutting processing estimate processing unit 253 of the processing unit 25 of the selection support device 2 shown in FIG. 1. The estimate results and evaluation values ​​for additive manufacturing are set with the estimate results and evaluation values ​​for the processing cost, delivery date, and difficulty level of additive manufacturing executed by the additive manufacturing estimate processing unit 254 of the processing unit 25 of the selection support device 2 shown in FIG. Note that items that the user does not input via the operation input unit 22 of the selection support device 2, or items whose execution was skipped by the cutting processing estimate processing unit 253 and the additive manufacturing estimate processing unit 254, are left blank.

[0035] For machining and additive manufacturing, the evaluation score is "A" if the estimated result exceeds the user's desired value. If the estimated result is below the user's desired value but higher than the processing method being compared, the evaluation score is "B." If the estimated result is below the user's desired value and the processing method being compared, the evaluation score is "C."

[0036] The difficulty level in cutting and additive manufacturing is an index used to quantitatively express the feasibility and difficulty of a process. For example, in cutting, a thin circular cutting tool with a diameter of 2 mm is used to cut a 1000 mm deep area. In this case, the process is difficult because the cutting area is too deep for the diameter of the cutting tool, the work takes a long time, the cutting tool experiences strong chatter vibrations and breaks during processing, or the surface cannot be processed properly.

[0037] In additive manufacturing, for example, suppose metal material is layered at a layering rate of 0.1 mm / sec to create a product 10 mm high. In this case, the product height is not very high compared to the layering rate, so the work time is not very long. Also, while metal materials are often more expensive than resins, the product height is not very high, so material costs are not high, and processing is easy.

[0038] Therefore, thresholds for determining the machining speed, layer pitch, size of the machining area, etc. are determined in advance, and the difficulty level for cutting and additive manufacturing is set according to the judgment results. For example, if the judgment result falls within the range where machining is possible, it will be rated as difficulty level A (machinable), if it falls within the range where machining is possible but precision is affected, it will be rated as difficulty level B (machinable, poor precision), and if it falls within the range where machining is not possible, it will be rated as difficulty level C (not machined).

[0039] For example, in FIG. 5, the column-wise user desired value items correspond to "¥20,000" as the processing cost and "23 / 11 / 30" as the delivery date. The difficulty item is also marked with a diagonal line to indicate a blank. The estimate result and evaluation items for cutting processing correspond to "¥27,800" as the processing cost, "C" as the rating, "23 / 12 / 04" as the delivery date, and "machinable" as the difficulty. The difficulty evaluation item is left blank. The estimate result and evaluation items for additive manufacturing correspond to "¥16,500" as the processing cost, "A" as the rating, "23 / 12 / 05" as the delivery date, and "machinable" as the difficulty. The difficulty evaluation item is also left blank.

[0040] From the comparison results table shown in Figure 5, the user can see that additive manufacturing is the only method that meets the user's desired processing cost, and that it can achieve manufacturing at a lower cost than cutting processing. Furthermore, the user can see that neither cutting processing nor additive manufacturing meets the user's desired delivery time, but that additive manufacturing, with its shorter delivery time, is rated highly after comparing the two. In terms of difficulty, the user can see that both cutting processing and additive manufacturing are possible. Based on the information read from these comparison results tables, the user can then decide which processing method to use to process the target product.

[0041] Next, the flow of operations of the selection support device 2 according to this embodiment will be described below with reference to the flowcharts shown in Figures 6A to 9. For example, when a user selects, from the operation input unit 22, an icon linked to the selection support processing program 241 arranged on the screen of the display unit 23 shown in Figure 1, the selection support device 2 causes the processor 307 shown in Figure 2 to read the selection support processing program 241 stored in the storage device 301 into the memory 306 and execute it.

[0042] In FIG. 6A, the data acquisition unit 251 of the processing unit 25 of the selection support device 2 shown in FIG. 1 first acquires various conditions necessary for estimating a processing method from the user (step S101). For example, the data acquisition unit 251 causes the comparison result output unit 256 to display a message on the display unit 23 prompting the user to input various conditions necessary for estimating a processing method. The various conditions necessary for estimating a processing method include design conditions such as the processing accuracy required for the surface of the target product, manufacturing conditions such as the user's desired processing cost and delivery date for the target product, estimation conditions for selecting either cutting or additive manufacturing or both as the processing method to be estimated, unit cost conditions such as the unit cost per unit time for cutting or additive manufacturing, and additive manufacturing conditions such as the manufacturing direction and materials used for additive manufacturing. Note that the design conditions are defined as annotations on a three-dimensional model of the target product to be estimated. When the user inputs these conditions via the operation input unit 22, the data acquisition unit 251 acquires them.

[0043] The design information processing unit 252 of the processing unit 25 of the selection support device 2 shown in Fig. 1 acquires design information data of a three-dimensional model of a target product to be estimated from the three-dimensional model data storage unit 1 via the connection unit 21 shown in Fig. 1. The design information processing unit 252 converts the acquired design information data into a format that can be processed by the processing unit 25 based on the various conditions input in step S101 (step S102). Next, the design information processing unit 252 determines whether the processing method to be estimated this time, which was input as an estimation condition in step S101, is cutting processing (step S103). If the processing method to be estimated is not cutting processing (step S103; NO), the design information processing unit 252 proceeds to step S106 and executes the steps from step S106 onwards.

[0044] 1 acquires data on cutting information that matches the manufacturing conditions and estimation conditions input in step S101 from the cutting information database 242 stored in the storage unit 24. For example, the cutting estimation processing unit 253 acquires data on the cutting speed, length and width of the workable machining area, and the name of the equipment associated with the data, stored in the table of the cutting information database 242 shown in FIG.

[0045] The cutting work estimation processing unit 253 converts the acquired cutting work information data into a format that can be processed by the processing unit 25 (step S104). The cutting work estimation processing unit 253 executes cutting work estimation processing (step S105). The cutting work estimation processing will be described below with reference to the flowchart shown in FIG.

[0046] The cutting work estimation processing unit 253 recognizes a cutting work area based on the design information data of the three-dimensional model of the target product that is the subject of the estimate acquired in step S102 (step S201). For example, the cutting work estimation processing unit 253 recognizes a first cutting work area 421 and a second cutting work area 422 as the work areas of the product for cutting work 4 shown in Figures 3A and 3B.

[0047] Next, the cutting work estimate processing unit 253 acquires design information data of the cutting work area (step S202). For example, for each of the first cutting work area 421 and the second cutting work area 422 recognized as the cutting work area of ​​the product 4 for cutting work, the cutting work estimate processing unit 253 acquires design information data such as design conditions, such as the volume of the cutting work area, the bottom area, information on the length, width, and depth of the rectangular parallelepiped covering the area, the smallest diameter value of the cylindrical surfaces formed at the corners of the side surfaces within the area, and annotation information defined on the bottom and side surfaces forming the cutting work area.

[0048] The cutting work estimate processing unit 253 determines whether cutting work in the cutting work area is possible (step S203). For example, the cutting work estimate processing unit 253 determines whether cutting work in the first cutting work area 421 of the product for cutting work 4 is possible based on the data of design information of the cutting work area acquired in step S202 and the data of cutting work information acquired in step S104 of Fig. 6A.

[0049] For example, in the cutting information data, the upper limit of the depth of simple cutting is set to less than 20 cm. In the cutting area design information data acquired in step S202, the depth of the first cutting area 421 is set to 18 cm. In this case, the depth of the first cutting area 421 satisfies the condition set in the cutting information data, so the cutting estimate processing unit 253 determines that cutting of the cutting area is possible. If cutting of the cutting area is possible (step S203; YES), the cutting estimate processing unit 253 proceeds to step S205 and processes the steps from step S205 onwards. Furthermore, since the determination result regarding the "depth of the first cutting area 421" falls within the range of possible cutting, the cutting estimate processing unit 253 sets the difficulty level to "Difficulty A: 'Cuttable'".

[0050] Also, in the data of the design information of the cutting work area acquired in step S202, the depth of the first cutting work area 421 is set to 21 cm. In this case, the depth of the first cutting work area 421 does not satisfy the conditions set in the data of the cutting work information. Therefore, the cutting work estimate processing unit 253 determines that cutting work is impossible for the cutting work area. If cutting work is impossible for the cutting work area (step S203; NO), the cutting work estimate processing unit 253 increases the difficulty level (step S204). For example, as described above, the depth of the first cutting work area 421 does not satisfy the conditions set in the data of the cutting work information. Therefore, the determination result for the "depth of the first cutting work area 421" falls within the range of impossible cutting work, and becomes difficulty level C "impossible to cut." Therefore, the cutting work estimate processing unit 253 increases the difficulty level from difficulty level A "possible to cut" to difficulty level C "impossible to cut."

[0051] The cutting work estimation processing unit 253 calculates the processing time of the cutting work area (step S205). For example, the cutting work estimation processing unit 253 calculates the processing time for cutting the first cutting work area 421 of the product for cutting work 4 based on the data of the design information of the cutting work area acquired in step S202 and the data of the cutting work information acquired in step S104 of Fig. 6A.

[0052] The cutting work estimation processing unit 253 determines whether or not there is an unestimated cutting work area (step S206). For example, the cutting work estimation processing unit 253 performs the estimation performed in steps S203 to S205 only for the first cutting work area 421. In this case, the second cutting work area 422 of the product for cutting work 4 shown in FIG. 3B is unestimated, so the cutting work estimation processing unit 253 performs an estimate for the second cutting work area 422. Therefore, if there is an unestimated cutting work area (step S206; YES), the cutting work estimation processing unit 253 returns to step S203 and executes the steps from step S203 onwards.

[0053] Also, for example, the cutting work estimation processing unit 253 performs the estimations in steps S203 to S205 for both the first cutting work area 421 and the second cutting work area 422. In this case, there are no unestimated cutting work areas. Therefore, if there are no unestimated cutting work areas (step S206; NO), the cutting work estimation processing unit 253 calculates the total machining time (step S207). For example, the cutting work estimation processing unit 253 adds up the machining time for the first cutting work area 421 and the machining time for the second cutting work area 422 calculated in step S205 to calculate the total machining time. Note that setup times such as the travel time from the first cutting work area 421 to the second cutting work area 422 and the time to switch between cutting machines may also be calculated and added to the total machining time.

[0054] The cutting work estimate processing unit 253 calculates the processing cost and delivery date based on the calculated total processing time (step S208). For example, the cutting work estimate processing unit 253 calculates the processing cost by multiplying the unit price per unit time of cutting work by the total processing time, which are the unit price conditions input by the user in step S101 of FIG. 6A. The cutting work estimate processing unit 253 also calculates the delivery date based on the number of hours of the total processing time. The cutting work estimate processing unit 253 ends the cutting work estimate processing. The processing cost, delivery date, and set difficulty level calculated by the cutting work estimate processing unit 253 are examples of the first manufacturing conditions in the claims.

[0055] Returning to Fig. 6A, the design information processing unit 252 determines whether the processing method to be estimated this time, which was input as an estimation condition in step S101, is additive manufacturing (step S106). If the processing method to be estimated is not additive manufacturing (step S106; NO), the design information processing unit 252 proceeds to step S109 shown in Fig. 6B and executes the steps from step S109 onwards.

[0056] 1 acquires additive manufacturing information data that matches the manufacturing conditions and estimation conditions input in step S101 from the additive manufacturing information database 243 stored in the storage unit 24. For example, the additive manufacturing estimation processing unit 254 acquires data such as the material for additive manufacturing, the layer pitch of the material, and the length and width of the layer area that can be layered, and the name of the device associated with that data, which are stored in the table of the additive manufacturing information database 243 shown in FIG.

[0057] The additive manufacturing estimate processing unit 254 converts the acquired additive manufacturing information data into a format that can be processed by the processing unit 25 (step S107). The additive manufacturing estimate processing unit 254 executes additive manufacturing estimate processing (step S108). The additive manufacturing estimate processing will be described below with reference to the flowchart shown in FIG.

[0058] The additive manufacturing estimate processing unit 254 determines the manufacturing direction based on the additive manufacturing conditions input in step S101 shown in FIG. 6A (step S301). During cutting, cutting is performed from multiple directions, but during additive manufacturing, the manufacturing direction is limited to one direction due to the characteristics of the additive manufacturing equipment. Next, the additive manufacturing estimate processing unit 254 recognizes an additive manufacturing area based on the design information data of the three-dimensional model of the target product for which an estimate is requested, acquired in step S102 (step S302). For example, the additive manufacturing estimate processing unit 254 recognizes the first additive manufacturing area 531, the second additive manufacturing area 532, and the third additive manufacturing area 533 of the additive manufacturing product 5 shown in FIGS. 3C and 3D.

[0059] The additive manufacturing estimate processing unit 254 acquires the locations where support materials are required (step S303). For example, the second additive manufacturing area 532 and the third additive manufacturing area 533 shown in FIG. 3D are hollow on the inside to form the opening 52. In this case, to prevent the second additive manufacturing area 532 and the third additive manufacturing area 533 from collapsing, support materials are placed in the hollow areas to provide support. Here, the area where the support materials are placed is the same range as the opening 52. Therefore, the additive manufacturing estimate processing unit 254 recognizes the same range as the opening 52 as the support material area 534 where the support materials are to be placed.

[0060] The additive manufacturing estimate processing unit 254 acquires design information data for the additive manufacturing areas, including the areas where support materials are required, acquired in step S303 (step S304). For example, the additive manufacturing estimate processing unit 254 acquires design information data such as design conditions, such as volume, bottom area, information on the length, width, depth, and surface roughness of the rectangular parallelepiped that covers the area, and annotation information defined on the bottom and side surfaces that make up the area, for each of the first additive manufacturing area 531, second additive manufacturing area 532, third additive manufacturing area 533, and support material area 534 of the additive manufacturing product 5.

[0061] The additive manufacturing estimate processing unit 254 determines whether additive manufacturing is possible in the additive manufacturing area (step S305). For example, the additive manufacturing estimate processing unit 254 makes this determination based on the design information data for each of the first additive manufacturing area 531, the second additive manufacturing area 532, the third additive manufacturing area 533, and the support material area 534 of the additive manufacturing product 5 acquired in step S304, and the additive manufacturing information data acquired in step S107 of FIG. 6A.

[0062] For example, suppose the additive manufacturing information data defines the surface roughness that is possible for the side surface of the additive manufacturing area. The surface roughness of the side surface of the first additive manufacturing area 531 of the additively manufactured product 5, set in the design information data acquired in step S304, does not exceed the surface roughness defined in the additive manufacturing information data. In this case, because the surface roughness of the side surface of the additive manufacturing area satisfies the condition set in the additive manufacturing information data, the additive manufacturing estimate processing unit 254 determines that additive manufacturing of the additive manufacturing area is possible. If additive manufacturing of the additive manufacturing area is possible (step S305; YES), the additive manufacturing estimate processing unit 254 proceeds to step S307 and processes the steps from step S307 onwards. Furthermore, because the determination result regarding the "surface roughness of the side surface of the additive manufacturing area" falls within the range of additive manufacturing feasible, the additive manufacturing estimate processing unit 254 sets the difficulty level to "Difficulty A: 'machinable'."

[0063] Furthermore, the surface roughness of the side surface of the first additive manufacturing area 531 of the additive manufacturing product 5, as set in the design information data acquired in step S304, exceeds the surface roughness defined in the additive manufacturing information data. In this case, the surface roughness of the side surface of the first additive manufacturing area 531 does not satisfy the conditions set in the additive manufacturing information data. Therefore, the additive manufacturing estimate processing unit 254 determines that additive manufacturing of the additive manufacturing area is impossible. If additive manufacturing of the additive manufacturing area is impossible (step S305; NO), the additive manufacturing estimate processing unit 254 increases the difficulty level (step S306). For example, as described above, the surface roughness of the side surface of the first additive manufacturing area 531 does not satisfy the conditions set in the additive manufacturing information data. Therefore, the determination result for the "surface roughness of the side surface of the additive manufacturing area" falls within the range of additive manufacturing impossibility, resulting in difficulty level C "unmachinable." Therefore, the additive manufacturing estimate processing unit 254 increases the difficulty level from difficulty level A "machinable" to difficulty level C "unmachinable."

[0064] The additive manufacturing estimate processing unit 254 calculates the manufacturing time of the additive manufacturing area (step S307). For example, the additive manufacturing estimate processing unit 254 calculates the manufacturing time for additively manufacturing the first additive manufacturing area 531 and the processing time for cutting the first cutting processing area 421 of the cutting processing product 4 based on the design information data of the additive manufacturing area acquired in step S304 and the additive manufacturing information data acquired in step S107 of FIG. 6A.

[0065] The additive manufacturing estimation processing unit 254 determines whether there are any unestimated additive manufacturing areas (step S308). For example, the additive manufacturing estimation processing unit 254 assumes that the estimation performed in steps S305 to S307 was performed only for the first additive manufacturing area 531. In this case, the second additive manufacturing area 532 and the third additive manufacturing area 533, and the supporting material area 534 shown in FIG. 3D have not been estimated. Therefore, the additive manufacturing estimation processing unit 254 estimates the second additive manufacturing area 532, the third additive manufacturing area 533, and the supporting material area 534 in that order. Therefore, if there are any unestimated additive manufacturing areas (step S308; YES), the additive manufacturing estimation processing unit 254 returns to step S305 and executes the steps from step S305 onwards.

[0066] Also, for example, it is assumed that the additive manufacturing estimate processing unit 254 performed the estimates in steps S305 to S307 for all of the first additive manufacturing area 531 to the third additive manufacturing area 533 and the supporting material area 534. In this case, there are no unestimated additive manufacturing areas. Therefore, if there are no unestimated additive manufacturing areas (step S308; NO), the additive manufacturing estimate processing unit 254 calculates the total manufacturing time (step S309). For example, the additive manufacturing estimate processing unit 254 adds up the manufacturing times calculated in step S307 for the first additive manufacturing area 531 to the third additive manufacturing area 533 and the supporting material area 534 to calculate the total manufacturing time. It is also possible to calculate setup times such as travel time between the first additive manufacturing area 531 to the third additive manufacturing area 533 and the supporting material area 534, and time to change additive manufacturing equipment or materials, and add these to the total processing time.

[0067] The additive manufacturing estimate processing unit 254 calculates the processing cost and delivery date based on the calculated total manufacturing time (step S310). For example, the additive manufacturing estimate processing unit 254 calculates the processing cost by multiplying the unit price per unit time of additive manufacturing by the total processing time in the unit price conditions input by the user in step S101 of FIG. 6A. The additive manufacturing estimate processing unit 254 also calculates the delivery date based on the number of hours in the total manufacturing time. The additive manufacturing estimate processing unit 254 ends the additive manufacturing estimate processing. The processing cost, delivery date, and set difficulty level calculated by the additive manufacturing estimate processing unit 254 are examples of second manufacturing conditions in the claims.

[0068] Returning to FIG. 6A, we proceed to the flowchart of FIG. 6B. The estimate result comparison unit 255 of the processing unit 25 of the selection support device 2 shown in FIG. 1 determines whether the processing method to be estimated this time is both cutting processing and additive manufacturing in the estimation conditions input in step S101 of FIG. 6A (step S109). If the processing method is not both cutting processing and additive manufacturing (step S109; NO), the estimate result comparison unit 255 determines the processing method input as the estimation conditions, proceeds to step S111, and executes step S111 and subsequent steps. If the processing method is both cutting processing and additive manufacturing (step S109; YES), the estimate result comparison unit 255 executes estimate result comparison processing (step S110). The estimate result comparison processing will be described below with reference to the flowchart shown in FIG. 9.

[0069] The estimate result comparison unit 255 first evaluates the estimate result for cutting work. The estimate result comparison unit 255 acquires the processing cost and delivery date calculated in step S208 of Fig. 7 from the cutting work estimate processing unit 253 as the estimate result for cutting work. The estimate result comparison unit 255 determines whether the processing cost and delivery date of the acquired estimate result for cutting work are less than the user's desired values ​​for the processing cost and delivery date included in the manufacturing conditions input in step S101 of Fig. 6A (step S401).

[0070] If the estimated cost is less than the user's desired value (step S401; YES), the estimate result comparison unit 255 sets the estimate result for cutting processing to an evaluation of "A," which is the highest evaluation (step S402). If the estimated cost is equal to or greater than the user's desired value (step S401; NO), the estimate result comparison unit 255 acquires the processing cost and delivery date calculated in step S310 of Fig. 8 from the additive manufacturing estimate processing unit 254 as the estimate result for additive manufacturing. The estimate result comparison unit 255 determines whether the processing cost and delivery date of the estimate result for cutting processing are less than the estimate result for additive manufacturing (step S403).

[0071] If the estimated result is less than the estimated result for additive manufacturing (step S403; YES), the estimate result comparison unit 255 sets the estimate result for cutting processing to a rating of "B" (step S404). If the estimated result is equal to or greater than the estimated result for additive manufacturing (step S403; NO), the estimate result comparison unit 255 sets the estimate result for cutting processing to a rating of "C" (step S405).

[0072] For example, as shown in the evaluation result table of FIG. 5, the machining cost of the "user desired value," which is the input value desired by the user, is "¥20,000" and the delivery date is "23 / 11 / 30." The machining cost and delivery date of the machining calculated by the machining estimate processing unit 253 in step S208 of FIG. 7 are "¥27,800" and "23 / 12 / 04," respectively, as shown in the evaluation result table of FIG. 5. Furthermore, the machining cost and delivery date of the additive manufacturing calculated by the additive manufacturing estimate processing unit 254 in step S310 of FIG. 8 are "¥16,500" and "23 / 12 / 05," respectively, as shown in the evaluation result table of FIG. 5. In this case, the machining cost of the machining is greater than the user desired value and the machining cost of the additive manufacturing. Therefore, the machining cost of the machining is evaluated as "C." Furthermore, the delivery date is later than the delivery date of the user desired value but earlier than the delivery date of the additive manufacturing. Therefore, the delivery time for cutting processing will be rated "B".

[0073] Next, the estimate result comparison unit 255 first evaluates the estimate results for additive manufacturing. The estimate result comparison unit 255 determines whether the processing cost and delivery date of the estimate results for additive manufacturing acquired in step S402 are less than the user's desired values ​​for the processing cost and delivery date included in the manufacturing conditions entered in step S101 of FIG. 6A (step S406). If they are less than the user's desired values ​​(step S406; YES), the estimate result comparison unit 255 assigns the highest rating of "A" to the estimate results for additive manufacturing (step S407). If they are equal to or greater than the user's desired values ​​(step S406; NO), the estimate result comparison unit 255 determines whether the processing cost and delivery date of the estimate results for additive manufacturing are less than the estimate results for cutting processing (step S408).

[0074] If the estimated cost is less than the estimated cost for cutting (step S408; YES), the estimate result comparison unit 255 sets the estimate result for additive manufacturing to a rating of "B" (step S409). If the estimated cost is equal to or greater than the estimated cost for cutting (step S408; NO), the estimate result comparison unit 255 sets the estimate result for additive manufacturing to a rating of "C" (step S410).

[0075] For example, as shown in the evaluation result table of FIG. 5, the processing cost of the "user desired value," which is the input value desired by the user, is "¥20,000" and the delivery date is "23 / 11 / 30." The additive manufacturing processing cost and delivery date calculated by the additive manufacturing estimate processing unit 254 in step S310 of FIG. 8 are assumed to be "¥16,500" and "23 / 12 / 05," respectively, as shown in the evaluation result table of FIG. 5. Also, the cutting processing cost and delivery date calculated by the cutting processing estimate processing unit 253 in step S208 of FIG. 7 are assumed to be "¥27,800" and "23 / 12 / 04," respectively, as shown in the evaluation result table of FIG. 5. In this case, the additive manufacturing processing cost is less than the user desired value. Therefore, the additive manufacturing processing cost is evaluated as "A." Furthermore, the delivery date is later than both the user desired value and the delivery date of the cutting processing. Therefore, the delivery date of the additive manufacturing is evaluated as "C." The ratings "A", "B", and "C" are examples of the first, second, and third ratings in the scope of the claims.

[0076] The estimate result comparison unit 255 ends the estimate result comparison process. Return to FIG. 6B. The comparison result output unit 256 of the processing unit 25 of the selection support device 2 shown in FIG. 1 displays the evaluation results on the display unit 23 (step S111). For example, the estimate result comparison unit 255 sets the user's desired values ​​for the processing cost and delivery date included in the manufacturing conditions input in step S101 of FIG. 6A, the machining cost and delivery date of the cutting processing calculated by the cutting processing estimate processing unit 253 in step S208 of FIG. 7, and the machining cost and delivery date of the additive manufacturing calculated by the additive manufacturing estimate processing unit 254 in step S310 of FIG. 8 in the evaluation result table shown in FIG. 5. In addition, the estimate result comparison unit 255 sets the difficulty level of the cutting processing set in step S204 of FIG. 7 and the difficulty level of the additive manufacturing set in step S306 of FIG. 8 in the evaluation result table. The estimate result comparison unit 255 displays the evaluation result table shown in FIG. 5 on the display unit 23.

[0077] Next, the estimate result comparison unit 255 requests the user to select a processing method for manufacturing the product (step S112). For example, the comparison result output unit 256 displays a message on the display unit 23 to prompt the user to select a processing method. This allows the user to select the optimal processing method based on the comparison results. The comparison result output unit 256 ends the selection support process.

[0078] As described above, according to the embodiment, the selection support device 2 can estimate the manufacturing conditions for parts in cutting and additive manufacturing, such as processing cost, delivery time, and difficulty, from the design information data of the 3D model, and present the comparison results to the user. This allows the selection support device 2 to support the user in selecting the optimal processing method for the product.

[0079] (Variation 1) In the above embodiment, the selection support system 100 is configured to have a three-dimensional model data storage unit 1 that stores design information data of parts to be manufactured, located outside the selection support device 2. The selection support system 100 includes the three-dimensional model data storage unit 1 and the selection support device 2. However, the present invention is not limited to this, and the three-dimensional model data storage unit 1 may be built into the selection support device 2 as a single device. Furthermore, the three-dimensional model data storage unit 1 and the functions that operate in the selection support device 2 may be placed on a server, and may be executable from a client terminal.

[0080] (Variation 2) In the above embodiment, the selection support device 2 is equipped with the display unit 23. However, the present invention is not limited to this, and the display unit 23 may be a display device separate from the selection support device 2. In this case, a terminal that transmits display data from the selection support device 2 to the separate display device corresponds to the display unit 23.

[0081] In addition, in the embodiment of the present disclosure, the selection support system 100 can be realized as a dedicated system. However, it can also be realized using a general computer system without using a dedicated system. For example, a program for realizing each function of the above-described selection support system 100 may be stored and distributed on a computer-readable recording medium such as a CD-ROM (Compact Disc Read Only Memory) or a DVD-ROM (Digital Versatile Disc Read Only Memory), and a computer that can realize each of the above-described functions may be configured by installing this program on a computer. Furthermore, if each function is realized by sharing the work between an OS (Operating System) and an application, or by cooperation between an OS and an application, only the application may be stored on the recording medium.

[0082] The technical scope of the present disclosure is not limited by the above-described embodiments and modifications, and the present disclosure can be freely applied, modified, or improved within the scope of the technical ideas described in the claims.

[0083] Various aspects of the present disclosure are summarized below as appendices.

[0084] (Appendix 1) a cutting processing estimation processing unit that estimates a first manufacturing condition for the part in the cutting processing based on design information data of a three-dimensional model of the part to be estimated and information data related to the cutting processing; an additive manufacturing estimation processing unit that estimates second manufacturing conditions for the part in the additive manufacturing based on design information data of a three-dimensional model of the part and information data related to additive manufacturing; an estimate result comparison unit that compares and evaluates the first manufacturing conditions and the second manufacturing conditions; a comparison result output unit that outputs the evaluation results evaluated by the estimate result comparison unit to present them to a user; Equipped with Selection aids. (Appendix 2) the estimate result comparison unit sets an evaluation of the first manufacturing conditions in accordance with a comparison result obtained by comparing the first manufacturing conditions with the manufacturing conditions input by the user and the second manufacturing conditions, and sets an evaluation of the second manufacturing conditions in accordance with a comparison result obtained by comparing the second manufacturing conditions with the manufacturing conditions input by the user and the first manufacturing conditions. 10. The selection assistance device of claim 1. (Appendix 3) The estimate result comparison unit sets a first evaluation to the first manufacturing condition when the first manufacturing condition is less than the manufacturing condition input by the user, sets a second evaluation to the first manufacturing condition when the first manufacturing condition is equal to or greater than the manufacturing condition input by the user and less than the second manufacturing condition, and sets a third evaluation to the first manufacturing condition when the first manufacturing condition is equal to or greater than the manufacturing condition input by the user and is equal to or greater than the second manufacturing condition. 3. A selection assistance device as described in appendix 2. (Appendix 4) The estimate result comparison unit sets a first evaluation to the second manufacturing conditions when the second manufacturing conditions are less than the manufacturing conditions input by the user, sets a second evaluation to the second manufacturing conditions when the second manufacturing conditions are equal to or greater than the manufacturing conditions input by the user and less than the first manufacturing conditions, and sets a third evaluation to the second manufacturing conditions when the second manufacturing conditions are equal to or greater than the manufacturing conditions input by the user and are equal to or greater than the first manufacturing conditions. 4. The selection assistance device according to claim 2 or 3. (Appendix 5) the first manufacturing condition is a processing cost, a delivery time, or a difficulty level when the part is processed by the cutting process, The second manufacturing condition is the processing cost, delivery time, or difficulty when manufacturing the part by additive manufacturing, 5. A selection assistance device according to any one of appendices 1 to 4. (Appendix 6) A method executed by a selection assistance device, comprising: Estimating first manufacturing conditions for the part in the cutting process based on design information data of a three-dimensional model of the part to be estimated and information data related to the cutting process; Estimating second manufacturing conditions for the part in the additive manufacturing based on design information data of the three-dimensional model of the part and information data related to additive manufacturing; comparing and evaluating the first manufacturing conditions with the second manufacturing conditions; Outputting the evaluation results for presentation to the user; method. (Appendix 7) On the computer, a process of estimating first manufacturing conditions for the part in cutting processing based on design information data of a three-dimensional model of the part to be estimated and information data related to the cutting processing; A process of estimating second manufacturing conditions for the part in the additive manufacturing based on design information data of the three-dimensional model of the part and information data related to additive manufacturing; a process of comparing and evaluating the first manufacturing conditions and the second manufacturing conditions; A process of outputting the evaluation results for presentation to a user; A program to execute. [Explanation of symbols]

[0085] 1 Three-dimensional model data storage unit, 2 Selection support device, 4 Cutting processing product, 5 Additive manufacturing product, 21 Connection unit, 22 Operation input unit, 23 Display unit, 24 Memory unit, 25 Processing unit, 41, 51 Housing, 42, 52 Opening, 100 Selection support system, 241 Selection support processing program, 242 Cutting processing information database, 243 Additive manufacturing information database, 251 Data acquisition unit, 252 Design information processing unit, 253 Cutting processing estimate processing unit, 254 Additive manufacturing estimate processing unit, 255 Estimate result comparison unit, 256 Comparison result output unit, 301 Storage device, 302 Connection device, 303 Operation input device, 304 Display device, 305 Display controller, 306 Memory, 307 Processor, 308 Data bus, 411 First cutting bottom surface, 412 Second cutting bottom surface, 421 First cutting processing area, 422 Second cutting area, 511, first additive manufacturing bottom surface, 512, second additive manufacturing bottom surface, 521, first additive manufacturing layer, 522, second additive manufacturing layer, 523, third additive manufacturing layer, 531, first additive manufacturing area, 532, second additive manufacturing area, 533, third additive manufacturing area, 534, support material area.

Claims

1. a cutting processing estimation processing unit that estimates a first manufacturing condition for the part in the cutting processing based on design information data of a three-dimensional model of the part to be estimated and information data related to the cutting processing; an additive manufacturing estimation processing unit that estimates second manufacturing conditions for the part in the additive manufacturing based on design information data of a three-dimensional model of the part and information data related to additive manufacturing; an estimate result comparison unit that compares and evaluates the first manufacturing conditions and the second manufacturing conditions; a comparison result output unit that outputs the evaluation results evaluated by the estimate result comparison unit to present them to a user; Equipped with Selection aids.

2. the estimate result comparison unit sets an evaluation of the first manufacturing conditions in accordance with a comparison result obtained by comparing the first manufacturing conditions with the manufacturing conditions input by the user and the second manufacturing conditions, and sets an evaluation of the second manufacturing conditions in accordance with a comparison result obtained by comparing the second manufacturing conditions with the manufacturing conditions input by the user and the first manufacturing conditions. The selection assistance device according to claim 1 .

3. The estimate result comparison unit sets a first evaluation to the first manufacturing condition when the first manufacturing condition is less than the manufacturing condition input by the user, sets a second evaluation to the first manufacturing condition when the first manufacturing condition is equal to or greater than the manufacturing condition input by the user and less than the second manufacturing condition, and sets a third evaluation to the first manufacturing condition when the first manufacturing condition is equal to or greater than the manufacturing condition input by the user and is equal to or greater than the second manufacturing condition. The selection assistance device according to claim 2 .

4. The estimate result comparison unit sets a first evaluation to the second manufacturing conditions when the second manufacturing conditions are less than the manufacturing conditions input by the user, sets a second evaluation to the second manufacturing conditions when the second manufacturing conditions are equal to or greater than the manufacturing conditions input by the user and less than the first manufacturing conditions, and sets a third evaluation to the second manufacturing conditions when the second manufacturing conditions are equal to or greater than the manufacturing conditions input by the user and are equal to or greater than the first manufacturing conditions. The selection support device according to claim 2 or 3.

5. the first manufacturing condition is a processing cost, a delivery time, or a difficulty level when the part is processed by the cutting process, The second manufacturing condition is the processing cost, delivery time, or difficulty when manufacturing the part by additive manufacturing, The selection support device according to claim 1 or 2.

6. A method executed by a selection assistance device, comprising: Estimating first manufacturing conditions for the part in the cutting process based on design information data of a three-dimensional model of the part to be estimated and information data related to the cutting process; Estimating second manufacturing conditions for the part in the additive manufacturing based on design information data of the three-dimensional model of the part and information data related to additive manufacturing; comparing and evaluating the first manufacturing conditions with the second manufacturing conditions; Outputting the evaluation results for presentation to the user; method.

7. On the computer, a process of estimating first manufacturing conditions for the part in cutting processing based on design information data of a three-dimensional model of the part to be estimated and information data related to the cutting processing; A process of estimating second manufacturing conditions for the part in the additive manufacturing based on design information data of the three-dimensional model of the part and information data related to additive manufacturing; a process of comparing and evaluating the first manufacturing conditions and the second manufacturing conditions; A process of outputting the evaluation results for presentation to a user; A program to execute.

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