Material selection assistance device, material selection method, material selection assistance method, material selection assistance program, and recording medium

Abstract

To provide a material selection auxiliary device, a material selection method, a material selection auxiliary method, a material selection auxiliary program, and a recording media that accurately select materials in consideration of the required characteristics of a part.SOLUTION: A material selection auxiliary device for generating information presenting characteristics to be compared between two or more candidate materials when two or more candidate materials are considered as materials for one part, includes: a required characteristic acquisition unit for acquiring requirement characteristic information indicating required characteristics that are required for the one part; a part characteristics extraction unit that extracts part quality characteristics of parts related to each of the required characteristics; a material characteristics extraction unit that extracts material quality characteristics of items related to characteristics of the material associated with each of the required characteristics; and an information generating unit that generates information in a manner that enables perceptual contrast between a first characteristic value that is a value indicating each of the material quality characteristics of one of two or more candidate materials, and a second characteristic value that is a value indicating each of the material quality characteristics of the other candidate materials.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a material selection assistance device, a material selection method, a material selection assistance program, and a recording medium, and in particular to a material selection assistance device, a material selection method, a material selection assistance program, and a recording medium that generate information regarding the appropriate selection of materials for automobile-related parts. [Background technology]

[0002] When selecting materials for parts, it is important to appropriately select materials that can satisfy the properties required for the part. For example, Patent Document 1 discloses a material selection method in which a material selection processing unit accesses an integrated database to extract standard specifications that match input part names and material selection conditions, and further extracts materials that match the standard specifications. Patent Document 1 discloses that the material selection conditions are the type and characteristic values ​​of the material, which are input by the designer (paragraphs

[0014] ,

[0021] , etc.). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-73744 Summary of the Invention [Problem to be solved by the invention]

[0004] For example, to select the appropriate material for an automobile part, it is necessary to accurately determine which characteristics of the material should be focused on, and this requires judgment based on both specialized knowledge about automobile parts and specialized knowledge about materials. Therefore, currently, material selection for automobile parts often relies on the judgment of a very small number of experienced engineers. There is a need for a versatile material selection method that can automatically select the appropriate material without extensive specialized knowledge.

[0005] The present invention has been made in consideration of the above points, and aims to provide a material selection assistance device, a material selection method, a material selection assistance program, and a recording medium that enable accurate material selection taking into account the characteristics required for a part. [Means for solving the problem]

[0006] The material selection assistance device of the present invention is a material selection assistance device that generates information presenting characteristics to be compared between two or more candidate materials when two or more candidate materials are being considered as materials for a single part, and is characterized by having: a required characteristic acquisition unit that acquires required characteristic information indicating required characteristics that are characteristics required of the single part; a part characteristic extraction unit that extracts, for each of the required characteristics, part quality characteristics that are characteristics of the part related to the required characteristics; a material characteristic extraction unit that extracts material quality characteristics that are items related to the characteristics of the material related to each of the part quality characteristics; and an information generation unit that generates information in a manner that allows perceptual comparison between first characteristic values ​​that are values ​​indicating each of the material quality characteristics of one of the two or more candidate materials and second characteristic values ​​that are values ​​indicating each of the material quality characteristics of another of the two or more candidate materials.

[0007] The material selection method of the present invention is a material selection method for selecting a material for one part from two or more candidate materials, and is characterized by comprising: a required characteristic identification step for identifying required characteristic information indicating required characteristics that are characteristics required for the one part; a part characteristic extraction step for extracting, for each of the required characteristics, part quality characteristics that are characteristics of the part related to the required characteristics; a material characteristic extraction step for extracting material quality characteristics that are items related to the physical properties of the material related to each of the part quality characteristics; and a step of selecting a material based on a perceptual comparison between a first characteristic value that is a value indicating each of the material quality characteristics for one of the candidate materials and a second characteristic value that is a value indicating each of the material quality characteristics for another of the candidate materials.

[0008] The material selection assistance method of the present invention is a material selection assistance method executed by a material selection assistance device that generates information presenting characteristics to be compared between two or more candidate materials when two or more candidate materials are being considered as materials for one part, and is characterized by having: a required characteristic acquisition step that acquires required characteristic information indicating required characteristics that are characteristics required for the one part; a part characteristic extraction step that extracts, for each of the required characteristics, part quality characteristics that are characteristics of the part related to the required characteristics; a material characteristic extraction step that extracts material quality characteristics that are items related to the physical properties of the material related to each of the part quality characteristics; and an information generation step that generates information in a manner that allows perceptual comparison between first characteristic values ​​that are values ​​indicating each of the material quality characteristics for one of the candidate materials and second characteristic values ​​that are values ​​indicating each of the material quality characteristics for the other candidate materials.

[0009] The material selection assistance program of the present invention is a material selection assistance program executed by a material selection assistance device having a computer, which generates information presenting characteristics to be compared between two or more candidate materials when considering the two or more candidate materials as materials for a single part. The material selection assistance program causes the computer to execute the following steps: a required characteristic acquisition step to acquire required characteristic information indicating required characteristics that are characteristics required for the single part; a part characteristic extraction step to extract, for each of the required characteristics, part quality characteristics that are characteristics of the part related to the required characteristics; a material characteristic extraction step to extract material quality characteristics that are items related to the physical properties of the material related to each of the part quality characteristics; and an information generation step to generate information in a manner that allows perceptual comparison between first characteristic values ​​that are values ​​indicating each of the material quality characteristics for one of the candidate materials and second characteristic values ​​that are values ​​indicating each of the material quality characteristics for the other candidate materials. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing an example of the configuration of a material selection assisting device according to an embodiment of the present invention; [Figure 2]FIG. 10 is a diagram illustrating an example of the contents of a database related to required characteristics according to the embodiment. [Figure 3] FIG. 2 is a diagram showing an example of the contents of a database relating to part quality characteristics in the embodiment. [Figure 4] FIG. 10 is a diagram showing an example of the contents of a database relating to material quality characteristics in an embodiment. [Figure 5] 3 is a flowchart showing an example of a material selection assistance routine executed by the material selection assistance device of the embodiment. [Figure 6] FIG. 2 is a diagram showing an example of an operation screen of the material selection assisting device of the embodiment. [Figure 7] FIG. 2 is a diagram showing an example of a display screen of the material selection assisting device of the embodiment. [Figure 8] FIG. 2 is a diagram showing an example of a display screen of the material selection assisting device of the embodiment. [Figure 9] FIG. 10 is a diagram showing an example of an output screen of the material selection assisting device of the embodiment. [Figure 10] FIG. 10 is a diagram showing an example of an output screen of the material selection assisting device of the embodiment. [Figure 11] FIG. 10 is a diagram showing an example of an output screen of the material selection assisting device of the embodiment. [Figure 12] FIG. 10 is a diagram showing an example of an output screen of the material selection assisting device of the embodiment. [Figure 13] FIG. 10 is a diagram showing an example of an output screen of the material selection assisting device of the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the following description and accompanying drawings, substantially the same or equivalent parts are designated by the same reference numerals. [Example]

[0012] The configuration of a material selection assistance device 10 that executes the material selection assistance method of this embodiment will be described with reference to the drawings. The material selection assistance device 10 is a terminal device equipped with a computer. In this embodiment, the material selection assistance device 10 is a desktop or notebook personal computer (hereinafter also referred to as a PC). The material selection assistance device 10 may be another type of terminal device, such as a tablet or smartphone. The material selection assistance device 10 may also be a specialized computer specialized in information processing related to material selection assistance.

[0013] Furthermore, material selection assist device 10 may be a server device that receives information input to a client terminal, generates new information based on the received information, and transmits the new information to the client terminal. In other words, material selection assist device 10 may be realized by cloud computing.

[0014] Figure 1 is a block diagram showing the configuration of a material selection assistance device 10. The material selection assistance device 10 is a device that generates information related to material selection based on input information and presents it to a user. As shown in Figure 1, the material selection assistance device 10 is configured by connecting each unit via a system bus 11.

[0015] The input unit 13 is an interface that acquires data from an external device. The input unit 13 is connected to an input device 15. The input device 15 is a device that accepts information input by a user, such as a keyboard, a mouse, or a touch panel.

[0016] The input unit 13 receives input of information related to material selection by receiving input via the input device 15. For example, the input unit 13 receives input of information such as the type of part for which material is to be selected, the current material, candidate materials, or properties required for material selection, i.e., input of selection conditions.

[0017] The storage unit 17 is a storage device configured, for example, by a hard disk drive, a solid state drive (SSD), a flash memory, or the like. The storage unit 17 stores various programs executed in the material selection assistance device 10. Note that the various programs may be acquired, for example, from another server device or the like via a network, or may be recorded on a recording medium and read via various drive devices. For example, the storage unit 17 stores a material selection assistance program executed in the material selection assistance device 10.

[0018] The storage unit 17 also stores various databases in which information used to generate information that assists the material selection assist device 10 in selecting materials is stored.

[0019] For example, the storage unit 17 stores a required characteristic database (referred to as a required characteristic DB in the drawings) 17A in which required characteristic information indicating required characteristics that are characteristics required for each part is stored.

[0020] 2 is a diagram showing an example of the required characteristic database 17A in which the required characteristics for each part are stored. As shown in FIG. 2, the required characteristic database 17A stores the primary required characteristic and the secondary required characteristic in association with each part.

[0021] In this embodiment, the primary required characteristics are described as subjective or abstract expressions of the characteristics required for each part. Also, in this embodiment, the secondary required characteristics are described as more specific and detailed expressions of the characteristics required for each part than the primary required characteristics. In other words, the primary required characteristics and secondary required characteristics are two hierarchical levels that classify the items that indicate the characteristics required for each part.

[0022] As shown in FIG. 2, each primary required characteristic is associated with a secondary required characteristic, which is a specific or subdivided characteristic of the primary required characteristic.

[0023] In the example shown in Figure 2, for example, the primary required characteristic of a rearview mirror housing, which is an existing part, is "clean appearance," and the secondary required characteristics are "clean surface," "free from scratches," "no discoloration," "no distortion," and "no deterioration over time."

[0024] The storage unit 17 also stores, for example, a part quality characteristic database (part quality characteristic DB in FIG. 1) 17B in which information indicating part quality characteristics, which are characteristics of parts related to each of the required characteristics, is stored.

[0025] The part quality characteristics are, for example, properties of a finished part (product) that should be noted or items that should be tested on the finished part in order to satisfy required characteristics.

[0026] Fig. 3 is a diagram showing an example of part quality characteristic database 17B. As shown in Fig. 3, part quality characteristic database 17B stores, for each secondary required characteristic, part quality characteristics that are related to the secondary required characteristic and are characteristics of the part, in association with each other.

[0027] As shown in FIG. 3, in the part quality characteristic database 17B, the part quality characteristics are described separately as primary part characteristics that indicate general characteristics related to the quality of the part, and secondary part quality characteristics that indicate characteristics that are more detailed than the primary part characteristics.

[0028] In the part quality characteristic database 17B, the required characteristics and the part quality characteristics are associated with each other by attaching a mark indicating the secondary part quality characteristic associated with each secondary required characteristic.

[0029] In the example shown in Figure 3, the required characteristics and part quality characteristics are associated by marking the secondary part quality characteristics that are related to each secondary required characteristic with a "◯" and marking the secondary part quality characteristics that are strongly related to the secondary required characteristic with a "◎". Note that, as shown in Figure 3, multiple part quality characteristics are often associated with one secondary required characteristic.

[0030] Furthermore, for example, the memory unit 17 stores a material quality characteristic database (material quality characteristic DB in FIG. 1) 17C that stores information indicating material quality characteristics, which are items related to the characteristics of materials associated with each of the part quality characteristics.

[0031] Fig. 4 is a diagram showing an example of the material quality characteristic database 17C. As shown in Fig. 4, the material quality characteristic database 17C stores material quality characteristics, which are items related to the properties of materials associated with each of the secondary part quality characteristics, in association with each other.

[0032] As shown in Figure 4, in the material quality characteristic database 17C, material quality characteristics are described separately as primary material quality characteristics that indicate general characteristics regarding the quality of the material, and secondary material quality characteristics that indicate characteristics that are more detailed than the primary material quality characteristics.

[0033] In addition, in the material quality characteristic database 17C, the part quality characteristics and the material quality characteristics are associated with each other by marking each secondary part quality characteristic with an associated secondary material quality characteristic.

[0034] In the example shown in Figure 4, part quality characteristics and material quality characteristics are associated by marking secondary material quality characteristics related to each secondary part quality characteristic with a "◯" and secondary material quality characteristics that are strongly related to the secondary part quality characteristic with a "◎". Note that, as shown in Figure 4, multiple material quality characteristics are often associated with one part quality characteristic.

[0035] Furthermore, for example, the storage unit 17 stores a material characteristic value database (material characteristic value DB in FIG. 1) 17D in which information indicating characteristic values, which are values ​​indicating each of the material quality characteristics of each material, is stored. The material characteristic value database 17D stores information indicating characteristic values, such as values ​​indicating strength and physical properties, or values ​​or symbols indicating durability and formability, in association with each material.

[0036] The control unit 19 is configured with a CPU (Central Processing Unit) 19A, a ROM (Read Only Memory) 19B, a RAM (Random Access Memory) 19C, etc., and functions as a computer. The CPU 19A reads and executes various programs stored in the ROM 19B and the storage unit 17, thereby realizing various functions.

[0037] The control unit 19 generates information that can assist in material selection by reading and executing the material selection assistance program stored in the storage unit 17. For example, when two or more candidate materials are being considered as materials for one part, the control unit 19 generates information that presents the characteristics to be compared between the two or more candidate materials.

[0038] For example, one of the two or more candidate materials is the current material of one part, and the control unit 19 generates information presenting the characteristics to be compared between the current material of one part and a candidate material that is a candidate for changing from the current material. Also, for example, the two or more candidate materials may be multiple materials that are candidates for the material of a new part, and the control unit 19 generates information presenting the characteristics to be compared between each of the two or more candidate materials.

[0039] The output unit 21 is connected to an output device 23 such as a display, a touch panel display, a speaker, etc. The output unit 21 is an interface that supplies various information to the output device 23 in accordance with commands from the control unit 19. In this embodiment, a case will be described in which the output device 23 is a display.

[0040] The output unit 21 supplies, for example, information to the output device 23 for displaying an input screen for accepting input of selection conditions required when starting material selection.

[0041] Furthermore, the output unit 21 supplies, for example, information generated by the control unit 19 that can be useful in selecting a material to the output device 23. For example, the output unit 21 supplies, to the output device 23, information presenting properties to be compared between two or more candidate materials.

[0042] The communication unit 25 is a network adapter such as a NIC (Network Interface Card) for performing communication such as sending and receiving data to and from the outside in accordance with instructions from the control unit 19.

[0043] For example, the communication unit 25 communicates when the material selection assist device 10 acquires information necessary for material selection from an external database or an external terminal device. The communication unit 25 communicates when, for example, receiving information indicating selection conditions such as the type of part to be selected from the outside. The communication unit 25 also communicates when receiving information indicating characteristic values ​​such as physical property values ​​of candidate materials from an external database (not shown) that is not stored in the material characteristic value DB 17D.

[0044] The generation of information relating to material selection executed by the material selection assisting device 10 of this embodiment will be described with reference to FIGS. 5 and 6 to 13.

[0045] 5 is a flowchart showing a material selection assistance routine RT1, which is an example of a routine executed by the control unit 19 of the material selection assistance device 10 of this embodiment. The control unit 19 starts the material selection assistance routine RT1 when, for example, receiving an operation to start the material selection process via the input unit.

[0046] When the control unit 19 starts the material selection assistance routine RT1, it accepts input of material selection conditions (step S101). In step S101, for example, the control unit 19 causes the output device 23 to display an input screen for accepting input of selection conditions via the output unit 21.

[0047] FIG. 6 is a diagram showing an example of an input screen for material selection conditions displayed on the output device 23 in step S101.

[0048] As shown in Fig. 6, the input screen for material selection conditions has an input field F1 for a part name. For example, the input field F1 for the part name is displayed so that one part name can be selected from a plurality of part names by using a pull-down function or the like. Alternatively, for example, the input field F1 for the part name may be displayed so that the part name can be input via a keyboard or a touch panel. For example, with regard to the part name on the input screen shown in Fig. 6, for example, an existing part stored in the required characteristics DB (Fig. 2) can be selected from a pull-down menu, and a new part not stored in the required characteristics DB can be input in the input field F1.

[0049] Furthermore, the input screen for material selection conditions has an input field F2 for primary required characteristics, as shown in Fig. 6. As described above, primary required characteristics are requirements that subjectively or abstractly express the characteristics required for each part.

[0050] For example, in the case of existing parts stored in the required characteristic DB, primary required characteristics are associated with each part in the required characteristic DB, and the input field F2 for primary required characteristics may be configured so that when a part name is entered in the above-mentioned input field for part name, the primary required characteristics associated with that part are automatically displayed. Also, the input screen may be configured so that primary required characteristics can be entered individually.

[0051] In the example shown in Fig. 6, the part name is displayed selectably from a pull-down menu, and an existing automobile part, "rearview mirror housing," is selected. In addition, in the example shown in Fig. 6, by selecting the rearview mirror housing as the part name, the primary required characteristics that are pre-associated with the rearview mirror housing are automatically displayed.

[0052] Furthermore, as shown in Fig. 6, the input screen for material selection conditions has a material name input field F3. The material name input field F3 is configured to allow input of two or more materials to be compared in terms of material properties when selecting materials using the material selection auxiliary routine RT1.

[0053] For example, if an existing part is entered in the part name input field F1, the current material and candidate materials may be automatically displayed in the material name input field F3, or selection may be possible using a pull-down function.

[0054] In the example shown in Fig. 6, a screen is displayed for use when the material selection assist device 10 of this embodiment is used to consider which material is suitable for changing materials. Therefore, the material name input field is configured to input the current material and a candidate material for the change of material. In the example shown in Fig. 6, "X resin" is input as the current material and "Y resin" is input as the candidate material for the change of material.

[0055] The use of the material selection assistance device of this embodiment is not limited to the consideration of replacement materials when changing materials, but can also be used to select new materials. In that case, for example, a candidate material can be entered in the current material field. In other words, the current material is also one of the candidate materials in that it is compared with other materials and becomes a target for selection.

[0056] If two or more materials are entered in F3 and the decision button B1 is selected, the process proceeds to step S102, where information is processed to enable comparison of properties, for example, between the current material and the candidate material, or between multiple candidate materials.

[0057] After executing step S101, the control unit 19 refers to the required characteristics database 17A in the storage unit 17, for example, based on the information input in step S101, and acquires the required characteristics for the parts related to the material selection (step S102).

[0058] In step S102, the control unit 19 acquires secondary required characteristics necessary for the progress of this routine. In step S102, for example, the control unit 19 acquires primary required characteristics and secondary required characteristics based on the input part name. Also, for example, if primary required characteristics are input in step S101, the control unit 19 acquires secondary required characteristics based on the input primary required characteristics.

[0059] The secondary required characteristics acquired in step S102 may or may not be displayed on the output device 23. If they are displayed, the material selection process according to this routine is clearly presented to the user, which can assist in material selection.

[0060] In step S102, the control unit 19 functions as a required characteristic acquisition unit that executes a step (required characteristic acquisition step) of acquiring secondary required characteristic information as required characteristic information indicating required characteristics that are characteristics required for one part.

[0061] After executing step S102, the control unit 19 refers to, for example, the part quality characteristic database 17B based on the secondary required characteristics acquired in step S102, and extracts part quality characteristics, which are the characteristics of the part related to each required characteristic, for each required characteristic (step S103).

[0062] In step S103, the control unit 19 extracts secondary part quality characteristics necessary for the progress of this routine. In step S103, the control unit 19 extracts secondary part quality characteristics associated with each of the secondary required characteristics acquired in step S102, based on the part quality characteristic database 17B.

[0063] 7 shows the state in which the results of extracting part quality characteristics related to each required characteristic of the rearview mirror housing in step S103 are displayed on the output device 23. Note that the results of extracting part quality characteristics do not have to be displayed. If they are displayed, it will be clear to the user what part quality characteristics have been extracted in the material selection process by this routine, which can assist in material selection. For example, the display screen in FIG. 7 may be configured so that pressing a confirmation button will proceed to the next step.

[0064] In step S103, the control unit 19 functions as a part characteristic extraction unit that executes a step of extracting part quality characteristics, which are characteristics of parts related to each required characteristic, for each required characteristic (part characteristic extraction step).

[0065] After executing step S103, the control unit 19 extracts material quality characteristics, which are items related to the properties of materials associated with each of the part quality characteristics, based on the secondary part quality characteristics extracted in step S103, for example, by referring to the material quality characteristic database 17C (step S104).

[0066] In step S104, the control unit 19 extracts secondary material quality characteristics necessary for the progress of this routine. In step S104, the control unit 19 extracts, from the material quality characteristic database 17C, secondary material quality characteristics associated with each of the secondary part quality characteristics extracted in step S103.

[0067] The material quality characteristics extracted in step S104 are related to properties of interest or items to be tested for the part, and are items related to properties to be compared between multiple materials when selecting a material for the part.

[0068] FIG. 8 shows the state in which the results of extracting the material quality characteristics related to each of the part quality characteristics for the rearview mirror housing are displayed on the output device 23 in step S104.

[0069] In the example shown in Figure 8, for example, the deformation amount of a part when stress is applied is related to the tensile modulus and flexural modulus. In other words, to compare material properties that affect the deformation amount of a part when stress is applied between multiple materials, the tensile modulus and flexural modulus can be compared. Similarly, to compare material properties that affect the results of a drop impact test of a part, the test results of Charpy impact strength and tensile strain at break can be compared between multiple materials.

[0070] In this way, by executing step S104, the component quality characteristics are expanded into material quality characteristics, thereby making it possible to clarify the material quality characteristics that are important to the component. Expanding component quality characteristics into material quality characteristics often requires advanced specialized knowledge about components and materials. For example, a material quality characteristic database such as that shown in FIG. 4 can be created in advance under the supervision of an expert, and step S104 can be executed by the material selection assisting device 10 of this embodiment to automatically expand component quality characteristics into material quality characteristics.

[0071] In step S104, the control unit 19 functions as a material property extraction unit that executes a step (material property extraction step) of extracting material quality properties that are items related to the properties of materials associated with each of the part quality properties.

[0072] After executing step S104, the control unit 19 acquires material quality characteristic values, which are values ​​indicating each of the material quality characteristics of two or more candidate materials, from the material characteristic value DB17D, and generates information in a manner that allows the material quality characteristic values ​​to be compared between the two candidate materials (step S105).

[0073] In step S105, the control unit 19 generates information that allows perceptual comparison between a first characteristic value, which is a value indicating each of the material quality characteristics of one of the two or more candidate materials, and a second characteristic value, which is a value indicating each of the material quality characteristics of the other of the two or more candidate materials.

[0074] In step S105, specifically, visually comparable information is generated for the material quality characteristic values, which are values ​​indicating each of the material quality characteristics extracted in step S104, for the current material (X resin) and candidate material (Y resin) input in step S101.

[0075] Fig. 9 is a diagram showing an example of information generated in step S105 and displayed on the output device 23. Fig. 9 shows the material quality characteristic values ​​of two candidate materials, namely, resin X, which is the current material, and resin Y, which is a candidate material for material change, displayed in a manner that allows perceptual comparison.

[0076] More specifically, first characteristic values, which are values ​​indicating each of the material quality characteristics of X resin, the current material, and second characteristic values, which are values ​​indicating each of the material quality characteristics of Y resin, the candidate material for material change, are arranged in a manner that allows visual comparison for each item.

[0077] For example, a user of the material selection assisting device 10 of this embodiment can check the display shown in FIG. 9 and compare the material quality characteristic values ​​to consider whether to change from the current material to the candidate material.

[0078] In step S105, the control unit 19 functions as an information generating unit that executes a step of generating information in a manner that allows perceptual comparison between the first characteristic value and the second characteristic value (information generating step).

[0079] After executing step S105, the control unit 19 generates and outputs information indicating good points, which are material quality characteristic items for which the candidate material is superior to the current material, and bad points, which are material quality characteristic items for which the candidate material is inferior to the current material, for the material quality characteristic values ​​acquired in step S105 (step S106).

[0080] In step S106, the control unit 19 determines whether one candidate material (candidate material, Y resin) is superior or inferior to another candidate material (current material, X resin) for each item constituting the material quality characteristics where the first characteristic value and the second characteristic value deviate by more than a threshold value or a predetermined percentage, and generates information indicating the results of the determination for each material quality characteristic.

[0081] In the evaluation, items in which the candidate material is judged to be superior to the current material are given good points, while items in which the candidate material is judged to be inferior to the current material are given bad points.

[0082] In step S106, the control unit 19 may generate information indicating whether the deviation between the first characteristic value and the second characteristic value is greater than a predetermined degree.

[0083] FIG. 10 shows an example in which information indicating good points and bad points among the material quality characteristic items is displayed on the output device 23.

[0084] In the example shown in Fig. 10, whether the deviation between the first characteristic value and the second characteristic value is greater than a predetermined degree is also displayed. In Fig. 10, if the deviation is greater than the predetermined degree, "large deviation" is displayed, and if the deviation does not exceed the predetermined degree, "small deviation" is displayed.

[0085] For example, the predetermined degree is determined in advance for each item of material quality characteristics and stored in the storage unit 17 or an external database. Note that, for example, the degree of deviation is not limited to two levels, "large deviation" and "small deviation," but may be determined in three or more levels.

[0086] For example, a user of the material selection assistance device 10 of this embodiment can check the display shown in FIG. 10 and consider whether to change from the current material to the candidate material by comparing the material quality characteristic values ​​while taking into account the good points and bad points.

[0087] After executing step S106, the control unit 19 develops the good points determined in step S106 into merits of the part (step S107).

[0088] Fig. 11 shows an example of the results of expanding good points into merits as a part, displayed on the output device 23. The table shown in Fig. 11 lists, for each material quality characteristic item determined to be a good point, the change in characteristic value and merits as a part when the material of the part is changed from the current material to a candidate material.

[0089] In the table of FIG. 11, for example, when the values ​​of tensile strength, flexural strength, impact strength, and flexural modulus are large, the advantages are that there is a low risk of breakage and the thickness can be reduced to reduce weight.

[0090] In step S107, the control unit 19 reads out the merits of the part from an internal or external database of the material selection assist device 10, for example, based on the fact that the part being the subject of material selection is a mirror housing and on each of the material quality characteristic items that have been given good points. For example, the storage unit 17 or an external database may store the merits of the part with respect to the material quality characteristic items that have been given good points for each part.

[0091] In other words, in step S107, the control unit 19 as an information generating unit generates part advantage information, which is information that corresponds, for each item of the material quality characteristics that is determined to be a good point, the advantage that the part gains, i.e., the advantage that is brought to the part, by the excellence of that good point item for the material of the part.

[0092] For example, when selecting materials for automobile parts, it may be difficult for engineers at automobile companies and automobile part manufacturers to understand just by looking at the values ​​of the material quality properties. In such cases, if the benefits shown in Figure 11 are presented, it will be easier for them to understand the advantages of switching from the current material to the candidate material.

[0093] After executing step S107, the control unit 19 develops a Failure Mode and Effects Analysis (FMEA) for the bad points determined in step S106 (step S108).

[0094] In step S108, the control unit 19 as an information generating unit generates failure mode information indicating, for each of the bad point items, failure modes (failure modes) that may occur in the part for which material selection is being performed due to the items of material quality characteristics for which other candidate materials are inferior, i.e., items determined to be bad points.

[0095] Furthermore, in step S108, the failure mode information may include information indicating, for each bad point item, measures to avoid the failure mode of the component for which material selection is being made.

[0096] Fig. 12 shows an example of the information generated in step S108 displayed on the output device 23. In the example shown in Fig. 12, for each item of material quality characteristics determined to be a bad point, the change in characteristic value and the failure mode when the current material is changed to the candidate material are listed.

[0097] The example shown in Figure 12 shows the change in the possibility of failure mode occurring when measures are taken against failure mode. For example, for "weather resistance," one of the bad points in Figure 12, the possibility of failure mode occurring is medium, but taking measures minimizes the possibility.

[0098] For example, a user of the material selection assist device 10 of this embodiment can refer to the information generated in step S108 to determine whether or not a candidate material can be adopted depending on the contents of the Fehler mode, or to determine whether or not a candidate material that is difficult to adopt can be adopted if appropriate measures are taken. This makes it possible to prevent defects related to the material of the part. After executing step S108, the control unit 19 determines whether or not the candidate material can be adopted (step S109). In step S109, the control unit 19 determines whether or not the candidate material can be adopted based on the result of step S105 or the results of any of steps S106 to S108, and outputs the result. In step S109, for example, the control unit 19 determines whether or not the candidate material can be adopted using a predetermined determination criterion.

[0099] In step S109, for example, the control unit 19 compares the characteristic values ​​of the material quality characteristics acquired in step S105 between the current material and the candidate material, determines whether the candidate material is adoptable, and outputs the result.

[0100] In step S109, for example, the control unit 19 may compare the characteristic values ​​of each material quality characteristic between the current material and the candidate material, and determine whether or not to adopt the candidate material based on a judgment criterion that reflects the good points and bad points obtained in step S106, and output the result. The judgment criterion may be set based on, for example, the number of good points obtained by executing step S106, whether important material quality characteristics are not bad points, etc. For example, a judgment criterion may be set that a candidate material with a large number of good points is adopted.

[0101] Furthermore, in step S109, for example, the control unit 19 may determine whether or not to adopt the candidate material based on criteria that reflect the results up to step S106, as well as the merits of the part obtained in step S107 or the information on the Fehler mode obtained in step S108, and output the result.

[0102] In step S109, for example, the control unit 19 outputs whether the candidate material can be adopted for the current material. For example, in step S109, the adoptability of each of a plurality of candidate materials may be output, or one adoptable candidate material may be identified and output.

[0103] For example, the determination of whether or not a material can be adopted may be performed using a learning model. The learning model is a neural network constructed by deep learning, and inputs at least one result from steps S105 to S108, and outputs a determination result of whether or not a material can be adopted. For example, when a numerical value indicating at least one result from steps S105 to S108 for each of a plurality of candidate materials to be determined is input to the learning model, a numerical value indicating the candidate material that can be adopted is output.

[0104] After executing step S109, the control unit 19 ends the material selection assistance routine RT1.

[0105] The material selection assistance routine RT1 does not have to include step S109, and the user of the material selection assistance device 10 may determine whether or not a candidate material can be adopted. When the user determines whether or not a candidate material can be adopted, at least one of the results of steps S105 to S108 is displayed on the output device 23, as shown in FIGS. 9 to 12, for example, and the user determines whether or not a candidate material can be adopted based on the display.

[0106] Moreover, the material selection assistance routine RT1 may end at any one of steps S105 to S108.

[0107] Furthermore, the material selection method of the present invention can be executed manually for each step along the steps of the material selection assistance routine RT1. In this case, a user selecting a material using the material selection method manually performs, for example, referring to documents and databases, creating a correspondence table, etc., at each step.

[0108] Specifically, for example, after determining the conditions in step S101, the user may refer to the required characteristics database 17A as shown in FIG. 2 based on the determined conditions to identify the required characteristics for the parts related to the material selection (step S102 as the required characteristics identification step).

[0109] For example, in step S103, the user may refer to the part quality characteristic database 17B as shown in FIG. 3 to extract part quality characteristics related to the required characteristics acquired in step S102, and may further create a table of the extraction results (extraction table) as shown in FIG. 7.

[0110] In step S104, the user may refer to the material quality characteristic database 17C as shown in FIG. 4, extract material quality characteristics associated with each of the part quality characteristics, and create an extraction table.

[0111] For example, the databases shown in FIGS. 2 to 4 are not limited to electronic databases, and may be recorded on paper media, for example.

[0112] Then, in step S105, the user can obtain material quality characteristic values ​​for each of the material quality characteristics extracted in step S104, for example, from the material characteristic value DB17D, and compare the material quality characteristic values ​​between the two candidate materials. The user may select a material based on this comparison. For example, the user may decide whether to adopt a candidate material over the current material, or which of two or more candidate materials to adopt as the material for the part.

[0113] Furthermore, the user may select a material after appropriately performing steps S106 to S108. For example, in step S106, good points and bad points of each material quality characteristic are identified based on the characteristic values ​​obtained in step S105. Thereafter, for example, the good points may be developed into the merits of the part (step S107), and FMEA may be developed for the bad points (step S108), and a material may be selected based on the results of steps S106 to S108.

[0114] 13, a decision analysis step that is executed after step S105 of the material selection assistance routine RT1, instead of steps S106 to S108, or in parallel with steps S106 to S108, will be described. This step is particularly effective when narrowing down and selecting a material to be adopted from multiple candidate materials, for example.

[0115] Fig. 13 shows a table showing an example of information generated by the control unit 19 executing the decision analysis step, displayed on the output device 23. In the table shown in Fig. 13, material quality characteristic values ​​are listed for each of four candidate materials A to D.

[0116] The "W" in the table shown in Fig. 13 indicates a weighting factor set according to the relative importance of each item of material quality characteristics for the target part, and is expressed numerically with 10 being the most important. For example, in the example shown in Fig. 13, when the part is a rearview mirror housing, the tensile strength, flexural strength, Charpy impact strength, flexural modulus, weather resistance, and water absorption are relatively important, and the weighting factor W is set to a value of 10. In Fig. 13, for example, the linear expansion coefficient, MFR, and mold shrinkage rate are relatively less important, and the weighting factor W is set to a value of 2.

[0117] In addition, the "S" in the table shown in Figure 13 indicates a score assigned based on the relative merits of each candidate material for each material quality characteristic value, and is expressed numerically with 10 being the best.

[0118] In FIG. 13, "W*S" indicates the product of the value W and the value S, and the result of calculating the sum of "W*S" for each material is shown.

[0119] In the decision analysis step, the control unit 19 assigns a weighting factor "W" to each of the material quality characteristics extracted by the material characteristic extraction unit according to the relative importance of the material quality characteristic items. For each candidate material, the control unit assigns a score "S" to each of the material quality characteristic items based on the relative merits of a first characteristic value (the characteristic value of the first candidate material) and a second characteristic value (the characteristic value of the other candidate materials). The control unit 19 then calculates the product (W*S) of the weighting factor and the score for each of the material quality characteristic items for each candidate material. Furthermore, the control unit 19 calculates the sum of the products (W*S) calculated for the first candidate material and the other candidate materials, and generates information that allows perceptual comparison between two or more candidate materials based on the calculated results. Thus, in the decision analysis step, the control unit 19 functions as a decision analysis information generator.

[0120] When the decision analysis step is performed manually, the decision analysis step proceeds as follows: A weighting factor "W" is assigned to each of the material quality characteristics extracted by the material characteristic extraction unit in step S104 according to the relative importance of the material quality characteristic items. For each candidate material, a score "S" is assigned to each of the material quality characteristic items based on the relative merits between a first characteristic value for one candidate material and the second characteristic values ​​for the other candidate materials.

[0121] Next, the product (W*S) of the weighting factor and the score for each of the material quality characteristic items for each candidate material is calculated. By comparing the calculation results between two or more candidate materials, it is possible to quantitatively compare the superiority or inferiority of the materials as parts.

[0122] According to the decision analysis step, weighting is performed according to the importance of the material quality characteristics, so that comparisons can be made that reflect the importance of the material quality characteristics. The scoring method shown in Fig. 13 is based on the well-known KT (Kepner-Tregoe) decision analysis (DA) method.

[0123] The control unit 19 of the material selection assist device 10 executes a step of generating information shown in Fig. 13 after step S105 or step S106 of the material selection assist routine RT1, for example, and displays the information on the output device 23. This allows efficient selection of the optimum material by comparing numerical values ​​when narrowing down multiple materials from a wide range of candidates, such as in the development of a new part or resin.

[0124] In Figure 13, values ​​surrounded by solid lines indicate good points, and values ​​surrounded by dashed lines indicate bad points. In this way, by clearly displaying the good points and bad points obtained in step S106 together with the results of the decision analysis, the user can use the good points and bad points, along with the total score obtained by the decision analysis, to make a decision on material selection. This allows even an inexperienced user to easily understand important points to focus on when selecting materials.

[0125] For example, the good points and bad points may be displayed by highlighting or color coding, and may be color coded according to the importance of the degree of deviation of the characteristic values, for example.

[0126] For example, when determining whether or not a candidate material can be adopted in step S109, the control unit 19 may have a determination criterion that, for example, if the sum of the scores obtained by decision analysis is equal among multiple candidate materials, the control unit 19 determines that a material with many good points or a material with few bad points can be adopted.

[0127] For example, a user of the material selection method of the present invention can select a material taking into consideration such points as which material properties are good or bad points, and which candidate materials have the most good or bad points.

[0128] In the above steps, the control unit 19 functions as a decision analysis unit that performs analysis to determine the material to be adopted by assigning a weighting coefficient W and a score S, calculating the product of W and S, and calculating the sum of the products.

[0129] Furthermore, the control unit 19 as a decision analysis unit may determine which material should be adopted based on the magnitude of the sum of the products of W and S, and generate information indicating the determination result.

[0130] The material selection assisting device 10 of this embodiment can be used to consider whether or not to adopt candidate materials when changing materials, as well as to propose new materials and set target values. As described above, the material selection assisting device 10 of this embodiment can also be used to narrow down and select a material to be adopted from multiple candidate materials.

[0131] As described above, the material selection assistance device of this embodiment is a material selection assistance device that generates information presenting the characteristics to be compared between two or more candidate materials when considering the two or more candidate materials as materials for one part.

[0132] The material selection assistance device of this embodiment has a required characteristic acquisition unit that acquires required characteristic information that indicates required characteristics that are characteristics required of the part in question, a part characteristic extraction unit that extracts, for each required characteristic, part quality characteristics that are characteristics of the part related to the required characteristic, and a material characteristic extraction unit that extracts material quality characteristics that are items related to the characteristics of the material related to each of the part quality characteristics.

[0133] The material selection assistance device also has an information generation unit that generates information that allows for comparison between a first characteristic value, which is a value indicating each of the material quality characteristics of one of two or more candidate materials, and a second characteristic value, which is a value indicating each of the material quality characteristics of one or more other candidate materials of the two or more candidate materials.

[0134] With this configuration, the material selection assistance device of this embodiment can automatically develop from the required characteristics of a part to the part quality characteristics to the material quality characteristics, and can generate information in a form that allows perceptual comparison of the values ​​of material quality characteristics important to the part between multiple materials.

[0135] Therefore, it is possible to provide a material selection aid, a material selection method, a material selection aid method, a material selection aid program, and a recording medium that enable an accurate material selection taking into consideration the characteristics required for the part.

[0136] The material selection assistance device of this embodiment executes the material selection assistance method of this embodiment by executing the material selection assistance program of this embodiment, and generates information in a form that allows perceptual comparison of values ​​of material quality characteristics important to parts between multiple materials, i.e., information that can be used to assist in material selection. In addition, the material selection method of this embodiment can be performed manually.

[0137] The configurations and routines in the above-described embodiments are merely examples, and can be appropriately selected and modified depending on the application, etc.

[0138] In the above embodiment, the storage unit 17 stores the required characteristic DB 17A, the part quality characteristic DB 17B, the material quality characteristic DB 17C, and the material characteristic value DB 17D. However, the present invention is not limited to this. For example, at least some of these various databases may exist outside the material selection device of the present application, and different databases may be used depending on the selection conditions, such as the type of part or material for which material is to be selected. [Explanation of symbols]

[0139] 10 Material selection aid device 17 Memory section 17A Required characteristics DB 17B Parts quality characteristics DB 17C Material quality characteristics DB 17D Material property value DB 19 Control Unit

Claims

1. A material selection assistance device that generates information presenting characteristics to be compared between two or more candidate materials when two or more candidate materials are being considered as materials for one part, a required characteristic acquisition unit that acquires required characteristic information indicating required characteristics that are characteristics required for the one part; a part characteristic extraction unit that extracts, for each of the required characteristics, a part quality characteristic that is a characteristic of a part related to the required characteristic; a material characteristic extraction unit that extracts material quality characteristics that are items related to the characteristics of materials associated with each of the part quality characteristics; an information generating unit that generates information that allows perceptual comparison between a first characteristic value, which is a value indicating each of the material quality characteristics of one of the two or more candidate materials, and a second characteristic value, which is a value indicating each of the material quality characteristics of another of the two or more candidate materials; A material selection assisting device comprising:

2. The material selection assistance device according to claim 1, wherein the information generating unit determines whether the other candidate materials are superior or inferior to the one candidate material for each of the items constituting the material quality characteristics where the first characteristic value and the second characteristic value deviate from each other by more than a threshold value or a predetermined percentage, and generates information indicating the results of the determination for each of the material quality characteristics.

3. 3. The material selection assisting device according to claim 2, wherein the information indicating the result of the judgment includes information indicating whether a deviation between the first characteristic value and the second characteristic value is greater than a predetermined degree.

4. The material selection assistance device according to claim 2 or 3, characterized in that the information generation unit generates part advantage information, which is information that associates, for each of the material quality characteristics in which the other candidate materials are superior, the advantages that the part gains as a result of the material being superior in that item.

5. 5. The material selection assistance device according to claim 2, wherein the information generating unit generates failure mode information indicating, for each of the material quality characteristics in which the other candidate materials are inferior, a failure mode that may occur in the one part due to the inferior item of the material quality characteristics.

6. 6. The material selection assisting device according to claim 5, wherein the failure mode information includes information indicating, for each of the inferior items, measures to avoid the failure mode of the one part.

7. 1. A material selection assistance method executed by a material selection assistance device that generates information presenting characteristics to be compared between two or more candidate materials when considering the two or more candidate materials as materials for one component, comprising: a required characteristic acquisition step of acquiring required characteristic information indicating required characteristics that are characteristics required for the one part; a part characteristic extraction step of extracting, for each of the required characteristics, part quality characteristics that are part characteristics related to the required characteristics; a material characteristic extraction step of extracting material quality characteristics that are items related to physical properties of materials associated with each of the part quality characteristics; an information generating step of generating information that allows perceptual comparison between a first characteristic value, which is a value indicating each of the material quality characteristics of one of the candidate materials, and a second characteristic value, which is a value indicating each of the material quality characteristics of another of the candidate materials; A material selection assistance method comprising:

8. A material selection assistance program executed by a material selection assistance device having a computer, the material selection assistance program generating information presenting characteristics to be compared between two or more candidate materials when the two or more candidate materials are being considered as materials for one component, the program comprising: a required characteristic acquisition step of acquiring required characteristic information indicating required characteristics that are characteristics required for the one part; a part characteristic extraction step of extracting, for each of the required characteristics, part quality characteristics that are part characteristics related to the required characteristics; a material characteristic extraction step of extracting material quality characteristics that are items related to physical properties of materials associated with each of the part quality characteristics; an information generating step of generating information that allows perceptual comparison between a first characteristic value, which is a value indicating each of the material quality characteristics of one of the candidate materials, and a second characteristic value, which is a value indicating each of the material quality characteristics of another of the candidate materials; A material selection assistance program for carrying out the above.

9. A computer-readable recording medium storing the material selection assistance program according to claim 8.

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