Recommended material search system, recommended material search method, and program

Abstract

The present invention makes it possible to select a more appropriate recommended material in consideration of molding quality. A recommended material search system has one or more processors and one or more memory resources, the memory resources storing a material search program, the processors performing, by executing the material search program, a process for searching for recommended materials using predetermined physical property evaluation items and physical property values as search conditions, and a process for searching for the recommended materials using the predetermined physical property evaluation items and physical property values as search conditions. A recommendation order determination unit that determines a recommendation order of the recommended materials on the basis of a comparison of similarities between the molding quality of the recommended materials and the molding quality of a reference material; and outputting a retrieval result in which the recommendation sequence is associated with the recommendation material.

Description

Technical Field

[0001] The present invention relates to a recommended material retrieval system, a recommended material retrieval method, and a program. The present invention claims priority from Japanese Patent Application No. 2023-049551 filed on March 27, 2023, and the content described in the application is incorporated herein by reference for the designated countries permitted by document citation. Background Art

[0002] In recent years, the demand for plastics has a tendency to increase. On the other hand, it is expected that the production volume of new plastics derived from petroleum, which are exhausted resources, will decrease in the future, and the proportion of recycled plastics will increase significantly.

[0003] In addition, recently, the release of products using recycled materials in appearance parts and the like has increased, and the utilization of recycled materials has gradually become a new axis of competition.

[0004] However, it can be said that the current situation is that the methods and data for selecting candidate materials are insufficient compared to the rapidly increasing demand for recycled materials. Therefore, it is a problem that manufacturers and the like need to repeat trial production before adopting appropriate candidate materials, which takes a lot of time and cost.

[0005] In addition, Patent Document 1 discloses an auxiliary device for determining forming conditions for predicting the molten state of resin in a mold. Specifically, Patent Document 1 describes "comprising: a feature quantity generation unit that generates a group of feature quantities related to detection data based on detection data detected by a sensor installed in an injection molding machine during molding; an identification parameter value calculation unit that calculates a resin state identification parameter indicating the molten state of the resin corresponding to each feature quantity based on the group of feature quantities and a group of control parameter values; and a group acquisition unit that applies multivariate analysis using the resin state identification as an explanatory variable based on the resin state identification parameter value, thereby obtaining a group of the molten state of the resin".

[0006] Prior Art Documents

[0007] Patent Documents

[0008] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2021-191621 Summary of the Invention

[0009] Problems to be Solved by the Invention

[0010] With the activation of the utilization of recycled materials, it is expected that the proportion of applying recycled materials to the appearance parts of products will further increase in the future. On the other hand, when using recycled materials for appearance parts, compared with the case of using them for internal parts, the required specifications for dimensions and forming quality accuracy are higher. Therefore, if appropriate recycled materials corresponding to the required specifications cannot be selected, it may lead to a situation that cannot be handled in the adjustment at the injection molding stage.

[0011] In addition, the forming conditions of Patent Document 1 determine the auxiliary device to group the molten state of the resin in the cavity and determine the correction amount of the injection molding conditions corresponding to the group. However, the technology of this document relates to the determination of injection molding conditions and does not consider the selection of candidate materials at an earlier stage. Therefore, it is difficult to solve the above problems in the technology of Patent Document 1.

[0012] The present invention has been completed in view of the above problems, and its object is to be able to select more appropriate candidate materials considering the forming quality.

[0013] Means for Solving the Problems

[0014] This application includes a plurality of means for solving at least a part of the above problems. If an example is cited, it is as follows. The recommended material retrieval system according to one aspect of the present invention for solving the above problems has one or more processors and one or more memory resources. Among them, the memory resources store a material retrieval program. By executing the material retrieval program, the processor retrieves recommended materials using predetermined physical property evaluation items and physical property values as retrieval conditions; determines the recommendation order of the recommended materials based on the comparison of the similarity between the forming quality of the retrieved recommended materials and the forming quality of a reference material; and outputs a retrieval result in which the recommendation order is associated with the recommended materials.

[0015] Advantages of the Invention

[0016] According to the present invention, it is possible to select more appropriate recommended materials considering the forming quality.

[0017] In addition, problems, configurations, effects, etc. other than the above are clarified by the following description of the embodiments. Description of the Drawings

[0018] Figure 1 It is a diagram showing an example of the overall configuration of the recommended material retrieval system.

[0019] Figure 2 It is a diagram showing an example of the schematic configuration of the recommended material retrieval device.

[0020] Figure 3 It is a diagram showing an example of material information.

[0021] Figure 4 It is a diagram showing an example of physical property information.

[0022] Figure 5 It is a diagram showing an example of a mathematical formula and a graph for calculating fluidity.

[0023] Figure 6It is a flowchart showing an example of a recommended material retrieval process.

[0024] Figure 7 It is a flowchart showing an example of a similarity comparison process.

[0025] Figure 8 It is a diagram showing an example of data plotting of a reference material and a candidate material.

[0026] Figure 9 It is a diagram showing a distribution example of the forming quality of a reference material and a candidate material that have been standardized.

[0027] Figure 10 It is a diagram showing an example of the relationship between the Euclidean distance of a reference material and a candidate material and the similarity of forming quality. Detailed implementation manners

[0028] The following implementation manners are examples for explaining the present invention, and appropriate omissions and simplifications have been made for the sake of clarity of explanation. The present invention can also be implemented in various other ways. In addition, unless otherwise specifically limited, each component can be single or multiple.

[0029] In addition, for the sake of easy understanding of the invention, the positions, sizes, shapes, ranges, etc. of the respective components shown in the drawings sometimes do not represent the actual positions, sizes, shapes, ranges, etc. Therefore, the present invention is not necessarily limited to the positions, sizes, shapes, ranges, etc. disclosed in the drawings.

[0030] In addition, as examples of various information, expressions such as "table" and "list" are sometimes used for explanation, but various information can also be expressed by data structures other than these. For example, various information such as "** table" can also be set as "** information". In addition, when explaining identification information, expressions such as "identification information", "identifier", "name", "ID", and "number" are used, but they can be mutually replaced.

[0031] In addition, when there are multiple components having the same or similar functions, sometimes different subscripts are attached to the same reference numerals for explanation. In addition, when it is not necessary to distinguish these multiple components, sometimes the subscripts are omitted for explanation.

[0032] In addition, in the embodiments, the processing performed for executing a program may sometimes be described. Here, a computer executes a program through a processor (e.g., a CPU: Central Processing Unit (central processing unit), a GPU: Graphics Processing Unit (graphics processing unit)), and uses storage resources (e.g., memory resources), interface devices (e.g., communication ports), etc. to perform the processing determined by the program. Therefore, the entity performing the processing for executing the program may also be set as the processor.

[0033] Similarly, the entity performing the processing for executing the program may also be a controller, a device, a system, a computer, or a node having a processor. The entity performing the processing for executing the program only needs to be an arithmetic unit (processing unit), and may also include a dedicated circuit for performing specific processing. Here, the dedicated circuit is, for example, a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), a Complex Programmable Logic Device (CPLD), etc.

[0034] In addition, the program may also be installed on a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server includes a processor and a storage resource for storing the program to be distributed, and the processor of the program distribution server may also distribute the program to be distributed to other computers. In addition, in the embodiments, two or more programs may be implemented as one program, or one program may be implemented as two or more programs.

[0035] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0036] The recommended material retrieval system of the present embodiment includes a recommended material retrieval device and an external device, and is a system for retrieving a material having a high similarity in forming quality to a reference material as a recommended material. In addition, the recommended material retrieval system can retrieve various materials, but in the present embodiment, materials for injection molding (e.g., recycled materials such as resin materials and plastic materials) are taken as an example for description.

[0037] The recommended material retrieval system is used, for example, when a manufacturer attempts to change from the currently used material to another material (e.g., a recycled material), etc., to select a suitable candidate material (hereinafter sometimes referred to as "candidate material", "recommended material", or "recommended material") that can be used in the manufacture of the target product.

[0038] Specifically, the recommended material retrieval device accepts input, for example, using current materials used in the manufacture of products and materials considered for use as reference materials (hereinafter sometimes referred to as "reference materials"). In addition, after reducing candidate materials according to the physical property values that the retrieval user values, the recommended material retrieval device determines the recommended order of candidate materials in the order of the forming quality approaching the reference material, and outputs it as a retrieval result.

[0039] According to such a recommended material retrieval system, materials with a forming quality close to that of materials used in current products, etc. can be selected as candidate materials, and the retrieval results can be presented to manufacturers, etc. That is, this system can realize the selection of more appropriate recommended materials considering the forming quality.

[0040] <Overall Structure of Recommended Material Retrieval System 1000>

[0041] Figure 1 It is a diagram showing an example of the overall structure of the recommended material retrieval system 1000. As shown in the figure, the recommended material retrieval device 100, for example, obtains material data (such as material information, physical property information, etc.) from an external device 10 such as a computer of a material manufacturer or recycler, and stores it in a database. In addition, the recommended material retrieval device 100, for example, accepts a retrieval request for candidate materials from the computer of the manufacturer, that is, the external device 10. In addition, the recommended material retrieval device 100 retrieves appropriate candidate materials from the database using predetermined information (such as physical property information, forming quality information), and outputs a retrieval result with a recommended order based on the similarity to the reference material.

[0042] <Schematic Structure of Recommended Material Retrieval Device 100>

[0043] Figure 2 It is a diagram showing an example of the schematic structure of the recommended material retrieval device 100. As shown in the figure, the recommended material retrieval device 100 (processor system) is connected to the external device 10 in a communicable manner through a communication cable, a predetermined communication network (such as the Internet, LAN (Local Area Network), or WAN (Wide Area Network), etc.) N.

[0044] 《External Device 10》

[0045] The external device 10 is a device that sends various information to the recommended material retrieval device 100. In this case, the external device 10 is, for example, a computer of a material manufacturer or recycler, and sends material data (such as material information, physical property information, etc.) to the recommended material retrieval device 100.

[0046] In addition, the external device 10 is a device that makes a retrieval request to the recommended material retrieval device 100 or displays the retrieval results. In this case, the external device 10 corresponds to, for example, a computer of an operator such as a manufacturer who uses the retrieval service provided by this system.

[0047] Details of the Recommended Material Retrieval Device 100

[0048] The recommended material retrieval device 100 is a processor system that reads programs and various information stored in the memory resource 30 through the processor 20 to perform various processes. Specifically, the recommended material retrieval device 100 performs a recommended material retrieval process for retrieving recommended materials (candidate materials) similar to the forming quality of the reference material. In addition, the details of this process will be described later.

[0049] The recommended material retrieval device 100 is, for example, a server computer, a cloud server, or a personal computer, and is a system that includes at least one or more of these computers.

[0050] Specifically, the recommended material retrieval device 100 includes a processor 20, a memory resource 30, an NI (Network Interface Device) 40, and a UI (User Interface Device) 50.

[0051] The processor 20 is an arithmetic device that reads the program 210 stored in the memory resource 30 and executes the process corresponding to the program 210. In addition, examples of the processor 20 include a microprocessor 20, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), or other semiconductor devices capable of performing arithmetic operations.

[0052] The memory resource 30 is a storage device that stores various information. Specifically, the memory resource 30 is a non-volatile or volatile storage medium, such as a RAM (Random Access Memory) or a ROM (Read Only Memory). In addition, the memory resource 30 can also be a rewritable storage medium such as a flash memory, a hard disk, or an SSD (Solid State Drive), a USB (Universal Serial Bus) memory, a memory card, and a hard disk.

[0053] NI40 is a communication device that communicates information with an external device 10. NI40 communicates information with the external device 10 via a predetermined communication network N such as a LAN or the Internet, for example. Additionally, unless otherwise specified, hereinafter, it is recommended that the information communication between the recommended material retrieval device 100 and the external device 10 be executed via NI40.

[0054] UI50 is an input device for inputting instructions from a user (operator) to the recommended material retrieval device 100 and an output device for outputting information generated by the recommended material retrieval device 100 and the like. Examples of the input device include pointing devices such as a keyboard, a touch panel, and a mouse, and a voice input device such as a microphone.

[0055] Additionally, examples of the output device include a display, a printer, and a voice synthesis device. Furthermore, unless otherwise specified hereinafter, it is assumed that operations by the user on the recommended material retrieval device 100 (such as input, output, and execution instructions for processing information) are executed via UI50.

[0056] Moreover, each structure, function, processing unit, etc. of the recommended material retrieval device 100 can also be implemented in part or in whole by hardware, for example, by designing using an integrated circuit. Additionally, the recommended material retrieval device 100 can implement part or all of each function by software, or can be implemented by the cooperation of software and hardware. Furthermore, the recommended material retrieval device 100 can use hardware with fixed circuits, or can use hardware capable of changing at least a part of the circuit.

[0057] In addition, the recommended material retrieval device 100 can also implement the system by a user (operator) performing part or all of the functions and processes implemented by each program.

[0058] Furthermore, the program executed by the recommended material retrieval device 100 can also be stored in a non-volatile storage medium readable by the device. The program stored in the non-volatile storage medium can be directly read by the recommended material retrieval device 100, but the program can also be read from the medium by a processor system for program distribution, and then sent (distributed) from the processor system for program distribution to the recommended material retrieval device 100. Examples of the non-volatile storage medium can include the non-volatile memory described as the memory resource 30, but can also be other optical disc media.

[0059] <<< Material Information DB110 >>>

[0060] The material information DB110 is a database that stores material information. In the material information, information related to various materials (including raw materials or recycled materials) used to manufacture products is registered. Specifically, in the material information, identification information 110a, material name / type 110b, model 110c, material manufacturer 110d, lot number 110e, and ratio 110f are correspondingly registered.

[0061] Figure 3 It is a diagram showing an example of material information. Here, the identification information 110a is information for uniquely identifying the materials of each record registered in the material information. The name / type 110b is information indicating the name and type of the material (for example, the type of resin material or plastic material). The model 110c, material manufacturer 110d, and lot number 110e are information indicating the model of the material, the material manufacturer, and the lot number respectively. The ratio 110f is, for example, information indicating the ratio of raw materials to recycled materials.

[0062] In addition, even for materials of the same type, different models, grades, etc. are assigned according to the material manufacturer, and their physical properties are also different from each other. Therefore, even for materials of the same type, materials of different models and grades are registered as different types of materials in the material information.

[0063] <<<Physical property information DB120>>>

[0064] The physical property information DB120 is a database that stores physical property information. In the physical property information, the physical property values of each material are registered. Specifically, in the physical property information, identification information 120a, material name / type 120b, material manufacturer 120c, and physical property value 120d are correspondingly registered.

[0065] Figure 4 It is a diagram showing an example of physical property information. Here, the identification information 120a is information for uniquely identifying the material, corresponding to the identification information of the material information. The name / type 120b and material manufacturer 120c are information indicating the name and type of the material and the material manufacturer respectively.

[0066] In addition, the physical property value 120d is information related to the physical properties of each material. For example, physical properties such as mechanical properties and thermal properties and their values are registered. Here, mechanical properties include, for example, elastic modulus, tensile strength, and impact properties, and thermal properties include, for example, crystallization temperature, melting temperature, and heat distortion temperature. In addition, these physical properties are just an example. In the physical property information, various types of physical properties and their values are registered in addition to the above examples.

[0067] <<<Forming quality information DB130>>>

[0068] The forming quality information DB 130 is a database that stores forming quality information. The forming quality information includes information related to forming quality, such as material fluidity (viscosity characteristics) and shrinkage. In this embodiment, fluidity and shrinkage are used as examples of forming quality for the following description.

[0069] Flowability is information indicating the flowability of a material and is calculated based on the output of a pressure sensor when, for example, a test piece is produced using an injection molding machine. Shrinkage is information indicating the shrinkage of a material and is obtained, for example, based on dimensional measurements of a test piece.

[0070] Such trial production is performed multiple times (eg, 10 times) for each combination of material type, model, material manufacturer, and lot number, and values related to fluidity and shrinkage are registered in the molding quality information each time.

[0071] Figure 5 This is a diagram showing an example of a mathematical formula and a graph for calculating fluidity (viscosity characteristic quantity). The graph shown in the figure shows that the start time t of the speed control is int To the end time t vend The interval control is fixed speed, at t vend The relationship between the sensor pressure P and time t when the pressure is variable is then controlled. index ) is the speed control interval (from t int to t vend The value of fluidity (viscosity characteristic quantity) is calculated based on the following formula (1).

[0072] [Formula 1]

[0073]

[0074] Here, P(t) represents the sum of the sensor pressures that change over time t.

[0075] Furthermore, the values of fluidity and shrinkage are registered in the molding quality information in association with the material identification information (corresponding to the identification information of the material information) and the number of trial productions (for example, the nth time).

[0076] <<<Environmental information DB140>>>

[0077] Environmental information DB 140 is a database that stores environmental information. In addition, information related to environmental load, such as information indicating carbon dioxide emissions, is registered in the environmental information. Specifically, information related to environmental load and material identification information (corresponding to the identification information of the material information) are registered in association with each other.

[0078] <<<Material Retrieval Program 211>>>

[0079] The material retrieval program 211 is a program for retrieving recommended materials (candidate materials). Specifically, the material retrieval program 211 performs a recommended material retrieval process. More specifically, the material retrieval program 211 retrieves candidate materials from a database and outputs a retrieval result with a recommended order based on the similarity of the forming quality to a reference material.

[0080] The above describes the details of the recommended material retrieval device 100.

[0081] <Explanation of Processing>

[0082] Figure 6 It is a flowchart showing an example of the recommended material retrieval process. When the recommended material retrieval device 100 receives a retrieval request for recommended materials from the external device 10, this process is executed by the processor 20 that has read in the material retrieval program 211.

[0083] When the process starts, the processor 20 receives the input of the reference material from the external device 10 (step S10). Specifically, the processor 20 receives the input of the name / type of the reference material from, for example, the retrieval user of the external device 10.

[0084] Next, the processor 20 obtains the material information, etc. of the reference material for which the input has been received (step S20). Specifically, the processor 20 allocates the corresponding material information from the material information DB110 based on the name / type of the input reference material. In addition, the processor 20 obtains the corresponding physical property information and forming quality information from the physical property information DB120 and the forming quality information DB130 respectively based on the identification information 110a of the allocated material information.

[0085] Next, the processor 20 receives the selection of physical property evaluation items and the input of evaluated physical property values (step S30). Specifically, the processor 20 receives the selection of physical property evaluation items that the retrieval user values from, for example, multiple physical property evaluation items corresponding to the physical property values 120d in the physical property information of the reference material, such as the elastic modulus in mechanical properties and the crystallization temperature in thermal properties. For example, when the physical property values 120d in the physical property information of the reference material are registered with the elastic modulus, tensile strength, and melting temperature, the processor 20 receives the selection of the physical property evaluation items that the retrieval user values (for example, the tensile strength and the melting temperature) from among them.

[0086] In addition, the processor 20 receives the input of evaluated physical property values for the selected physical property evaluation items. For example, when the elastic modulus and the crystallization temperature are selected as the physical property evaluation items, the processor 20 receives the numerical ranges of the elastic modulus and the crystallization temperature that the retrieval user desires (allows) as the evaluated physical property values.

[0087] Next, the processor 20 determines the search conditions for the candidate materials (step S40). Specifically, the processor 20 determines the physical property evaluation items and the evaluated physical property values for which the input has been received as the search conditions for the candidate materials. In addition, the processor 20 may include the type of reference material in the search conditions. By including the type of reference material as a search condition, the processor 20 can narrow down the search range to a narrower range and reduce the processing load.

[0088] Next, the processor 20 searches for candidate materials (step S50). Specifically, the processor 20 searches the physical property information DB120 and the material information DB110 based on the search conditions, and determines candidate materials that satisfy the search conditions. In addition, usually multiple candidate materials that satisfy the search conditions are determined.

[0089] Next, the processor 20 performs a similarity comparison process (step S60). Specifically, the processor 20 compares the similarity between the two based on the Euclidean distance between the reference material and the candidate materials.

[0090] Figure 7 FIG. is a flowchart showing an example of the similarity comparison process. First, the processor 20 generates data plots of the reference material and the candidate materials (step S061). Specifically, the processor 20 generates data plots of the reference material and the candidate materials according to predetermined quality evaluation items. More specifically, the processor 20 generates data plots with the shrinkage of the reference material and the candidate materials respectively as quality evaluation item 1 (horizontal axis) and the fluidity as quality evaluation item 2 (vertical axis).

[0091] Figure 8 FIG. is a diagram showing an example of the data plots of the reference material and the candidate materials. As shown in the figure, even if the reference material and the candidate materials are materials within the same lot number, there are some deviations in the forming quality measured each time. Therefore, the data plots are represented by a point group showing the deviations (distributions) of the forming quality of the reference material and the candidate materials respectively.

[0092] Next, the processor 20 standardizes the reference material and the candidate materials based on statistical quantities (step S062). The data plots are data with inconsistent absolute values etc. because the values of the quality evaluation items in different types of materials are represented by a point group. Therefore, the processor 20 uses the data plots and standardizes them based on statistical quantities such as the average value and standard deviation of the reference material and the candidate materials.

[0093] In addition, the following formulas (2) and (3) are used to perform the standardization.

[0094] [Equation 2]

[0095]

[0096] In addition, "X’" Ai " represents the position of the candidate material A in the horizontal axis direction after standardization. In addition, "X" Ai " represents the plotting position of the candidate material A in the horizontal axis direction before standardization. In addition, "Xo" represents the average value of the reference material in the horizontal axis direction before standardization. In addition, "σ" xo " represents the standard deviation of the reference material in the horizontal axis direction before standardization.

[0097] [Equation 3]

[0098]

[0099] In addition, "Y’" Ai " represents the position of the candidate material A in the vertical axis direction after standardization. In addition, "Y" Ai " represents the plotting position of the candidate material A in the vertical axis direction before standardization. In addition, "Yo" represents the average value of the reference material in the vertical axis direction before standardization. In addition, "σ" yo " represents the standard deviation of the reference material in the vertical axis direction before standardization.

[0100] In addition, Equations (2) and (3) are also used for the standardization of other candidate materials in the same manner.

[0101] Figure 9 is a diagram showing a distribution example of the forming quality of the reference material and candidate materials for standardization. Through standardization, the deviation of the forming quality of the reference material and each candidate material is quantified and made comparable to each other.

[0102] Next, the processor 20 calculates the Euclidean distance for similarity comparison (step S063). Specifically, the processor 20 calculates, for example, the Euclidean distance between the point group (cluster) of the reference material and the point group (cluster) of the candidate material using a known method such as the group average method. In addition, the calculation of the Euclidean distance d is performed using the following Equation (4).

[0103] [Equation 4]

[0104]

[0105] In addition, the above Equation (4) represents the sum of the distances of all the plotted points for standardization. Here, n represents the number of plots of the candidate material A. In addition, m represents the number of plots of the reference material. i and j are subscripts representing a certain point of the sum. In addition, Equation (4) is also used in the case of other candidate materials.

[0106] ​Next, the processor 20 compares the similarity between the reference material and the candidate materials (step S64). Specifically, the processor 20 compares the similarity between the reference material and each candidate material based on the magnitude of the Euclidean distance. More specifically, the closer the Euclidean distance, the higher the similarity evaluated by the processor 20. This is because the similarity is proportional to the Euclidean distance between the reference material and the recommended material that can be compared by standardizing the forming quality.

[0107] In addition, the processor 20 determines the recommendation order of the candidate materials based on the comparison of the similarities (step S65). Specifically, the processor 20 determines the recommendation order of the candidate materials by assigning high recommendation orders in descending order of similarity.

[0108] Figure 10 It is a diagram showing an example of the relationship between the Euclidean distance of the reference material and the candidate materials and the similarity of the forming quality. In the illustrated example, it is shown that the Euclidean distances to the reference material are close in the order of candidate materials B, C, and A. In this case, the processor 20 evaluates that the similarity of the reference material to the forming quality is high in the order of candidate materials B, C, and A, and determines the recommendation order of each candidate material in this order.

[0109] Moreover, after determining the recommendation order, the processor 20 moves the process to step S70 ( Figure 6 ).

[0110] Next, the processor 20 calculates the environmental impact degree based on the environmental information (step S70). Specifically, the processor 20 determines the corresponding environmental information according to the identification information of the candidate material. In addition, the processor 20 uses the determined environmental information to calculate the environmental impact degree related to a predetermined environmental load, such as the carbon dioxide emission amount. In addition, the environmental impact degree may also be the value itself related to the environmental load registered in the environmental information.

[0111] Next, the processor 20 outputs the search result (step S80). Specifically, the processor 20 generates a search result that associates the material information of each candidate material with the recommendation order, and outputs (sends) it to the computer of the search user. In addition, the processor 20 may also include the physical property information and the forming quality information of the candidate materials in the search result.

[0112] In addition, after outputting the search result, the processor 20 ends the processing of this flow.

[0113] The above has described the recommended material search process.

[0114] According to such a recommended material search system, it is possible to select a more appropriate recommended material considering the forming quality.

[0115] In particular, in the recommended material retrieval system, the recommended material retrieval device quantifies the deviations in forming qualities such as fluidity and shrinkage, and determines the recommendation order by comparing the similarity between the benchmark material after benchmarking and the candidate materials. Therefore, according to the recommended material retrieval system, it is possible to retrieve recommended materials with appropriate forming qualities similar to those of the benchmark material.

[0116] Moreover, in the retrieval results, information indicating the environmental load is attached to the recommended materials, so that the retrieval user can also select a suitable material with reference to the environmental load.

[0117] In addition, the recommended material retrieval device 100 may also attach the cost of the recommended materials to the retrieval results. Information related to the cost can be managed, for example, in association with various materials of the material information. According to such a recommended material retrieval system, the retrieval user can select a suitable material with reference to the cost of the recommended materials in addition to the similarity to the benchmark material and the environmental load.

[0118] Furthermore, the present embodiment is not limited to the above, and various modifications can be made. For example, in the foregoing embodiment, it has been described on the premise that the material information DB110, the physical property information DB120, the forming quality DB, and the environmental information DB140 are pre-stored in the memory resource 30, but these databases can also be stored in other computers (for example, cloud servers). That is, in the recommended material retrieval system 1000 in this case, the structure includes a computer (cloud server) storing the databases.

[0119] In this case, when the recommended material retrieval device 100 executes the recommended material retrieval process, it retrieves and obtains the target material information, physical property information, forming quality information, and environmental information from the databases of the computer (cloud server).

[0120] According to the recommended material retrieval system with such a structure, it is also possible to select a more appropriate recommended material considering the forming quality.

[0121] In addition, the present invention is not limited to the above-described embodiments, modification examples, etc., and further includes various embodiments and modification examples. For example, the above-described embodiments are embodiments described in detail for easy understanding of the present invention, and are not limited to having all the structures described. In addition, a part of the structure of a certain embodiment can be replaced with the structure of other embodiments or modification examples, and the structure of other embodiments can also be added to the structure of a certain embodiment. In addition, with respect to a part of the structure of each embodiment, addition, deletion, and replacement of other structures can be performed.

[0122] In addition, in the above description, the control lines and information lines represent the lines considered necessary for the description, and not all of the control lines and information lines may be represented on the product. In fact, it can be considered that almost all structures are interconnected.

[0123] Symbol Explanation

[0124] 1000... Recommended material retrieval system, 100... Recommended material retrieval device, 110... Material information DB, 120... Physical property information DB, 130... Forming quality information DB, 140... Environment information DB, 210... Program, 211... Material retrieval program, 20... Processor, 30... Memory resource, 40... NI (Network interface device), 50... UI (User interface device), 10... External device, N... Network.

Claims

1. A recommended material retrieval system having one or more processors and one or more memory resources, characterized in that, the memory resources store a material retrieval program, by executing the material retrieval program, the processor retrieves recommended materials using predetermined physical property evaluation items and physical property values as retrieval conditions, determines the recommendation order of the recommended materials based on a comparison of the similarity of the forming quality of the retrieved recommended materials with that of a reference material, and outputs a retrieval result in which the recommendation order is associated with the recommended materials.

2. The recommended material retrieval system according to claim 1, characterized in that, the forming quality is information indicating the fluidity and shrinkage of the recommended material and the reference material.

3. The recommended material retrieval system according to claim 1, characterized in that, the processor standardizes the recommended materials and the reference material based on the statistic of the forming quality, and compares the similarity between the standardized recommended materials and the reference material.

4. The recommended material retrieval system according to claim 3, characterized in that, the processor compares the similarity based on the Euclidean distance between the clusters of the standardized recommended materials and the clusters of the reference material. The closer the Euclidean distance, the higher the similarity is evaluated. A higher recommendation order is given to the recommended materials with a high similarity to the reference material.

5. The recommended material retrieval system according to claim 1, characterized in that, the processor calculates the environmental load of the recommended materials and includes it in the retrieval result.

6. The recommended material retrieval system according to claim 1, characterized in that, the processor accepts the selection of corresponding physical property evaluation items and the input of physical property values from the physical property information related to the reference material to retrieve the recommended materials.

7. The recommended material retrieval system according to claim 1, characterized in that, the reference material is the current material used in the product or the material intended to be used, and the recommended material is a recycled material.

8. A recommended material retrieval method performed by a recommended material retrieval system having one or more processors and one or more memory resources, characterized in that, the memory resources store a material retrieval program, by executing the material retrieval program, the processor performs the following steps: retrieving recommended materials using predetermined physical property evaluation items and physical property values as retrieval conditions; determining the recommendation order of the recommended materials based on a comparison of the similarity of the forming quality of the retrieved recommended materials with that of a reference material; and outputting a retrieval result in which the recommendation order is associated with the recommended materials.

9. The recommended material retrieval method according to claim 8, characterized in that, when determining the recommendation order of the recommended materials, the processor performs the following steps: standardizing the recommended materials and the reference material based on the statistic of the forming quality; and comparing the similarity between the standardized recommended materials and the reference material.

10. The recommended material retrieval method according to claim 9, characterized in that, In the step where the processor determines the recommendation order of the recommended materials, a step of comparing the similarity based on the Euclidean distance between the clustering of the benchmarked recommended materials and the clustering of the reference materials is performed. The closer the Euclidean distance is, the higher the similarity is evaluated. A higher recommendation order is given to the recommended materials with a high similarity to the reference materials.

11. A program read and executed by a processor of a recommended material retrieval system having one or more processors and one or more memory resources, characterized in that the memory resources store a material retrieval program, the material retrieval program executed by the processor retrieves recommended materials using predetermined physical property evaluation items and physical property values as retrieval conditions, determines the recommendation order of the recommended materials based on a comparison of the similarity between the forming quality of the retrieved recommended materials and the forming quality of a reference material, and outputs a retrieval result in which the recommendation order is associated with the recommended materials.

12. The program according to claim 11, characterized in that the material retrieval program executed by the processor benchmarks the recommended materials and the reference materials based on the statistic of the forming quality, and compares the similarity between the benchmarked recommended materials and the reference materials.

13. The program according to claim 12, characterized in that the material retrieval program executed by the processor compares the similarity based on the Euclidean distance between the clustering of the benchmarked recommended materials and the clustering of the reference materials. The closer the Euclidean distance is, the higher the similarity is evaluated. A higher recommendation order is given to the recommended materials with a high similarity to the reference materials.

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