Material Search Support Device, Method, and Program

Abstract

This material search support device: acquires product information for each of a plurality of products, the product information being collected from documents on the Internet, and including basic configuration information relating to the product, a compounding ratio of materials contained in the product, and specific information including at least one of a physical property of the product, a biomass content of the product, and process conditions when the product is used; on the basis of the acquired product information, estimates one or more candidates of the material compounding ratio and the specific information with respect to the basic configuration information of a designated product, by using an estimation model trained to estimate the material compounding ratio and the specific information with respect to the basic configuration information of the product; calculates an environmental impact index for each estimated candidate on the basis of the material compounding ratio and the specific information indicated by each candidate; and outputs support information in which each candidate is associated with the environmental impact index calculated by a calculating unit.

Description

Technical Field

[0001] The present disclosure relates to a material search support device, a material search support method, and a material search support program.

Background Art

[0002] In response to the recent global warming problem, there is a demand for carbon neutrality in product production. For example, the use of bio-based resources (biomass) as product materials is being promoted.

[0003] As a technology related to the use of biomass, a biomass effective utilization support system that can efficiently process biomass has been proposed. This system inputs the type and input amount of input biomass selected from the group consisting of sewage sludge, livestock manure, waste wood, food waste, and other wastes, respectively. In addition, this system pre-registers the unique characteristic data of equipment including a pretreatment device, an anaerobic digester, a dehydrator, a heat exchanger, an incinerator, and a generator, selects at least one of the registered equipment, and constructs a biomass treatment flow. Then, this system calculates at least one of the water quality of the wastewater generated when processing biomass with the set equipment configuration and treatment flow, the amount of waste generated, the amount of biogas generated, the amount of energy that can be recovered from the biogas or the amount of power generation energy that can be generated, and the running cost required when operating the treatment facility.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In addition to using bio-based materials as the materials constituting the product, there are factors that can contribute to carbon neutrality. Considering these factors, there is a desire to search for appropriate materials to be used in the production of the product.

[0006] An object of the present disclosure is to provide a material search support device, method, and program that can assist in searching for appropriate materials corresponding to carbon neutrality.

Means for Solving the Problems

[0007] To achieve the above object, a material search support device according to the present disclosure includes, for each of a plurality of products, product information collected from documents on the Internet, including basic configuration information of the product, a mixing ratio of materials included in the product, physical properties of the product, the biomass degree of the product, and specific information including at least one of process conditions during use of the product; an acquisition unit that acquires the product information; an estimation unit that estimates one or more candidates for the mixing ratio of materials and specific information for the basic configuration information of a designated product using an estimation model trained to estimate the mixing ratio of materials and specific information for the basic configuration information of the product based on the product information acquired by the acquisition unit; a calculation unit that calculates an environmental load index based on the mixing ratio of materials and specific information indicated by each of the candidates estimated by the estimation unit; and an output unit that outputs support information associating each of the candidates with the environmental load index calculated by the calculation unit. Thereby, it is possible to assist in searching for appropriate materials corresponding to carbon neutrality.

[0008] Further, the acquisition unit may extract information related to keywords corresponding to the product information from the document and acquire it as the product information.

[0009] Further, the document may include at least one of patent documents and public information of enterprises including catalogs.

[0010] Further, the material search support device may include a collection unit that collects the documents from the Internet.

[0011] Further, the basic configuration information of the product may include the schematic configuration of the product and the types of materials used.

[0012] Further, the calculation unit may calculate the carbon dioxide emissions related to the product when the mixing ratio of the material indicated by the candidate and the specific information are adopted as the environmental load index.

[0013] Further, the output unit may output support information ranking the candidates with the top predetermined number of the environmental load indexes.

[0014] Further, the output unit may add and output information searched on the Internet based on the document corresponding to the product information, the related information extracted from the document, or the support information to the support information.

[0015] Further, the material search support device may include a training unit that trains the estimation model based on the product information acquired by the acquisition unit.

[0016] In addition, the material search support method according to the present disclosure is a method executed by a material search support device including an acquisition unit, an estimation unit, a calculation unit, and an output unit. The acquisition unit acquires, for each of a plurality of products, product information collected from documents on the Internet, the product information including basic configuration information of the product, a blending ratio of materials included in the product, physical properties of the product, a biomass degree of the product, and specific information including at least one of process conditions during use of the product. The estimation unit uses an estimation model trained to estimate a blending ratio of materials and specific information with respect to the basic configuration information of a product based on the product information acquired by the acquisition unit, and estimates one or more candidates for the blending ratio of materials and specific information with respect to the basic configuration information of a designated product. The calculation unit calculates an environmental load index for each of the candidates estimated by the estimation unit based on the blending ratio of materials and specific information indicated by each of the candidates. The output unit outputs support information associating each of the candidates with the environmental load index calculated by the calculation unit.

[0017] In addition, the material search support program according to the present disclosure causes a computer to function as an acquisition unit that acquires, for each of a plurality of products, product information collected from documents on the Internet, the product information including basic configuration information of the product, a blending ratio of materials included in the product, physical properties of the product, a biomass degree of the product, and specific information including at least one of process conditions during use of the product; an estimation unit that uses an estimation model trained to estimate a blending ratio of materials and specific information with respect to the basic configuration information of a product based on the product information acquired by the acquisition unit, and estimates one or more candidates for the blending ratio of materials and specific information with respect to the basic configuration information of a designated product; a calculation unit that calculates an environmental load index for each of the candidates estimated by the estimation unit based on the blending ratio of materials and specific information indicated by each of the candidates; and an output unit that outputs support information associating each of the candidates with the environmental load index calculated by the calculation unit. [Advantages of the Invention]

[0018] According to the material search support device, method, and program according to the present disclosure, it is possible to support the search for appropriate materials corresponding to carbon neutrality.

Brief Description of the Drawings

[0019]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Modes for Carrying Out the Invention

[0020] Hereinafter, an example of the present embodiment will be described with reference to the drawings.

[0021] FIG. 1 is a block diagram showing the hardware configuration of the material search support device 10. As shown in FIG. 1, the material search support device 10 includes a CPU (Central Processing Unit) 12, a memory 14, a storage device 16, an input device 18, an output device 20, a storage medium reader 22, and a communication I / F (Interface) 24. Each configuration is connected to be communicable with each other via a bus 26.

[0022] The memory device 16 stores a material search support program for executing training processing and support processing related to the material search support method described later. The CPU 12 is a central processing unit that executes various programs and controls each component. That is, the CPU 12 reads a program from the memory device 16 and executes the program using the memory 14 as a work area. The CPU 12 performs control of each of the above components and various arithmetic processes according to the program stored in the memory device 16.

[0023] The memory 14 is composed of a RAM (Random Access Memory) and temporarily stores programs and data as a work area. The memory device 16 is composed of a ROM (Read Only Memory), HDD (Hard Disk Drive), SSD (Solid State Drive), etc., and stores various programs including an operating system and various data.

[0024] The input device 18 is a device for performing various inputs, such as a keyboard and a mouse. The output device 20 is a device for outputting various information, such as a display and a printer. By adopting a touch panel display as the output device 20, it may function as the input device 18.

[0025] The storage medium reader 22 reads data stored in various storage media such as a CD (Compact Disc)-ROM, DVD (Digital Versatile Disc)-ROM, Blu-ray Disc, USB (Universal Serial Bus) memory, etc., and writes data to the storage medium. The communication I / F 24 is an interface for communicating with other devices, and standards such as Ethernet (registered trademark), FDDI, or Wi-Fi (registered trademark) are used.

[0026] As shown in FIG. 2, the material search support device 10 is connected to the collection device 30 via a network.

[0027] The collection device 30 collects documents related to product information (details will be described later) from the Internet for each of a plurality of products. The documents are, for example, patent documents, public information of companies including catalogs, etc.

[0028] Specifically, the collection device 30 searches for and collects documents containing keywords related to product information on the Internet. For example, the collection device 30 collects documents containing information on specific formulation systems such as examples and comparative examples related to the product. The documents to be collected may be the entire document or those obtained by extracting appropriate parts from the document. In the latter case, for example, the collection device 30 may collect the information described in a specific item column as the collection information for documents whose formats have been specified in advance, such as patent documents. The collection device 30 inputs the collected documents to the material search support device 10.

[0029] Next, the functional configuration of the material search support device 10 will be described. As shown in FIG. 2, the material search support device 10 includes, as functional components, an acquisition unit 32, a training unit 34, an estimation unit 36, a calculation unit 38, and an output unit 40. Also, a product information DB (database) 42 and an estimation model 44 are stored in a predetermined storage area of the material search support device 10. Each functional component is realized by the CPU 12 reading out the material search support program stored in the storage device 16, expanding it in the memory 14, and executing it.

[0030] The acquisition unit 32 acquires the documents for each of a plurality of products collected by the collection device 30. Also, the acquisition unit 32 extracts product information from the acquired documents and stores it in the product information DB 42. The product information includes at least one of the basic configuration information of the product, the mixing ratio of the materials contained in the product, the physical properties of the product, the biomass degree of the product, and the process conditions during use of the product, and specific information. The product basic configuration information is the schematic configuration of the product (for example, the layer configuration in the case of a semiconductor device), the types of materials used, etc.

[0031] Specifically, the acquisition unit 32 extracts information related to keywords corresponding to product information from the documents acquired from the collection device 30, and acquires it as product information. Keywords regarding the blending ratio of materials may be, for example, component names such as epoxy, acrylate, filler, and curing accelerator, and content. Also, keywords regarding physical properties may be, for example, glass transition point, linear expansion coefficient, elastic modulus, etc., and reliability tests such as humidity and heat resistance tests like high temperature and high humidity storage tests, temperature cycle tests, and accelerated degradation tests. Also, keywords regarding biomass content may be, for example, keywords related to the ratio of carbon derived from biomass raw materials contained in raw materials or products. Also, keywords regarding process conditions may be, for example, keywords related to the temperature, time, pressure during use of the product, temperature during storage or transportation, and lifetime.

[0032] The acquisition unit 32 stores the acquired product information in the product information DB 42. FIG. 3 shows an example of the product information DB 42. In the example of FIG. 3, product information such as "blending ratio of materials", "physical properties", "biomass content", and "process conditions" is stored in association with the "basic configuration information" of the product. Note that the data structure of the product information DB 42 is an example, and it may be structured in a format applicable to the training of the estimation model 44 described later.

[0033] The training unit 34 trains the estimation model 44 to estimate the blending ratio and specific information of materials for the basic configuration information of the product based on the product information stored in the product information DB 42. The estimation model 44 may be a machine learning model or an interface such as material informatics or statistical analysis software. The training unit 34 stores the trained estimation model 44 in a predetermined storage area of the material search support device 10.

[0034] The estimation unit 36 estimates one or more candidates for the blending ratio and specific information of materials for the basic configuration information of the designated product using the estimation model 44. Specifically, the estimation unit 36 receives a designation of the basic configuration information of the product to be produced from the user. The estimation unit 36 inputs the received basic configuration information into the estimation model 44 and acquires one or more candidates for the blending ratio and specific information of materials output from the estimation model 44.

[0035] The calculation unit 38 calculates an environmental load index for each of the candidates estimated by the estimation unit 36 based on the blending ratio of the materials indicated by each of the candidates and the specific information. Specifically, the calculation unit 38 calculates the LCA (Life Cycle Assessment) value for the product when the blending ratio of the materials indicated by the candidate and the specific information are adopted in the designated basic configuration information. The LCA value is an index that quantitatively indicates the environmental load in the life cycle of the product. The LCA value may be, for example, a value that becomes higher as the biomass degree is higher. Also, the LCA value may be a value that becomes higher as the curing time, which is an example of the process conditions, is lower, or as the curing temperature is lower. For example, the LCA value may be an evaluation value regarding the carbon dioxide emission amount.

[0036] The output unit 40 outputs support information in which each of the candidates for the blending ratio of the materials and the specific information is associated with the environmental load index calculated by the calculation unit 38 for each candidate. Specifically, the output unit 40 outputs support information ranking the candidates with the top predetermined number of environmental load indexes. FIG. 4 shows an example of the support information to be output.

[0037] Further, the output unit 40 may add to the support information a document corresponding to the product information indicated by each candidate of the support information, related information extracted from the document, or information searched on the Internet based on the product information indicated by each candidate of the support information. For example, the output unit 40 searches the product information DB 42 for product information that matches or is similar to the product information indicated by each candidate of the support information, and may use the document corresponding to the searched product information as additional information. Also, the output unit 40 may use, as additional information, information such as the effects regarding the LCA achieved by a product with a specific composition disclosed in the document, the propriety when applying a specific material to the product, the effects regarding the LCA required for the product, and the types of materials restricted by regulations.

[0038] Next, the operation of the material search support apparatus 10 according to the present embodiment will be described.

[0039] When the training of the estimation model 44 is instructed, the material search support device 10 executes the training process shown in FIG. 5. Also, when the basic configuration information of the product is specified and the output of the support information is instructed, the material search support device 10 executes the support process shown in FIG. 6.

[0040] First, the training process shown in FIG. 5 will be described.

[0041] In step S10, the acquisition unit 32 acquires the documents for each of the plurality of products collected by the collection device 30. Next, in step S12, the acquisition unit 32 extracts product information from the acquired documents and stores it in the product information DB 42.

[0042] Next, in step S14, the training unit 34 trains the estimation model 44 so as to estimate the mixing ratio and specific information of the material for the basic configuration information of the product based on the product information stored in the product information DB 42. Next, in step S16, the training unit 34 stores the trained estimation model 44 in a predetermined storage area of the material search support device 10, and the training process ends.

[0043] Next, the support process shown in FIG. 6 will be described.

[0044] In step S20, the estimation unit 36 receives the designation of the basic configuration information of the product to be produced from the user. Next, in step S22, the estimation unit 36 inputs the received basic configuration information into the estimation model 44 and acquires one or more candidates for the mixing ratio and specific information of the material output from the estimation model 44.

[0045] Next, in step S24, the calculation unit 38 calculates the LCA value for the product when the mixing ratio and specific information of the material indicated by each estimated candidate are adopted for the specified basic configuration information.

[0046] Next, in step S26, the output unit 40 acquires, as additional information, the document corresponding to the product information indicated by each candidate of the support information, the related information extracted from the document, or the information searched on the Internet based on the product information indicated by each candidate of the support information.

[0047] Next, in step S28, the output unit 40 associates each of the material blending ratio and the candidate of the specific information with the environmental load index calculated for each candidate, ranks the candidates with the top predetermined number of environmental load indexes, adds additional information, and outputs the support information, and the support process ends.

[0048] As described above, the material search support device according to the present embodiment obtains, for each of a plurality of products, product information collected from documents on the Internet, which includes basic configuration information of the product, the blending ratio of the materials included in the product, and at least one of the physical properties of the product, the biomass degree of the product, and the process conditions during use of the product. Further, the material search support device uses an estimation model trained to estimate the blending ratio and specific information of the material with respect to the basic configuration information of the product based on the obtained product information, and estimates one or more candidates for the blending ratio and specific information of the material with respect to the basic configuration information of the specified product. Then, the material search support device calculates an environmental load index for each of the estimated candidates based on the blending ratio and specific information of the material indicated by each of the candidates, and outputs support information associating each of the candidates with the calculated environmental load index. Thereby, it is possible to support the search for appropriate materials corresponding to carbon neutrality.

[0049] Note that the function of the collection device in the above embodiment may be provided in the material search support device. Further, in the above embodiment, the case where the acquisition unit of the material search support device extracts and acquires product information from the documents collected by the collection device has been described. However, the collection device may extract the product information up to the material search support device and input it to the material search support device.

[0050] Further, in the above embodiment, the processing executed by the CPU by reading software (program) may be executed by various processors other than the CPU. Examples of the processor in this case include a PLD (Programmable Logic Device) whose circuit configuration can be changed after manufacture, such as an FPGA (Field-Programmable Gate Array), and a dedicated electric circuit which is a processor having a circuit configuration dedicated to executing specific processing, such as an ASIC (Application Specific Integrated Circuit). Further, it may be executed by one of these various processors, or may be executed by a combination of two or more processors of the same type or different types (for example, a plurality of FPGAs, and a combination of a CPU and an FPGA). More specifically, the hardware structure of these various processors is an electric circuit combining circuit elements such as semiconductor elements.

[0051] Further, in the above embodiment, the mode in which the material search support program is pre-stored (installed) in the storage device has been described, but the present invention is not limited to this. The program may be provided in a form stored in a storage medium such as a CD-ROM, a DVD-ROM, or a USB memory. Further, the program may be in a form downloaded from an external device via a network.

[0052] The following are the appended claims.

[0053] (Appended Claim 1) An acquisition unit that acquires product information for each of a plurality of products, the product information being product information collected from documents on the Internet and including at least one of basic configuration information of the product, a mixing ratio of materials included in the product, physical properties of the product, a biomass degree of the product, and process conditions during use of the product; An estimation unit that estimates one or more candidates for a mixing ratio of materials and specific information with respect to basic configuration information of a specified product, using an estimation model trained to estimate a mixing ratio of materials and specific information with respect to basic configuration information of a product based on the product information acquired by the acquisition unit; For each of the candidates estimated by the estimation unit, a calculation unit that calculates an environmental impact index based on the mixing ratio and specific information of the material indicated by each of the candidates; An output unit that outputs support information associating each of the candidates with the environmental impact index calculated by the calculation unit; A material search support device including the above.

[0054] (Additional item 2) The material search support device according to claim 1, wherein the acquisition unit extracts information related to a keyword corresponding to the product information from the document and acquires the information as the product information.

[0055] (Additional item 3) The material search support device according to claim 1 or 2, wherein the document includes at least one of patent documents and public information of a company including a catalog.

[0056] (Additional item 4) The material search support device according to any one of claims 1 to 3, including a collection unit that collects the document from the Internet.

[0057] (Additional item 5) The material search support device according to any one of claims 1 to 4, wherein the basic configuration information of the product includes a schematic configuration of the product and types of materials used.

[0058] (Additional item 6) The material search support device according to any one of claims 1 to 5, wherein the calculation unit calculates the carbon dioxide emission amount related to the product when the mixing ratio and the specific information of the material indicated by the candidate are adopted as the environmental impact index.

[0059] (Additional item 7) The material search support device according to any one of claims 1 to 6, wherein the output unit outputs support information ranking the candidates with the top predetermined number of the environmental impact indices.

[0060] (Additional item 8) The output unit adds information retrieved on the Internet based on the document corresponding to the product information, the related information extracted from the document, or the support information to the support information and outputs the same, which is the material search support device according to any one of appended claims 1 to 7.

[0061] (Appended claim 9) The material search support device according to any one of appended claims 1 to 8, further including a training unit that trains the estimation model based on the product information acquired by the acquisition unit.

Explanation of reference numerals

[0062] 10 Material search support device 12 CPU 14 Memory 16 Storage device 18 Input device 20 Output device 22 Storage medium reader 24 Communication I / F 26 Bus 30 Collection device 32 Acquisition unit 34 Training unit 36 Estimation unit 38 Calculation unit 40 Output unit 42 Product information DB 44 Estimation model

Claims

**Claim 1** For each of a plurality of products, product information collected from documents on the Internet, including basic configuration information of the product, the mixing ratio of materials included in the product, physical properties of the product, the biomass degree of the product, and specific information including at least one of process conditions during use of the product; an acquisition unit that acquires the product information; Based on the product information acquired by the acquisition unit, an estimation unit that estimates one or more candidates for the mixing ratio of materials and specific information with respect to the basic configuration information of a specified product using an estimation model trained to estimate the mixing ratio of materials and specific information with respect to the basic configuration information of the product; For each of the candidates estimated by the estimation unit, a calculation unit that calculates an environmental load index based on the mixing ratio of materials and specific information indicated by each of the candidates; An output unit that outputs support information associating each of the candidates with the environmental load index calculated by the calculation unit; A material search support device including the above. **Claim 2** The material search support device according to claim 1, wherein the acquisition unit extracts information related to keywords according to the product information from the document and acquires the information as the product information. **Claim 3** The material search support device according to claim 1 or claim 2, wherein the document includes at least one of patent documents and public information of enterprises including catalogs. **Claim 4** The material search support device according to claim 1 or claim 2, further including a collection unit that collects the document from the Internet. **Claim 5** The material search support device according to claim 1 or claim 2, wherein the basic configuration information of the product includes a schematic configuration of the product and types of materials used. **Claim 6** The material search support device according to claim 1 or claim 2, wherein the calculation unit calculates the carbon dioxide emission amount related to the product when the mixing ratio of materials and the specific information indicated by the candidate are adopted as the environmental load index. **Claim 7** The material search support device according to claim 1 or claim 2, wherein the output unit outputs support information ranking the candidates with the top predetermined number of environmental load indexes. **Claim 8** The material search support device according to claim 1 or claim 2, wherein the output unit adds information searched on the Internet based on the document corresponding to the product information, related information extracted from the document, or the support information to the support information and outputs the same. **Claim 9** The material search support device according to claim 1 or claim 2, comprising a training unit that trains the estimation model based on the product information acquired by the acquisition unit.

10. A material search support method executed by a material search support device including an acquisition unit, an estimation unit, a calculation unit, and an output unit, wherein the acquisition unit acquires, for each of a plurality of products, product information collected from documents on the Internet, the product information including basic configuration information of the product, a mixing ratio of materials included in the product, physical properties of the product, a biomass degree of the product, and specific information including at least one of process conditions during use of the product, the estimation unit uses an estimation model trained to estimate a mixing ratio of materials and specific information for basic configuration information of a product based on the product information acquired by the acquisition unit, and estimates one or more candidates for the mixing ratio of materials and specific information for basic configuration information of a specified product, the calculation unit calculates an environmental load index for each of the candidates estimated by the estimation unit based on the mixing ratio of materials and specific information indicated by each of the candidates, and the output unit outputs support information associating each of the candidates with the environmental load index calculated by the calculation unit. Material search support method.

11. A computer, an acquisition unit that acquires, for each of a plurality of products, product information collected from documents on the Internet, the product information including basic configuration information of the product, a mixing ratio of materials included in the product, physical properties of the product, a biomass degree of the product, and specific information including at least one of process conditions during use of the product, an estimation unit that uses an estimation model trained to estimate a mixing ratio of materials and specific information for basic configuration information of a product based on the product information acquired by the acquisition unit, and estimates one or more candidates for the mixing ratio of materials and specific information for basic configuration information of a specified product, a calculation unit that calculates an environmental load index for each of the candidates estimated by the estimation unit based on the mixing ratio of materials and specific information indicated by each of the candidates, and an output unit that outputs support information associating each of the candidates with the environmental load index calculated by the calculation unit as a material search support program for causing the computer to function.

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