Information processing method, information processing device, and computer program

Abstract

Identifiers for identifying a plurality of users, factory identifiers for identifying a plurality of factories belonging to each of the plurality of users, device identifiers for identifying a plurality of industrial machines provided in each of the plurality of factories, and device-related information including the specifications of each of the plurality of industrial machines are associated with each other and stored in a database. A factory identifier, a device identifier, and device-related information associated with an identifier of one user are read from a database, and a device list including a plurality of factories belonging to one user, a plurality of industrial machines provided in the plurality of factories, and device-related information is created. And providing data of the created device list to one user and external related personnel related to the user.

Description

Technical Field

[0001] The present invention relates to an information processing method, an information processing device, and a computer program. Background Art

[0002] Patent document 1 discloses an industrial machinery management device that enables a manager of a group to easily grasp the overall status of industrial machinery in the group. Specifically, the industrial machinery management device calculates statistics of information related to the production of the entire injection molding machine belonging to the group based on information related to the production of a plurality of injection molding machine units in a factory classified into a group according to a predetermined criterion, and displays the statistics as management information.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Publication No. 2018-94888 Summary of the invention

[0006] However, it is impossible to manage the specifications of each of a plurality of industrial machines installed in a plurality of factories belonging to one user.

[0007] Assuming that the specifications of industrial machinery installed in all factories of the user can be known, the industrial machinery can be properly relocated and operated according to the production plan, but it is not necessarily easy to know the specifications of the operating machinery of each factory. On the other hand, if the salesperson who sells industrial machinery or components to the user of industrial machinery or performs maintenance inspection can know the specifications of the industrial machinery of each factory belonging to the user, he can make more appropriate suggestions, but it is difficult to know the above specifications.

[0008] The present disclosure aims to provide an information processing method, an information processing device, and a computer program capable of providing a device list showing specifications of a plurality of industrial machines installed in a plurality of factories belonging to the user to the user and external personnel related to the user.

[0009] An information processing method involved in one aspect of the present disclosure establishes a correspondence between identifiers for identifying multiple users, factory identifiers for identifying multiple factories respectively belonging to the multiple users, equipment identifiers for identifying multiple industrial machines respectively installed in the multiple factories, and equipment-related information including the specifications of the multiple industrial machines, and stores them in a database; reads the factory identifier, the equipment identifier and the equipment-related information that have established a correspondence with the identifier of one of the users from the database, creates an equipment list that includes the multiple factories belonging to the one user, the multiple industrial machines installed in the multiple factories and the equipment-related information; and provides the data of the created equipment list to the one user and external relevant personnel related to the one user.

[0010] An information processing device involved in one aspect of the present disclosure comprises: a database, which establishes a correspondence between identifiers for identifying multiple users, factory identifiers for identifying multiple factories respectively belonging to the multiple users, equipment identifiers for identifying multiple industrial machines respectively installed in the multiple factories, and equipment-related information containing specifications of each of the multiple industrial machines; a processing unit, which reads out the factory identifier, the equipment identifier and the equipment-related information that have established a correspondence with the identifier of one of the users from the database, and creates an equipment list, which includes the multiple factories belonging to the one user, the multiple industrial machines installed in the multiple factories and the equipment-related information; and a communication unit, which provides the data of the created equipment list to the one user and external relevant personnel related to the one user.

[0011] One aspect of the present disclosure relates to a computer program that enables a computer to perform the following processing: establishing a correspondence between identifiers for identifying multiple users, factory identifiers for identifying multiple factories respectively belonging to the multiple users, device identifiers for identifying multiple industrial machines respectively installed in the multiple factories, and device-related information including specifications of the multiple industrial machines, and storing them in a database; reading from the database the factory identifier, the device identifier, and the device-related information that have established a correspondence with the identifier of one of the users; creating an equipment list that includes the multiple factories belonging to the one user, the multiple industrial machines installed in the multiple factories, and the equipment-related information; and providing the data of the created equipment list to the one user and external relevant personnel related to the one user.

[0012] Effects of the Invention

[0013] According to the present disclosure, it is possible to provide a device list indicating the specifications of each of a plurality of industrial machines installed in a plurality of factories belonging to a user to the user and external personnel related to the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a block diagram showing a configuration example of a molding machine system according to the first embodiment.

[0015] Figure 2 This is a conceptual diagram of the molding machine system according to the first embodiment.

[0016] Figure 3 This is a block diagram showing a configuration example of a data collection device according to the first embodiment.

[0017] Figure 4 This is a block diagram showing a configuration example of the information processing device according to the first embodiment.

[0018] Figure 5 This is a conceptual diagram showing an example of a record layout of a collected data DB.

[0019] Figure 6 This is a conceptual diagram showing an example of a record layout of a user DB.

[0020] Figure 7 This is a conceptual diagram showing an example of a record layout of a delivery machine DB.

[0021] Figure 8 This is a conceptual diagram showing an example of a record layout of a component DB.

[0022] Fig. 9 This is a conceptual diagram showing an example of a record layout of a material DB.

[0023] Fig.10 This is a conceptual diagram showing an example of a record layout of a quote DB.

[0024] Fig.11 This is a conceptual diagram showing an example of a record layout of an order DB.

[0025] Fig.12 This is a block diagram showing an estimation processing unit that predicts the remaining life or abnormality of a component.

[0026] Fig.13 This is a flowchart showing the processing procedure of the information processing device according to the first embodiment.

[0027] Fig.14 This is a schematic diagram showing an example of a delivery machine list display screen.

[0028] Fig.15 This is a schematic diagram showing an example of a delivery machine detail screen.

[0029] Fig.16 This is a schematic diagram showing an example of a document list display screen.

[0030] Fig.17 This is a schematic diagram showing an example of a quote target component selection screen.

[0031] Fig.18 This is a schematic diagram showing an example of a quote history list display screen.

[0032] Fig.19 This is a diagram showing an example of an order status list display screen.

[0033] Fig. 20 This is a flowchart showing the information processing procedure including the transfer processing to the device management website according to the second embodiment.

[0034] Fig.21 It is a schematic diagram showing an example of the estimation result display screen.

[0035] Fig. 22 This is a flowchart showing the information processing procedure including the transfer processing to the device status information providing website according to the second embodiment. DETAILED DESCRIPTION

[0036] Hereinafter, the information processing method, information processing device and computer program involved in the embodiments of the present disclosure are described with reference to the accompanying drawings. In addition, the present disclosure is not limited to these examples, but is shown by the claims, and is intended to include all changes within the meaning and scope equivalent to the claims. In addition, at least a part of the embodiments described below can also be arbitrarily combined.

[0037] (Implementation Method 1)

[0038] Figure 1 is a block diagram showing an example of the configuration of a molding machine system according to the first embodiment. Figure 2 1 is a conceptual diagram of a molding machine system according to the first embodiment. The molding machine system includes a molding machine 1, a plurality of sensors 2, a data collection device 3, a router 4, an information processing device 5, and terminal devices 6a and 6b. The molding machine 1 includes an injection molding machine and an extruder. In the following, as an example, the molding machine 1 is described as an extruder.

[0039] exist Figure 1The figure shows one molding machine 1 and a data collection device 3, but a plurality of data collection devices 3 not shown are connected to the information processing device 5 via a network. One or more molding machines 1 are connected to the data collection device 3. The information processing device 5 can collect information of each of the plurality of molding machines 1, manage the specifications and status of each molding machine 1, and estimate the remaining life or abnormality of one or more components constituting each molding machine 1. The plurality of molding machines 1 and the data collection device 3 are installed in respective factories of a plurality of users who own the molding machines 1. In the first embodiment, as shown in FIG. Figure 2 As shown in FIG. 1 , a user has multiple factories, and each of the multiple factories has one or more molding machines 1. The user is an organization such as a legal person that owns the molding machine 1. In addition, the user includes employees, staff, etc. belonging to the organization who operate the terminal device 6a. Hereinafter, the organization, employee, or staff will be collectively referred to as a user. In addition, as Figure 2 As shown in the figure, service providers such as sales personnel who sell the molding machine 1 or components constituting the molding machine 1 to the user and maintenance management personnel who perform maintenance management of the molding machine 1 of the user are allocated to the user. Hereinafter, the service providers are referred to as sales personnel. In addition, the operator on the sales personnel side who provides maintenance management services for the components constituting the molding machine 1 to the user and manufactures and sells the components is referred to as a maintenance management operator.

[0040] The terminal devices 6a and 6b are communication terminals having a display unit such as a computer, a tablet terminal, or a smartphone. The terminal device 6a is a terminal used by a user, and the terminal device 6b is a terminal used by a salesperson.

[0041] <Molding machine 1>

[0042] The molding machine 1 includes two screws 11, a cylinder 10 having a hopper into which a resin raw material is fed, and a die 12 provided at the outlet portion of the cylinder 10. The two screws 11 are arranged substantially parallel to each other in a meshing state, and are rotatably inserted into the hole of the cylinder 10 to push the resin raw material fed into the hopper in an extrusion direction ( Figure 1 The molten resin raw material is discharged from the mold 12 having a through hole.

[0043] The screw 11 is formed by combining and integrating a plurality of screw segments into one screw 11. For example, the screw 11 is formed by arranging and combining a forward thread segment of a helical screw shape for conveying the resin raw material in the forward direction, a reverse thread segment for conveying the resin raw material in the reverse direction, a kneading segment for kneading the resin raw material, etc. in an order and position corresponding to the characteristics of the resin raw material.

[0044] The molding machine 1 has a motor 13 that outputs a driving force for rotating the screw 11, a reducer 14 that reduces the speed of the driving force of the motor 13, and a control device 15. The screw 11 is connected to the output shaft of the reducer 14. The screw 11 is rotated by the driving force of the motor 13 reduced by the reducer 14.

[0045] <Sensor 2>

[0046] The sensor 2 detects a physical quantity associated with the state of the components constituting the molding machine 1, and outputs the detected physical quantity data directly or indirectly to the data collection device 3. The physical quantity data is data representing the sensor value of the time series of the detected physical quantity. The sensor 2 includes a sensor provided in the molding machine 1 as a sensor required for the operation control of the molding machine 1 and a sensor provided for estimating the life of the components. Some of the multiple sensors 2 are connected to the data collection device 3, and the data collection device 3 obtains the physical quantity data from the sensor 2. Some of the multiple sensors 2 are connected to the control device 15, and the data collection device 3 obtains the physical quantity data from the sensor 2 via the control device 15.

[0047] Physical quantities include temperature, position, velocity, acceleration, current, voltage, pressure, time, image data, torque, force, strain, power consumption, weight, etc. These physical quantities can be measured using a thermometer, a position sensor, a velocity sensor, an acceleration sensor, an ammeter, a voltmeter, a pressure gauge, a timer, a camera, a torque sensor, a power meter, a weight meter, etc.

[0048] The multiple sensors 2 include, for example, a first sensor 21 for detecting physical quantities related to the reducer 14 , a second sensor 22 for detecting physical quantities related to the screw 11 , a third sensor 23 for detecting physical quantities related to the motor 13 , and a fourth sensor 24 for detecting physical quantities related to the mold 12 .

[0049] The first sensor 21 is, for example, a vibration detector for detecting the vibration of the reducer 14. The second sensor 22 is a torque detector for detecting the shaft torque of the screw 11, a tachometer for detecting the rotation speed of the screw 11, a pressure gauge for detecting the pressure at the top of the screw, a thermometer for detecting the temperature of the screw 11, a displacement sensor for detecting the displacement of the rotation center of the screw 11, etc. The third sensor 23 is an ammeter for detecting the motor current, a tachometer for detecting the motor rotation speed, etc. The fourth sensor 24 is a pressure gauge for detecting the die head pressure acting on the mold 12.

[0050] <Control device 15>

[0051] The control device 15 is a computer that performs operation control of the molding machine 1 , and includes a transceiver (not shown) that transmits and receives information with the data collection device 3 , and a display unit.

[0052] Specifically, the control device 15 sends the operation data indicating the operation state of the molding machine 1 to the data collection device 3. The operation data include, for example, the motor current, the rotation speed of the screw 11, the pressure at the top of the screw 11, the die pressure, the feeder supply amount (supply amount of the resin raw material), the extrusion amount, the cylinder temperature, the resin pressure, and the like.

[0053] The control device 15 receives various chart data sent from the data collection device 3 and estimated result data indicating the remaining life or abnormality of the components constituting the molding machine 1. The control device 15 displays the contents of the received chart data and estimated result data. In addition, the control device 15 outputs a warning based on the remaining life or abnormality indicated by the received estimated result data.

[0054] <Data collection device 3>

[0055] Figure 3 1 is a block diagram showing a configuration example of the data collection device 3 of the present embodiment 1. The data collection device 3 is a computer, and has a control unit 31, a storage unit 32, a communication unit 33, and a data input unit 34, and the storage unit 32, the communication unit 33, and the data input unit 34 are connected to the control unit 31. The data collection device 3 is, for example, a PLC (Programmable Logic Controller).

[0056] The control unit 31 has a CPU (Central Processing Unit), a multi-core CPU, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array) and other arithmetic processing circuits, a ROM (Read Only Memory), a RAM (Random Access Memory) and other internal storage devices, I / O terminals, etc. The control unit 31 collects physical quantity data and sends it to the information processing device 5 by executing a control program stored in the storage unit 32 described later. In addition, each functional unit of the data collection device 3 can be implemented in software, or partially or entirely in hardware.

[0057] The storage unit 32 is a nonvolatile memory such as a hard disk, an EEPROM (Electrically Erasable Programmable ROM), a flash memory, etc. The storage unit 32 stores a control program for causing a computer to perform a collection process of physical quantity data.

[0058] The communication unit 33 is a communication circuit that sends and receives information according to a communication protocol specified by Ethernet (registered trademark) or the like. The communication unit 33 is connected to the control device 15 via a first communication network such as a LAN, and the control unit 31 can send and receive various information with the control device 15 via the communication unit 33. The control unit 31 acquires physical quantity data via the communication unit 33.

[0059] The first network is connected to a router 4, and the communication unit 33 is connected to an information processing device 5 on a cloud serving as a second communication network via the router 4. The control unit 31 can transmit and receive various information to and from the information processing device 5 via the communication unit 33 and the router 4.

[0060] The data input unit 34 is an input interface for inputting a signal output from the sensor 2 . The sensor 2 is connected to the data input unit 34 , and the control unit 31 acquires physical quantity data via the data input unit 34 .

[0061] <Information processing device 5>

[0062] Figure 4 : is a block diagram showing an example of the configuration of the information processing device 5 of the present embodiment 1. The information processing device 5 is a computer, and has a processing unit 51, a storage unit 52, and a communication unit 53. The storage unit 52 and the communication unit 53 are connected to the processing unit 51. In addition, the information processing device 5 may be a structure composed of a plurality of computers and performing distributed processing, or may be implemented by a plurality of virtual machines set in a server, or may be implemented by using a cloud server, or may be partially constituted by a quantum computer.

[0063] The processing unit 51 is a processor, and has a CPU, a multi-core CPU, a GPU (Graphics Processing Unit), a GPGPU (General-purpose computing on graphics processing units), a TPU (Tensor Processing Unit), an ASIC, an FPGA, an NPU (Neural Processing Unit), and other computing processing circuits, an internal storage device such as a ROM and a RAM, an I / O terminal, etc. The processing unit 51 functions as the information processing device 5 of the first embodiment by executing a computer program (computer program product) P stored in a storage unit 52 described later.

[0064] The information processing device 5 of the first embodiment functions as a device management network server (first server) that manages the specifications and status of the molding machines 1 of each of the plurality of users. In addition, the information processing device 5 functions as a device status information providing network server (second server) that provides information related to the status of the molding machine 1 to the user and the salesperson. In addition, each functional unit of the information processing device 5 may be implemented in software, or partially or entirely in hardware. In addition, the information processing device 5 may be configured to be composed of a plurality of computers, each of which functions as a device management network server and a device status information providing network server.

[0065] The communication unit 53 is a communication circuit that sends and receives information according to a communication protocol specified by Ethernet (registered trademark) etc. The communication unit 53 is connected to the data collection device 3 and the terminal devices 6a, 6b via the second communication network, and the processing unit 51 can send and receive various information between the data collection device 3 and the terminal devices 6a, 6b via the communication unit 53.

[0066] The storage unit 52 is a non-volatile memory such as a hard disk, an EEPROM, or a flash memory. The storage unit 52 stores a computer program P for causing a computer to perform a process of estimating the life of components constituting the molding machine 1, a prediction learning model 54, a collected data DB (database) 52a, a user DB (database) 52b, a delivery machine DB (database) 52c, a component DB (database) 52d, a material DB (database) 52e, a quotation DB (database) 52f, and an order DB (database) 52g.

[0067] The computer program P, etc. may also be recorded in a computer-readable manner on the recording medium 50. The storage unit 52 stores the computer program P, etc. read from the recording medium 50 by a reading device not shown in the figure. The recording medium 50 is a semiconductor memory such as a flash memory. In addition, the recording medium 50 may also be an optical disk such as a CD (Compact Disc)-ROM, a DVD (Digital Versatile Disc)-ROM, or a BD (Blu-ray (registered trademark) Disc). In addition, the recording medium 50 may also be a magnetic disk such as a floppy disk or a hard disk, a magneto-optical disk, etc. In addition, the computer program P, etc. may be downloaded from an external server not shown in the figure connected to a communication network not shown in the figure, and stored in the storage unit 52.

[0068] The computer program P can be deployed on a single computer or in one website, or can be deployed in a manner distributed over a plurality of websites and executed on a plurality of computers interconnected via a communication network.

[0069] The prediction learning model 54 is an image recognition learning model that outputs data indicating the remaining life or abnormality of a component constituting the molding machine 1 when image data generated based on physical quantity data is input. The prediction learning model 54 includes, for example, a CNN (Convolutional Neural Network). The processing unit 51 can generate a learning model dedicated to estimating the remaining life or abnormality of a specific molding machine 1 and component by performing transfer learning or fine-tuning of an existing learned model.

[0070] Figure 5 This is a conceptual diagram showing an example of the record layout of the collected data DB52a. The collected data DB52a has a hard disk and a DBMS (DataBase Management System), and stores various physical quantity data collected from the molding machine 1. For example, the collected data DB52a has a "No." (record number) column, a "device ID" column, an "operation date and time" column, an "operation data" column, a "vibration data" column, and a "shaft torque data" column.

[0071] The "Device ID" column stores the device identifier of the molding machine 1. The "Operation Date and Time" column stores information indicating the year, month, day, and time when various data stored as records are obtained. The "Operation Data" column stores time-series physical quantities indicating the operating state of the molding machine 1, such as motor current, rotation speed of the screw 11, top pressure of the screw 11, die pressure, feeder supply amount (resin raw material supply amount), extrusion amount, cylinder temperature, resin pressure, etc. The "Vibration Data" column stores vibration data as time-series physical quantity data. The "Shaft Torque Data" column stores torque data of the screw 11 as time-series physical quantity data.

[0072] Figure 6 This is a conceptual diagram showing an example of the record layout of the user DB 52b. The user DB 52b has a hard disk and a DBMS, and stores basic information of users, etc. For example, the user DB 52b has a "user ID" column, a "company name" column, a "user basic information" column, a "factory ID" column, and a "salesperson ID" column.

[0073] The "User ID" column stores the identifier of the user of the molding machine 1. The "Company Name" column stores the name of the legal person of the user. The "User Basic Information" column stores the basic information of the user, such as the capital, sales, number of employees and other corporate information of the company of the user. The "Factory ID" column stores the factory identifier that identifies one or more factories belonging to the user. The factory identifier is associated with factory-related information such as the factory name. The "Sales Personnel ID" column stores the sales person ID for identifying the sales person of the user identified by the user ID.

[0074] Figure 7 This is a conceptual diagram showing an example of the record layout of the delivery machine DB52c. The delivery machine DB52c has a hard disk and a DBMS, and stores equipment-related information such as specifications and status of the molding machine 1 brought into the user's factory. For example, the delivery machine DB52c includes an "original work number" column, a "machine model" column, a "factory name" column, a "production line name" column, a "delivery year" column, a "status" column, a "maintenance history" column, a "user ID" column, a "raw material" column, a "capacity" column, and a "data number" column.

[0075] The "Original Work Number" column stores the original work number, which is the device identifier of the molding machine 1 brought into the user's factory. The "Model" column stores information indicating the model of the molding machine 1. The "Factory Name" column stores the factory name or factory identifier where the molding machine 1 is installed. The "Production Line Name" column stores the name of the production line where the molding machine 1 is installed. The "Delivery Year" column stores the year, month, and day when the molding machine 1 was delivered. The "Status" column stores information indicating the status of the molding machine 1. The information indicating the status of the molding machine 1 includes, for example, information indicating the status such as setting, non-setting, operating, and fault repair. The "Maintenance History" column stores the maintenance history including information such as the maintenance date, maintenance content, and person in charge of the molding machine 1. The "User ID" column stores the user ID of the company to which the molding machine 1 is delivered. The user ID is equivalent to the name of the company that demands the molding machine 1. The "Raw Material" column stores information indicating the raw materials fed into the molding machine 1. The "Capacity" column stores the capacity of the molding machine 1, for example, in the case of an extruder, the production volume per unit time (kg / hour). The "Document Number" column stores the manual and specification information of the molding machine 1.

[0076] Figure 8 This is a conceptual diagram showing an example of the record layout of the component DB 52d. The component DB 52d has a hard disk and a DBMS, and stores information on components constituting the molding machine 1 used by the user. For example, the component DB 52d has a "component ID" column, a "molding machine original job number" column, a "component name" column, a "component specification information" column, and a "remaining life or abnormality" column.

[0077] The "Component ID" column stores the component identifier of the component constituting the molding machine 1. The "Molding Machine Original Work Number" column stores the original work number corresponding to the device identifier of the molding machine 1. The molding machine original work number is preferably structured to include information that can distinguish whether it is a product of the maintenance and management operator or a product of another company.

[0078] The "Component Name" column stores the name of the component. The "Component Specification Information" column stores specification information indicating the product specifications of the component corresponding to the component ID. For example, the specification information of the screw 11 and the reducer 14 constituting the extruder is stored. The components constituting the molding machine 1 are not necessarily mass-produced products, but are components of special specifications manufactured for each user. The specification information includes information for estimating the replacement cost of the component. The specification information includes information required to secure spare parts in order to manufacture components, etc.

[0079] The “remaining life or abnormality degree” column stores the remaining life or abnormality degree of the component corresponding to the component ID. The remaining life or abnormality degree is predicted by the prediction learning model 54 .

[0080] The material DB 52e stores arbitrary information, such as TIPS information, related to the components constituting the molding machine 1. The TIPS information includes a description of the components, a maintenance inspection method, and the like.

[0081] Fig. 9 This is a conceptual diagram showing an example of the record layout of the document DB 52e. The document DB 52e has a hard disk and a DBMS, and stores the technical information of the molding machine 1. For example, the document DB 52e has a "document number" column, a "title" column, a "summary" column, and a "document data" column.

[0082] The "Document Number" column stores the document number used to identify the document. The "Title" column stores the title of the document. The "Summary" column stores the summary of the document. The "Document Data" column stores the document data such as the advertising information associated with the molding machine 1, the technical information of the molding machine 1, the manual of the molding machine 1, the specification information, the maintenance management method, TIPS information, and the video. The TIPS information includes the description of the component, the maintenance inspection method, etc.

[0083] Fig.10 This is a conceptual diagram showing an example of the record layout of the quotation DB 52f. The quotation DB 52f has a hard disk and a DBMS, and stores the history of quotations provided to users. For example, the quotation DB 52f has a "quotation request number" column, a "quotation request date" column, a "production line name" column, a "machine model" column, a "purpose" column, a "factory name" column, a "original job number" column, and a "user ID" column.

[0084] The "Quotation Request Number" column stores quotation request numbers for identifying multiple quotation requests from users. The "Quotation Request Date" column stores the year, month, and day when the information processing device 5 receives the quotation request. The "Production Line Name" column stores the name of the production line that uses the component to be quoted. The "Model" column stores the model name of the molding machine 1 that uses the component. The "Purpose" column stores the purpose of the component to be quoted, such as inventory replenishment and overhaul. The "Factory Name" column stores the name of the factory that uses the component. The "Original Work Number" column stores the original work number of the molding machine 1 that uses the component. The "User ID" column stores the user ID of the order source.

[0085] Fig.11 This is a conceptual diagram showing an example of the record layout of the order DB 52g. The order DB 52g has a hard disk and a DBMS, and stores information related to the order of the molding machine 1 or its components. For example, the order DB 52g has a "shipping guide number" column, a "status" column, a "component job number" column, a "machine model" column, a "factory name" column, a "production line name" column, a "user ID" column, a "source order number" column, a "person in charge" column, and a "contract delivery date" column.

[0086] The "Shipping Guide Number" column stores the number of the shipping guide that identifies the component. The "Status" column stores information indicating the shipping status of the component. The "Component Job Number" column stores the job number that identifies the component that is the shipping object. The "Model" column stores information indicating the model of the molding machine 1 that uses the component. The "Factory Name" column stores the name of the factory that uses the component. The "Production Line Name" column stores the name of the production line that uses the component. The "User ID" column stores the user ID that indicates the shipping destination of the component. The "Order Source Order Number" column stores the order source order number. The "Person in Charge" column stores information identifying the person in charge of ordering the component. The "Contract Delivery Period" column stores information indicating the delivery period of the component.

[0087] Fig.12 1 is a block diagram showing an estimation processing unit M for predicting the remaining life or abnormality of a component. The estimation processing unit M includes a prediction learning model 54, a frequency analysis unit 55, and an image generation unit 56. Each functional unit of the estimation processing unit M may be implemented in software by the processing of the processing unit 51, or may be partially or entirely implemented in hardware.

[0088] The frequency analysis unit 55 is an operation processing unit that Fourier transforms the physical quantity data of the time series into the physical quantity data of the frequency component. The frequency analysis unit 55 can perform the Fourier transform of the physical quantity data by the short-time Fourier transform (STFT: Short-Time Fourier Transform). The image generation unit 56 is an operation processing unit that transforms the physical quantity data after the Fourier transform into image data represented by an image. For example, the physical quantity data can be represented on an image plane in which the horizontal axis of the image is set to the frequency and the vertical axis is set to the size of the frequency component. Hereinafter, the image obtained by Fourier transforming the physical quantity data is referred to as a Fourier transform image.

[0089] In addition, the frequency analysis method is not limited to STFT, and wavelet transform, Stockwell transform, Wigner distribution function, empirical mode decomposition, Hilbert-Huang transform, etc. can also be used.

[0090] The prediction learning model 54 is a convolutional neural network (CNN) having an input layer 54a to which image data of a Fourier transform image is input, an intermediate layer 54b, and an output layer 54c to output remaining life data or abnormality data indicating the remaining life or abnormality of a component.

[0091] The input layer 54a has a plurality of nodes to which the pixel values ​​of each pixel constituting the Fourier transform image are input. The intermediate layer 54b has a structure in which a convolution layer and a pooling layer are alternately connected, the convolution layer convolves the pixel values ​​of each pixel of the Fourier transform image input to the input layer 54a, and the pooling layer maps the pixel values ​​obtained by the convolution in the convolution layer. The intermediate layer 54b extracts the feature quantity of the Fourier transform image while compressing the image information of the Fourier transform image, and outputs the extracted Fourier transform image, that is, the feature quantity of the physical quantity data, to the output layer 54c.

[0092] The output layer 54 c has nodes that output remaining life data or abnormality degree data indicating the remaining life or abnormality degree of the component at the physical quantity data measurement point in time.

[0093] The prediction learning model 54 learns to output remaining life data indicating a remaining life of at least a predetermined period required to secure spare parts of the components of the molding machine 1. The prediction learning model 54 learns to output the degree of abnormality occurring at least before the predetermined period.

[0094] The method of generating the prediction learning model 54 is as follows. First, the prediction learning model 54 before adjustment is prepared. For example, an image recognition model that has been previously learned using general image data as training data may be prepared.

[0095] Next, the prepared prediction learning model 54 is trained and fine-tuned using known training data. For example, a component with a known remaining life or abnormality is mounted on the molding machine 1 as a test machine and operated. Label data representing the known remaining life or abnormality is assigned to the image data obtained by the operation of the test machine, thereby creating known training data.

[0096] The remaining life assigned when creating the training data includes a remaining life of a predetermined period or more required to ensure spare parts for the components of the molding machine 1. When generating the prediction learning model 54 of the output abnormality, the abnormality assigned when creating the training data includes the abnormality generated at least before the predetermined period. That is, the training data is created using image data obtained by operating the molding machine 1 having a component having a remaining life of a predetermined period or more required to ensure spare parts for the components of the molding machine 1.

[0097] Then, the prepared prediction learning model 54 is subjected to machine learning using the known training data. More specifically, the processing unit 51 optimizes the weight coefficient of the prediction learning model 54 by using the error back propagation method, the error gradient descent method, etc. using the training data, thereby subjecting the prediction learning model 54 to machine learning. Then, the processing unit 51 stores the learned prediction learning model 54 in the storage unit 52 of the information processing device 5.

[0098] In addition, the processing unit 51 may also create new training data based on image data obtained during the actual operation of the molding machine 1, and use the created new training data at an appropriate timing to relearn the prediction learning model 54. The processing unit 51 creates new training data and relearns the prediction learning model 54 by assigning correction labels to physical quantity data obtained from the molding machine 1 during operation as training data.

[0099] In addition, here, an example in which the information processing device 5 performs relearning is described, but it is also possible to configure another computer or server to relearn the prediction learning model 54 and send various parameters of the relearned prediction learning model 54 to the information processing device 5.

[0100] In addition, as an example of the prediction learning model 54, CNN is illustrated, but it can be composed of a multilayer perceptron (Multilayerperceptron: MLP), a convolutional neural network (Convolutional Neural Network: CNN), a graph neural network (Graph Neural Network: GNN), a graph convolutional network (Graph Convolutional Network: GCN), RNN (Recurrent Neural Network), LSTM (Long Short Term Memory), and other neural network models. In addition, the prediction learning model 54 can also be composed of algorithms such as decision trees, random forests, and SVM (Support Vector Machine).

[0101] Fig.13 1 is a flowchart showing the processing procedure of the information processing device 5 according to Embodiment 1. The processing unit 51 of the information processing device 5 performs the following processing according to the access and request of the terminal device 6a, 6b to the device management website. The details of the request and response processing performed between the information processing device 5 and the terminal devices 6a, 6b are appropriately omitted.

[0102] When the terminal devices 6a and 6b access the equipment management website provided by the information processing device 5, the processing unit 51 of the information processing device 5 provides the data of the web page constituting the equipment management website to the terminal devices 6a and 6b, thereby causing them to display the top screen 7 of the equipment management website (see Figure 2 )(Step S11).

[0103] like Figure 2 As shown, the top-level screen 7 of the equipment management website has multiple icons such as a "my page" icon 71, an "order status confirmation" icon 72, a "delivery machine list" icon 73, a "data download" icon 74, a "quotation entrustment" icon 75, and a "consultation" icon 76.

[0104] Next, in response to the login request from the terminal devices 6a and 6b, the processing unit 51 of the information processing device 5 performs a login process for the user or salesperson of the authentication terminal devices 6a and 6b (step S12). The logged-in user or salesperson can access the page corresponding to each icon by tapping or clicking the icon displayed on the top-level screen 7 of the device management website. In the following, for simplicity of explanation, it is assumed that the user has logged in to the device management website. When the salesperson has logged in to the device management website, he or she can use the user ID associated with the logged-in salesperson (refer to Figure 6) to view various information of users that the sales staff is responsible for.

[0105] When the "delivery machine list" icon 73 is operated, the processing unit 51 creates a delivery machine list 81b of the logged-in user and provides the delivery machine list data to the logged-in user (step S13). Specifically, the processing unit 51 accesses the delivery machine DB 52c, extracts the data of the delivery machine of the logged-in user using the user ID of the logged-in user as a key, and creates the delivery machine list 81b. Then, the processing unit 51 sends web page data for displaying the delivery machine list display screen 81 to the terminal device 6a. The terminal device 6a receives the web page data and displays the delivery machine list display screen 81.

[0106] Fig.14 81 is a schematic diagram showing an example of a delivery machine list display screen 81. The delivery machine list display screen 81 has a device search table 81a for searching for delivery machines. In addition, the delivery machine list display screen 81 includes a delivery machine list 81b including the model of the molding machine 1 owned by the logged-in user, the factory name and production line name where the molding machine 1 is installed, the original work number, the delivery year, the status, and the name of the demander's company. When the search condition is input into the device search table 81a and the search button is operated, the processing unit 51 determines the molding machine 1 owned by the user who meets the search condition and displays it in the delivery machine list 81b. A hyperlink is inserted in the character representing the machine model.

[0107] When the model name is tapped or clicked, the processing unit 51 provides the terminal device 6 b with a delivery machine details screen 82 listing detailed information of the molding machine 1 corresponding to the operated model name.

[0108] Fig.15 8 is a schematic diagram showing an example of a delivery machine detailed screen 82. The delivery machine detailed screen 82 includes, for example, detailed information including the specifications of the extruder as the delivery machine in addition to the above-mentioned delivery machine information. For example, the delivery machine detailed screen 82 includes a display of the raw materials and capacity to be fed into the extruder. In addition, the delivery machine detailed screen 82 includes a link for downloading the delivery machine manual, which includes information on the operation method of the delivery machine and more detailed specifications. When the link is tapped or clicked, the processing unit 51 accesses the delivery machine DB 52c and the material DB 52e, reads the data of the delivery machine manual of the delivery machine or the molding machine 1, and sends it to the terminal device 6b.

[0109] Next, when the "Document Download" icon 74 is operated, the processing unit 51 provides the document related to the delivery machine of the logged-in user (step S14). Specifically, the processing unit 51 accesses the delivery machine DB 52c, and uses the user ID of the logged-in user as a key to identify the document number associated with the delivery machine of the logged-in user. Then, the processing unit 51 accesses the document DB 52e, and uses the document number as a key to extract the data of the document related to the delivery machine of the logged-in user, and creates a document list 83a. The processing unit 51 sends web page data for displaying the document list 83a to the terminal device 6a. The terminal device 6a receives the web page data and displays the document list display screen 83.

[0110] Fig.16 8 is a schematic diagram showing an example of a document list display screen 83. The document list display screen 83 includes, for example, a document list 83a showing the document title and summary of each document associated with the delivery machine of the logged-in user. The document list 83a has a document download button 83b for downloading each document. When the document download button 83b is operated, the processing unit 51 reads the document data corresponding to the operated document download button 83b from the document DB 52e and transmits it to the terminal device 6a.

[0111] Next, when the "quotation request" icon 75 is operated, the processing unit 51 prepares a quotation for the replacement cost of the components constituting the delivery machine of the logged-in user, and provides it to the logged-in user (step S15). Specifically, the processing unit 51 accesses the delivery machine DB 52c and the component DB 52d to extract information on the components constituting the delivery machine of the logged-in user, and displays a quotation target component selection screen 84 for accepting quotation target components. Then, the processing unit 51 sends web page data for displaying the quotation target component selection screen 84 to the terminal device 6a. The terminal device 6a receives the web page data and displays the quotation target component selection screen 84.

[0112] Fig.17 : is a schematic diagram showing an example of a quotation target component selection screen 84. The quotation target component selection screen 84 includes a device image 84a such as a side view, a top view, and a front view showing the appearance or cross-section of the molding machine 1, and a component list 84b that is a list of components constituting the molding machine 1. The device image 84a includes numbers representing components constituting the molding machine 1. The component list 84b is a table that lists the numbers, product names, dimensions and specifications, materials, quantities, and qualities assigned to the components. The component list 84b has a selection button ( Fig.17The "Add" button 84c in the figure is provided in the rows corresponding to the plurality of components. When the "Add" button 84c is operated, the information processing device 5 accepts the component corresponding to the operated "Add" button 84c as a quotation object. When the quotation preparation button (not shown) is operated, the processing unit 51 prepares a quotation for replacing the selected component. Then, the processing unit 51 sends the quotation data to the terminal device 6a.

[0113] Next, when the "My Page" icon 71 is operated and the quotation request list display operation included in the My Page is performed, the processing unit 51 of the information processing device 5 creates the quotation history list display screen 85 and provides it to the logged-in user (step S16).

[0114] Fig.18 8 is a schematic diagram showing an example of a quotation history list display screen 85. The quotation history list display screen 85 has a quotation search table 85a for searching for quotation sheets. In addition, the quotation history list display screen 85 includes a quotation history list 85b, which includes a quotation request date, a quotation request number, a production line name, a machine model, a purpose, a factory name, an original work number, and a demander company name. When a search condition is input into the quotation search table 85a and a search button is operated, the processing unit 51 determines the quotation sheets that meet the search condition and displays them in a list in the quotation history list 85b.

[0115] If there is no problem with the quotation prepared in step S15, the logged-in user can order the components via the terminal device 6a. The information processing device 5 that receives the order instruction performs the component ordering process (step S17). For example, the information processing device 5 sends the component ordering content to the terminal of the component manufacturing factory. The information processing device 5 can also be configured to notify the terminal device 6b of the salesperson of the logged-in user of the component order.

[0116] Next, when the "order status confirmation" icon 72 is operated, an order status overview display screen 86 showing the order status of the component is created and provided to the logged-in user (step S18). In addition, when the "inquiry" icon 76 is operated, the information processing device 5 displays an inquiry screen and accepts inquiries from the logged-in user (step S19).

[0117] Fig.198 is a schematic diagram showing an example of an order status list display screen 86. The order status list display screen 86 has an order search table 86a. In addition, the order status list display screen 86 has an order status list 86b, which includes a shipping guide number, a status, a component work number, a machine type, a factory name, a production line name, a demander company name, an order source order number, a person in charge, and a contract delivery period. The processing unit 51 accesses the order DB 52g, uses the user ID of the logged-in user as a keyword, reads out data related to the order status of the components of the logged-in user, and creates the order status list 86b. Then, the processing unit 51 sends web page data for displaying the order status list display screen 86 to the terminal device 6a. The terminal device 6a receives the web page data and displays the order status list display screen 86. When the search condition is input to the order search table 86a and the search button is operated, the processing unit 51 determines the data associated with the order status that meets the search condition, and displays the order status list in the order status list 86b.

[0118] As described above, the case where the user logs in to the equipment management website is described. However, when the salesperson logs in to the equipment management website using the terminal device 6b, the specifications and status of the molding machine 1 of the responsible user can also be confirmed in the same manner. Specifically, the processing unit 51 accesses the user DB 52b and determines one or more user IDs associated with the ID of the logged-in salesperson. Then, the processing unit 51 performs the same processing as described above by using the determined user ID, and can provide the terminal device 6b with various information indicating the specifications and status of the molding machine 1 of the user in charge of the salesperson.

[0119] As described above, according to the information processing method and the like of the first embodiment, it is possible to provide a device list showing the specifications and states of each of the plurality of molding machines 1 installed in a plurality of factories belonging to each user to the user and the user's salesperson.

[0120] For example, users and sales personnel can confirm the repair history, technical information, maintenance management methods, etc. of each molding machine.

[0121] In addition, the processing unit 51 can display the delivery machine list display screen 81, the delivery machine detail screen 82, the data list display screen 83, the quotation history list display screen 85, and the order status list display screen 86 on the terminal devices 6a and 6b. The user and the salesperson can check each display screen to understand the status and specifications of the delivery machines located in the plurality of factories belonging to the user, the quotation history of the components, the order status, etc.

[0122] (Implementation Method 2)

[0123] The information processing device 5 of the second embodiment is configured to enable the device management website (first website) and the device status information providing website (second website) to be transferred to each other, which is different from the first embodiment. The other structures of the information processing device 5 are the same as those of the information processing device 5 of the first embodiment, so the same reference numerals are attached to the same parts and detailed descriptions are omitted.

[0124] Fig. 20 This is a flowchart showing an information processing procedure including a transfer process to a device management website according to Embodiment 2. The data collection device 3 of the molding machine 1 collects physical quantity data associated with the states of the plurality of components constituting the molding machine 1 (step S31), and sends the collected physical quantity data to the information processing device 5 functioning as the first server (step S32). In addition, there are a plurality of molding machines 1 and data collection devices 3, and the plurality of data collection devices 3 send the physical quantity data collected from the plurality of molding machines 1 to the information processing device 5.

[0125] The processing unit 51 of the first server receives the physical quantity data transmitted from the data collection device 3 (step S33). The processing unit 51 stores the received physical quantity data in the collected data DB 52a (step S34). The processing unit 51 that performs the process of step S33 functions as an acquisition unit that acquires physical quantity data.

[0126] Next, the processing unit 51 estimates the remaining life or abnormality of the components constituting the molding machine 1 based on the physical quantity data accumulated in the collected data DB 52a (step S35). Specifically, the processing unit 51 performs frequency analysis on the physical quantity data and converts it into image data, inputs the image data representing the physical quantity data into the prediction learning model 54, and outputs the remaining life data or abnormality data of the components. In addition, the processing unit 51 calculates the remaining life or abnormality of each of the multiple components constituting the multiple molding machines 1. When the physical quantity data associated with the states of the multiple components constituting one molding machine 1 is obtained, the processing unit 51 calculates the remaining life or abnormality of each of the multiple components.

[0127] Next, the processing unit 51 determines whether the remaining life is less than a predetermined time N (step S36). The predetermined time N is preferably at least longer than the time required to manufacture the component and secure a spare part. The predetermined time N varies depending on the type of component.

[0128] Furthermore, the processing unit 51 may be configured to determine whether the abnormality degree is smaller than a predetermined value corresponding to the predetermined time N described above.

[0129] If it is determined that the remaining life is greater than the predetermined time N (step S36: No), the processing unit 51 returns the process to step S33. If it is determined that the remaining life is less than the predetermined time N (step S36: Yes), the processing unit 51 makes the estimated result display screen 9 visible on the device status providing website (step S37). That is, when the user and the salesperson access the device status providing website via the terminal device 6a, 6b, the processing unit 51 makes the estimated result display screen 9 display the remaining life of the component.

[0130] Fig.21 This is an example of the estimation result display screen 9. The estimation result display screen 9 includes a status display unit 91 for displaying the status of components constituting each molding machine 1 for one or more molding machines 1 used by the user. The status display unit 91 includes, for example, a component name display unit 92 for displaying the name of the component constituting the molding machine 1 and an icon 93 indicating whether the component is abnormal. "Abnormal" corresponds to, for example, a remaining life less than a predetermined time N. In addition, the status display unit 91 displays the abnormality of the component in digits.

[0131] When an abnormality occurs in a component constituting the molding machine 1, the state display unit 91 displays a remaining life display icon 94 for displaying the estimated remaining life of the component. When the remaining life display icon 94 is operated by the user, the information processing device 5 displays a graph showing a time change of a physical quantity associated with the state of the component and the estimated remaining life of the component.

[0132] When there is an abnormality in a component constituting the molding machine 1, the status display unit 91 displays a quotation icon 95 and a document icon 96 for transferring to a device management website that provides a quotation and document data of the replacement cost of the component. The quotation icon 95 includes the address of a web page for quotation entrustment in the device management website and the original work number of the molding machine 1. The quotation icon 95 is sent to the terminal device 6a. The document icon 96 includes the address of a web page of a document list display screen 83 in the device management website and the original work number of the molding machine 1 according to the user.

[0133] The user's terminal device 6a requests the estimated result related to the remaining life of the component from the device status information providing website in accordance with the operation of the remaining life display icon 94 performed by the user (step S38). The processing unit 51 of the device status information providing website sends the estimated result of the remaining life of the component to the terminal device 6a in accordance with the request from the terminal device 6a (step S39). The terminal device 6a receives the estimated result sent from the device status information providing website and displays the received estimated result. The user can view the estimated result of the remaining life or abnormality of the component.

[0134] The user's terminal device 6a requests the equipment management website for the data related to the molding machine 1 indicated by the original work number according to the operation of the data icon 96 performed by the user (step S40). The processing unit 51 of the equipment management website reads out and provides the data data associated with the original work number from the data DB 52e according to the request from the terminal device 6a (step S41).

[0135] The user's terminal device 6a requests the equipment management website to prepare a quotation for the components constituting the molding machine 1 indicated by the original job number according to the operation of the quotation icon 95 by the user (step S42). The processing unit 51 of the equipment management website displays the quotation target component selection screen 84 in response to the request from the terminal device 6a, and prepares and provides the quotation (step S43).

[0136] Fig. 22 1 is a flowchart showing the information processing process including the transfer process to the equipment status information providing website in Embodiment 2. The user's terminal device 6a requests the delivery machine list 81b according to the user's operation (step S51). The processing unit 51 of the equipment management website creates the delivery machine list 81b according to the request from the terminal device 6a and provides it to the logged-in user (step S52). The delivery machine list 81b in Embodiment 2 has a remaining life display icon of the molding machine 1.

[0137] The user's terminal device 6a requests the estimated result of the remaining life from the equipment status information providing website according to the operation of the remaining life display icon by the user (step S53). The processing unit 51 of the equipment status information providing website provides the estimated result of the remaining life of the molding machine 1 according to the request from the terminal device 6a (step S54).

[0138] The case where the user logs in to the equipment management website and the equipment status information providing website has been described. However, when the salesperson logs in to the equipment management website and the equipment status information providing website using the terminal device 6b, the specifications and status of the molding machine 1 of the responsible user, the remaining life and abnormality of the components constituting each molding machine 1, etc. can also be confirmed. Specifically, the processing unit 51 accesses the user DB 52b and determines one or more user IDs associated with the ID of the logged-in salesperson. Then, the processing unit 51 performs the same processing as described above by using the determined user ID, and can provide the terminal device 6b with various information indicating the specifications and status of the molding machine 1 of the user in charge of the salesperson, the remaining life and abnormality of the components constituting the molding machine 1, etc.

[0139] As described above, according to the information processing method of this embodiment 1, by transferring between the device status information providing website and the device management website, it is possible to manage the specifications and status of the molding machines 1 respectively installed in multiple factories belonging to the user, and it is possible to confirm more specific equipment status such as the remaining life of the molding machine 1.

[0140] In addition, the information processing device 5 can provide information indicating the remaining life or abnormality of components constituting each molding machine of the user to the user and the salesperson.

[0141] Means for solving the problems of the present disclosure are appended.

[0142] (Note 1)

[0143] An information processing method, wherein:

[0144] Identifiers for identifying multiple users, factory identifiers for identifying multiple factories belonging to the multiple users, equipment identifiers for identifying multiple industrial machines respectively installed in the multiple factories, and equipment association information including specifications of the multiple industrial machines are established in a corresponding relationship and stored in a database.

[0145] The factory identifier, the equipment identifier, and the equipment-related information that are associated with the identifier of one of the users are read from the database, and an equipment list is created, the equipment list including a plurality of the factories belonging to the one user, a plurality of the industrial machines installed in the plurality of factories, and the equipment-related information.

[0146] The data of the created equipment list is provided to the one user and external stakeholders related to the one user.

[0147] (Note 2)

[0148] The information processing method according to Supplement 1, wherein:

[0149] The device-related information includes information indicating a state of the industrial machine.

[0150] (Note 3)

[0151] The information processing method according to Appendix 1 or 2, wherein:

[0152] The equipment-related information includes a maintenance history of the industrial machine, technical information of the industrial machine, or a maintenance management method of the industrial machine.

[0153] (Note 4)

[0154] The information processing method according to any one of Notes 1 to 3, wherein:

[0155] The order status and scheduled delivery date of the components constituting the plurality of industrial machines are stored in the database in a corresponding relationship with the identifiers of the plurality of users;

[0156] reading out the order status and the scheduled delivery date associated with the identifier of the one user, and creating an order list of the order status and the scheduled delivery date of the component of the one user,

[0157] The created order list data is provided to the one user and external stakeholders related to the one user.

[0158] (Note 5)

[0159] The information processing method according to any one of Notes 1 to 4, wherein:

[0160] acquiring physical quantity data associated with states of components constituting the industrial machine of the one user,

[0161] Based on the acquired physical quantity data, the remaining life or abnormality of the component is estimated,

[0162] The generated estimation result is provided to the one user of the industrial machine and external persons related to the user.

[0163] (Note 6)

[0164] The information processing method according to Supplement 5, wherein:

[0165] The device list and the estimation result are provided via a first website that displays the device list and a second website that displays the estimation result.

[0166] (Note 7)

[0167] The information processing method according to Supplement 6, wherein:

[0168] the first website includes a link for transferring from a page related to the device list to a page related to the estimation result of the second website,

[0169] The second website includes a link for transitioning from a page related to the estimation result to a page related to the device list of the first website.

[0170] Description of Reference Numerals

[0171] 1: Molding machine

[0172] 2: Sensor

[0173] 3: Data collection device

[0174] 4: Router

[0175] 5: Information processing device

[0176] 6a: User's terminal device

[0177] 6b: Terminal device for sales staff

[0178] 10: Cylinder

[0179] 10a: Hopper

[0180] 11: Screw

[0181] 12: Mould

[0182] 13: Motor

[0183] 14: Reducer

[0184] 15: Control device

[0185] 31: Control Department

[0186] 32: Storage

[0187] 33: Ministry of Communications

[0188] 34: Data input section

[0189] 50: Recording medium

[0190] 51: Processing Department

[0191] 52: Storage

[0192] 53: Ministry of Communications

[0193] 54: Predictive Learning Model

[0194] 54a: Input layer

[0195] 54b: Middle layer

[0196] 54c: Output layer

[0197] 55: Frequency Analysis Department

[0198] 56: Image generation unit

[0199] 52a: Collect data DB

[0200] 52b: User DB

[0201] 52c: User device DB

[0202] 52d: Component related information DB

[0203] 52e: Quotation Template

[0204] P: Computer program.

Claims

1. An information processing method, wherein: Identifiers for identifying multiple users, factory identifiers for identifying multiple factories belonging to the multiple users, equipment identifiers for identifying multiple industrial machines respectively installed in the multiple factories, and equipment association information including specifications of the multiple industrial machines are established in a corresponding relationship and stored in a database. The factory identifier, the equipment identifier, and the equipment-related information that are associated with the identifier of one of the plurality of users are read from the database, and an equipment list is prepared, the equipment list including the plurality of factories belonging to the one user, the plurality of industrial machines installed in the plurality of factories, and the equipment-related information. The data of the created equipment list is provided to the one user and external stakeholders related to the one user.

2. The information processing method according to claim 1, wherein: The device-related information includes information indicating a state of the industrial machine.

3. The information processing method according to claim 1 or 2, wherein: The equipment-related information includes a maintenance history of the industrial machine, technical information of the industrial machine, or a maintenance management method of the industrial machine.

4. The information processing method according to any one of claims 1 to 3, wherein: The order status and scheduled delivery date of the components constituting the plurality of industrial machines are stored in the database in a corresponding relationship with the identifiers of the plurality of users; reading out the order status and the scheduled delivery date associated with the identifier of the one user, and creating an order list of the order status and the scheduled delivery date of the component of the one user, The created order list data is provided to the one user and external stakeholders related to the one user.

5. The information processing method according to any one of claims 1 to 4, wherein: acquiring physical quantity data associated with states of components constituting the industrial machine of the one user, Based on the acquired physical quantity data, the remaining life or abnormality of the component is estimated, The generated estimation result is provided to the one user of the industrial machine and external persons related to the user.

6. The information processing method according to claim 5, wherein: The device list and the estimation result are provided via a first website that displays the device list and a second website that displays the estimation result.

7. The information processing method according to claim 6, wherein: the first website includes a link for transferring from a page related to the device list to a page related to the estimation result of the second website, The second website includes a link for transitioning from a page related to the estimation result to a page related to the device list of the first website.

8. An information processing device, wherein: have: a database storing identifiers for identifying a plurality of users, factory identifiers for identifying a plurality of factories respectively belonging to the plurality of users, equipment identifiers for identifying a plurality of industrial machines respectively installed in the plurality of factories, and equipment-related information including specifications of the plurality of industrial machines in a corresponding relationship; a processing unit that reads the factory identifier, the equipment identifier, and the equipment-related information that are associated with an identifier of one of the users from the database, and creates an equipment list that includes a plurality of the factories belonging to the one user, a plurality of the industrial machines installed in the plurality of factories, and the equipment-related information; as well as The communication unit provides the created data of the device list to the one user and external stakeholders related to the one user.

9. A computer program for causing a computer to execute the following processing: Identifiers for identifying multiple users, factory identifiers for identifying multiple factories belonging to the multiple users, equipment identifiers for identifying multiple industrial machines respectively installed in the multiple factories, and equipment association information including specifications of the multiple industrial machines are established in a corresponding relationship and stored in a database. The factory identifier, the equipment identifier, and the equipment-related information that are associated with the identifier of one of the users are read from the database, and an equipment list is created, the equipment list including a plurality of the factories belonging to the one user, a plurality of the industrial machines installed in the plurality of factories, and the equipment-related information. The data of the created equipment list is provided to the one user and external stakeholders related to the one user.

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