Information processing method, information processing device, and computer program

Abstract

The use registration information indicating the presence or absence of use of a maintenance management service, which is a service for securing a spare part of a component before the component constituting the molding machine is damaged, is associated with an identifier of a user of the molding machine, and is stored in a storage unit. Acquiring physical quantity data associated with a state of a component constituting the molding machine; estimating the remaining life or the degree of abnormality of the component from the acquired physical quantity data; determining, on the basis of the estimated remaining life or abnormality of the component, whether or not spare parts of the component need to be secured at the latest before a prescribed period corresponding to the component; when it is determined that the spare part of the component needs to be secured, processing related to securing the spare part of the component that needs to be replaced is executed on the basis of the use registration information stored in the storage unit.

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 a life prediction device for predicting the remaining life of a rotating part in an injection molding machine, etc. The life prediction device of Patent document 1 accumulates the number of rotations of the rotating part rotated by a driving motor, and calculates the fatigue life of the rotating part based on the accumulated number of rotations and the torque required to rotate the rotating part.

[0003] Patent Document 2 discloses an abnormality detection device including a vibration sensor for detecting vibration of a ball screw provided in an injection molding machine, and detecting abnormality of the ball screw by analyzing the intensity of vibration detected by the vibration sensor.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 6-91683

[0007] Patent Document 2: Japanese Patent Application Publication No. 2021-74917 Summary of the invention

[0008] Some of the components that make up molding machines such as injection molding machines and extruders require considerable time to secure replacement parts. Even if the remaining life of a component can be predicted, if the work required to replace the component is not advanced, it will be impossible to prepare a new component before the component breaks, and there is a risk that the molding machine will not be able to operate.

[0009] The purpose of the present disclosure is to provide an information processing method, an information processing device and a computer program, which can estimate the remaining life or abnormality of a component before the molding machine cannot operate due to damage of the component, and ensure spare parts of the component in advance.

[0010] In an information processing method according to one aspect of the present disclosure, registration information indicating whether or not a maintenance management service has been utilized is established and stored in a storage unit in correspondence with an identifier of a user of a molding machine, wherein the maintenance management service is a service for ensuring a spare part of a component before the component constituting the molding machine is damaged; obtaining physical quantity data associated with the state of the component constituting the molding machine; estimating the remaining life or abnormality of the component based on the acquired physical quantity data; determining whether it is necessary to ensure a spare part for the component at least before a prescribed period required to ensure a spare part for the component based on the estimated remaining life or abnormality of the component; and if it is determined that it is necessary to ensure a spare part for the component, executing processing related to ensuring a spare part for the component that needs to be replaced based on the registration information stored in the storage unit.

[0011] An information processing device according to one aspect of the present disclosure comprises: an acquisition unit for acquiring physical quantity data associated with the state of a component constituting a molding machine; a storage unit for storing utilization registration information indicating whether or not a maintenance management service has been utilized in correspondence with an identifier of a user of the molding machine, wherein the maintenance management service is a service for ensuring spare parts for the component in advance before the component constituting the molding machine is damaged; and a processing unit for estimating a remaining life or abnormality of the component based on the acquired physical quantity data; determining whether it is necessary to ensure spare parts for the component at the latest before a prescribed period required for ensuring spare parts for the component is determined based on the estimated remaining life or abnormality of the component; and if it is determined that it is necessary to ensure spare parts for the component, executing processing related to ensuring spare parts for the component that needs to be replaced based on the utilization registration information stored in the storage unit.

[0012] A computer program according to one aspect of the present disclosure is used to cause a computer to perform the following processing: storing utilization registration information indicating whether or not a maintenance management service has been utilized in correspondence with an identifier of a user of a molding machine in a storage unit, wherein the maintenance management service is a service for ensuring a spare part of a component before the component constituting the molding machine is damaged; acquiring physical quantity data associated with the state of the component constituting the molding machine; estimating the remaining life or abnormality of the component based on the acquired physical quantity data; determining whether it is necessary to ensure a spare part for the component at least before a prescribed period required to ensure a spare part for the component based on the estimated remaining life or abnormality of the component; and if it is determined that it is necessary to ensure a spare part for the component, executing processing related to ensuring a spare part for the component that needs to be replaced based on the utilization registration information stored in the storage unit.

[0013] Effects of the Invention

[0014] According to the present disclosure, before a molding machine cannot be operated due to damage of a component constituting the molding machine, the remaining life or abnormality of the component can be estimated, and spare parts of the component can be secured in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a block diagram showing a configuration example of a molding machine system according to the first embodiment.

[0016] Figure 2 It is a schematic diagram showing a configuration example of a molding machine according to the first embodiment.

[0017] Figure 3 It is a block diagram showing a configuration example of the data collection device according to the first embodiment.

[0018] Figure 4 This is a block diagram showing a configuration example of an information processing device according to Embodiment 1.

[0019] Figure 5 This is a conceptual diagram showing an example of a record layout of a collected data DB.

[0020] Figure 6 This is a conceptual diagram showing an example of a record layout of a user DB.

[0021] Figure 7 This is a conceptual diagram showing an example of a record layout of a user device DB.

[0022] Figure 8 This is a conceptual diagram showing an example of a record layout of a report DB.

[0023] Fig. 9 This is a block diagram showing an estimation processing unit that predicts the remaining life or abnormality of a component.

[0024] Fig.10 Flowchart showing the processing procedure of the information processing device.

[0025] Fig.11 Flowchart showing the processing procedure of the information processing device.

[0026] Fig.12 Flowchart showing the processing procedure of the information processing device.

[0027] Fig.13 This is a graph showing the cost-effectiveness of the maintenance management according to the first embodiment.

[0028] Fig.14 This is a block diagram showing an estimation processing unit according to the second embodiment.

[0029] Fig.15 This is a conceptual diagram showing an example of a record layout of a user device DB according to the third embodiment. DETAILED DESCRIPTION

[0030] The information processing method, information processing device and computer program of the embodiments of the present disclosure are described below 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 be combined arbitrarily.

[0031] (Implementation Method 1)

[0032] Figure 1 1 is a block diagram showing a configuration example 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, 6b, and 6c. The molding machine 1 includes an injection molding machine and an extruder. In the following, an extruder is described as an example of the molding machine 1.

[0033] Figure 1 One molding machine 1 and a data collection device 3 are shown, but a plurality of data collection devices 3 not shown are connected to an 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 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 the respective factories of a plurality of users who own the molding machines 1. The user is an employee or staff member of an organization such as a legal person who owns the molding machine 1. Hereinafter, the employee or staff member is referred to as a user.

[0034] The terminal devices 6a, 6b, and 6c are communication terminals with display units such as computers, tablet terminals, and smart phones. The terminal device 6a is a terminal used by the user. The terminal device 6b is a terminal used by service providers such as sales personnel and maintenance managers related to the molding machine 1 of the user. The terminal device 6c is a terminal used by personnel in a factory that manufactures components constituting the molding machine 1.

[0035] Hereinafter, the service provider will be referred to as a salesperson. In addition, the operator on the salesperson side who provides maintenance and management services of the components constituting the molding machine 1 to the user and performs production and sales of the components will be referred to as a maintenance and management operator.

[0036] Background

[0037] The molding machine system of the present embodiment 1 optimizes the maintenance management of the components of the molding machine 1. The components constituting the molding machine 1 include mass-produced general-purpose products and customized products that vary depending on the user and the molding machine 1. Among the customized products, there are components that require time from ordering to manufacturing, and there are also components that do not. The present embodiment 1 is particularly effective for the maintenance management of components that are customized products and require time to manufacture. For example, the reducer 14 of the extruder is one example. The specifications of the reducer 14 vary depending on the user and the molding machine 1, and there are cases where the manufacture of the reducer 14 takes several months, and the shutdown of the molding machine 1 due to damage to the reducer 14 is a major risk.

[0038] Therefore, the user usually performs maintenance such as overhaul of the reducer 14 at a certain period of several years. Overhaul at intervals of several years will minimize the risk of stopping operation, but it is not necessarily the best overhaul period depending on the working conditions and use environment of the molding machine 1. However, if the overhaul period is set to be long and the reducer 14 is damaged as a result, serious damage will occur due to the shutdown of the molding machine 1.

[0039] Although the maintenance and management operator can prepare spare parts for the reducer 14, preparing customized products for different users in advance will bring risks to the maintenance and management operator. If the period from the preparation of spare parts to the actual replacement of parts is too long, the cost of storage and status management of parts will become high. In addition, if the molding machine 1 is no longer used before the parts are replaced, or if the products of other operators are adopted, the spare parts will be discarded.

[0040] The molding machine system of the first embodiment makes it easy to predict the time of component replacement by estimating the remaining life or abnormality of the components of the molding machine 1 and notifying the user and the salesperson. In addition, the molding machine system enables the maintenance operator to start securing spare parts (new parts) at the best time before the components such as the reducer 14 are damaged.

[0041] When the molding machine system of the first embodiment is used, the maintenance operator starts manufacturing the customized product before the parts of the molding machine 1 are damaged, and therefore bears a certain risk. Here, the following service form is assumed in the first embodiment.

[0042] The maintenance management operator provides the following services, that is, the remaining life or abnormality of the components constituting the molding machine 1 is estimated, and the status of the molding machine 1 and the components are notified to the user. In addition, the maintenance management operator predicts the replacement time of the components constituting the molding machine 1, and manufactures spare parts in advance, and provides spare parts of the components before or when the components are damaged. Through these services, the user can replace the components of the molding machine 1 at the optimal time and avoid the risk of the molding machine 1 stopping operation.

[0043] For the above services, the user pays the maintenance management operator a warranty fee of a certain amount on a monthly basis. The user pays the maintenance management operator a replacement fee when replacing a component. The replacement fee varies depending on the operating conditions of the molding machine 1, the usage environment, the failure frequency of the component, etc. This is because the risk borne by the maintenance management operator varies with these various factors.

[0044] <Molding machine 1>

[0045] Figure 2 1 is a schematic diagram showing a configuration example of a molding machine 1 according to the first embodiment. The molding machine 1 includes a cylinder 10 equipped with a hopper 10a into which a resin raw material is fed, two screws 11, and a mold 12 provided at an outlet portion of the cylinder 10 (see Figure 1 The two screws 11 are arranged approximately parallel to each other in a meshing state, and are inserted into the hole of the cylinder 10 in a rotatable manner to push the resin raw material fed into the hopper 10a in the extrusion direction ( Figure 1 and Figure 2 The molten resin raw material is discharged from the mold 12 having a through hole.

[0046] The screw 11 is formed by combining a plurality of screw segments and integrating them into one screw 11. For example, the screw 11 is formed by arranging and combining a forward spiral segment in a spiral screw shape for conveying the resin raw material in the forward direction, a reverse spiral segment for conveying the resin raw material in the reverse direction, and a kneading segment for kneading the resin raw material in the order and position corresponding to the characteristics of the resin raw material.

[0047] In addition, the molding machine 1 includes 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.

[0048] <Sensor 2>

[0049] 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 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.

[0050] 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 thermometers, position sensors, velocity sensors, acceleration sensors, ammeters, voltmeters, pressure gauges, timers, cameras, torque sensors, power meters, weight meters, etc.

[0051] 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.

[0052] The first sensor 21 is, for example, a vibration detector for detecting the vibration of the reducer 14. The second sensor 22 is, for example, 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.

[0053] <Control device 15>

[0054] The control device 15 is a computer that performs operation control on 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.

[0055] Specifically, the control device 15 sends the operation data indicating the operation status 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 top pressure of the screw 11, the mold pressure, the feeder supply amount (the supply amount of the resin raw material), the extrusion amount, the cylinder temperature, the resin pressure, etc.

[0056] The control device 15 receives various chart data and estimated result data indicating the remaining life or abnormality of the components constituting the molding machine 1 sent from the data collection device 3. 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 according to the remaining life or abnormality indicated by the received estimated result data.

[0057] <Data collection device 3>

[0058] Figure 31 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 includes 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).

[0059] The control unit 31 has arithmetic processing circuits such as a CPU (Central Processing Unit), a multi-core CPU, an ASIC (Application Specific Integrated Circuit), and an FPGA (Field-Programmable Gate Array), internal storage devices such as a ROM (Read Only Memory), and a RAM (Random Access Memory), and I / O terminals, etc. The control unit 31 collects physical quantity data and transmits it to the information processing device 5 by executing a control program stored in a storage unit 32 described later. In addition, each functional unit of the data collection device 3 can be implemented in the form of software, and part or all of it can also be implemented in the form of hardware.

[0060] The storage unit 32 is a nonvolatile memory such as a hard disk, an EEPROM (Electrically Erasable Programmable ROM), or a flash memory. The storage unit 32 stores a control program for causing a computer to perform a collection process of physical quantity data.

[0061] The communication unit 33 is a communication circuit that transmits and receives information according to a predetermined communication protocol such as Ethernet (registered trademark). 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 transmit and receive various information with the control device 15 via the communication unit 33. The control unit 31 obtains physical quantity data via the communication unit 33.

[0062] 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.

[0063] The data input unit 34 is an input interface to which a signal output from the sensor 2 is input. 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.

[0064] <Information processing device 5>

[0065] Figure 4 1 is a block diagram showing a configuration example of the information processing device 5 according to Embodiment 1. The information processing device 5 is a computer, and includes 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 .

[0066] 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.

[0067] The information processing device 5 of the first embodiment functions as a device status providing web server that provides information on the status of the molding machine 1 to users and sales personnel. In addition, the information processing device 5 functions as a component information providing web server that provides information on components constituting the molding machine 1 to users and sales personnel. The component information providing web server performs processing such as accepting component orders. In addition, each functional unit of the information processing device 5 may be implemented in the form of software, or part or all of it may be implemented in the form of hardware.

[0068] The communication unit 53 is a communication circuit that sends and receives information according to a predetermined communication protocol such as Ethernet (registered trademark). The communication unit 53 is connected to the data collection device 3 and the terminal devices 6a, 6b, 6c 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, 6c via the communication unit 53.

[0069] 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 that causes 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 user device DB (database) 52c, and a report DB (database) 52d.

[0070] The computer program P, etc. may also be recorded in the recording medium 50 in a computer-readable manner. 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.

[0071] The prediction learning model 54 is an image recognition learning model, and when image data generated from physical quantity data is input, it outputs data indicating the remaining life or abnormality of the components constituting the molding machine 1. The prediction learning model 54 has, 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 learning model.

[0072] Figure 5 This is a conceptual diagram showing an example of the record layout of the collected data DB52a. The collected data DB52a includes 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.

[0073] 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 physical quantities representing the time series of the operating state of the molding machine 1, such as motor current, rotation speed of the screw 11, top pressure of the screw 11, mold 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.

[0074] 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 "user basic information" column, a "service utilization registration" column, a "utilization registration date" column, and a "parts purchase history" column.

[0075] The "User ID" column stores the identifier of the user of the molding machine 1. The "User Basic Information" column stores the basic information of the user, for example, information indicating whether the company information such as the number of employees or maintenance schedule of the company as the user is used. The "Service Utilization Registration" column stores information indicating whether the maintenance management service of the present embodiment 1 is used as utilization registration information.

[0076] The "registration date" column stores the registration date for the maintenance management service of this embodiment 1. The "parts purchase history" column stores the purchase history of the parts purchased by the user. The purchase history stores, for example, the type of parts purchased, the purchase date, the purchase quantity, etc.

[0077] Figure 7 This is a conceptual diagram showing a row of record layouts of the user device DB 52c. The user device DB 52c includes a hard disk and a DBMS, and stores information on components constituting the molding machine 1 used by the user. For example, the user device DB 52c has a "user ID" column, a "device ID" column, a "component ID" column, a "component specification information" column, and a "remaining life or abnormality" column.

[0078] The "user ID" column stores the identifier of the user of the molding machine 1. The "equipment ID" column stores the equipment identifier of the molding machine 1. The "component ID" column stores the component identifier of the component constituting the molding machine 1 and being the target of the prediction of the remaining life or abnormality.

[0079] 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 products of special specifications manufactured for each user. The specification information includes information required to manufacture components, etc., in order to ensure spare parts.

[0080] The “remaining life or abnormality” column stores the remaining life or abnormality of the component corresponding to the component ID. The remaining life or abnormality is predicted by the prediction learning model 54 .

[0081] Figure 8This is a conceptual diagram showing an example of the record layout of the report DB 52d. The report DB 52d includes a hard disk and a DBMS, and stores information on components constituting the molding machine 1 used by the user. For example, the report DB 52d has a "report ID" column, a "device ID" column, a "component ID" column, a "report date and time" column, a "report data" column, and the like.

[0082] The "report ID" column stores an identifier for identifying report data of maintenance results submitted by the user. The "equipment ID" column and the "component ID" column store an equipment identifier and a component identifier for identifying the molding machine 1 and the component to be reported.

[0083] The "Report Date" column stores the year, month, and day when the report data submitted by the user is received. The "Report Data" column stores the report data submitted by the user. The report data includes data on the maintenance results of the molding machine 1 or the component. The report data includes image data obtained by photographing the molding machine 1 or the component.

[0084] Fig. 9 1 is a block diagram showing an estimation processing unit M for estimating 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 can be implemented in software through the processing of the processing unit 51, or part or all of it can be implemented in hardware.

[0085] The frequency analysis unit 55 is a calculation 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 use the short-time Fourier transform (STFT: Short-Time Fourier Transform) to perform Fourier transform on the physical quantity data. The image generation unit 56 is a calculation 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. In the following, the image obtained by Fourier transforming the physical quantity data is called a Fourier transform image.

[0086] 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.

[0087] The prediction learning model 54 is a convolutional neural network (CNN) having an input layer 54a to which image data of a Fourier transformed 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.

[0088] 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 for convolving the pixel values ​​of each pixel of the Fourier transform image input to the input layer 54a and a pooling layer for mapping the pixel values ​​obtained by convolution in the convolution layer are alternately connected. 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 feature quantity of the Fourier transform image, i.e., the physical quantity data, to the output layer 54c.

[0089] 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 time point of physical quantity data measurement.

[0090] The prediction learning model 54 is learned to output remaining life data indicating the remaining life of a predetermined period or more required to secure spare parts of the components of the molding machine 1 at the latest. The prediction learning model 54 is learned to output the degree of abnormality occurring at least before the predetermined period.

[0091] 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 learned in advance using general image data as training data is prepared.

[0092] 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.

[0093] The remaining life given when creating the training data includes a remaining life of more than a prescribed period required to ensure spare parts of the components of the molding machine 1. When creating the prediction learning model 54 of the output abnormality, the abnormality given when creating the training data includes at least the abnormality that occurred before the prescribed 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 more than a prescribed period required to ensure spare parts of the components of the molding machine 1.

[0094] 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 weighting factor of the prediction learning model 54 by using an error back propagation algorithm, an error gradient descent algorithm, etc. of the training data, thereby subjecting the prediction learning model 54 to machine learning. Furthermore, the processing unit 51 causes the storage unit 52 of the information processing device 5 to store the learned prediction learning model 54.

[0095] In addition, the processing unit 51 can 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 to relearn the prediction learning model 54 at an appropriate time. The processing unit 51 creates new training data by assigning correction labels to the physical quantity data obtained from the molding machine 1 during the operation as training data, so as to relearn the prediction learning model 54.

[0096] In addition, here, an example of relearning of the information processing device 5 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 prediction learning model 54 obtained by relearning to the information processing device 5.

[0097] In addition, CNN is cited as an example of the prediction learning model 54, but it can be composed of a multilayer perceptron (Multilayer perceptron: 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), or 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).

[0098] <Handling of spare parts for secured parts>

[0099] Fig.10 , Fig.11 and Fig.12 2 is a flowchart showing the processing procedure of the information processing device 5. The processing unit 51 of the information processing device 5 executes the registration process of the maintenance management service according to the first embodiment (step S11).

[0100] The user can register for the use of the maintenance management service of the first embodiment using the terminal device 6a. Alternatively, the user can apply for the use of the maintenance management service to the salesperson, and the salesperson can register for the use of the maintenance management service of the first embodiment using the terminal device 6b. The terminal devices 6a and 6b accept the operation of the user or the salesperson, and transmit various registration information required for starting the use of the maintenance management service. When the processing unit 51 receives the registration information of the maintenance management service via the terminal devices 6a and 6b, it stores the registration information indicating the use of the maintenance management service in the user DB in correspondence with the user identifier.

[0101] Next, the processing contents assuming a specific user are described. The processing unit 51 of the information processing device 5 determines whether there is a registration for use of the maintenance management service in the present embodiment 1 (step S12). If it is determined that there is no registration for use (step S12: No), the processing unit 51 ends the processing.

[0102] On the other hand, 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 S13), and transmits the collected physical quantity data to the information processing device 5 (step S14). In addition, there are a plurality of molding machines 1 and data collection devices 3, and the plurality of data collection devices 3 transmit the physical quantity data collected from the plurality of molding machines 1 to the information processing device 5.

[0103] When it is determined in step S12 that there is a registration for use (step S12: Yes), the processing unit 51 receives the physical quantity data sent from the data collection device 3 (step S15). The processing unit 51 stores the received physical quantity data in the collected data DB 52a (step S16). In addition, the processing unit 51 that executes the process of step S15 functions as an acquisition unit that acquires physical quantity data.

[0104] The terminal device 6b of the salesperson requests the information processing device 5 for data related to the operating status of the user's molding machine 1 according to the operation of the salesperson (step S17). The processing unit 51 of the information processing device 5 responds to the request from the terminal device 6b and sends physical quantities such as vibration data and shaft torque data, operating data, etc. to the terminal device 6b (step S18). The terminal device 6b receives the data sent from the information processing device 5 and displays the received data on the operating status. The salesperson can access the website provided by the information processing device 5, view the physical quantity data related to the status of the molding machine 1 and its components, and confirm the status of the molding machine 1 and its components.

[0105] Next, the processing unit 51 of the information processing device 5 determines whether it is the maintenance period of the molding machine 1 (step S19). The method for setting the maintenance period is not particularly limited. The maintenance period is set, for example, to come every predetermined period from the start date of use of the molding machine 1. The maintenance period can be changed according to the operating status of the molding machine 1, the use environment and place of use of the molding machine 1, and the total operating time.

[0106] If it is determined that it is not the maintenance period of the molding machine 1 (step S19: No), the processing unit 51 performs the processing after step S27 described later. If it is determined that it is the maintenance period (step S19: Yes), the processing unit 51 sends maintenance request data requesting maintenance of the molding machine 1 to the terminal device 6a of the user of the molding machine 1 (step S20).

[0107] The terminal device 6b receives the maintenance request data transmitted from the information processing device 5 (step S21). The terminal device 6b that has received the maintenance request data notifies the molding machine 1 of the maintenance time, displays a message urging maintenance, and accepts input of maintenance information (step S22).

[0108] The user of the molding machine 1 performs maintenance on the molding machine 1 and images at least one of the molding machine 1 and the components. The user inputs the maintenance results and image data obtained by imaging the molding machine 1 or the components into the terminal device 6b as maintenance information.

[0109] The terminal device 6b transmits the report data including the input maintenance information to the information processing device 5 (step S23).

[0110] The information processing device 5 receives the report data transmitted from the terminal device 6b (step S24), and the processing unit 51 stores the received report data in the report DB 52d (step S25).

[0111] The terminal device 6b of the salesperson requests the user's report data from the information processing device 5 according to the operation of the salesperson (step S26). In response to the request from the terminal device 6b, the processing unit 51 of the information processing device 5 reads the report data from the report DB 52d and sends it to the terminal device 6b (step S27). The terminal device 6b receives the report data sent from the information processing device 5 and displays the received report data. The salesperson can read the report and confirm the maintenance status of the molding machine 1.

[0112] 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 S28). Specifically, the processing unit 51 performs frequency analysis on the physical quantity data and converts it into image data, and inputs the image data representing the physical quantity data into the prediction learning model 54, thereby outputting 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. In the case where the physical quantity data associated with the states of the multiple components constituting one molding machine 1 has been obtained, the processing unit 51 calculates the remaining life or abnormality of each of the multiple components.

[0113] Next, the processing unit 51 determines whether the remaining life is less than a predetermined time N (step S29). 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.

[0114] 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.

[0115] When it is determined that the remaining life is greater than the predetermined time N (step S29: No), the processing unit 51 returns the process to step S15. When it is determined that the remaining life is less than the predetermined time N (step S29: Yes), the processing unit 51 transmits notification data indicating that the remaining life of a certain component is less than the predetermined time N to the terminal device 6a of the user of the molding machine 1 equipped with the component and the terminal device 6b of the salesperson (step S30).

[0116] The user's terminal device 6a receives the notification data sent from the information processing device 5 (step S31). The terminal device 6a that has received the notification data displays that the remaining life of the specific component is less than the specified time N. The user can take actions required to replace the notified component. For example, the user can access a website provided by the information processing device 5, browse information related to the component, and request estimated data on the cost required to replace the component.

[0117] The terminal device 6b of the salesperson receives the notification data sent from the information processing device 5 (step S32). The terminal device 6b that has received the notification data displays that the remaining life of the specific component is less than the specified time N. The salesperson can take actions required to maintain the notified component. For example, the salesperson can access the website provided by the information processing device 5, browse the information related to the component, and explain to the user about the replacement of the component.

[0118] On the other hand, the user's terminal device 6a requests the information processing device 5 for the estimated result related to the remaining life of the component according to the user's operation (step S33). In response to the request from the terminal device 6a, the information processing device 5 sends the estimated result of the remaining life of the component to the terminal device 6a (step S34). The terminal device 6a receives the estimated result sent from the information processing device 5 and displays the received estimated result. The user can view the estimated result of the remaining life or abnormality of the component.

[0119] Similarly, the terminal device 6b of the salesperson requests the information processing device 5 for the estimated result related to the remaining life of the component according to the operation of the salesperson (step S35). In response to the request from the terminal device 6b, the information processing device 5 sends the estimated result of the remaining life of the component to the terminal device 6b (step S34). The terminal device 6b receives the estimated result sent from the information processing device 5 and displays the received estimated result. The salesperson can view the estimated result of the remaining life or abnormality of the component.

[0120] The processing unit 51 of the information processing device 5 determines whether a prescribed number of days have passed since the registration for the maintenance management service (step S36). After a prescribed number of days have passed since the registration date for the maintenance management service, the user can receive the service of securing spare parts for the components in advance. If the prescribed number of days has not passed since the registration date, for example, the user cannot receive the service of securing spare parts for the components.

[0121] When it is determined that the predetermined number of days has passed (step S36 : Yes), the processing unit 51 refers to the report DB 52 d and determines whether maintenance has been performed regularly (step S37 ).

[0122] When it is determined that the molding machine 1 is regularly maintained (step S37 : Yes), the processing unit 51 refers to the collection DB to determine whether or not there is abnormal operation or the like (step S38 ).

[0123] If it is determined that there is no abnormal operation (step S38: Yes), the processing unit 51 sends spare parts securing notification data to the terminal device 6c of the factory, requesting to secure spare parts for components whose remaining life is less than the prescribed time N (step S39). The process of sending spare parts securing notification data to the terminal device 6c of the factory is one of the processes related to securing spare parts for components that need to be replaced.

[0124] In steps S36 to S38, when it is determined that the prescribed number of days has not passed (step S36: No), when it is determined that the molding machine 1 has not been regularly maintained (step S37: No), or when it is determined that an abnormal operation has occurred (step S38: No), the processing unit 51 will not perform processing related to ensuring spare parts for the components.

[0125] In addition, steps S36 to S38 are examples of conditions for accepting the service of the spare parts of the pre-secured components, and the presence or absence of the service provision conditions may be determined by executing part of these processes.

[0126] The terminal device 6c of the factory receives the spare parts securing notification data (step S40). The terminal device 6c that has received the spare parts securing notification data executes a process for securing spare parts (step S41). When there is a stock of parts, the terminal device 6c secures the parts in the stock as spare parts for replacing the parts of the notified molding machine 1. When there is a stock database of parts, the terminal device 6c defines the parts in the stock as spare parts by changing the records of the stock database. When there is no stock of parts, a process for requesting the manufacture of parts is executed.

[0127] Furthermore, the example in which the spare parts securing notification data is sent to the terminal device 6c of the factory has been described, but the processing unit 51 may be configured to send the spare parts securing notification data to the terminal device 6b of the salesperson. The salesperson requests the factory to secure spare parts of a component.

[0128] Fig.13 This is a graph showing the cost-effectiveness of the maintenance management according to the first embodiment. Fig.13 The horizontal axis of the graph shows the number of years that have passed since the molding machine 1 was put into use, and the vertical axis shows the total amount of the maintenance cost and the loss caused by the stoppage of production of the molding machine 1. Hereinafter, this total amount is referred to as maintenance cost, etc.

[0129] Fig.13 Graph A in FIG. 1 shows the maintenance cost when no overhaul or other maintenance is performed. Graph B shows the maintenance cost when overhaul is performed regularly. Graph C shows the maintenance cost when the maintenance of the first embodiment is performed.

[0130] Without overhaul, damage to the components constituting the molding machine 1 is inevitable. Fig.13 In the example of, although there is no regular maintenance cost, the biggest loss still occurs due to the damage of the parts. The parts such as the reducer 14 of the extruder which require time to manufacture, during the manufacturing period, the molding machine 1 stops working, resulting in a significant loss.

[0131] When the overhaul is performed regularly, there is no serious loss caused by the molding machine 1 stopping operation, but the cost of regular overhaul is high, and the maintenance cost in this case is higher than the maintenance cost of this embodiment. It can be said that the maintenance cost is high due to excessive maintenance management.

[0132] According to the maintenance management method of the first embodiment, although maintenance costs continue to be incurred monthly, the replacement time of components can be predicted and spare parts can be prepared, so that maintenance by overhaul is not required and the risk of shutdown of the molding machine 1 can be avoided.

[0133] In summary, according to the information processing method and the like of the first embodiment, before a component constituting the molding machine 1 is damaged and cannot work, the remaining life or abnormality of the component can be estimated, and spare parts of the component can be prepared in advance. Thus, compared with the maintenance management of periodic overhaul, the maintenance cost of the molding machine 1 can be controlled. In other words, the condition of the molding machine 1 can be efficiently and well maintained while avoiding the loss caused by the stoppage of the molding machine 1 and the cost caused by producing spare parts of the component at an inappropriate time.

[0134] Furthermore, by transmitting specification information to sales personnel and the terminal devices 6 b and 6 c of the factory, it is possible to quickly start manufacturing components constituting the customized product of the molding machine 1 of the user.

[0135] Furthermore, by urging the user to perform maintenance on the molding machine 1 and managing the maintenance status, the molding machine 1 can be kept in a better state and the risk of stopping operation can be reduced.

[0136] Furthermore, by configuring so that spare parts of components are secured when maintenance is appropriately performed, maintenance of the molding machine 1 can be more effectively promoted.

[0137] (Implementation Method 2)

[0138] The information processing device 5 of the second embodiment is different from the first embodiment in that it also calculates the remaining life or abnormality of the component using the image data included in the report data. The other configurations 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 used for the same parts and detailed description is omitted.

[0139] Fig.14 1 is a block diagram showing an estimation processing unit M according to Embodiment 2. The estimation processing unit M is the same as that of Embodiment 1, and includes a prediction learning model 54 , a frequency analysis unit 55 , and an image generation unit 56 .

[0140] The prediction learning model 54 is a convolutional neural network, and includes an input layer 54a, an intermediate layer 54b, and an output layer 54c. The input layer 54a is input with image data of a Fourier transform image and image data included in report data related to a component as a remaining life prediction target, and the output layer 54c outputs remaining life data or abnormality data indicating the remaining life or abnormality of the component. Hereinafter, the image data included in the report data is referred to as report image data.

[0141] The input layer 54a has a plurality of nodes to which the pixel values ​​of each pixel constituting the Fourier transform image and the pixel values ​​of each pixel constituting the report image data are input. The intermediate layer 54b has a structure in which a convolution layer for convolving the pixel values ​​of each pixel of the Fourier transform image and the report image data input to the input layer 54a and a pooling layer for mapping the pixel values ​​convolved in the convolution layer are alternately connected. The intermediate layer 54b extracts the feature value of the Fourier transform image while compressing the image information of the Fourier transform image and the report image data, and outputs it to the output layer 54c.

[0142] 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 time point of physical quantity data measurement.

[0143] In the process of step S28, the processing unit 51 of the information processing device 5 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 DB52a and the image data contained in the report data stored in the report DB52d. Specifically, the processing unit 51 performs frequency analysis on the physical quantity data and converts it into image data. In addition, the processing unit 51 reads the report data related to the component as the prediction object of the remaining life from the report DB52d, and extracts the image data contained in the read report data. The processing unit 51 inputs the image data representing the physical quantity data and the image data extracted from the report data into the prediction learning model 54, so that it outputs the remaining life data or abnormality data of the component.

[0144] In summary, according to the information processing method and the like of the second embodiment, the remaining life and abnormality of the components constituting the molding machine 1 can be estimated with higher accuracy, and spare parts of the components can be prepared at a more appropriate timing.

[0145] (Implementation 3)

[0146] The information processing device 5 of the third embodiment is different from the first or second embodiment in that it is capable of managing the supply status of substitutes to the user when there is not enough time to secure the components constituting the molding machine 1. The other configurations of the information processing device 5 are the same as those of the information processing device 5 of the first or second embodiment, so the same reference numerals are used for the same parts and detailed description is omitted.

[0147] Fig.15This is a conceptual diagram showing an example of the record layout of the user device DB 52c of the third embodiment. The user device DB 52c of the third embodiment has a "substitute supply status" column in addition to the "user ID" column, the "device ID" column, the "component ID" column, the "component specification information" column, and the "remaining life or abnormality" column. The "substitute supply status" column stores information indicating the supply status of substitutes provided to the user when the components constituting the molding machine 1 are not secured in time. For example, the "substitute supply status" column stores information on the specifications of the substitute, the substitute supply date, the usable period of the substitute (the durability of the substitute), and other information.

[0148] The salesperson who provides the substitute product inputs information identifying the molding machine 1 and the component and information on the supply status of the substitute product to the terminal device 6b. The information identifying the molding machine 1 and the component is, for example, a device identifier and a component identifier indicating the specific molding machine 1 and the component.

[0149] The terminal device 6b transmits the device identifier, the component identifier, and information indicating the status of supply of substitute products to the information processing device 5. The information processing device 5 receives the component identifier and the information indicating the status of supply of substitute products and stores them in the user device DB 52c.

[0150] When a request is made for information on the status of provision of substitute products from the terminal device 6 b operated by the salesperson, the information processing device 5 reads the information on the status of provision of substitute products from the user device DB 52 c and transmits the information to the terminal device 6 b of the salesperson.

[0151] Furthermore, the information processing device 5 may be configured to notify the terminal device 6b of the business operator that the usable period of the substitute product is approaching when the usable period of the substitute product is approaching.

[0152] In summary, according to the information processing method and the like of the second embodiment, it is possible to manage the provision status of substitutes to the user when components constituting the molding machine 1 cannot be secured in time.

[0153] Means for solving the problems of the present disclosure are supplemented.

[0154] (Note 1)

[0155] An information processing method, wherein:

[0156] storing registered information indicating whether or not a maintenance management service is used in association with an identifier of a user of the molding machine in a storage unit, wherein the maintenance management service is a service for securing spare parts of a component constituting the molding machine before the component is damaged;

[0157] Acquiring physical quantity data associated with the state of the component constituting the molding machine; estimating the remaining life or abnormality of the component based on the acquired physical quantity data;

[0158] determining whether it is necessary to secure a spare part for the component at least before a predetermined period required for securing a spare part for the component based on the estimated remaining life or abnormality of the component;

[0159] When it is determined that a spare part of the component needs to be secured, a process related to securing a spare part of the component that needs to be replaced is executed based on the utilization registration information stored in the storage unit.

[0160] (Note 2)

[0161] The information processing method according to Supplement 1, wherein:

[0162] Reading specification information of the component to be replaced from a database, wherein the database stores specification information of a plurality of users and each of the components constituting a plurality of different molding machines used by the plurality of users in a corresponding manner;

[0163] Based on the read specification information, a process related to securing spare parts of the component that needs to be replaced is performed.

[0164] (Note 3)

[0165] The information processing method according to Supplement 1 or Supplement 2, wherein:

[0166] Notify users of maintenance implementation;

[0167] Acquiring report data indicating maintenance results of the molding machine from a user;

[0168] The acquired report data is stored in the storage unit.

[0169] (Note 4)

[0170] The information processing method according to Supplement 3, wherein:

[0171] When the storage unit stores the report data, a process related to securing spare parts of the component that needs to be replaced is executed.

[0172] (Note 5)

[0173] The information processing method according to Supplement 3 or Supplement 4, wherein:

[0174] The report data includes image data obtained by photographing the molding machine or the component;

[0175] The remaining life or abnormality of the component is estimated based on the physical quantity data and the image data included in the report data.

[0176] (Note 6)

[0177] The information processing method according to any one of Supplement 1 to Supplement 5, wherein:

[0178] Information indicating that a substitute for the component has been provided to the user is stored in the storage unit.

[0179] (Note 7)

[0180] An information processing device comprising:

[0181] an acquisition unit that acquires physical quantity data associated with states of components constituting the molding machine;

[0182] A storage unit for storing registered information indicating whether or not a maintenance management service is used in association with an identifier of a user of the molding machine, wherein the maintenance management service is a service for securing spare parts of a component constituting the molding machine before the component is damaged; and

[0183] Processing Department,

[0184] The processing unit estimates the remaining life or abnormality of the component based on the acquired physical quantity data,

[0185] The processing unit determines whether it is necessary to secure a spare part of the component based on the estimated remaining life or abnormality of the component at least before a predetermined period required for securing a spare part of the component.

[0186] When determining that it is necessary to secure a spare part of the component, the processing unit executes processing related to securing a spare part of the component that needs to be replaced based on the utilization registration information stored in the storage unit.

[0187] (Note 8)

[0188] A computer program for causing a computer to execute the following processing:

[0189] storing registered information indicating whether or not a maintenance management service is used in association with an identifier of a user of the molding machine in a storage unit, wherein the maintenance management service is a service for securing spare parts of a component constituting the molding machine before the component is damaged;

[0190] acquiring physical quantity data associated with the states of the components constituting the molding machine;

[0191] estimating the remaining life or abnormality of the component based on the acquired physical quantity data;

[0192] determining whether it is necessary to secure a spare part for the component at least before a predetermined period required for securing a spare part for the component based on the estimated remaining life or abnormality of the component;

[0193] When it is determined that a spare part of the component needs to be secured, a process related to securing a spare part of the component that needs to be replaced is executed based on the utilization registration information stored in the storage unit.

[0194] Description of Reference Numerals

[0195] 1: Molding machine

[0196] 2: Sensor

[0197] 3: Data collection device

[0198] 4: Router

[0199] 5: Information processing device

[0200] 6a: User's terminal device

[0201] 6b: Terminal device for sales staff

[0202] 6c: Factory terminal device

[0203] 10: Cylinder

[0204] 10a: Hopper

[0205] 11: Screw

[0206] 12: Mould

[0207] 13: Motor

[0208] 14: Reducer

[0209] 15: Control device

[0210] 21: First sensor

[0211] 22: Second sensor

[0212] 23: Third sensor

[0213] 24: Fourth sensor

[0214] 31: Control Department

[0215] 32: Storage

[0216] 33: Ministry of Communications

[0217] 34: Data input section

[0218] 50: Recording medium

[0219] 51: Processing Department

[0220] 52: Storage

[0221] 53: Ministry of Communications

[0222] 54: Predictive Learning Model

[0223] 74a: Input layer

[0224] 74b: Middle layer

[0225] 74c: Output layer

[0226] 55: Frequency Analysis Department

[0227] 56: Image generation unit

[0228] 52a: Collect data DB

[0229] 52b: User DB

[0230] 52c: User device DB

[0231] 52d: Report DB

[0232] P: Computer program.

Claims

1. An information processing method, characterized in that: storing in a storage unit usage registration information indicating whether or not a maintenance management service is used in association with an identifier of a user of the molding machine, wherein the maintenance management service is a service for securing spare parts of a component constituting the molding machine before the component is damaged; acquiring physical quantity data associated with the states of the components constituting the molding machine; estimating the remaining life or abnormality of the component based on the acquired physical quantity data; determining whether it is necessary to secure a spare part for the component at least before a predetermined period required for securing a spare part for the component based on the estimated remaining life or abnormality of the component; When it is determined that a spare part of the component needs to be secured, a process related to securing a spare part of the component that needs to be replaced is executed based on the utilization registration information stored in the storage unit.

2. The information processing method according to claim 1, characterized in that: Reading specification information of the component to be replaced from a database, wherein the database stores specification information of a plurality of users and the components constituting the plurality of different molding machines used by the plurality of users in a corresponding manner; Based on the read specification information, a process related to securing spare parts of the component that needs to be replaced is performed.

3. The information processing method according to claim 1 or claim 2, characterized in that: Notify users of maintenance implementation; Acquiring report data indicating the maintenance implementation result of the molding machine from a user; The acquired report data is stored in the storage unit.

4. The information processing method according to claim 3, characterized in that: When the storage unit stores the report data, a process related to securing spare parts of the component that needs to be replaced is executed.

5. The information processing method according to claim 3 or claim 4, characterized in that: The report data includes image data obtained by photographing the molding machine or the component; The remaining life or abnormality of the component is estimated based on the physical quantity data and the image data included in the report data.

6. The information processing method according to any one of claims 1 to 5, characterized in that: Information indicating that a substitute for the component has been provided to the user is stored in the storage unit.

7. An information processing device, characterized in that: have: an acquisition unit that acquires physical quantity data associated with states of components constituting the molding machine; A storage unit for storing registered information indicating whether or not a maintenance management service is used in association with an identifier of a user of the molding machine, wherein the maintenance management service is a service for securing spare parts of the component before the component constituting the molding machine is damaged; and Processing Department, The processing unit estimates the remaining life or abnormality of the component based on the acquired physical quantity data, The processing unit determines whether it is necessary to secure a spare part of the component based on the estimated remaining life or abnormality of the component at least before a predetermined period required for securing a spare part of the component. When determining that it is necessary to secure a spare part of the component, the processing unit executes processing related to securing a spare part of the component that needs to be replaced based on the utilization registration information stored in the storage unit.

8. A computer program, characterized in that Used to enable the computer to perform the following processing: storing in a storage unit usage registration information indicating whether or not a maintenance management service is used in association with an identifier of a user of the molding machine, wherein the maintenance management service is a service for securing spare parts of a component constituting the molding machine before the component is damaged; acquiring physical quantity data associated with the states of the components constituting the molding machine; estimating the remaining life or abnormality of the component based on the acquired physical quantity data; determining whether it is necessary to secure a spare part for the component at least before a predetermined period required for securing a spare part for the component based on the estimated remaining life or abnormality of the component; When it is determined that a spare part of the component needs to be secured, a process related to securing a spare part of the component that needs to be replaced is executed based on the utilization registration information stored in the storage unit.

Images