Management method and device for manufacturing dry electrode of intelligent manufacturing digital twin system

Abstract

The invention relates to a management method and device for manufacturing a dry electrode of an intelligent manufacturing digital twin system. The method comprises the steps of collecting manufacturing data generated in the manufacturing process under the condition that the dry electrode is manufactured through a physical manufacturing device; wherein the manufacturing data comprises manufacturing state data of the physical manufacturing device and manufacturing product data of the dry electrode; constructing a production line model corresponding to the dry-type electrode according to the manufacturing data through a digital twin model device; wherein the production line model comprises a simulation object of the physical manufacturing device; and analyzing the manufacturing data and simulation data generated by the production line model through the information physical cloud integration device to obtain a manufacturing result of the dry-type electrode. By adopting the method, the manufacturing process of the dry electrode can be detected in real time, the corresponding production line model is constructed to simulate a manufacturing scene, and reasonable and effective data analysis is performed, so that problems in production can be found in time, production interruption is reduced, and the production efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent manufacturing technology, and in particular to a management method and device for dry electrode manufacturing in an intelligent manufacturing digital twin system. Background Art

[0002] As the manufacturing industry transforms towards intelligence and informatization, intelligent and refined control of the manufacturing process of dry electrodes is of great significance for improving product quality and reducing costs. Dry electrode preparation not only improves battery performance and reduces costs, but also simplifies the process. In addition, the use of new materials also helps achieve environmental protection and sustainable development.

[0003] However, the existing dry electrode manufacturing process lacks efficient data integration, analysis and management mechanisms, making it difficult to achieve real-time monitoring and optimization of the manufacturing process. Summary of the invention

[0004] Based on this, it is necessary to provide a management method and device for dry electrode manufacturing of an intelligent manufacturing digital twin system that can intelligently and efficiently manage the manufacturing process of dry electrodes in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a management method for dry electrode manufacturing of an intelligent manufacturing digital twin system, comprising:

[0006] In the case of manufacturing the dry electrode by a physical manufacturing device, collecting manufacturing data generated during the manufacturing process; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode;

[0007] By using the digital twin model device, a production line model corresponding to the dry electrode is constructed according to the manufacturing data; wherein the production line model includes a simulation object of the physical manufacturing device;

[0008] Through the information-physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode.

[0009] In one embodiment, the method further comprises:

[0010] Through visual management and display devices, the manufacturing results are converted into media data and the media data is displayed.

[0011] In one embodiment, the physical manufacturing device includes a raw material processing device, a molding device and a heat treatment device; manufacturing a dry electrode by the physical manufacturing device includes:

[0012] Pre-processing the dry electrode raw material by a raw material processing device; wherein the pre-processing includes at least one of screening, washing, drying, crushing and mixing;

[0013] The pre-treated dry electrode raw material is converted into an initial dry electrode according to preset specifications and shapes by a forming device;

[0014] The initial dry electrode is heated by a heat treatment device to obtain a target dry electrode.

[0015] In one embodiment, collecting manufacturing data generated during the manufacturing process includes:

[0016] The manufacturing status data of the physical manufacturing device is collected through a sensor network unit; wherein the sensor network unit includes at least one of a temperature sensor, a pressure sensor, a humidity sensor and an electrolyte concentration sensor;

[0017] The manufacturing product data of the dry electrode is collected through an image recognition and monitoring unit; wherein the image recognition and monitoring unit includes at least one camera, and the manufacturing product data includes at least one of size and shape.

[0018] In one embodiment, a production line model corresponding to a dry electrode is constructed based on manufacturing data through a digital twin model device, including:

[0019] Through the digital twin model device, the initial production line model is configured according to the manufacturing data to obtain the production line model corresponding to the dry electrode; wherein the production line model is used to simulate the manufacturing process of the dry electrode based on the simulation object of the physical manufacturing device to obtain the corresponding simulation data.

[0020] In one embodiment, the manufacturing data and the simulation data generated by the production line model are analyzed by the cyber-physical cloud integration device to obtain the manufacturing results of the dry electrode, including:

[0021] Through the cyber-physical cloud integration device, the simulation data generated by the manufacturing data and the production line model are uploaded to the cloud corresponding to the intelligent manufacturing digital twin system;

[0022] The manufacturing results of the dry electrode are obtained by receiving the cloud based on the manufacturing data and simulation data analysis.

[0023] In the second aspect, the present application also provides a management device for dry electrode manufacturing of an intelligent manufacturing digital twin system, including:

[0024] A data acquisition module, used for collecting manufacturing data generated during the manufacturing process when the dry electrode is manufactured by a physical manufacturing device; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode;

[0025] A model building module is used to build a production line model corresponding to the dry electrode according to the manufacturing data through a digital twin model device; wherein the production line model includes a simulation object of a physical manufacturing device;

[0026] The data analysis module is used to analyze the manufacturing data and the simulation data generated by the production line model through the information-physical cloud integration device to obtain the manufacturing results of the dry electrode.

[0027] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0028] In the case of manufacturing the dry electrode by a physical manufacturing device, collecting manufacturing data generated during the manufacturing process; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode;

[0029] By using the digital twin model device, a production line model corresponding to the dry electrode is constructed according to the manufacturing data; wherein the production line model includes a simulation object of the physical manufacturing device;

[0030] Through the information-physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode.

[0031] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0032] In the case of manufacturing the dry electrode by a physical manufacturing device, collecting manufacturing data generated during the manufacturing process; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode;

[0033] By using the digital twin model device, a production line model corresponding to the dry electrode is constructed according to the manufacturing data; wherein the production line model includes a simulation object of the physical manufacturing device;

[0034] Through the information-physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode.

[0035] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0036] In the case of manufacturing the dry electrode by a physical manufacturing device, collecting manufacturing data generated during the manufacturing process; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode;

[0037] By using the digital twin model device, a production line model corresponding to the dry electrode is constructed according to the manufacturing data; wherein the production line model includes a simulation object of the physical manufacturing device;

[0038] Through the information-physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode.

[0039] The management method and device for dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system, when manufacturing dry electrodes through physical manufacturing devices, collects manufacturing data generated during the manufacturing process; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode; through the digital twin model device, according to the manufacturing data, a production line model corresponding to the dry electrode is constructed; wherein the production line model includes a simulation object of the physical manufacturing device; through the information-physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode. The present application provides an intelligent manufacturing digital twin system, which performs real-time detection of the manufacturing process of dry electrodes, constructs a corresponding production line model to simulate the manufacturing scenario, and conducts reasonable and effective data analysis, which is conducive to timely discovery of problems in production, reducing production interruptions, and thus improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0041] FIG1 is an application environment diagram of a management method for dry electrode manufacturing of an intelligent manufacturing digital twin system in one embodiment;

[0042] FIG2 is a schematic flow chart of a method for managing dry electrode manufacturing in an intelligent manufacturing digital twin system in one embodiment;

[0043] FIG3 is a schematic diagram of a process for manufacturing a dry electrode in one embodiment;

[0044] FIG4 is a schematic diagram of a process for collecting manufacturing data in one embodiment;

[0045] FIG5 is a schematic diagram of a process for analyzing manufacturing data and simulation data in one embodiment;

[0046] FIG6 is a flow chart of a management method for dry electrode manufacturing in an intelligent manufacturing digital twin system in another embodiment;

[0047] FIG7 is a structural block diagram of a management device for dry electrode manufacturing in an intelligent manufacturing digital twin system in one embodiment;

[0048] FIG8 is a structural block diagram of a management device for dry electrode manufacturing in an intelligent manufacturing digital twin system in another embodiment;

[0049] FIG. 9 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] The management method and device for dry electrode manufacturing of the intelligent manufacturing digital twin system provided in the embodiment of the present application can be applied to the application environment shown in Figure 1. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. When the server 104 manufactures the dry electrode through a physical manufacturing device, the manufacturing data generated during the manufacturing process is collected; wherein the manufacturing data includes the manufacturing status data of the physical manufacturing device and the manufacturing product data of the dry electrode; through the digital twin model device, according to the manufacturing data, a production line model corresponding to the dry electrode is constructed; wherein the production line model includes the simulation object of the physical manufacturing device; through the information-physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode.

[0052] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, portable wearable devices, etc. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0053] In an exemplary embodiment, as shown in FIG2 , a management method for dry electrode manufacturing of an intelligent manufacturing digital twin system is provided. The intelligent manufacturing digital twin system can be run on the server in FIG1 . Specifically, the method includes:

[0054] S201, when a dry electrode is manufactured by a physical manufacturing device, manufacturing data generated during the manufacturing process is collected.

[0055] Among them, the physical manufacturing device is the physical device corresponding to the intelligent manufacturing data twin system. In the actual production scenario, it can be represented as a complete manufacturing device corresponding to at least one production line, including but not limited to cleaning machines, dryers, crushers, tablet presses, high-temperature heating furnaces, etc. These devices can be coordinated through an automated control system to ensure the automation and intelligence of the manufacturing process.

[0056] Exemplarily, the intelligent manufacturing data twin system running on the server sends production instructions to the physical manufacturing device to instruct the physical manufacturing device to manufacture dry electrodes.

[0057] Accordingly, the manufacturing data generated during the manufacturing process are collected by collecting devices pre-installed at key positions of the physical manufacturing device, wherein the manufacturing data includes the manufacturing status data of the physical manufacturing device and the manufacturing product data of the dry electrode.

[0058] The manufacturing status data of the physical manufacturing device is used to characterize the various manufacturing states in the manufacturing process of the dry electrode, such as the operating status and production process of the physical manufacturing device, the material flow and key parameters at each stage of the production process, among which the key parameters include but are not limited to temperature, pressure and humidity.

[0059] The manufacturing product data of dry electrodes is used to characterize the manufacturing precision of the raw materials and finished products of dry electrodes, such as the size, shape and density of the raw materials and finished products of dry electrodes.

[0060] S202, constructing a production line model corresponding to the dry electrode according to manufacturing data through a digital twin model device.

[0061] The digital twin model device can be configured on a terminal or server, including a twin model library module, an algorithm library module, a virtual scene construction module, a simulation verification and virtual debugging module, and a virtual-reality interaction module.

[0062] Among them, the twin model library module is used to store key information of various equipment and process flows in the production process of dry electrodes, namely manufacturing data. The twin model library module adopts a data-driven modeling method and uses artificial intelligence technology for modeling, so as to build a production line model corresponding to the dry electrode, and perform information processing based on the production line model to provide data support for subsequent simulation verification and virtual debugging.

[0063] Optionally, the artificial intelligence technologies used by the twin model library module include but are not limited to linear regression models, decision trees, random forest models, recurrent neural networks, and convolutional neural networks.

[0064] The production line model includes a simulation object of a physical manufacturing device, and the simulation object is used to simulate the operation of the physical manufacturing device.

[0065] The algorithm library module is used to classify and organize the functional algorithm models of the artificial intelligence technology used by the above-mentioned twin model library module, and use algorithm scripts to automate specific tasks or processes to improve the degree of automation of the production line.

[0066] The virtual scene construction module is used to quickly build a virtual scene corresponding to the production line model, simulate the actual production operation status, and provide a more similar environment for simulation verification and virtual debugging.

[0067] The simulation verification and virtual debugging module is used to complete the simulation verification and virtual debugging of the production line in a virtual scene. By simulating the operation process of the actual production line, it predicts possible production problems and debugs and optimizes the predicted production problems in advance to ensure the stability and efficiency of actual production.

[0068] The virtual-reality interaction module is used to realize the connection between the virtual production line and the actual production line on the basis of completing virtual debugging, and can realize the collection and interaction of twin data through interface components.

[0069] S203, analyzing the manufacturing data and the simulation data generated by the production line model through the information-physical cloud integration device to obtain the manufacturing results of the dry electrode.

[0070] Specifically, it is detected whether there is abnormal data in the manufacturing data and the simulation data, and then the manufacturing result of the dry electrode is formed according to the detection result.

[0071] Exemplarily, the manufacturing data and simulation data are compared with preset standard production data. If the comparison result shows that the difference between any data and the standard production data exceeds a preset threshold, the data is determined to be abnormal and recorded in the manufacturing results of the dry electrode.

[0072] The preset threshold value may be set based on extensive experiments or product standards for dry electrode manufacturing.

[0073] In the management method of dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system, when the dry electrode is manufactured by a physical manufacturing device, the manufacturing data generated in the manufacturing process is collected; wherein the manufacturing data includes the manufacturing status data of the physical manufacturing device and the manufacturing product data of the dry electrode; through the digital twin model device, according to the manufacturing data, a production line model corresponding to the dry electrode is constructed; wherein the production line model includes the simulation object of the physical manufacturing device; through the information physical cloud integration device, the manufacturing data and the simulation data generated by the production line model are analyzed to obtain the manufacturing results of the dry electrode. This embodiment provides an intelligent manufacturing digital twin system, which performs real-time detection of the manufacturing process of the dry electrode, constructs a corresponding production line model to simulate the manufacturing scenario, and performs reasonable and effective data analysis, which is conducive to timely discovery of problems in production, reducing production interruptions, and thus improving production efficiency.

[0074] In an exemplary embodiment, the management method for dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system further includes:

[0075] Through visual management and display devices, the manufacturing results are converted into media data and the media data is displayed.

[0076] Among them, the intelligent manufacturing digital twin system also includes a visual management and display device, which is used to generate corresponding media data based on the manufacturing results; the media data includes but is not limited to graphics, icons, animations and other forms. The media data can intuitively display the manufacturing process and manufacturing results of the dry electrode, which is conducive to clearly showing the operating status of the production line, production efficiency and product quality to users.

[0077] Exemplarily, in response to the media data acquisition instruction, the media data is directly displayed on a device associated with the visual management and display apparatus.

[0078] Optionally, in response to a media data acquisition instruction initiated by a terminal held by a user, the generated media data is transmitted to the terminal and displayed on the terminal. The terminal held by the user includes but is not limited to a computer, a tablet or a mobile phone.

[0079] Optionally, the visual management and display device includes a data visualization unit, a user interface and interaction unit, and a decision support and reporting unit. The data visualization unit visualizes the analyzed and processed data in the form of graphics, charts, animations, etc., so that users can intuitively understand the data and results. The user interface and interaction unit provides an interactive interface between the user and the system, including a graphical interface, command input, operation control, etc. The decision support and reporting unit provides decision support and report generation functions based on the results of the visualization display and the results of the data analysis.

[0080] In this embodiment, an interface for managing the manufacturing process of the dry electrode is provided in a visual manner, and can be intuitively displayed in a digitized form, which is conducive to reducing the difficulty of managing the manufacturing process.

[0081] In an exemplary embodiment, the physical manufacturing device includes a raw material processing device, a molding device and a heat treatment device; as shown in FIG3 , the above-mentioned manufacturing of the dry electrode by the physical manufacturing device includes:

[0082] S301, pre-processing the dry electrode raw material through the raw material processing device.

[0083] The pretreatment includes at least one of screening, washing, drying, crushing and mixing.

[0084] Specifically, the raw material processing device includes a screening machine, a cleaning machine, a drying box, a crusher, a mixer and other equipment. The screening machine is used to strictly screen the dry electrode raw materials and remove impurities therein; the cleaning machine is used to clean the pollutants on the surface of the dry electrode raw materials; the drying box is used to remove excess moisture from the dry electrode raw materials; the crusher is used to crush the dry electrode raw materials to a suitable particle size; and the mixer is used to evenly mix the dry electrode raw materials. Each device is executed in a certain order to jointly complete the pretreatment steps of the dry electrode raw materials.

[0085] S302, converting the pretreated dry electrode raw material into an initial dry electrode according to preset specifications and shapes through a forming device.

[0086] The forming device may be a tablet press or an extruder to press or extrude the pretreated dry electrode raw material into a preset specification and shape to obtain an initial dry electrode.

[0087] Preset specifications and shapes can be made based on production standards for dry electrodes.

[0088] S303, performing heat treatment on the initial dry electrode by a heat treatment device to obtain a target dry electrode.

[0089] The heat treatment device may use a high temperature heating furnace to precisely control parameters such as heating temperature, event and atmosphere. The initial dry electrode is subjected to a heating treatment, i.e., a high temperature treatment, so that the chemical substances in the electrode undergo a chemical reaction, thereby improving the performance and stability of the electrode.

[0090] In this embodiment, dry electrodes are manufactured by physical manufacturing devices, which can improve the reliability of the manufacturing process and facilitate the collection of various manufacturing data during the manufacturing process. In this way, when difference data is detected, it can be quickly matched with the nodes involved in the physical manufacturing device. Compared with the existing technology, this embodiment can improve the intelligent manufacturing process.

[0091] In an exemplary embodiment, as shown in FIG4 , the above S201 includes:

[0092] S401, collecting manufacturing status data of a physical manufacturing device through a sensor network unit.

[0093] The sensor network unit includes at least one of a temperature sensor, a pressure sensor, a humidity sensor and an electrolyte concentration sensor.

[0094] Exemplarily, the electrode temperature when the initial dry electrode is heated is collected by a temperature sensor; the pressure when the dry electrode raw material is pressed or squeezed is collected by a pressure sensor; the raw material humidity after the dry electrode raw material is dried is collected by a humidity sensor; and the electrolyte concentration when the initial dry electrode is heated is collected by an electrolyte concentration sensor.

[0095] S402, collecting manufacturing product data of dry electrodes through an image recognition and monitoring unit.

[0096] The image recognition and monitoring unit includes at least one camera, and the manufacturing product data includes at least one of size and shape.

[0097] The camera can be installed at a key position of the physical manufacturing device to photograph products at various stages of the dry electrode manufacturing process, such as photographing dry electrode raw materials before and after pretreatment, photographing initial dry electrodes and target dry electrodes, and obtaining corresponding manufacturing product data.

[0098] Optionally, the density of the dry electrode products at each stage is determined according to the size and shape in the manufacturing product data.

[0099] In this embodiment, by collecting different manufacturing data through different units, the manufacturing status data and manufacturing product data in the manufacturing data can be collected more accurately, which is conducive to the subsequent construction of a production line model based on the manufacturing data that is closer to the actual production line.

[0100] In an exemplary embodiment, the above S202 includes:

[0101] Through the digital twin model device, the initial production line model is configured according to the manufacturing data to obtain the production line model corresponding to the dry electrode; wherein the production line model is used to simulate the manufacturing process of the dry electrode based on the simulation object of the physical manufacturing device to obtain the corresponding simulation data.

[0102] Specifically, a virtual physical manufacturing device in the production line model, i.e., a simulation object of the physical manufacturing device, is constructed according to the actual physical manufacturing device. Then, an initial production line model is obtained according to the simulation object of the physical manufacturing device. The initial production line model can be a template of a production line model constructed before the dry electrode is manufactured by the actual physical manufacturing device.

[0103] Exemplarily, the actual manufacturing data collected during the manufacturing process of the dry electrode is imported into the initial production line model to configure the initial production line model accordingly, thereby obtaining a production line model corresponding to the dry electrode manufactured in this application.

[0104] Optionally, after constructing the production line model corresponding to the dry electrode, the production line model is controlled to run through the digital twin model device, so as to simulate the manufacturing process of the dry electrode and obtain the simulation data generated in the simulated manufacturing process. The simulation data includes configuration data and simulated manufacturing data.

[0105] In this embodiment, a production line model corresponding to the dry electrode is constructed through a digital twin model device, and then the production line model can be run to predict possible manufacturing problems in the manufacturing process. In this way, when corresponding manufacturing problems arise in the actual manufacturing process, they can be dealt with in a timely manner, which is conducive to improving the efficiency of manufacturing dry electrodes.

[0106] In an exemplary embodiment, as shown in FIG5 , the above S203 includes:

[0107] S501, upload the simulation data generated by the manufacturing data and the production line model to the cloud corresponding to the intelligent manufacturing digital twin system through the information-physical cloud integration device.

[0108] S502, receiving the manufacturing results of the dry electrode obtained by analyzing the manufacturing data and simulation data in the cloud.

[0109] When the information-physical cloud integration device has a certain data processing capability, the information-physical cloud integration device can process the manufacturing data and simulation data locally to obtain the manufacturing results of the dry electrode, and then upload the manufacturing results to the corresponding cloud.

[0110] In the case where the data processing capacity of the information-physical cloud integrated device is limited, the information-physical cloud integrated device supports multiple communication protocols and data formats, which can ensure compatibility with different devices and systems, upload manufacturing data and simulation data to the cloud, so that the cloud can analyze the manufacturing data and simulation data, and then feed back the manufacturing results obtained from the analysis to the information-physical cloud integrated device.

[0111] Optionally, the cyber-physical cloud integration device includes a data transmission and communication unit, a cloud computing platform unit, and a remote control and management unit. The data transmission and communication unit uploads manufacturing data and simulation data to the cloud, and communicates and interacts with other devices or systems; the cloud computing platform unit stores and processes a large amount of data, and provides functions such as data analysis, machine learning, and artificial intelligence; and the remote control and management unit enables remote monitoring, control, and management of devices or systems, including adjusting parameters and optimizing operations.

[0112] In this embodiment, by processing the manufacturing data and simulation data through cloud coordination, more accurate dry electrode manufacturing results can be obtained, thereby improving the efficiency of data analysis and processing.

[0113] In an exemplary embodiment, as shown in FIG6 , a management method for dry electrode manufacturing of an intelligent manufacturing digital twin system is provided, including:

[0114] S601, pre-processing the dry electrode raw material through the raw material processing device.

[0115] The pretreatment includes at least one of screening, washing, drying, crushing and mixing.

[0116] S602, converting the pretreated dry electrode raw material into an initial dry electrode according to preset specifications and shapes through a forming device.

[0117] S603, heating the initial dry electrode by a heat treatment device to obtain a target dry electrode.

[0118] S604, collecting manufacturing status data of the physical manufacturing device through the sensor network unit.

[0119] The sensor network unit includes at least one of a temperature sensor, a pressure sensor, a humidity sensor and an electrolyte concentration sensor.

[0120] S605, collecting manufacturing product data of the dry electrode through the image recognition and monitoring unit.

[0121] The image recognition and monitoring unit includes at least one camera, and the manufacturing product data includes at least one of size and shape.

[0122] S606, configuring the initial production line model according to the manufacturing data through the digital twin model device to obtain the production line model corresponding to the dry electrode.

[0123] The production line model is used to simulate the manufacturing process of the dry electrode based on the simulation object of the physical manufacturing device to obtain corresponding simulation data. The production line model includes the simulation object of the physical manufacturing device;

[0124] S607, upload the simulation data generated by the manufacturing data and the production line model to the cloud corresponding to the intelligent manufacturing digital twin system through the information-physical cloud integration device.

[0125] S608, receiving the manufacturing results of the dry electrode obtained by analyzing the manufacturing data and simulation data in the cloud.

[0126] S609, converting the manufacturing result into media data through a visual management and display device, and displaying the media data.

[0127] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0128] Based on the same inventive concept, the embodiment of the present application also provides a dry electrode manufacturing management device for implementing the dry electrode manufacturing management method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more dry electrode manufacturing management device embodiments provided below can refer to the limitations of the dry electrode manufacturing management method above, and will not be repeated here.

[0129] In an exemplary embodiment, as shown in FIG7 , a management device for dry electrode manufacturing of an intelligent manufacturing digital twin system is provided, comprising:

[0130] The data acquisition module 10 is used to collect manufacturing data generated during the manufacturing process when the dry electrode is manufactured by a physical manufacturing device; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode.

[0131] The model building module 20 is used to build a production line model corresponding to the dry electrode according to the manufacturing data through the digital twin model device; wherein the production line model includes a simulation object of the physical manufacturing device.

[0132] The data analysis module 30 is used to analyze the manufacturing data and the simulation data generated by the production line model through the information-physical cloud integration device to obtain the manufacturing results of the dry electrode.

[0133] In an exemplary embodiment, based on FIG. 7 , as shown in FIG. 8 , the management device for manufacturing dry electrodes further includes:

[0134] The data display module 40 converts the manufacturing results into media data and displays the media data through the visual management and display device.

[0135] In an exemplary embodiment, the physical manufacturing device includes a raw material processing device, a molding device and a heat treatment device; the management device for dry electrode manufacturing also includes:

[0136] The first manufacturing module is used to pre-treat the dry electrode raw material through a raw material processing device; wherein the pre-treatment includes at least one of screening, cleaning, drying, crushing and mixing.

[0137] The second manufacturing module is used to convert the pre-treated dry electrode raw material into an initial dry electrode according to preset specifications and shapes through a forming device.

[0138] The third manufacturing module is used to heat the initial dry electrode through a heat treatment device to obtain a target dry electrode.

[0139] In an exemplary embodiment, the data acquisition module 10 includes:

[0140] The first acquisition unit is used to collect manufacturing status data of the physical manufacturing device through a sensor network unit; wherein the sensor network unit includes at least one of a temperature sensor, a pressure sensor, a humidity sensor and an electrolyte concentration sensor.

[0141] The second acquisition unit is used to collect manufacturing product data of the dry electrode through the image recognition and monitoring unit; wherein the image recognition and monitoring unit includes at least one camera, and the manufacturing product data includes at least one of size and shape.

[0142] In an exemplary embodiment, the model building module 20 includes:

[0143] The model configuration unit is used to configure the initial production line model according to the manufacturing data through the digital twin model device to obtain the production line model corresponding to the dry electrode; wherein the production line model is used to simulate the manufacturing process of the dry electrode based on the simulation object of the physical manufacturing device to obtain the corresponding simulation data.

[0144] In an exemplary embodiment, the data analysis module 30 includes:

[0145] The data upload unit is used to upload the simulation data generated by the manufacturing data and the production line model to the cloud corresponding to the intelligent manufacturing digital twin system through the information-physical cloud integration device.

[0146] The result receiving unit is used to receive the manufacturing result of the dry electrode obtained by the cloud based on the analysis of manufacturing data and simulation data.

[0147] Each module in the management device for dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0148] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG9. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store manufacturing data, etc. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a management method for dry electrode manufacturing is implemented.

[0149] Those skilled in the art will understand that the structure shown in FIG. 9 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0150] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the management method for dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system are implemented.

[0151] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the management method for dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system are implemented.

[0152] In one embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps of the management method for dry electrode manufacturing of the above-mentioned intelligent manufacturing digital twin system.

[0153] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0154] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0155] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A management method for dry electrode manufacturing in an intelligent manufacturing digital twin system, characterized in that: The method comprises: In the case of manufacturing the dry electrode by a physical manufacturing device, collecting manufacturing data generated during the manufacturing process; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode; By means of a digital twin model device, a production line model corresponding to the dry electrode is constructed according to the manufacturing data; wherein the production line model includes a simulation object of the physical manufacturing device; The manufacturing data and the simulation data generated by the production line model are analyzed by an information-physical cloud integration device to obtain the manufacturing result of the dry electrode.

2. The method according to claim 1, characterized in that The method further comprises: The manufacturing result is converted into media data through a visual management and display device, and the media data is displayed.

3. The method according to claim 1, characterized in that The physical manufacturing device includes a raw material processing device, a molding device and a heat treatment device; the manufacturing of the dry electrode by the physical manufacturing device includes: The dry electrode raw material is pre-processed by the raw material processing device; wherein the pre-processing includes at least one of screening, washing, drying, crushing and mixing; The pre-treated dry electrode raw material is converted into an initial dry electrode according to preset specifications and shapes by the forming device; The initial dry electrode is subjected to a heat treatment by the heat treatment device to obtain a target dry electrode.

4. The method according to claim 1, characterized in that The manufacturing data generated during the manufacturing process is collected, including: The manufacturing status data of the physical manufacturing device is collected through a sensor network unit; wherein the sensor network unit includes at least one of a temperature sensor, a pressure sensor, a humidity sensor and an electrolyte concentration sensor; The manufacturing product data of the dry electrode is collected through an image recognition and monitoring unit; wherein the image recognition and monitoring unit includes at least one camera, and the manufacturing product data includes at least one of size and shape.

5. The method according to claim 1, characterized in that The method of constructing a production line model corresponding to the dry electrode according to the manufacturing data by using a digital twin model device includes: Through the digital twin model device, the initial production line model is configured according to the manufacturing data to obtain the production line model corresponding to the dry electrode; wherein the production line model is used to simulate the manufacturing process of the dry electrode based on the simulation object of the physical manufacturing device to obtain corresponding simulation data.

6. The method according to claim 1, characterized in that The manufacturing data and the simulation data generated by the production line model are analyzed by the information-physical cloud integration device to obtain the manufacturing result of the dry electrode, including: Uploading the manufacturing data and the simulation data generated by the production line model to the cloud corresponding to the intelligent manufacturing digital twin system through an information-physical cloud integration device; The cloud receives a manufacturing result of the dry electrode obtained by analyzing the manufacturing data and the simulation data.

7. A management device for dry electrode manufacturing in an intelligent manufacturing digital twin system, characterized in that: The device comprises: A data acquisition module, used for acquiring manufacturing data generated in the manufacturing process when the dry electrode is manufactured by a physical manufacturing device; wherein the manufacturing data includes manufacturing status data of the physical manufacturing device and manufacturing product data of the dry electrode; A model building module, used to build a production line model corresponding to the dry electrode according to the manufacturing data through a digital twin model device; wherein the production line model includes a simulation object of the physical manufacturing device; The data analysis module is used to analyze the manufacturing data and the simulation data generated by the production line model through an information-physical cloud integration device to obtain the manufacturing results of the dry electrode.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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