Digital twin billboard design system and method

Abstract

The invention discloses a digital twin billboard design system and method, and the system comprises a data collection and processing module which is used for carrying out the real-time preprocessing of the data of five parts: human-machine-method-material-ring; the data integration and analysis module is used for carrying out data integration and association analysis by utilizing an AI technology to obtain association relationships belonging to each part of data and between different parts of data; the visual content design module is used for providing a human-machine-method-material-ring five-part plate which allows a user to create and edit; and the billboard generation and interactive design module is used for correspondingly filling the obtained association relationship between each part of data and different part of data into the five parts of plates which finish creation and content editing, namely human-machine-method-material-ring, so as to generate a billboard. And providing an interaction component for a user to select and specify an interaction mode to adjust the layout of the plate and the data in the plate. According to the invention, the data visualization board of the digital twinborn model, which is intuitive and meets humanized requirements, can be provided.

Description

Technical Field

[0001] This application relates to the technical field of data visualization of digital twin models in manufacturing, and particularly to a digital twin dashboard design system and method. Background Art

[0002] The application of digital twin technology in manufacturing is becoming increasingly widespread. By digitally modeling and simulating a large amount of data generated during the actual production and operation processes, it can significantly improve production efficiency, reduce failure rates, and optimize resource allocation. This technology not only helps enterprises achieve refined management but also provides a scientific basis for enterprise decision-making. However, how to effectively manage and display this complex data has become an urgent problem to be solved.

[0003] Currently, to address this challenge, the industry generally adopts various means to process and display multi-dimensional data in the manufacturing process. For example, some enterprises use traditional SCADA (Supervisory Control and Data Acquisition) systems combined with charts and reports to display key indicators; others use BI (Business Intelligence) tools to present various types of data through preset dashboards and report templates. In addition, some enterprises have tried to introduce big data analysis platforms and use machine learning algorithms to deeply mine the data to discover potential trends and patterns.

[0004] Although the above methods have solved the problem of data display to a certain extent, there are still many deficiencies. Especially for comprehensive data involving multiple aspects such as man-machine-method-material-environment, existing solutions often fail to cover comprehensively and lack flexibility and interactivity. This results in users being unable to obtain an intuitive and personalized experience when viewing and analyzing data, thereby affecting the effectiveness and timeliness of data analysis. Summary of the Invention

[0005] In order to timely provide an intuitive and user-friendly data visualization dashboard for digital twin models in manufacturing, this application provides a digital twin dashboard design system and method.

[0006] In a first aspect, this application provides a digital twin dashboard design system, including: A data collection and processing module, configured to collect in real time the data of the five parts of man-machine-method-material-environment of the entity model corresponding to the digital twin model in manufacturing and perform data preprocessing; A data integration and analysis module, configured to use AI technology to perform data integration and correlation analysis on the preprocessed data, and obtain the data of each part of man-machine-method-material-environment and the correlation relationships between the data of different parts; A visual content design module for providing five parts of man - machine - method - material - environment that allow users to create and edit. Each part is set with a display layer for users to select and display the data information of the corresponding part. And each part is set with a variety of visualization components for users to select and specify the visualization form to display the data information. And data association components are set between each part for users to select and specify the association form to represent the data information of the association relationship and the strength of the association relationship between the corresponding parts. A dashboard generation and interaction design module for filling the data of each part of man - machine - method - material - environment and the association relationship between different parts of data into the five - part board of man - machine - method - material - environment that has been created and content - edited to generate a dashboard. And for the generated dashboard, it provides interaction components for users to adjust the layout of the parts and the data within the parts through the specified interaction methods selected.

[0007] By adopting the above - mentioned solution, through the comprehensive collection, processing and integrated analysis of the data of the five parts of man - machine - method - material - environment in the manufacturing digital twin model, accurately extract the data of each part and their mutual association relationships; design the five - part basic board of man - machine - method - material - environment, provide rich layer selection and a variety of visualization components, realize highly flexible visualization design, enabling users to freely customize the dashboard content and display form according to actual needs, thus significantly improving the efficiency and accuracy of data analysis and decision - making.

[0008] Preferably, the data integration and analysis module is also used for classifying and analyzing the data of each part of man - machine - method - material - environment for status or application scenarios, obtaining the data of each part of man - machine - method - material - environment under different statuses or application scenarios and the association relationships between the data of each part of man - machine - method - material - environment under different statuses or application scenarios; the status includes normal and abnormal conditions; the application scenarios include production line application scenarios, production quality inspection application scenarios, and warehousing application scenarios. The visual content design module is also used for providing a synchronous layer selection component for users to select the display layers of each part under the same status and application scenario conditions. Each part is set with multiple display layers and different display layers are used for users to select to display the data information of the corresponding part under a single status or a single application scenario. The dashboard generation and interaction design module is also used for filling the data of each part of man - machine - method - material - environment under different statuses or application scenarios and the association relationships between the data of each part of man - machine - method - material - environment under different statuses or application scenarios into the five - part board of man - machine - method - material - environment that has been created and content - edited to generate a dashboard under the specified status or application scenario.

[0009] By adopting the above solution, multi-dimensional state and application scenario classification analysis is carried out on the data of the five parts of man-machine-method-material-environment in the digital twin model of the manufacturing industry, so as to more accurately reflect the data changes and their correlation relationships under different states or different application scenarios; a synchronous layer selection component is designed for users to flexibly select the display layers of each part in a specific state or application scenario, ensuring that the information displayed on the dashboard is more intuitive and targeted. Finally, the generated dashboard in a specified state or application scenario improves the accuracy of data analysis and enhances the operation convenience and user experience of users.

[0010] Preferably, the visual content design module is further configured to provide five parts of man-machine-method-material-environment that allow users to create and automatically edit after creation. Each part is provided with an automatic display layer to display the corresponding part data information selected according to the user's historical preferences, and the data information is displayed in the visual form selected according to the user's historical preferences. An automatic data association component is set between each part to represent the data information of the correlation relationship and the correlation relationship strength between the corresponding parts according to the correlation form selected by the user's historical preferences.

[0011] By adopting the above solution, the display content and correlation relationship of the dashboard can be automatically configured based on the personalized needs and historical preferences of users, improving the user experience and operation efficiency.

[0012] Preferably, the data integration and analysis module is further configured to use AI technology to perform data prediction and correlation analysis on the preprocessed data, and obtain the prediction data of each part of man-machine-method-material-environment within a future preset time period and the correlation relationship between the prediction data of each part of man-machine-method-material-environment within a future preset time period; The visual content design module is further configured to provide five parts of man-machine-method-material-environment that allow users to create and edit and are added with a time axis. Each part is provided with a display layer adjustment component for users to select to display the corresponding part data information within a specified time span; The dashboard generation and interaction design module is further configured to correspondingly fill the obtained data of each part of man-machine-method-material-environment, the prediction data within a future preset time period, the correlation relationship between the data of each part of man-machine-method-material-environment, and the correlation relationship between the prediction data of each part of man-machine-method-material-environment within a future preset time period into the five parts of man-machine-method-material-environment that have completed creation and contain content editing within a future preset time period to generate a dashboard.

[0013] By adopting the above solution, a visual content design module with a time axis is provided, enabling users to flexibly select and display the data and their correlation relationships of each part of man-machine-method-material-environment within a future preset time period under different time spans.

[0014] Preferably, the visualization content design module is further configured to provide a multi-person editing priority selection component for each part of the board for the user to select a multi-person editing priority rule and screen and determine the corresponding board data information, the visualization form selected by multiple users, and the association form selected by multiple users according to the multi-person editing priority rule, so that there is no conflict in the corresponding board data information, the visualization form selected by multiple users, and the association form selected by multiple users after screening and determination.

[0015] By adopting the above solution, a multi-person editing priority selection function is provided to ensure orderly management of editing permissions when multiple users operate simultaneously, and to ensure the consistency and accuracy of the finally displayed data information, visualization form, and association relationship.

[0016] Preferably, the data integration and analysis module is configured to use AI technology and pre-set custom rules to perform data integration and correlation analysis on the pre-processed data, and obtain custom data belonging to each part of man-machine-method-material-environment and meeting the custom rules, as well as custom correlation relationships that meet the custom rules between custom data belonging to each part of man-machine-method-material-environment and meeting the custom rules. The visualization content design module is further configured to provide five parts of the board of man-machine-method-material-environment that support users to create and customize edits. Each part of the board is set with a custom display layer for the user to select and display the custom data information of the corresponding board, and a data association component is set between each part of the board for the user to select and specify an association form to represent the data information with a custom association relationship and a custom association relationship strength between the corresponding boards.

[0017] By adopting the above solution, multi-dimensional data of the corresponding entity model of the manufacturing digital twin model is analyzed to obtain data and its association relationships that meet the user's custom requirements, and five parts of the board of man-machine-method-material-environment that support users to create and customize edits are provided for the user to display the custom association relationship between custom data according to the requirements, ensuring the flexibility and convenience of the dashboard content during the user's use.

[0018] Preferably, it further includes: The dashboard feedback and optimization design module is configured to provide a dashboard feedback interface for the user to record the satisfaction with the displayed data of each part of the board and the data association relationship between each part of the board in the generated dashboard, and generate an optimization prompt message and feedback it to the data integration and analysis module if it is determined according to the content recorded in the dashboard feedback interface that the satisfaction with the displayed data of any part of the board or the data association relationship between each part of the board is lower than the preset satisfaction. The data integration and analysis module is further configured to optimize the AI technology in an incremental learning manner when receiving optimization prompt information.

[0019] By adopting the above solution, through the collection and analysis of user feedback, and continuously adjusting the AI algorithm in an incremental learning manner, continuous improvement and optimization of the generated dashboard are achieved.

[0020] In a second aspect, the present application provides a digital twin dashboard design method, including: Real-time collecting the data of the five parts of man-machine-method-material-environment of the physical model corresponding to the manufacturing digital twin model and performing data preprocessing; Using AI technology to perform data integration and correlation analysis on the preprocessed data to obtain the data belonging to each part of man-machine-method-material-environment and the correlation relationships between the data of different parts; Completing the creation and editing of the five parts of man-machine-method-material-environment; specifically including: creating the five parts of man-machine-method-material-environment according to user instructions, and editing the data information displayed in the display layer of each part, the visualization form of the data information, and the correlation form between the data information representing the correlation relationship and the correlation strength between each part according to user selection; Filling the obtained data belonging to each part of man-machine-method-material-environment and the correlation relationships between the data of different parts into the five parts of man-machine-method-material-environment that have been created and content-edited to generate a dashboard; Adjusting the layout of the parts and the data within the parts in the dashboard by selecting a specified interaction method.

[0021] By adopting the above solution, it is provided that users are allowed to freely select and edit the content and its display form of the five parts of man-machine-method-material-environment, and generate an intuitive dashboard that meets the humanized needs and displays the real-time data and data correlation relationships of the physical model corresponding to the manufacturing digital twin model.

[0022] In a third aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method as described above.

[0023] In a fourth aspect, the present application provides a computer device, where the computer device includes a memory, a processor, and a program stored on the memory and executable, and when the program is executed by the processor, it implements the steps of the method as described above.

[0024] In summary, the present application has the following beneficial effects: 1. The data acquisition and processing module collects and preprocesses the data of the five parts of man - machine - method - material - environment in real time. Combining with the data integration and analysis module supported by AI technology, it can comprehensively extract and reveal the data of each part and the correlation relationship between them, solving the problem of incomplete comprehensive data coverage. Combining with the visual content design module to provide flexible plate creation and editing functions, it supports users to freely select the display data of the display layer, the visualization form, and the correlation form indicating the association and the strength of the association between the data, and generates a dashboard that can intuitively meet the personalized needs of users. 2. Classify and analyze the data of each part of man - machine - method - material - environment obtained for the status or application scenario, and more accurately obtain the data of each part of man - machine - method - material - environment and their correlation relationship under different statuses or application scenarios. Combining with the display layer provided by the visual content design model to display the data information under different statuses or application scenarios, a dashboard that better meets the different viewing needs of users is generated. 3. Conduct data prediction and correlation analysis on the data of each part of man - machine - method - material - environment obtained. Combining with the visual content design module provided with a time axis, a dashboard is generated that not only shows the current data status but also shows the data of each part of man - machine - method - material - environment and their correlation relationship within a preset future time period. Description of the Drawings

[0025] Figure 1 It is a schematic structural diagram of the digital twin dashboard design system described in the specific embodiment; Figure 2 It is a flowchart of the digital twin dashboard design method described in the specific embodiment. Detailed Embodiments

[0026] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the 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.

[0027] As Figure 1 shown, the embodiment of the present application discloses a digital twin dashboard design system, which specifically includes: a data acquisition and processing module 1, a data integration and analysis module 2, a visual content design module 3, and a dashboard generation and interaction design module 4; among them, each module that establishes a communication connection with each other works efficiently through data streams in coordination to achieve the purpose of displaying multi - dimensional data in the manufacturing process in real time, accurately and comprehensively.

[0028] Specifically, the data acquisition and processing module 1 includes a data acquisition unit 11 and a data preprocessing unit 12. The data acquisition unit 1 can use a sensor network or an industrial Internet platform to collect real-time data on the five parts of the human-machine-method-material-environment corresponding to the physical model of the manufacturing digital twin model. Such as: the real-time location, working status and efficiency indicators of staff; the operating status, production capacity, fault and maintenance records of production equipment; the implementation of the production process flow, process optimization suggestions, etc.; the inventory, usage speed, supply chain status of materials; the temperature, humidity, air quality, etc. in the environment. The data preprocessing unit 2 is used to perform preprocessing such as cleaning, denoising, and normalization on the data of the five parts of the physical model of the human-machine-method-material-environment to improve the accuracy of subsequent analysis.

[0029] Specifically, the data integration and analysis module 2 includes a data integration unit 21 and a data analysis unit 22. The data integration unit 21 is used to integrate the preprocessed data by using artificial intelligence AI technology to extract the data belonging to each part of the human-machine-method-material-environment in order to intuitively and accurately display the data of each part to the user; the data analysis unit 22 is used to identify and obtain the correlation relationship of the integrated data of each part by using artificial intelligence AI technology in order to more intuitively and accurately display the correlation relationship between the data of each part to the user, such as: equipment failure caused by user operation errors, etc.; among them, the artificial intelligence AI technology selects the LSTM neural network or other deep learning algorithms.

[0030] Specifically, the visualization content design module 3 includes a plate creation unit 31, a layer content specification unit 32, and a component selection unit 33. The plate creation unit 31 is used to provide a basic plate that allows users to create the five parts of the human-machine-method-material-environment. Each basic plate is provided with a display layer for displaying the data related to the corresponding plate. Such as: the personnel plate is set to display the relevant data such as the real-time location, working status and efficiency indicators of the personnel. The layer content specification unit 32 is used to provide a plate of the five parts of the human-machine-method-material-environment that allows users to edit in order to meet the user's needs for the display content of each plate. Each plate is set with a display layer with a content specification function for the user to select and display the data information corresponding to the plate. Such as: display the data information of the real-time location and working status of the personnel plate selected by the user.

[0031] In order to display data information in the display layer more intuitively and effectively, various visualization forms can be selected. The component selection unit 33 is used to provide a variety of visualization components for each part of the board, such as statistical graph components such as bar charts, line charts, and pie charts, thermodynamic graph components, 3D model components and other visualization graph components for users to select and specify the visualization form to display data information. In addition, in order to effectively display the association relationship between specified data in the display layer and facilitate users to comprehensively understand the status information of the digital twin model, the component selection unit 33 is also used to provide data association components for each part of the board for users to select and specify the association form to represent the data information with the association relationship and the association relationship strength between the corresponding parts. Among them, the specified association forms include: association lines and association color blocks; for example, using lines or arrows to represent the association relationship between data in the corresponding display layers of different parts, such as connecting personnel flow with equipment utilization rate with a line; using color changes to represent the strength of the association relationship between data in the corresponding display layers of different parts, such as the association color block between equipment failure rate and environmental temperature and humidity is red.

[0032] Specifically, the dashboard generation and interaction design module 4 includes a board filling unit 41 and an interaction component unit 42. The board filling unit 41 includes filling the data belonging to each part of man-machine-method-material-environment and the association relationship between different part of data into the five-part board of man-machine-method-material-environment that has been created and content-edited to generate a dashboard. Among them, the five-part board of man-machine-method-material-environment with content editing completed includes: selecting the corresponding part data information in the five parts, selecting the visualization form of the displayed data information, and selecting the specified association form of the data information with the association relationship and the association relationship strength between the corresponding parts. The interaction component unit 42 is used to provide interaction components for the generated dashboard for users to adjust the board layout and the data within the board through the specified interaction methods selected; among them, the interaction methods include: operations such as dragging, scaling, and clicking. For example, users can change the layout of each part in the generated dashboard through the dragging action.

[0033] In a specific embodiment, considering that the manufacturing digital twin system usually has different application scenarios or is in a specific state, and the corresponding users have the need to view data for different application scenarios and states. In order to generate dashboards in different states or scenarios, the system includes: The data integration unit 21 in the data integration and analysis module 3 is further configured to classify the data of each part of man-machine-method-material-environment obtained according to the status or application scenario, and obtain the data of each part of man-machine-method-material-environment in different statuses or application scenarios; wherein, the status includes normal conditions and (pre-set in advance) abnormal conditions (such as: fault maintenance status); the application scenarios include production line application scenarios (including: early stage, middle stage, and late stage, etc.), production quality inspection application scenarios (including: initial inspection, repeated inspection, etc.), and warehousing application scenarios (including: direct storage, transfer storage), etc.

[0034] The data analysis unit 22 in the data integration and analysis module 3 is further configured to use AI technology to analyze the data of each part of man-machine-method-material-environment obtained through integration under different statuses or application scenarios, and extract the correlation relationships between the data of each part of man-machine-method-material-environment under different statuses or application scenarios, such as: the correlation relationships between the data of each part of man-machine-method-material-environment under a single status or a single application scenario.

[0035] Correspondingly, in order to display the data of the digital twin system under different statuses or scenarios, multiple display layers are set for different part dashboards, and each display layer is used to display the data of the digital twin system in a single status or a single application scenario; specifically, the visualization content design module 3 further includes a layer selection unit 34, which is used to provide a synchronous layer selection component for the user to select the display layer of each part panel under the same status and application scenario conditions, such as the user selects the display layer of each part panel of man-machine-method-material-environment under the same production line application scenario conditions; multiple display layers are set for each part panel, and different display layers are used for the user to select to display the data information of the corresponding panel under a single status or a single application scenario.

[0036] Correspondingly, the plate filling unit 41 in the dashboard generation and interaction design module 4 is further configured to correspondingly fill the obtained data of each part of man-machine-method-material-environment under different statuses or application scenarios and the correlation relationships between the data of each part of man-machine-method-material-environment under different statuses or application scenarios into the five-part panel of man-machine-method-material-environment that has been created and includes content editing of status or application scenario, so as to generate a dashboard under a specified status or application scenario.

[0037] A specific embodiment, on the basis of timely providing an intuitive and user-friendly data visualization dashboard for the manufacturing digital twin model, further considers user preferences to generate a visualization dashboard that conforms to user habits. The system includes: The visual content design module 3 is further configured to provide five parts of human - machine - method - material - environment that allow users to create and automatically edit after creation. Each part is provided with an automatic display layer to display the corresponding part data information selected according to the user's historical preferences, and display the data information in the visual form selected according to the user's historical preferences. And an automatic data association component is set between each part to represent the data information with an association relationship and an association relationship strength between the corresponding parts according to the association form selected according to the user's historical preferences. Among them, the user's historical preferences can be obtained by using AI technology to perform intelligent analysis on historical data.

[0038] In a specific embodiment, in addition to generating a visual dashboard that conforms to the user's habits by considering the user's preferences, it can also provide a visual dashboard that displays the user - defined data for the digital twin system, facilitating the user to quickly obtain the required information; The system includes: The data integration unit 21 in the data integration and analysis module 2 is further configured to use AI technology and pre - set custom rules to perform data integration and correlation analysis on the pre - processed data, and obtain custom data that belongs to each part of human - machine - method - material - environment and meets the custom rules; Among them, the pre - set custom rules can be set by the user himself and uploaded and stored in the system. The custom rules include custom data, such as: custom personnel efficiency indicators, custom association relationships.

[0039] The data analysis unit 22 in the data integration and analysis module 2 is further configured to use AI technology to analyze the association relationships between the custom data that belongs to each part of human - machine - method - material - environment and meets the custom rules, and obtain the custom association relationships that meet the custom rules between the custom data that belongs to each part of human - machine - method - material - environment and meets the custom rules.

[0040] The visual content design module 3 is further configured to provide five parts of human - machine - method - material - environment that support users to create and customize edits. Each part is provided with a custom display layer for the user to select and display the custom data information of the corresponding part, and a data association component is set between each part for the user to select and specify an association form to represent the data information with a custom association relationship and a custom association relationship strength between the corresponding parts.

[0041] In a specific embodiment, considering that the digital twin system can not only display the running state of the physical model in real time, but also further predict the running of the physical model to generate warning information, the dashboard of the corresponding digital twin system is also designed to comprehensively display the prediction results, which helps users to comprehensively understand the manufacturing business situation; The system includes: The data integration unit 21 in the data integration and analysis module 2 is further configured to use AI technology to perform data prediction and correlation analysis on the preprocessed data, and obtain prediction data for each part of man-machine-method-material-environment within a future preset time period, where the future preset time period can be set manually.

[0042] The data analysis unit 22 in the data integration and analysis module 2 is further configured to use AI technology to analyze the prediction data for each part of man-machine-method-material-environment within a future preset time period, and obtain the correlation relationships between the prediction data for each part of man-machine-method-material-environment within a future preset time period.

[0043] The visualization content design module 3 is further configured to provide a five-part board of man-machine-method-material-environment that allows users to create and edit and is added with a timeline. Each part of the board is provided with a display layer adjustment component for the user to select and display the data information of the corresponding board under a specified time span; the display layer adjustment component is a component for adjusting the time span of the data information in the display layer.

[0044] The dashboard generation and interaction design module 4 is further configured to fill the obtained data for each part of man-machine-method-material-environment, the prediction data within a future preset time period, the correlation relationships between the data for each part of man-machine-method-material-environment, and the correlation relationships between the prediction data for each part of man-machine-method-material-environment within a future preset time period into the five-part board of man-machine-method-material-environment that has been created and contains content editing of the future preset time period to generate a dashboard, that is, to correspond and match the real-time data with the prediction data of the future preset time period and fill them into the five-part board with specified data, specified visualization forms, and specified correlation forms for display, and generate a visual dashboard.

[0045] In a specific embodiment, to avoid content conflicts during the collaborative editing of the dashboard content by multiple users, a function of selecting the priority of multiple-person editing is provided to ensure orderly management of editing permissions when multiple users operate simultaneously. The system includes: The visualization content design module 3 is further configured to provide a multiple-person editing priority selection component for each part of the board, so that the user can select the multiple-person editing priority rule and screen and determine the data information of the corresponding board selected by multiple users, the visualization form selected by multiple users, and the correlation form selected by multiple users according to the multiple-person editing priority rule, so that there are no conflicts in the data information of the corresponding board selected by multiple users, the visualization form selected by multiple users, and the correlation form selected by multiple users after screening and determination. Among them, the multiple-person editing priority selection component includes a function component for indirectly setting the priority of the specified content of multiple users according to the priority of multiple users and a function component for directly setting the priority according to the specified content of the user.

[0046] In a specific embodiment, a kanban feedback and optimization mechanism is added to further optimize the content displayed on the kanban to improve the user viewing experience. The system further includes: a kanban feedback and optimization design module 5.

[0047] The kanban feedback and optimization design module 5 is used to provide a kanban feedback interface for users to record their satisfaction with the display data of each part of the generated kanban and the correlation relationship between the data of each part. When it is determined according to the content recorded in the kanban feedback interface that the satisfaction with the display data of any part or the correlation relationship between the data of each part is lower than the preset satisfaction (indicating that there are parts that users are not satisfied with in the content displayed on the kanban), an optimization prompt message is generated and fed back to the data integration and analysis module.

[0048] In addition, according to whether the satisfaction with the display data of any specific part or the correlation relationship between the data of each part is lower than the preset satisfaction, an integrated data optimization prompt message or a data correlation relationship analysis optimization prompt message can be generated correspondingly.

[0049] The data integration and analysis module 2 is further used to, when receiving the optimization prompt message, optimize the AI technology in an incremental learning manner, including optimizing the AI model for extracting data belonging to each part of man-machine-method-material-environment and the AI model for identifying the correlation relationship between the data of each part.

[0050] As Figure 2 shown, an embodiment of the present application discloses a digital twin kanban design method, including the following steps: S1. Real-time collect the data of the five parts of man-machine-method-material-environment of the entity model corresponding to the manufacturing digital twin model and perform data preprocessing.

[0051] S2. Use AI technology to perform data integration and correlation analysis on the preprocessed data to obtain the data belonging to each part of man-machine-method-material-environment and the correlation relationship between the data of different parts.

[0052] S3. Complete the creation and editing of the five parts of man-machine-method-material-environment.

[0053] Specifically, it includes: creating the five parts of man-machine-method-material-environment according to the user's instructions, and editing the corresponding data information displayed in the display layer of each part, the visual form of the data information, and the correlation form between the data information representing the correlation relationship and the correlation strength between each part according to the user's selection.

[0054] S4. Fill the obtained data belonging to each part of man-machine-method-material-environment and the correlation relationship between the data of different parts into the five parts of man-machine-method-material-environment that have been created and content-edited to generate a kanban.

[0055] S5. Adjust the layout of the sections and the data within the sections on the kanban board according to the selected specified interaction method.

[0056] A specific embodiment further includes the following steps: Classify and analyze the data of each part of man-machine-method-material-environment obtained according to the status or application scenario, and obtain the correlation relationship between the data of each part of man-machine-method-material-environment in different states or application scenarios and the data of each part of man-machine-method-material-environment in different states or application scenarios; Edit the display layers of each part of the section under the same state and application scenario conditions according to the user's selection to display the data information of the corresponding section in a single state or a single application scenario; Fill the obtained correlation relationship between the data of each part of man-machine-method-material-environment in different states or application scenarios and the data of each part of man-machine-method-material-environment in different states or application scenarios into the five-part sections of man-machine-method-material-environment that have been created and content-edited to generate a kanban board in a specified state or application scenario.

[0057] A specific embodiment, the creation and editing of the five-part sections of man-machine-method-material-environment further includes: After completing the five-part sections of man-machine-method-material-environment according to the user's instructions, automatically edit the display layers in each section to display the data information of the corresponding section according to the user's preferences, automatically edit the visualization form of the displayed data information, and automatically edit the association form of the data information representing the correlation relationship and the strength of the correlation relationship between each section.

[0058] A specific embodiment, the method further includes the following steps: Using AI technology, perform data prediction and correlation analysis on the preprocessed data to obtain the predicted data of each part of man-machine-method-material-environment within a future preset time period and the correlation relationship between the predicted data of each part of man-machine-method-material-environment within a future preset time period; The editing of the five-part sections of man-machine-method-material-environment further includes: adjusting the components of the display layer according to the user's selected display layer, and editing the display layer to display the data information of the corresponding section under a specified time span; Fill the obtained data of each part of man-machine-method-material-environment, the predicted data within a future preset time period, the correlation relationship between the data of each part of man-machine-method-material-environment, and the correlation relationship between the predicted data of each part of man-machine-method-material-environment within a future preset time period into the five-part sections of man-machine-method-material-environment that have been created and contain content editing for a future preset time period to generate a kanban board.

[0059] A specific embodiment, the method further includes the following steps: Completing the editing of the five parts of man - machine - method - material - environment also includes: screening and determining the corresponding part data information displayed by multiple users, the visualization forms specified by multiple users, and the association forms specified by multiple users according to the multi - user selection priority rules selected by the user, so that there are no conflicts among the corresponding part data information displayed by multiple users, the visualization forms specified by multiple users, and the association forms specified by multiple users after screening and determination.

[0060] In a specific embodiment, the method further includes the following steps: Using AI technology and pre - set custom rules, performing data integration and correlation analysis on the pre - processed data to obtain custom data belonging to each part of man - machine - method - material - environment and meeting the custom rules, and custom correlation relationships that meet the custom rules between custom data belonging to each part of man - machine - method - material - environment and meeting the custom rules. Completing the custom editing of the five parts of man - machine - method - material - environment, including: according to the user's selection, editing the custom data information of the parts displayed in the custom display layer, and according to the user's selection, editing the specified association form representing the custom correlation relationship and the strength of the custom correlation relationship between the corresponding parts.

[0061] In a specific embodiment, the method further includes the following steps: Obtaining the satisfaction degree recorded by the user in the kanban feedback interface for the display data of each part of the generated kanban and the data correlation relationship of each part of the kanban. If it is determined according to the content recorded in the kanban feedback interface that the satisfaction degree of any part of the display data or the data correlation relationship of each part of the kanban is lower than the preset satisfaction degree, generating and feeding back an optimization prompt message. When receiving the optimization prompt message, optimizing the AI technology in an incremental learning manner.

[0062] The embodiment of the present application also discloses a computer - readable storage medium.

[0063] Specifically, this computer - readable storage medium stores a computer program that can be loaded and executed by a processor, such as the digital twin kanban design method described above. This computer - readable storage medium includes, for example: various media such as USB flash drives, external hard drives, read - only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0064] The embodiment of the present application also discloses a computer device.

[0065] Specifically, the computer device includes a memory and a processor, and a computer program capable of being loaded and executed by the processor for the above digital twin dashboard design method is stored on the memory.

[0066] The above are all preferred embodiments of the present application. Without restricting the protection scope of the present application according to this, any feature disclosed in this specification (including the abstract and drawings), unless specifically described, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically described, each feature is only an example of a series of equivalent or similar features.

Claims

1. A digital twin dashboard design system, characterized in that, Including: A data acquisition and processing module for real-time collecting the data of the five parts of man-machine-method-material-environment of the entity model corresponding to the digital twin model of manufacturing and performing data preprocessing; A data integration and analysis module for using AI technology to perform data integration and correlation analysis on the preprocessed data to obtain the data of each part of man-machine-method-material-environment and the correlation relationships between the data of different parts; A visual content design module for providing five parts of man-machine-method-material-environment plates that allow users to create and edit. Each part of the plate is set with a display layer for users to select and display the data information of the corresponding plate, and each part of the plate is set with a variety of visual components for users to select and specify the visual form to display the data information, and data association components are set between the parts of the plate for users to select and specify the association form to represent the data information with the association relationship and the strength of the association relationship between the corresponding plates; A dashboard generation and interaction design module for filling the obtained data of each part of man-machine-method-material-environment and the correlation relationships between the data of different parts into the five parts of man-machine-method-material-environment plates that have been created and content-edited to generate a dashboard, and providing interaction components for the generated dashboard for users to adjust the layout of the plates and the data within the plates through the specified interaction methods selected; 2. The digital twin dashboard design system according to claim 1, wherein The data integration and analysis module is also used for classifying and analyzing the data of each part of man-machine-method-material-environment for status or application scenarios, and obtaining the data of each part of man-machine-method-material-environment under different statuses or application scenarios and the correlation relationships between the data of each part of man-machine-method-material-environment under different statuses or application scenarios; the status includes normal situation and abnormal situation; the application scenarios include production line application scenarios, production quality inspection application scenarios, and warehousing application scenarios; The visual content design module is also used for providing a synchronous layer selection component for users to select the display layers of each part of the plate under the same status and application scenario conditions. Each part of the plate is set with multiple display layers, and different display layers are used for users to select to display the data information of the corresponding plate under a single status or a single application scenario; The dashboard generation and interaction design module is also used for filling the obtained data of each part of man-machine-method-material-environment under different statuses or application scenarios and the correlation relationships between the data of each part of man-machine-method-material-environment under different statuses or application scenarios into the five parts of man-machine-method-material-environment plates that have been created and content-edited to generate a dashboard under the specified status or application scenario; 3. The digital twin dashboard design system according to claim 1, characterized in that, The visual content design module is also used for providing five parts of man-machine-method-material-environment plates that allow users to automatically edit after creation. Each part of the plate is set with an automatic display layer to display the data information of the corresponding plate selected according to the user's historical preferences, and display the data information in the visual form selected according to the user's historical preferences, and automatic data association components are set between the parts of the plate to represent the data information with the association relationship and the strength of the association relationship between the corresponding plates according to the association form selected according to the user's historical preferences.

4. The digital twin dashboard design system according to claim 1, characterized in that, The data integration and analysis module is also used to utilize AI technology to perform data prediction and correlation analysis on the preprocessed data, and obtain the predicted data for each part of man-machine-method-material-environment within a future preset period and the correlation relationships between the predicted data for each part of man-machine-method-material-environment within a future preset period; The visualization content design module is also used to provide a five-part board of man-machine-method-material-environment that allows users to create and edit and is added with a timeline. Each part of the board is provided with a display layer adjustment component for the user to select and display the data information of the corresponding part under a specified time span; The dashboard generation and interaction design module is also used to fill the obtained data for each part of man-machine-method-material-environment, the predicted data within a future preset period, the correlation relationships between the data for each part of man-machine-method-material-environment, and the correlation relationships between the predicted data for each part of man-machine-method-material-environment within a future preset period into the five-part board of man-machine-method-material-environment that has been created and contains content editing for the future preset period to generate a dashboard.

5. The digital twin dashboard design system according to claim 1, characterized in that, The visualization content design module is also used to provide a multi-user editing priority selection component for each part of the board for the user to select the multi-user editing priority rule and screen and determine the corresponding part of the board data information, the visualization form selected by multiple users, and the correlation form selected by multiple users according to the multi-user editing priority rule, so that there is no conflict among the corresponding part of the board data information, the visualization form selected by multiple users, and the correlation form selected by multiple users after screening and determination.

6. The digital twin dashboard design system according to claim 1, wherein The data integration and analysis module is used to utilize AI technology and pre-set custom rules to perform data integration and correlation analysis on the preprocessed data, and obtain the custom data that belongs to each part of man-machine-method-material-environment and meets the custom rules and the custom correlation relationships that meet the custom rules between the custom data that belongs to each part of man-machine-method-material-environment and meets the custom rules; The visualization content design module is also used to provide a five-part board of man-machine-method-material-environment that supports user creation and custom editing. Each part of the board is provided with a custom display layer for the user to select and display the custom data information of the corresponding part, and a data correlation component is provided between each part of the board for the user to select and specify a correlation form to represent the data information of the custom correlation relationship and the custom correlation relationship strength between the corresponding parts of the board.

7. The digital twin dashboard design system according to claim 1, characterized in that, It also includes: The dashboard feedback and optimization design module is used to provide a dashboard feedback interface for the user to record the satisfaction with the displayed data of each part of the generated dashboard and the data correlation relationships of each part of the board, and when it is judged according to the content recorded in the dashboard feedback interface that the satisfaction with the displayed data of any part of the board or the data correlation relationships of each part of the board is lower than the preset satisfaction, generate an optimization prompt message and feedback it to the data integration and analysis module; The data integration and analysis module is also used to optimize the AI technology in an incremental learning manner when receiving the optimization prompt message.

8. A digital twin dashboard design method using the system described in any one of claims 1 to 6, characterized in that It includes: Collect the data of the five parts of man-machine-method-material-environment corresponding to the entity model of the digital twin model in the manufacturing industry in real time and perform data preprocessing; Using AI technology, perform data integration and correlation analysis on the preprocessed data to obtain the data of each part of man-machine-method-material-environment and the correlation relationships between the data of different parts; Complete the creation and editing of the five parts of man-machine-method-material-environment; specifically including: creating the five parts of man-machine-method-material-environment according to the user's instructions, and editing the data information within the corresponding part displayed on the display layer of each part according to the user's selection, editing the visual form of the data information, and editing the correlation form between the data information representing the correlation relationships and the strength of the correlation relationships between the parts; Fill the obtained data of each part of man-machine-method-material-environment and the correlation relationships between the data of different parts into the five parts of man-machine-method-material-environment that have been created and content-edited to generate a dashboard; Adjust the layout of the parts in the dashboard and the data within the parts by the selected specified interaction method.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method according to any one of claims 1 to 7.

10. A computer device, characterized in that, The computer device includes a memory, a processor, and a program stored on the memory and executable. When the program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 7.

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