Digital twin development system and digital twin model generation method

Abstract

The invention discloses a digital twin development system and a digital twin model generation method, and the system comprises a scene design module which is used for providing a preset component library matched with different manufacturing business objects; receiving a component selected by a user from a correspondingly matched preset component library according to a demand, matching a corresponding component billboard, and creating a digital twinning scene; the scene editing module is used for providing a preset editing tool library matched with different manufacturing business objects; receiving an editing tool selected from a preset editing tool library matched by the user, and editing the digital twin scene selected by the user; the data linkage module is used for carrying out synchronous association binding on the business data of the manufacturing business object and a digital twinning scene established based on the same manufacturing business object; and the billboard design module is used for generating the billboard of the corresponding component according to the information type combination contained in the different components in the different preset component libraries. According to the invention, efficient development of digital twin systems of different manufacturing services can be realized.

Description

Technical Field

[0001] This application relates to the field of digital twin technology, and particularly to a digital twin development system and a digital twin model generation method. Background Art

[0002] The application of digital twin technology in the manufacturing industry is becoming increasingly widespread. By real-time mapping and interacting between the physical world and the virtual world, it improves the visualization, controllability, and optimization capabilities of the manufacturing process. This technology can not only help enterprises achieve transparent management of the production process but also significantly improve production efficiency and product quality. With the popularization of the concept of Industry 4.0, digital twin has become an important part of intelligent manufacturing, providing enterprises with new means of management and decision-making support.

[0003] To realize the development and application of digital twins, existing technologies usually simply provide templates or toolkits required for the development of digital twin systems, for users to manually create digital twin scenarios through 3D modeling software and import the actual data of the factory to develop and generate digital twin models. Obviously, existing technologies have significant limitations in practical applications. Especially in the process of building digital twin models, the differences between different scenarios are often ignored, and it is difficult to provide accurate scenario design components and editing tools. This results in the need for personnel with strong professional knowledge to complete the development and application of digital twin scenarios in the development process, increasing labor costs and technical thresholds. Moreover, when dealing with large-scale and multi-level manufacturing business objects, problems such as data synchronization errors often occur, thus affecting the overall performance and user experience of the digital twin system.

[0004] Therefore, how to efficiently and flexibly realize the development of digital twin systems for manufacturing objects, especially to provide accurate design components and editing tools for different scenarios, has become a technical problem to be solved urgently. Summary of the Invention

[0005] To efficiently and flexibly realize the development of digital twin systems for manufacturing objects, this application provides a digital twin development system and a digital twin model generation method.

[0006] In a first aspect, this application provides a digital twin development system, including: including: a scenario design module, a scenario editing module, a data linkage module, and a dashboard design module; The scenario design module is used to provide a preset component library that matches different manufacturing business objects; each preset component library stores components associated with the manufacturing business objects that match it, including: a personnel model, a device model, a material model, a process flow model, and an environment model that have an associated relationship with the manufacturing business knowledge graph of the manufacturing business object that matches the preset component library; receive the components selected by the user from the corresponding preset component library according to the manufacturing business requirements, and match the corresponding component kanban from the kanban design module according to the components selected by the user; create a digital twin scenario based on the components selected by the user and the corresponding component kanban. The scenario editing module is used to provide a preset editing tool library that matches different manufacturing business objects. Each preset editing tool library stores editing tools associated with the manufacturing business objects that match it, including: editing tools applied to the components in the preset component library that are the same as the business objects that match the preset editing tool library; receive and, according to the editing tools selected by the user from the selected preset editing tool library, perform editing processing on the digital twin scenario created by the user for the business objects that match the preset editing tool library. The data linkage module is used to synchronously associate and bind the business data of the actual manufacturing business object with the digital twin scenario established based on the same manufacturing business object. The kanban design module is used to generate the kanban for the corresponding components according to the combination of the information types included in the different components in different preset component libraries.

[0007] By adopting the above solution, a preset component library and a preset editing tool library that match different manufacturing business objects are provided, enabling users to flexibly select appropriate components and editing tools according to specific manufacturing business requirements, thereby efficiently creating and editing digital twin scenarios; through the real-time synchronous association between the actual manufacturing business data and the digital twin scenario, the data accuracy and timeliness of the developed digital twin model are ensured; generating corresponding kanbans according to the information types included in different components further improves the operation convenience and visualization effect of users.

[0008] Preferably, the scenario design module is further configured to provide a number of preset sub-component libraries belonging to the preset component library when receiving a preset component library selected by the user; each preset component library has a number of preset sub-component libraries; each preset component library divides the stored personnel model, equipment model, material model, process flow model, and environment model into the corresponding nodes according to the scenario type corresponding to the nodes in the tree structure of the preset component library; the nodes in the tree structure of each preset component library include: a production overview scenario node as the root node, a production line scenario node, a production quality inspection scenario node, and a warehousing scenario node as leaf nodes; each preset sub-component library stores the personnel model, equipment model, material model, process flow model, and environment model belonging to the corresponding nodes; receive the components selected from the preset sub-component library selected by the user to replace the components selected from the preset component library selected by the user.

[0009] By adopting the above solution, each preset component library is hierarchically divided into multiple preset sub-component libraries according to the tree structure. While providing more detailed preset sub-component libraries, it improves the user's selection efficiency of components during the development of the digital twin model and ensures a high degree of fit between the selected components and the actual manufacturing business, realizing more fine-grained scenario construction and component selection.

[0010] Preferably, the scenario design module is further configured to provide a number of preset unit component libraries belonging to the preset sub-component library when receiving a preset sub-component library selected by the user; each preset sub-component library has a number of preset unit component libraries; each preset sub-component library divides the stored personnel model, equipment model, material model, process flow model, and environment model into the corresponding nodes according to the phase type corresponding to the nodes in the parallel structure of the preset sub-component library; the nodes in the parallel structure of each preset sub-component library include: different production phase scenario nodes in the production line scenario, different inspection phase scenario nodes in the production quality inspection scenario, and different warehousing phase scenario nodes in the warehousing scenario; each preset unit component library stores the personnel model, equipment model, material model, process flow model, and environment model belonging to the corresponding nodes; receive the components selected from the preset unit component library selected by the user to replace the components selected from the preset sub-component library selected by the user.

[0011] By adopting the above solution, each preset component library is hierarchically divided into multiple preset unit component libraries according to the phase parallel structure. While providing more detailed preset unit component libraries, it improves the user's selection efficiency of components during the development of the digital twin model and ensures a high degree of match between the selection of components and specific business phases, realizing more fine-grained scenario construction and component selection.

[0012] Preferably, the scenario editing module is further configured to determine the scenario type or stage type to which the digital twin scenario created for the business object matching the preset editing tool library selected by the user belongs; according to the determined scenario type or stage type, filter out the editing tools that match the corresponding scenario type or stage type from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library; wherein, the editing tools stored in the preset editing tool library are pre-associated with the preset scenario type or stage type according to the functional attributes of the editing tools.

[0013] By adopting the above solution, when the user selects the digital twin scenario to be edited, the scenario type or stage type is automatically identified and determined. By filtering and locking the editing tools, refined editing is achieved, avoiding the user getting lost among a large number of tools and reducing the possibility of misoperation, thus enhancing the user experience.

[0014] Preferably, the scenario editing module is further configured to provide the editing order management of the digital twin scenario, arrange the digital twin scenarios created for the business object matching the preset editing tool library selected by the user in the selected time order; according to the arrangement order, pre-determine the scenario type or stage type to which each selected digital twin scenario belongs; monitor the operation process of editing the selected digital twin scenario, and when it is detected that the operation process of editing has been completed, filter out the editing tools that match the scenario type or stage type of the next order from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library.

[0015] By adopting the above solution, monitor the operation process of editing the selected digital twin scenario, and automatically filter out the editing tools required for the digital twin scenario to be edited in the next order when the editing is completed, so as to realize the orderly management and efficient editing of multiple digital twin scenarios.

[0016] Preferably, the data linkage module is configured to preprocess the business data of the actual manufacturing business object obtained, and input the preprocessed business data into the first neural network of the corresponding manufacturing business object to correspondingly obtain the scenario type to which the preprocessed business data belongs; perform clustering processing on the business data according to the scenario type to which the obtained preprocessed business data belongs, and synchronously associate and bind the business data of the corresponding scenario type with the digital twin scenario created based on the same manufacturing business object and belonging to one scenario type; wherein, the first neural network database includes multiple first neural networks, and each first neural network is trained by the business data of a manufacturing business object with a historically marked scenario type. For multiple groups of business data after clustering processing, each group of business data is respectively input into a second neural network corresponding to the manufacturing business object and the corresponding scenario type, and the stage type to which each group of business data belongs is correspondingly obtained; clustering processing is performed on each group of business data according to the obtained stage type to which each group of business data belongs; according to each determined stage type, the business data of the corresponding stage type is synchronously associated and bound with the digital twin scenario established based on the same manufacturing business object and belonging to one stage type; among them, the second neural network database includes multiple second neural networks, and each second neural network is trained and generated by historical annotation of the business data of a manufacturing business object of one stage type under one scenario type.

[0017] By adopting the above scheme, through multiple clustering processes and neural network analyses, it is ensured that the business data of different scenario types and stage types can be synchronously associated and bound with the corresponding digital twin scenarios efficiently and accurately, improving the data processing ability of the entire system and the adaptability of the application scenarios.

[0018] Preferably, the kanban design module is further configured to generate a corresponding sub-component kanban according to the information type combinations included in different components in different preset sub-component libraries.

[0019] By adopting the above scheme, generating a corresponding sub-component kanban according to the information type combinations included in different components in different preset sub-component libraries can more intuitively understand the specific information of each sub-component, thereby better managing and optimizing the manufacturing business process.

[0020] In a second aspect, the present application provides a digital twin model generation method applying the above development system, including: Obtain the target manufacturing business object required by the user, and display the preset component library matching the corresponding manufacturing business object; Receive the components selected by the user from the corresponding matching preset component library according to the manufacturing business requirements, match the corresponding component kanban according to the components selected by the user; create a digital twin scenario according to the components selected by the user and the corresponding matching component kanban; Obtain the target manufacturing business object required by the user, and display the preset editing tool library matching the corresponding manufacturing business object; receive the editing tool selected by the user from the corresponding preset editing tool library, and perform editing processing on the digital twin scenario created by the user for the business object matching the preset editing tool library according to the editing tool selected by the user; Synchronously associate and bind the business data of the actual manufacturing business object with the digital twin scenario established based on the same manufacturing business object.

[0021] By adopting the above solution, by using the provided preset component library and preset editing tool library that match different manufacturing business objects, users can flexibly select corresponding components and editing tools according to specific manufacturing business requirements, thereby efficiently creating and editing digital twin scenarios. In a third aspect, the present application provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method as described above.

[0022] In a fourth aspect, the present application provides a computer device, which includes a memory, a processor, and a program stored and executable on the memory. When the program is executed by the processor, it implements the steps of the method as described above.

[0023] In summary, the present application has the following beneficial effects: 1. Provide a preset component library and an editing tool library that match different manufacturing business objects, enabling users to quickly select appropriate components and editing tools according to specific manufacturing business requirements, effectively reducing the professional threshold and technical difficulty of digital twin scenario development; synchronously associating and binding actual manufacturing business data with digital twin scenarios ensures data consistency and accuracy, and solves the problem of system performance degradation caused by data synchronization errors in the prior art. 2. By setting a multi-level component library structure (such as a preset sub-component library and a preset unit component library), more refined and flexible scenario design options are provided, meeting the diverse business needs in complex manufacturing environments, and enhancing the applicability and scalability of the system. 3. By determining the type of digital twin scenario selected by the user, the corresponding screening and locking of editing tools are completed, realizing refined editing and improving the pertinence and effectiveness of editing work. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic structural diagram of the digital twin development system in a specific embodiment; Figure 2 It is a flowchart of generating a digital twin model by applying the digital twin development system in a specific embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] In order to make the objectives, technical solutions, and advantages of the present application clearer, the present application will be further described in detail below with reference to 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.

[0026] Embodiment 1 As Figure 1As shown in the figure, the embodiment of the present application discloses a digital twin development system, which specifically includes four major modules, namely: a scene design module 101, a scene editing module 202, a data linkage module 303, and a dashboard design module 404. Among them, each module is interconnected through data interfaces and communication protocols, forming a complete digital twin development platform.

[0027] Specifically, the scene design module 101 is used to provide a preset component library that matches different manufacturing business objects. Each preset component library stores components associated with the manufacturing business objects that match it, including: a personnel model, an equipment model, a material model, a process flow model, and an environment model that have an association relationship with the manufacturing business knowledge graph of the manufacturing business object that matches the preset component library. These components can be pre-made through CAD software or other 3D modeling tools and stored in a cloud server. For example: the personnel model can be the standard action models of different workers, the equipment model can be the working state simulation of different models of machines, the material model can be the 3D images of various raw materials and finished products, the process flow model can be the animation demonstration of a series of processes, and the environment model can be the layout and environmental parameters of the workshop.

[0028] It is used to receive the components selected by the user from the corresponding preset component library according to the manufacturing business requirements, and match the corresponding component dashboard from the dashboard design module according to the components selected by the user. For example: when the user selects to manufacture surgical instruments, the preset component library for surgical instruments is matched; when the user selects an equipment model on a certain production line, the corresponding monitoring dashboard is automatically matched for it to display the real-time working status and performance indicators of the equipment.

[0029] It is used to create a digital twin scene according to the components selected by the user and the corresponding component dashboard. In addition, in order to ensure that each component can work properly and cooperate in the same environment, the operation of the digital twin scene can be simulated in a virtual environment to timely discover problem components and optimize or replace them.

[0030] The scene editing module 202 is used to provide a preset editing tool library that matches different manufacturing business objects. Each preset editing tool library stores editing tools associated with the manufacturing business objects that match it, including: editing tools applied to the components in the same preset component library that matches the business object of the preset editing tool library. For example, basic editing tools such as rotation, scaling, and movement, or more advanced editing tools such as path planning and collision detection.

[0031] It is used to receive and, according to the editing tools selected by the user from the selected preset editing tool library, perform editing processing on the digital twin scene created by the user for the business object that matches the preset editing tool library.

[0032] The data linkage module 303 is used to synchronously associate and bind the business data of the actual manufacturing business object with the digital twin scenario established based on the same manufacturing business object. For example, the data collected on the actual production line (such as sensor data, equipment status information, etc.) will be transmitted to the cloud in real time, and then synchronized and updated with the virtual objects (components) in the digital twin scenario through the API interface.

[0033] The dashboard design module 404 is used to generate the dashboards for the corresponding components according to the information type combinations included in the different components in different preset component libraries. For example, an equipment monitoring dashboard is generated according to the equipment model, displaying information such as the working status and fault alarm of the equipment; another example is that a logistics tracking dashboard is generated according to the material model, displaying information such as the location, quantity, and transportation progress of the materials.

[0034] As described above, the development system realizes the whole process from component selection, scenario creation, scenario editing to data linkage by integrating multiple functional modules, greatly simplifying the development process of the digital twin model. Especially with the support of accurate components and editing tools in different scenarios, users can easily complete the development of complex digital twin scenarios without having profound professional knowledge. At the same time, the high flexibility and scalability of the system also enable it to adapt to the changing production and market demands, having high practical value and market prospects.

[0035] Embodiment 2 The difference from Embodiment 1 is that, in order to meet the refined requirements of users for manufacturing operations and provide more fine-grained scenario construction and component selection, the system further includes: The scenario design module 101 is further used to provide a number of preset sub-component libraries belonging to the selected preset component library when receiving the preset component library selected by the user; wherein, each preset component library is provided with a number of preset sub-component libraries; each preset component library divides the stored personnel model, equipment model, material model, process flow model, and environment model into the corresponding nodes according to the scenario types corresponding to the nodes in the tree structure of the preset component library; the nodes in the tree structure of each preset component library include: the production overview scenario node as the root node, the production line scenario node, the production quality inspection scenario node, and the warehousing scenario node as the leaf nodes, etc.; each preset sub-component library stores the personnel model, equipment model, material model, process flow model, and environment model belonging to the corresponding nodes; for example, the components belonging to the production line scenario are divided into the production line scenario node. It is used to receive the components selected from the selected preset sub-component library by the user to replace the components selected from the preset component library selected by the user himself / herself, so as to enable the user to create a digital twin scenario in a more refined manner.

[0036] In addition, in addition to the refinement from the overall manufacturing overview to each manufacturing node, there are multiple manufacturing links within each manufacturing node itself. To further provide more refined component selection for these manufacturing links, the system further includes: The scenario design module 101 is further configured to provide a number of preset unit component libraries belonging to a preset sub-component library when receiving a preset sub-component library selected by the user; wherein, each preset sub-component library is provided with a number of preset unit component libraries; each preset sub-component library divides the stored personnel model, equipment model, material model, process flow model, and environment model into their respective nodes according to the node corresponding stage types in the parallel structure of the preset sub-component library; the nodes in the parallel structure of each preset sub-component library include: different production stage scenario nodes in the production line scenario, different detection stage scenario nodes in the production quality inspection scenario, and different warehousing stage scenario nodes in the warehousing scenario; each preset unit component library stores the personnel model, equipment model, material model, process flow model, and environment model of its corresponding node.

[0037] Specifically, different production stage scenario nodes include: production initial stage scenario nodes, production middle stage scenario nodes, and production later stage scenario nodes, etc.; different detection stage scenario nodes include: preliminary detection stage scenario nodes, repeated detection stage scenario nodes, etc.; different warehousing stage scenario nodes include: initial storage stage scenario nodes, transfer storage stage scenario nodes, etc.; for example, components belonging to the production line scenario and the production initial stage scenario are classified into the production initial stage scenario nodes.

[0038] It is used to receive the components selected from the preset unit component library selected by the user to replace the components selected from the preset sub-component library selected by the user.

[0039] Using the above system, the sub-component library designed according to the tree structure and the unit component library designed according to the parallel structure enable each node to correspond to different scenario types, allowing users to further refine and select the required components according to specific manufacturing business requirements, achieving more refined customized configuration and meeting the needs of specific manufacturing operations.

[0040] Embodiment 3 Different from the above Embodiment 2, in order to achieve refined editing of the digital twin scenario selected by the user and meet the user's efficient editing requirements, the system further includes: The scenario editing module 202 is further configured to determine the belonging scenario type or belonging stage type for the digital twin scenario created based on the business object matched with the preset editing tool library selected by the user; for example, if the business object matched with the preset editing tool library is a medical device manufacturing business object, the production line digital twin scenario created based on this object is determined to belong to the production line scenario in terms of its belonging scenario type. It is also used to screen out the editing tools that match the corresponding scenario type or stage type from the provided preset editing tool library according to the determined scenario type or stage type to which it belongs, and lock the remaining editing tools in the preset editing tool library; wherein, the editing tools stored in the preset editing tool library are all pre-associated with the preset scenario type or stage type according to the functional attributes of the editing tools; for example, screen out the editing tools that match the production line scenario from the preset library, such as basic editing tools like rotation, scaling, and moving, and lock the editing tools related to production detection scenarios such as collision detection.

[0041] In addition to avoiding the user getting lost among a large number of tools and reducing misoperations by locking the editing tools irrelevant to the current scenario, it can also perform an orderly management of multiple digital twin scenarios to be edited, and pre-screen and lock the editing tools for each digital twin scenario to be edited in advance, further improving the editing efficiency of the digital twin scenario; specifically, the system further includes: The scenario editing module 202 is further used to provide an editing sequence management for the digital twin scenario, arrange the digital twin scenarios created based on the business objects matched with the preset editing tool library selected by the user in the order of selection; according to the arranged order, pre-determine the scenario type or stage type to which each selected digital twin scenario belongs; monitor the operation process of editing the selected digital twin scenario, and when it is detected that the operation process of editing has been completed, screen out the editing tools that match the scenario type or stage type of the next order from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library.

[0042] In addition, it is also used to allow the user to adjust the selected arrangement order according to the needs. Considering that there is often a time sequence arrangement for different stages in some scenarios, after completing the editing of the digital twin scenario corresponding to one stage type, the next step will be to complete the editing of the digital twin scenario corresponding to the next stage type in sequence according to the stage implementation order; therefore, the scenario editing module 202 is also used to, when the sequence arrangement corresponding to the digital twin scenario created based on the business object selected by the user and matched with the preset editing tool library is not obtained, according to the stage type to which the current digital twin scenario to be edited belongs, combined with the different stage types corresponding to the scenario type to which the current digital twin scenario to be edited belongs, use the next order stage type as the stage type to which the next digital twin scenario to be edited belongs, and thus pre-complete the setting of the next order editing tool.

[0043] Embodiment 4 The difference from the above Embodiment 2 is that in order to realize the multi-level and precise processing and classification of the business data of the actual manufacturing business object, and ensure the high synchronization and precise binding between the business data and the digital twin scenario, the system further includes: The data linkage module 303 is further configured to preprocess the service data of the obtained actual manufacturing service object, and input the preprocessed service data into the first neural network corresponding to the manufacturing service object to correspondingly obtain the scenario type to which the preprocessed service data belongs; wherein, the preprocessing includes data cleaning, data compensation, etc.; the first neural network is stored in the first neural network database, and the first neural network database includes multiple first neural networks, and each first neural network is trained and generated by the service data of a manufacturing service object with a historically marked scenario type.

[0044] Perform clustering processing on the service data according to the scenario type to which the obtained preprocessed service data belongs. According to each determined scenario type, synchronously associate and bind the service data of the corresponding scenario type with the digital twin scenario that is created based on the same manufacturing service object and belongs to a scenario type, so as to realize the classification and data association binding of the service data under a specific service object and a specific digital twin scenario, and reduce the service data synchronization error for driving the digital twin scenario.

[0045] On the basis of the classification of the service data under a specific service object and a specific digital twin scenario, further complete the classification and data association binding of the service data at a specific stage under a specific service object and a specific digital twin scenario. The data linkage module 303 is further configured to, for each group of the clustered service data, input each group of service data into the second neural network corresponding to the manufacturing service object and the corresponding scenario type to correspondingly obtain the stage type to which each group of service data belongs; wherein, the second neural network database includes multiple second neural networks, and each second neural network is trained and generated by the service data of a manufacturing service object with a historically marked stage type under a scenario type.

[0046] Perform clustering processing on each group of service data according to the stage type to which each group of obtained service data belongs; according to each determined stage type, synchronously associate and bind the service data of the corresponding stage type with the digital twin scenario that is established based on the same manufacturing service object and belongs to a stage type.

[0047] Embodiment 5 Different from the above Embodiment 2, in order to further enable the user to more intuitively understand the specific information in the digital twin scenario from the designed dashboard and better manage and optimize the manufacturing business process, the system further includes: The dashboard design module 404 is further configured to generate a dashboard corresponding to a sub-component according to the information type combinations included in different components in different preset sub-component libraries.

[0048] Considering the information overlap among the dashboards generated based on the preset component library and the corresponding preset sub-component library, the design method of the associated dashboard can be further adopted; that is, the dashboard design module is also used to integrate the information of the sub-components belonging to the same preset sub-component library in the dashboards of the corresponding components generated according to the information type combinations of different components in different preset component libraries, and link them to the dashboards of the sub-components generated by the same preset sub-component library in the form of links, so as to directly jump to view.

[0049] As Figure 2 shown, this embodiment provides a digital twin model generation method applying the system described in any one of the above embodiments, and the specific steps include: S1. Obtain the target manufacturing business object required by the user, and display the preset component library matching the corresponding manufacturing business object.

[0050] S2. Receive the components selected by the user from the corresponding matching preset component library, and match the corresponding component dashboards according to the components selected by the user.

[0051] S3. Create a digital twin scenario according to the components selected by the user and the corresponding matching component dashboards.

[0052] S4. Obtain the target manufacturing business object required by the user, and display the preset editing tool library matching the corresponding manufacturing business object.

[0053] S5. Receive the editing tool selected by the user from the corresponding preset editing tool library, and perform editing processing on the digital twin scenario created for the business object matching the preset editing tool library selected by the user according to the editing tool selected by the user.

[0054] S6. Synchronously associate and bind the business data of the actual manufacturing business object with the digital twin scenario established based on the same manufacturing business object.

[0055] In a specific embodiment, the step S2 further includes: When receiving the preset component library selected by the user, provide several preset sub-component libraries belonging to the preset component library; receive the components selected from the preset sub-component libraries selected by the user to replace the components selected by the user from the selected preset component library.

[0056] In a specific embodiment, the step S2 further includes: When receiving the preset sub-component library selected by the user, provide several preset unit component libraries belonging to the preset sub-component library; receive the components selected from the preset unit component libraries selected by the user to replace the components selected by the user from the selected preset sub-component library.

[0057] In a specific embodiment, the step S5 further includes: Determine the scenario type or stage type to which the digital twin scenario created for the business object matching the preset editing tool library selected by the user belongs; according to the determined scenario type or stage type, screen out the editing tools that match the corresponding scenario type or stage type from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library.

[0058] A specific embodiment, the step S5 further includes: Provide the editing order management of the digital twin scenario, and arrange the digital twin scenarios created for the business object matching the preset editing tool library selected by the user in the selected time order; according to the arrangement order, pre-determine the scenario type or stage type to which each selected digital twin scenario belongs; monitor the operation process of the editing process of the digital twin scenario selected by the user, and when it is monitored that the operation process of the editing process has been completed, screen out the editing tools that match the scenario type or stage type of the next order from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library.

[0059] A specific embodiment, the step S6 specifically includes: Preprocess the business data of the obtained actual manufacturing business object, and input the preprocessed business data into the first neural network of the corresponding manufacturing business object to obtain the scenario type to which the preprocessed business data belongs; perform clustering processing on the business data according to the scenario type to which the obtained preprocessed business data belongs, and according to each determined scenario type, synchronously associate and bind the business data of the corresponding scenario type with the digital twin scenario created based on the same manufacturing business object and belonging to one scenario type; for each group of business data after clustering processing, input each group of business data into the second neural network of the corresponding manufacturing business object and the corresponding scenario type to obtain the stage type to which each group of business data belongs; perform clustering processing on each group of business data according to the stage type to which each group of business data belongs; according to each determined stage type, synchronously associate and bind the business data of the corresponding stage type with the digital twin scenario established based on the same manufacturing business object and belonging to one stage type.

[0060] The embodiment of the present application also discloses a computer-readable storage medium.

[0061] Specifically, this computer-readable storage medium stores a computer program that can be loaded and executed by a processor, such as the digital twin model generation method described above. This computer-readable storage medium includes, for example: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0062] The embodiment of the present application also discloses a computer device.

[0063] 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 model generation method is stored on the memory.

[0064] The above are all preferred embodiments of the present application. Without limiting 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 in a series of equivalent or similar features.

Claims

1. A digital twin development system, characterized in that, Including: A scenario design module, a scenario editing module, a data linkage module, and a dashboard design module; The scenario design module is used to provide a preset component library that matches different manufacturing business objects; Each preset component library stores components associated with the manufacturing business object that matches it, including: a personnel model, a device model, a material model, a process flow model, and an environment model that have an associated relationship with the manufacturing business knowledge graph of the manufacturing business object that matches the preset component library; receives components selected by the user from the corresponding preset component library according to the manufacturing business requirements, and matches the corresponding component dashboard from the dashboard design module according to the components selected by the user; creates a digital twin scenario according to the components selected by the user and the corresponding component dashboard; The scenario editing module is used to provide a preset editing tool library that matches different manufacturing business objects. Each preset editing tool library stores editing tools associated with the manufacturing business object that matches it, including: editing tools applied to components in the same preset component library as the business object that matches the preset editing tool library; receives and, according to the editing tool selected by the user from the selected preset editing tool library, performs editing processing on the digital twin scenario created by the user for the business object that matches the preset editing tool library; The data linkage module is used to synchronously associate and bind the business data of the actual manufacturing business object with the digital twin scenario established based on the same manufacturing business object; The dashboard design module is used to generate the dashboard for the corresponding component according to the information type combination included in different components in different preset component libraries.

2. The digital twin development system according to claim 1, wherein The scenario design module is further used to provide a number of preset sub-component libraries belonging to the selected preset component library when receiving the preset component library selected by the user; each preset component library has a number of preset sub-component libraries; each preset component library divides the stored personnel model, device model, material model, process flow model, and environment model into the corresponding nodes according to the scenario type corresponding to the nodes in the tree structure of the preset component library; the nodes in the tree structure of each preset component library include: a production overview scenario node as the root node, a production line scenario node, a production quality inspection scenario node, and a warehousing scenario node as the leaf nodes; each preset sub-component library stores the personnel model, device model, material model, process flow model, and environment model belonging to the corresponding node; receives the components selected by the user from the selected preset sub-component library to replace the components selected by the user from the selected preset component library.

3. The digital twin development system according to claim 2, characterized in that, The described scenario design module is further configured to provide a number of preset unit component libraries belonging to a preset sub-component library when receiving a preset sub-component library selected by the user; each preset sub-component library is provided with a number of preset unit component libraries; each preset sub-component library divides the stored personnel model, equipment model, material model, process flow model, and environment model into the corresponding nodes according to the node corresponding stage types in the parallel structure of the preset sub-component library; the nodes in the parallel structure of each preset sub-component library include: different production stage scenario nodes in the production line scenario, different detection stage scenario nodes in the production quality inspection scenario, and different warehousing stage scenario nodes in the warehousing scenario; each preset unit component library stores the personnel model, equipment model, material model, process flow model, and environment model corresponding to the corresponding nodes; receive the components selected in the preset unit component library selected by the user to replace the components selected in the preset sub-component library selected by the user.

4. The digital twin development system according to claim 3, characterized in that The described scenario editing module is further configured to determine the belonging scenario type or belonging stage type for the digital twin scenario created based on the business object matched with the preset editing tool library selected by the user; according to the determined belonging scenario type or belonging stage type, screen out the editing tools that match the corresponding scenario type or stage type from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library; among them, the editing tools stored in the preset editing tool library are all pre-associated with the preset scenario type or stage type according to the functional attributes of the editing tools.

5. The digital twin development system according to claim 4, wherein The described scenario editing module is further configured to provide the editing order management of the digital twin scenario, and arrange the digital twin scenarios created based on the business object matched with the preset editing tool library selected by the user in the selected time sequence; According to the arrangement order, pre-determine the belonging scenario type or belonging stage type of each selected digital twin scenario; monitor the operation process of editing and processing the digital twin scenario selected by the user, and when it is detected that the operation process of editing and processing has been completed, screen out the editing tools that match the belonging scenario type or stage type of the next order from the provided preset editing tool library, and lock the remaining editing tools in the preset editing tool library.

6. The digital twin development system according to claim 3, wherein The described data linkage module is used to preprocess the business data of the obtained actual manufacturing business object, and input the preprocessed business data into the first neural network corresponding to the manufacturing business object to obtain the belonging scenario type of the preprocessed business data; Perform clustering processing on the business data according to the belonging scenario type of the obtained preprocessed business data, and synchronously associate and bind the business data of the corresponding scenario type with the digital twin scenario created based on the same manufacturing business object and belonging to one scenario type; among them, the first neural network database includes a variety of first neural networks, and each first neural network is trained by the business data of a manufacturing business object with a historically marked scenario type. For multiple groups of service data after clustering processing, each group of service data is respectively input into a second neural network corresponding to the manufacturing service object and the corresponding scenario type, and the stage type to which each group of service data belongs is correspondingly obtained; clustering processing is performed on each group of service data according to the stage type to which each group of service data belongs; according to each determined stage type, the service data of the corresponding stage type is synchronously associated and bound with a digital twin scenario established based on the same manufacturing service object and belonging to one stage type; wherein, the second neural network database includes multiple second neural networks, and each second neural network is trained and generated by historical annotation of service data of one manufacturing service object of one stage type under one scenario type.

7. The digital twin development system according to claim 3, characterized in that, The kanban design module is further configured to generate a corresponding sub-component kanban according to the information type combination included in different components in different preset sub-component libraries.

8. A method for generating a digital twin model applying the system according to any one of claims 1 to 7, characterized in that, Including: Obtain the target manufacturing service object required by the user and display the preset component library matching the corresponding manufacturing service object; Receive the component selected by the user from the corresponding preset component library according to the manufacturing service requirement, match the corresponding component kanban according to the component selected by the user; create a digital twin scenario according to the component selected by the user and the corresponding matching component kanban; Obtain the target manufacturing service object required by the user and display the preset editing tool library matching the corresponding manufacturing service object; receive the editing tool selected by the user from the corresponding preset editing tool library, and perform editing processing on the digital twin scenario created by the user for the service object selected based on the matching of the preset editing tool library according to the editing tool selected by the user; Synchronously associate and bind the service data of the actual manufacturing service object with the digital twin scenario established based on the same manufacturing service object.

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 claim 8.

10. A computer device, characterized in that, 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 according to claim 8.

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