Methods and systems for joint development of workshop logistics systems based on Metaverse

Abstract

The present invention relates to the technical field of joint R&D of workshop logistics systems, and in particular to methods and systems for joint R&D of workshop logistics systems based on the Metaverse. The request information of logistics solution providers is obtained, a virtual joint R&D space is constructed and permissions are allocated, and the target users are allowed to generate encrypted digital requirement documents based on the requirements, which are converted into digital drawings for collaborative modeling, and then simulated and optimized using a digital twin model to finally achieve a digital delivery process. The present invention integrates multiple technologies of the Metaverse to enhance R&D immersion and collaboration, reduce the risk of technology leaks; comprehensively simulate and analyze the system to improve design rationality; adopt distributed joint dynamic simulation and encryption technology to improve simulation efficiency and data security; realize two-way digital delivery, enhance delivery capabilities, and innovate the R&D model of workshop logistics systems.

Description

Technical Field

[0001] The present invention relates to the technical field of joint research and development of workshop logistics systems, and in particular to a method and system for joint research and development of workshop logistics systems based on the metaverse. Background Art

[0002] With the rapid development of the manufacturing industry, the complexity and importance of workshop logistics systems have become increasingly prominent. However, traditional workshop logistics system development methods face many challenges, including:

[0003] ① High cost and low efficiency: Traditional R&D methods that rely on 2D drawings and on-site testing are not only time-consuming and labor-intensive, but also costly. Every design change requires re-creation of a physical model and on-site testing, which significantly prolongs the R&D cycle.

[0004] ② Information silos and collaboration difficulties: Workshop logistics systems involve multiple parties, including owners, logistics solution providers, equipment suppliers, and architectural design institutes. These parties often use different tools and platforms, leading to untimely and inaccurate information transfer, creating information silos and severely impacting the efficiency of collaborative R&D.

[0005] ③ Lack of comprehensive simulation and optimization: Existing simulation tools often focus on simulating a single piece of equipment or a specific process, lacking comprehensive coverage and dynamic interactive simulation of the entire workshop logistics system. This makes it difficult to fully evaluate system performance during the design phase, leading to numerous issues in actual operation, such as irrational equipment layout and suboptimal logistics routing.

[0006] ④Digital delivery and maintenance challenges: The traditional system delivery model lacks effective digital asset delivery and reverse feedback mechanisms, making it difficult to maintain and update the system, affecting the long-term stable operation of the system.

[0007] To solve the above problems and improve the R&D efficiency and quality of workshop logistics systems, an innovative R&D platform and method is urgently needed that can achieve efficient collaborative modeling, joint simulation and digital delivery among all parties while ensuring the security and consistency of information.

[0008] Furthermore, existing collaborative R&D technologies mostly use a two-dimensional web-based collaborative R&D model, which lacks user immersion and participation, resulting in poor collaborative effects. Furthermore, existing collaborative R&D work often involves the exchange of technical data and models, posing a risk of technology leaks.

[0009] In addition, existing digital twin-based simulation and optimization technologies mostly focus on the modeling and simulation of logistics production lines and equipment, lacking dynamic simulation and analysis of all factors in the workshop logistics system, including workers and factory buildings, making it difficult to accurately optimize logistics solutions.

[0010] In addition, existing logistics system modeling and simulation are mainly centralized by logistics solution providers, which leads to long modeling cycles, high computational overhead, and computational bottlenecks, resulting in low simulation efficiency.

[0011] In addition, existing technologies lack methods and means to seamlessly connect R&D to digital delivery, resulting in poor delivery capabilities. Summary of the Invention

[0012] In view of this, the purpose of the present invention is to provide a method and system for the joint development of workshop logistics systems based on the metaverse, so as to solve the technical problems in the existing technology such as poor immersion in the collaborative development of workshop logistics systems, insufficient simulation, long development cycle, poor technical confidentiality, and poor delivery capabilities.

[0013] According to a first aspect of an embodiment of the present invention, a method for joint development of a workshop logistics system based on a metaverse is provided, the method comprising:

[0014] Obtain the first request information of the preset logistics solution provider;

[0015] Using the first request information of the logistics solution provider, constructing a workshop logistics virtual joint R&D space, and using the workshop logistics virtual joint R&D space to allocate permissions to target users;

[0016] Obtain the second request information from the preset logistics solution provider, use the second request information from the logistics solution provider and the results of the target user's authority allocation in the workshop logistics virtual joint R&D space, require the relevant target users to participate in the docking requirements according to the digital human role, and use the preset large model to process the demand docking content, and generate a real-time updated digital demand document that is encrypted and stored in the Metaverse distributed data center;

[0017] Using a preset algorithm, the encrypted digital requirement document that is updated in real time and stored in the Metaverse distributed data center is converted into a digital drawing that is updated in real time and supports multiple interactive operations and reflects layout information;

[0018] By utilizing the real-time updated digital drawings that support multiple interactive operations and reflect layout information, collaborative modeling of a preset workshop logistics system is performed according to fields;

[0019] Using the results of the collaborative modeling of the preset workshop logistics system, the preset digital twin model is used to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation;

[0020] The results of simulating and optimizing the preset workshop logistics plan are used to realize digital delivery of the workshop logistics system.

[0021] Furthermore, the first request information of the logistics solution provider is used to construct a workshop logistics virtual joint R&D space, and the workshop logistics virtual joint R&D space is used to allocate permissions to target users, including:

[0022] Using the first request information of the logistics solution provider, using space modeling technology and virtual environment generation algorithm, constructing a virtual joint R&D space for workshop logistics;

[0023] By utilizing the results of constructing a virtual joint R&D space for workshop logistics, access rights are allocated according to the roles and responsibilities of different participants in the project based on the RBAC model and dynamic permission allocation strategy.

[0024] Furthermore, the method utilizes a preset algorithm to convert the encrypted digital requirement document stored in the Metaverse distributed data center, which is updated in real time, into a digital drawing that supports multiple interactive operations and reflects layout information, including:

[0025] Using pre-set system engineering analysis tools and logistics system planning algorithms, determine the interrelationships between the various functional areas of the pre-set workshop logistics system and the spatial layout principles, and generate pre-set workshop logistics system CAD drawings containing quantitative and qualitative information, precise dimensions, locations, and annotations;

[0026] The interactive function is developed by utilizing the principles of human-computer interaction and virtual reality interaction to convert the preset workshop logistics system CAD drawings containing quantitative and qualitative information, precise dimensions, positions and annotations into digital drawings that reflect workshop layout information and support multiple interactive operations.

[0027] Furthermore, the real-time updated digital drawings that support multiple interactive operations and reflect layout information are used to collaboratively model the preset workshop logistics system according to the field, including:

[0028] Using the real-time updated digital drawings that support multiple interactive operations and reflect layout information, virtual guidance elements are constructed in the workshop logistics virtual joint R&D space based on computer graphics and spatial positioning technology;

[0029] Utilizing the virtual guiding elements, a collaborative modeling assistance mode based on digital drawings is constructed;

[0030] Based on the collaborative modeling assistance mode of the digital drawings, each unit is used to concurrently build and upload digital twin models of their respective fields, and the digital twin models are arranged according to the virtual guiding elements;

[0031] The digital twin model is adjusted and optimized using a preset bounding box conflict detection algorithm to obtain the result of collaborative modeling of the preset workshop logistics system according to the field.

[0032] Furthermore, the construction process of the digital twin model includes:

[0033] Using 3D modeling software to create a 3D geometric model of the logistics unit, and using the 3D geometric model to accurately characterize the shape, size and appearance characteristics of the logistics unit;

[0034] Using the creation results of the three-dimensional geometric model, finite element simulation software is used to analyze the physical performance of the logistics unit under different working conditions and construct a physical dimension model;

[0035] Also, use algorithm simulation analysis software to model and analyze the logistics flow patterns, storage characteristics, and scheduling algorithms in the workshop logistics system to build a mechanism dimension model;

[0036] The data fusion algorithm is used to fuse models of different dimensions to obtain a digital twin model.

[0037] Furthermore, the digital twin model is adjusted and optimized using a preset bounding box conflict detection algorithm to obtain the results of collaborative modeling of the preset workshop logistics system according to the domain, including:

[0038] Compare the bounding box of each model in the actual scene layout with the bounding box in the preset scene layout information to determine whether there is a conflict in the model layout;

[0039] If a large positional or dimensional deviation is detected in the layout, the model location of the error will be prompted using voice and visual elements, and the error area and deviation value will be clearly marked on the digital drawing;

[0040] The model is adjusted through various interactive methods. After the adjustment is completed, the system performs layout detection again until it meets the requirements.

[0041] Furthermore, the method of utilizing the collaborative modeling results of the preset workshop logistics system and simulating and optimizing the preset workshop logistics plan by means of distributed joint dynamic simulation using the preset digital twin model includes:

[0042] Constructing a joint dynamic simulation task domain of a workshop logistics system; the joint dynamic simulation task domain of the workshop logistics system includes: a joint simulation domain and several sub-simulation domains;

[0043] The digital twin models of each sub-simulation domain dynamically adjust and calculate according to the received preset simulation data stream and the actual workshop logistics operation logic to obtain a first processing result;

[0044] Each sub-simulation domain receives data from other sub-simulation domains in real time, performs calculations and updates based on the data and its own model logic, and then feeds the generated new data back into the simulation data stream, which is then used by other sub-simulation domains to obtain a second processing result.

[0045] Utilizing the first and second processing results, executing a distributed computing model driven by simulation data streams, having the computing tasks of each sub-simulation domain performed by local hardware terminals of relevant units, utilizing edge computing capabilities and communication interfaces to achieve data interaction and collaboration, and utilizing blockchain technology combined with the elliptic curve cryptography algorithm (ECC) to encrypt various transmission data exchanged between the sub-simulation domains during the joint simulation of the workshop logistics system, thereby obtaining a third processing result;

[0046] Utilizing the third processing result, the simulation process and results are dynamically presented in real time in the joint R&D space through three-dimensional visualization technology. Each sub-simulation domain feeds back the results to the Metaverse platform in real time. The platform conducts comprehensive analysis and evaluation. If any anomalies are found, adjustment instructions are sent to the corresponding sub-simulation domain, prompting it to adjust model parameters or run logic before continuing the simulation, thereby accurately simulating and optimizing the logistics plan, thereby obtaining the fourth processing result.

[0047] The fourth processing result is used to prepare a simulation report and confirm the simulation results.

[0048] Furthermore, it also includes:

[0049] The joint simulation domain is the coupling of sub-simulation domains, which is expressed by the formula:

[0050] J= （1）

[0051] J represents the joint simulation domain; Represents a sub-simulation domain; each sub-simulation domain has its own specific task objectives. There is data flow between the sub-simulation domains, and they are carried out by different units, and the hardware terminals of the simulation calculations are set in different units respectively; each unit is responsible for the simulation tasks of the corresponding sub-simulation domain, and can also further subdivide the sub-simulation domain it is responsible for to meet the task requirements of its simulation domain.

[0052] Furthermore, the elliptic curve cryptography algorithm ECC is used to encrypt various transmission data exchanged between sub-simulation domains during the joint simulation of the workshop logistics system, including:

[0053] In the data encryption process, the elliptic curve encryption algorithm is used. For the simulation data to be transmitted, the joint simulation data encryption process is expressed as:

[0054] (2)

[0055] in is the public key, It is encrypted simulation data; only the recipient with the corresponding private key can decrypt the encrypted data, effectively preventing the data from being stolen or tampered with during transmission.

[0056] According to a second aspect of an embodiment of the present invention, a system for jointly developing a pre-set workshop logistics system based on a metaverse is provided, which is applied to any of the above-mentioned methods for jointly developing a pre-set workshop logistics system based on a metaverse, and the system includes:

[0057] An acquisition module, used to obtain the first request information of a preset logistics solution provider;

[0058] A first processing module is configured to use the first request information of the logistics solution provider to build a virtual joint R&D space for workshop logistics, and use the virtual joint R&D space for workshop logistics to allocate permissions to target users;

[0059] The second processing module is used to obtain the second request information of the preset logistics solution provider, use the second request information of the logistics solution provider and the results of the target user's authority allocation in the workshop logistics virtual joint R&D space, and require the relevant target users to participate in the docking requirements according to the digital human role, and use the preset large model to process the docking requirements content, and generate a real-time updated digital requirement document that is encrypted and stored in the Metaverse distributed data center;

[0060] A third processing module is configured to convert the encrypted digital requirement document stored in the Metaverse distributed data center, which is updated in real time, into a digital drawing that supports multiple interactive operations and reflects layout information, which is updated in real time, using a preset algorithm;

[0061] A fourth processing module is configured to collaboratively model a preset workshop logistics system according to fields using the real-time updated digital drawings that support multiple interactive operations and reflect layout information;

[0062] a fifth processing module, configured to utilize the collaborative modeling results of the preset workshop logistics system and utilize the preset digital twin model to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation;

[0063] The sixth processing module is used to realize digital delivery of the workshop logistics system by utilizing the results of simulating and optimizing the preset workshop logistics plan.

[0064] The technical solutions provided by the embodiments of the present invention may have the following beneficial effects:

[0065] ① By integrating metaverse virtual space management, rights management, XR, digital twins, digital humans, human-computer interaction and other technologies, and using auxiliary tools such as digital drawings and virtual guidance elements, the immersiveness of workshop logistics system R&D work is enhanced, promoting close collaboration among all parties, while effectively reducing the risk of technology leaks;

[0066] ②By introducing plant structure simulation and personnel operation simulation in the operation of the logistics system, a comprehensive simulation analysis of the workshop logistics system solution is carried out to further improve the scientificity and rationality of the system design;

[0067] ③ By adopting distributed joint dynamic simulation and blockchain data encryption technology, and utilizing the simulation domain allocation mechanism, cross-regional and cross-domain distributed computing and simulation can be achieved, reducing computing overhead and costs, improving R&D efficiency, and ensuring data security;

[0068] ④ By collaboratively developing and deploying the workshop logistics digital twin system, and establishing a joint R&D platform for the workshop logistics system and a data transmission mechanism for the workshop logistics digital twin system, the forward and reverse digital delivery of the workshop logistics system can be achieved, effectively improving the delivery capability of the workshop logistics system.

[0069] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0071] Figure 1 is a schematic diagram of steps of a method for joint development of a workshop logistics system based on Metaverse according to an exemplary embodiment;

[0072] Figure 2 is a schematic diagram of the implementation process steps of the joint development of a workshop logistics system based on the Metaverse according to an exemplary embodiment;

[0073] Figure 3 It is a schematic diagram of the system composition of the joint development of a workshop logistics system based on the metaverse according to an exemplary embodiment. DETAILED DESCRIPTION

[0074] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0075] Example 1

[0076] See also Figure 1 , Figure 1 1 is a schematic diagram of steps of a method for joint development of a workshop logistics system based on a metaverse according to an exemplary embodiment, the method comprising:

[0077] S1. Get the first request information of the preset logistics solution provider;

[0078] S2. Using the first request information of the logistics solution provider, constructing a virtual joint research and development space for workshop logistics, and using the virtual joint research and development space for workshop logistics to allocate permissions to target users;

[0079] S3. Obtain the second request information from the pre-set logistics solution provider. Utilize the second request information from the logistics solution provider and the results of the target user's authority allocation in the workshop logistics virtual joint R&D space. Instruct the relevant target users to participate in the docking requirements according to their digital human roles. Use the pre-set large model to process the docking requirements content, generating a real-time updated digital requirements document encrypted and stored in the Metaverse distributed data center.

[0080] S4 uses a preset algorithm to convert the encrypted digital demand document stored in the Metaverse distributed data center into a real-time updated digital drawing that supports multiple interactive operations and reflects the layout information;

[0081] S5. Using the real-time updated digital drawings that support multiple interactive operations and reflect layout information, collaborative modeling of the preset workshop logistics system is performed according to the field;

[0082] S6. Using the results of the collaborative modeling of the preset workshop logistics system, the preset digital twin model is used to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation;

[0083] S7. Utilize the results of the simulation and optimization of the preset workshop logistics plan to achieve digital delivery of the workshop logistics system.

[0084] In specific implementation, the joint R&D method of workshop logistics based on the Metaverse is based on a preset platform, initiated by logistics solution providers, and jointly participated by owners, equipment suppliers, architectural design institutes and other units. It can realize the docking of workshop logistics system needs, digital drawing creation, collaborative modeling, joint simulation and digital delivery.

[0085] In specific implementation, the preset platform architecture includes:

[0086] Basic resource layer, data management layer, core function layer, and application service layer.

[0087] L1: Basic resource layer

[0088] This layer includes edge servers, professional software (modeling, simulation, management, and monitoring), network communication facilities, interactive terminal equipment (XR\PC\mobile), and workshop data collection devices, etc., which provide software and hardware resources.

[0089] L2: Data management layer

[0090] This layer includes data management related modules or components such as data interface, data bus, data processing algorithm, data encryption algorithm, distributed database, etc., providing data management functions for platform operation.

[0091] L3: Core Function Layer

[0092] The core functional layer includes virtual space construction management module, model management module, distributed simulation module, and collaborative communication and collaboration module.

[0093] 1) Virtual space management module

[0094] The virtual space management module supports the use of 3D modeling and virtual reality technology to create virtual joint R&D spaces, and supports obtaining models and data from the basic resource layer to present scene elements such as warehouses, equipment, materials, and operators, and provides scene editing tools.

[0095] 2) Model management module

[0096] It supports the construction, uploading, combination, inspection and modification of workshop logistics digital twin related models, as well as the creation of user digital human characters, giving them appearance, movements and behavioral logic, and realizing natural movement simulation with the help of motion capture or preset animation.

[0097] 3) Rights Management Module

[0098] Supports permission management based on user access permission allocation, user identity authentication, role, model, data access permission setting, etc.

[0099] 4) Distributed simulation module

[0100] This module generates data flow-driven model operations based on logistics plans, coordinates local hardware terminals of all parties to perform computing tasks, and combines blockchain encryption and intelligent scheduling algorithms to ensure data security and improve simulation efficiency.

[0101] 5) Communication and collaboration module

[0102] The communication and collaboration module offers multiple communication methods, including text chat, voice calls, video conferencing, and virtual meetings, allowing users to quickly exchange information and discuss issues in depth. It also features file sharing and collaborative editing, supports users uploading and downloading project materials, and provides a collaborative data interaction interface, enabling multi-user collaboration in workshop logistics system modeling, simulation, and delivery.

[0103] L4: Platform service layer

[0104] The platform service layer mainly includes intelligent assistance services, collaborative modeling services, joint simulation services, and digital delivery services.

[0105] 1) Intelligent assistance services

[0106] Based on intelligent algorithms such as large language models, systems engineering analysis algorithms, logistics planning algorithms, and spatial detection and positioning algorithms, this system is used to provide intelligent support for joint R&D work. The large language model assists with demand analysis and meeting recording, while systems engineering analysis tools and logistics planning algorithms facilitate functional analysis and solution design for workshop logistics systems. Spatial detection algorithms ensure the rationality of model layout, providing intelligent decision-making support for R&D work.

[0107] 2) Collaborative modeling service

[0108] CAD drawing and human-computer interaction technology are used to create digital drawings of the workshop logistics system that contain detailed quantitative and qualitative information. Rich interactive operation functions such as zooming, panning, and click-to-query are also provided to facilitate viewing and use by all parties. The impact of demand changes on drawings and plans can be effectively managed, laying a solid foundation for subsequent R&D work.

[0109] 3) Joint simulation service

[0110] A simulation launch and monitoring interface is provided, allowing users to set simulation parameters and initiate joint simulations, displaying the operating status and key data of sub-simulation domains in real time. Results analysis and evaluation capabilities are provided, generating statistical charts and reports that visually display changes in indicators such as logistics efficiency and equipment utilization, providing a basis for optimizing logistics solutions. Metaverse access rights and various interactive functions are provided to clients, allowing them to easily confirm whether the solution meets their needs.

[0111] 4) Digital delivery services

[0112] Supports digital asset packaging, digital twin system development, deployment and update, and data reverse delivery.

[0113] Specifically, as described in steps S1-S2, during the specific implementation, the steps include:

[0114] Obtain the first request information of the preset logistics solution provider, use the request information to create a virtual joint R&D space for workshop logistics in the Metaverse joint R&D platform, and assign access rights, including access and use rights to the space for owners, logistics solution providers, equipment suppliers, architectural design institutes and other units, and support entering the space area with a digital human character through an interactive terminal to participate in workshop logistics joint R&D related work.

[0115] S2-1: Creation of Virtual Joint R&D Space

[0116] See also Figure 2 A logistics solutions provider has leveraged spatial modeling technology and virtual environment generation algorithms to construct a virtual joint R&D space for workshop logistics. This space accurately simulates the digital ecosystem of a real-world workshop logistics environment, encompassing every aspect, including the warehouse's architectural structure, the layout of logistics equipment, and the storage and flow of goods. Furthermore, the space features a virtual conference room, providing a venue for R&D participants to meet and communicate. Personnel from the client, logistics solutions provider, equipment supplier, architectural design institute, and other organizations can enter the space as digital human characters using interactive terminals (such as VR, AR, and PC devices).

[0117] S2-2: Create and assign access rights to a virtual joint R&D space

[0118] Once the virtual joint R&D space is created, the logistics solution provider assigns access rights based on the project roles and responsibilities of different stakeholders using the RBAC model and dynamic permission allocation strategy. Each user entering the virtual joint R&D space must undergo a rigorous identity authentication process. This authentication utilizes multi-factor authentication technology, combining user account and password, biometrics, and dynamic verification codes to ensure that only authorized users can access the system. Once authentication is successful, the system automatically assigns appropriate access rights based on the user's organization and role.

[0119] The above-mentioned user permissions include general permissions and non-general permissions. General permissions include virtual space roaming permissions, digital human role management permissions, communication and collaboration permissions, etc., so that users can achieve immersive visual interaction and collaboration in the platform. In addition to general permissions, corresponding non-general permissions are set for users of different units to reduce the risk of technology leakage in joint R&D. Among the non-general permissions, the owner has the operator simulation permission so that they can have an in-depth understanding of the actual performance of manual operation links in the system; the logistics solution provider, as the organizer and coordinator of the project, has multiple key permissions such as space development, scheme design, and task allocation, and can control the overall direction and progress of the project from a macro perspective; the civil engineering design institute and equipment supplier focus on the key permissions for the research and development of sub-fields related to plants and equipment, respectively, including product design modeling, model layout and simulation optimization in their respective fields.

[0120] In the specific implementation, as described in step S3, it includes: docking and management of workshop logistics system R&D requirements, specifically including the following implementation steps:

[0121] S3-1: Demand Matching

[0122] After completing the creation and assigning permissions for the virtual joint R&D space, the logistics solution provider invites the client, architectural design institute, equipment supplier, and other entities to conduct a needs matching session. To improve efficiency and reduce costs, this matching session can be conducted in the joint R&D space's virtual conference room. Individual entities can select personnel to discuss the meeting using digital human avatars to fully understand the client's requirements for the workshop logistics system and the design resource needs of the logistics solution provider, architectural design institute, and equipment supplier.

[0123] S3-2: Demand Management

[0124] The big model is used to record requirements matching meetings and refine the content, creating structured, visual digital requirements documents. These documents are stored in the Metaverse distributed data center and encrypted using blockchain technology to prevent tampering. When requirements change, multiple parties must reconvene to discuss them. Once consensus is reached, the requirements document is updated and broadcasted to relevant parties via mobile phones and computers via the Metaverse platform, ensuring that all participants are kept up to date. Furthermore, these changed requirements are stored in a version management repository for subsequent review and tracing.

[0125] In specific implementation, as described in step S4, it includes:

[0126] Workshop logistics system digital drawing creation process:

[0127] After gathering the needs of all parties, logistics solution providers need to translate these requirements into specific, interactive digital blueprints of the workshop logistics system solution. Creating digital blueprints relies on a fusion of logistics planning knowledge, CAD drawing, human-computer interaction, and virtual reality technology. If the owner's needs change, the digital blueprints must be updated promptly to ensure consistency with the latest system solution, while also archiving historical versions. Creating digital blueprints for the workshop logistics system primarily involves the following steps:

[0128] S4-1: System Overall Design

[0129] Solution providers need to use system engineering analysis tools and logistics system planning algorithms to conduct functional decomposition and process analysis of the workshop logistics system, and determine the relationships and spatial layout principles of the functional areas of the workshop logistics system (such as storage areas, sorting areas, loading and unloading areas, etc.).

[0130] S4-2: CAD drawing of the scheme

[0131] Based on these analysis results, CAD drawings of the workshop logistics system with precise dimensions, positions, and annotations are created using CAD and other software, including quantitative information (such as total output, production efficiency, cargo storage capacity, number of equipment, energy consumption, etc.) and qualitative information (such as work process priority, space utilization preference, etc.) in the requirements.

[0132] S4-3: Drawings can be interactively empowered

[0133] After completing the digital drawings, the logistics solution provider will upload them to the joint R&D space and develop interactive functions through human-computer interaction technology and virtual reality interaction principles to convert CAD drawings into digital drawings that meet interactive needs. This allows them to reflect information such as workshop layout and process procedures, and support interactive operations such as interface retrieval, hiding, zooming in, zooming out, panning, rotating, clicking, alarming, and transparency adjustment.

[0134] In the specific implementation, as described in step S5, it includes: the processing process of collaborative modeling of the workshop logistics system. Specifically, after the digital drawings are created, the workshop logistics system is collaboratively modeled by field to improve modeling efficiency, while reducing the mutual transmission of models between units to prevent technology leaks.

[0135] S5-1: Constructing virtual guidance elements for collaborative modeling of workshop logistics

[0136] Logistics solution providers use computer graphics and spatial positioning technology to build virtual guidance elements in the joint R&D space, providing intuitive and accurate reference for the subsequent layout of the workshop digital twin model.

[0137] Virtual guidance elements include various types of visualization elements, such as three-dimensional dimension lines, reference planes, center points, dimension data, installation surfaces, three-dimensional scene names, and layout description boxes. Among them, three-dimensional dimension lines accurately draw line segments in three-dimensional space and mark the corresponding length, angle and other dimension information to intuitively display the spatial distance and positional relationship between various components; the reference plane serves as a fixed reference plane to provide a benchmark for the placement and alignment of the model; the center point is used to identify the center coordinates of key positions or components to facilitate positioning during the layout process; the dimension data records the specific dimensional parameters of each part in detail to ensure that the size of the model is consistent with the design requirements; the installation surface clarifies the installation position and direction of the equipment or components; the three-dimensional scene name and layout description box provide a text description of the entire scene and layout. Among them, the layout description box includes not only the layout description of the three-dimensional scene, but also the data interface specifications and model storage location.

[0138] S5-2: Develop collaborative modeling assistance functions based on digital drawings

[0139] In order to quickly realize the construction of digital twin scenarios for workshop logistics, collaborative modeling auxiliary functions based on digital drawings are developed, including operation interaction, positioning transmission and alarm prompts.

[0140] ① Operation interaction

[0141] Develop interactive digital blueprint manipulation features, allowing users to interact with digital blueprints in a variety of ways. Users can zoom in, zoom out, and rotate digital blueprints using specific gestures (such as pinching, stretching, and rotating). This allows for clearer review of workshop logistics plan details and precise guidance for modeling workshop logistics systems. When users need to view detailed dimensions and installation requirements for a piece of equipment, they can zoom in on the corresponding area on the digital blueprint using gestures to obtain the required information.

[0142] ② Positioning transmission

[0143] Based on spatial positioning algorithms and associating three-dimensional spatial positions with two-dimensional coordinate information, we have developed real-time positioning and location transfer functions for digital drawings. The real-time positioning function allows users to mark and locate their current location on a digital drawing in real time. By tracking the user's location information in the metaverse and matching it with the coordinate system in the digital drawing, precise positioning is achieved, helping users quickly confirm their location. Furthermore, digital drawings also support location transfer. When a user clicks on any point on the digital drawing, the system will quickly transfer the user to the corresponding virtual scene location based on the coordinate information of that point, improving the user's browsing efficiency.

[0144] ③Alarm prompt

[0145] Develop an alarm alert feature. When the layout of the workshop logistics system model does not meet the design requirements, the digital drawings will display an alarm at the corresponding location. This feature is based on pre-set layout rules and constraints. By comparing the actual layout with the design requirements, an alarm is automatically triggered when deviations exceed the allowable range. Alarms can use eye-catching color markings, flashing effects, or sound prompts to attract users' attention, allowing them to promptly identify and resolve layout issues.

[0146] S5-3: Concurrently constructing a digital twin model of the workshop logistics system

[0147] Each unit concurrently builds and uploads digital twin models of their respective areas within the workshop logistics system, and accurately arranges the models based on virtual guidance elements. Furthermore, each unit can set permissions to prohibit downloading, measuring, and disassembling models involving technical confidentiality, thereby maximizing the protection of the company's relevant technologies.

[0148] Logistics solution providers are responsible for building the logistics digital twin model. During the construction process, they first use 3D modeling software to create a 3D geometric model of the logistics unit, accurately depicting its shape, size, and appearance. Then, using finite element simulation software, they analyze the physical properties of the logistics unit under different operating conditions, such as stress deformation and stability, to construct a physical dimensional model. Simultaneously, algorithmic simulation and analysis software is used to model and analyze the logistics flow patterns, storage characteristics, and scheduling algorithms within the workshop logistics system, constructing a mechanism dimensional model. Finally, by configuring specific data or software interfaces, they use data fusion algorithms to fuse the models of different dimensions to form a complete logistics digital twin model.

[0149] The Architectural Design Institute was responsible for constructing a digital twin model of the logistics plant's civil engineering structure. Based on the architectural design drawings and relevant specifications, professional architectural modeling software was used to create a 3D geometric model of the plant, including details such as the building's exterior, interior structure, walls, doors, and windows. Finite element analysis software was used to analyze the plant's mechanical properties, such as structural strength and seismic resistance, to construct a physical dimensional model. Furthermore, simulation software was used to construct a mechanistic dimensional model, taking into account the plant's thermal and ventilation performance under various environmental conditions. Similarly, these models were integrated through data interfaces and fusion algorithms to produce a digital twin model that accurately reflects the plant's civil engineering structure.

[0150] Equipment suppliers are responsible for building digital twin models of their equipment. First, they use 3D modeling software to create a geometric model of the equipment based on the equipment's design drawings and technical specifications, ensuring that the model closely matches the actual equipment in appearance and structure. Then, using performance data and simulation software provided by the equipment manufacturer, they simulate and analyze the equipment's operating principles and performance, building models in both physical and mechanical dimensions. Data fusion technology is used to integrate these dimensional models into a digital twin model of the equipment.

[0151] The owner needs to create a digital twin model of the workers, support data-driven models collected from XR devices, motion capture, smart bracelets, cameras and other devices, support human motion simulation and heart rate collection in work scenarios such as manual picking and manual loading and unloading, and comprehensively evaluate the work efficiency, intensity and other effects of workers in the logistics plan.

[0152] After initially constructing the digital twin models for each domain, preliminary simulations are conducted on each domain model to check for internal interference, whether the structural design meets performance requirements, and whether operating patterns meet expectations. For example, for equipment digital twin models, individual simulations can simulate the startup, operation, and shutdown processes of the equipment, checking for collisions and interference between components and ensuring that operating parameters are within normal ranges.

[0153] After the initial simulation meets the requirements, each unit will upload the digital twin model of their respective domain to the joint R&D space and store it in the Metaverse distributed database according to the system prompts. At the same time, each unit will set access rights to the digital twin model and open the model's data interface.

[0154] S5-4: Workshop logistics system model layout inspection and adjustment

[0155] During the construction of the workshop logistics system model, the bounding box conflict detection algorithm is used to detect whether the three-dimensional model layout of the factory building and equipment is correct by comparing the actual scene layout with the preset scene layout information, and the model is adjusted and optimized.

[0156] When there are large positional and dimensional deviations in the layout of a plant or equipment model, the system will promptly use voice and visual elements to prompt the model location where the error is located. At the same time, the digital drawing will clearly indicate the area where the error exists and the deviation value, allowing users to quickly locate the problem. When there are deviations in the model layout, users can adjust the model through a variety of interactive methods. Gesture operations allow users to perform model editing operations such as stretching, scaling, translating, and rotating the model through natural hand movements; voice operations allow users to adjust the model by speaking commands; the UI click method provides an intuitive operation interface, and users can complete model adjustments by clicking buttons on the interface or entering specific parameters.

[0157] Once adjustments are complete, the system will perform another layout check. If the results meet the requirements, the adjustment is complete, and the digital drawings will no longer indicate errors. Furthermore, different units can collaborate on layout adjustments within the virtual joint R&D space, achieving collaborative layout optimization. Finally, each unit broadcasts its adjustments within the Metaverse.

[0158] In specific implementation, as described in step S6, it includes: the processing process of joint simulation of the workshop logistics system. Specifically, after the workshop logistics digital twin model is built, in order to verify whether the workshop logistics plan meets the design requirements and reduce redundant design and under-design, it is necessary to simulate and optimize the workshop logistics plan based on the digital twin model. In order to reduce the computational overhead of simulating complex workshop logistics systems and improve simulation efficiency, the present invention adopts a distributed joint dynamic simulation method. The specific process is as follows:

[0159] S6-1: Simulation Task Domain Division

[0160] The joint dynamic simulation task domain of the entire workshop logistics system can be divided into one joint simulation domain and several sub-simulation domains. The sub-simulation domains include logistics dynamic simulation domain, equipment dynamic simulation domain, plant structure dynamic simulation domain, manual operation simulation domain, etc. The joint simulation domain J is a sub-simulation domain. The coupling is expressed as:

[0161] J= (1)

[0162] Each sub-domain has its own specific mission objectives. Data flows between sub-domains, each of which is managed by a different unit. The hardware terminals for simulation calculations are located in different units. Each unit is responsible for the simulation tasks of its corresponding sub-domain and can further subdivide the sub-domain to meet the mission requirements of its simulation domain.

[0163] The dynamic logistics simulation domain focuses on the flow of goods within a shop floor logistics system, including warehousing, storage, sorting, and outbound delivery. This domain considers factors such as the type, quantity, and flow rate of goods, as well as the flow logic between different goods, to simulate the dynamic flow of goods within the system and the logistics scheduling algorithms.

[0164] The equipment dynamics simulation domain focuses on the operating status and performance of various logistics equipment, such as forklifts, conveyors, and automated sorting equipment. Within this sub-domain, the equipment's startup, operation, and shutdown processes are meticulously simulated, analyzing performance indicators such as operating efficiency, energy consumption, and failure probability.

[0165] The plant structure dynamic simulation domain focuses on studying the mechanical properties and stability of logistics plant civil structures under different operating conditions. This domain analyzes the structural stress distribution, deformation, and seismic performance of the plant under external forces such as cargo loading, equipment vibration, and natural disasters, ensuring the safety and reliability of the plant structure.

[0166] The manual operation simulation domain emphasizes the role of human factors in workshop logistics operations. By having the owner select actual workers to wear XR equipment to enter the metaverse space for simulated interaction, it simulates manual operation links such as manual picking of goods and manual forklift operation, taking into account the impact of factors such as personnel's operating habits, fatigue level, and work efficiency fluctuations on the entire workshop logistics system.

[0167] Data interaction interfaces are configured between simulation domains to ensure simulation data and collaborative interaction between digital twin models in different simulation domains, ultimately achieving joint dynamic simulation and optimization.

[0168] S6-2: Simulation data driven and interactive collaboration

[0169] Create simulation data flow based on workshop logistics plan , and the logistics solution provider initiates a joint simulation on the platform. During the simulation, each sub-simulation domain digital twin model receives the simulation data stream. Dynamic adjustment and calculation are carried out to simulate the actual workshop logistics operation logic. For example, when the cargo flow in the logistics dynamic simulation domain changes, the corresponding data will be simulated through the simulation data flow. The data is passed to the equipment dynamic simulation domain, where the equipment digital twin model will adjust its own operating parameters according to changes in cargo flow, such as speeding up or slowing down the delivery speed, to adapt to new logistics needs.

[0170] There is a close data flow and collaborative interaction between the sub-simulation domains to achieve joint dynamic simulation, ensuring that the sub-simulation domains can cooperate with each other to jointly simulate the real operation of the entire workshop logistics system. In actual operation, each sub-simulation domain receives data from other sub-simulation domains in real time, and performs calculations and updates based on this data and its own model logic, and then feeds the generated new data back to the simulation data flow. For use by other sub-simulation domains. For example, the plant structure dynamic simulation domain analyzes the impact of vibrations generated by equipment operation and the weight distribution of stored cargo on the plant structure, and feeds structural stress and deformation data back to the simulation data stream. The operator's operation behavior data in the manual operation simulation domain will also affect the cargo flow speed and path selection in the logistics dynamic simulation domain. Under such data interaction and synergy, each sub-simulation domain can realize a comprehensive and dynamic simulation of the workshop logistics system.

[0171] S6-3: Distributed Computing and Data Encryption

[0172] Based on simulation data flow The driver initiates a distributed computing mode, whereby the simulation computing tasks of each sub-simulation domain are executed by the local hardware terminals of the relevant units. These local terminals possess independent edge computing capabilities and, through communication interfaces with the Metaverse platform, enable data exchange and collaboration with other sub-simulation domains. This avoids computational bottlenecks and single points of failure that can arise from centralized computing, improves the reliability and scalability of the entire joint simulation system, and ultimately enhances the efficiency of complex system simulations.

[0173] At the same time, in order to ensure the privacy of data transmission, each simulation domain responsible unit uses blockchain technology to encrypt and ensure data security. In the data encryption process, the elliptic curve encryption algorithm ECC is used to encrypt the simulation data to be transmitted. , then the joint simulation data encryption process is expressed as:

[0174] (2)

[0175] in is the public key, This is the encrypted simulation data. Only the recipient with the corresponding private key can decrypt the encrypted data, effectively preventing the data from being stolen or tampered with during transmission.

[0176] S6-4: Simulation Visualization and Feedback Optimization

[0177] Through 3D visualization technology, the simulation process and results are presented in real-time dynamic 3D visualization in the joint R&D space, so that the digital twin model of the workshop logistics system in the metaverse can intuitively simulate the real production situation.

[0178] During the joint dynamic simulation process, each sub-simulation domain feeds simulation results back to the Metaverse platform in real time. The platform comprehensively analyzes and evaluates this feedback data to determine whether the logistics system's operation meets design requirements. If a sub-simulation domain's simulation results are abnormal or inconsistent with expectations, the platform promptly sends adjustment instructions to the corresponding sub-simulation domain. The sub-simulation domain adjusts its model parameters or operating logic accordingly and then continues the simulation, ensuring that the entire joint dynamic simulation process accurately simulates the actual operation of the shop floor logistics system and continuously optimizes the logistics plan.

[0179] S6-5: Simulation report preparation

[0180] After completing all joint simulations, the logistics solution provider will produce a detailed simulation results report. This report comprehensively summarizes the entire workshop logistics system simulation process and results, covering multiple key aspects, including performance indicator analysis, production capacity assessment, equipment utilization analysis, and energy consumption analysis. It utilizes a combination of charts, data tables, and textual explanations to ensure the client can intuitively and clearly understand the simulation results. Simultaneously, the Metaverse platform integrates and optimizes all types of data generated during the simulation process to ensure accuracy and completeness. A data query terminal is also provided in the virtual space. Clients can click on the terminal to select the data category they wish to view, and the system will present the relevant data in a visual manner (such as dynamic data annotation on the 3D model and virtual chart display).

[0181] S6-6: Confirmation of simulation results

[0182] After the owner obtains permission to enter the Metaverse joint R&D space, he can use various interactive modes to fully confirm the integration and simulation results of the logistics system.

[0183] In terms of interactive mode application, the zoom-in function allows owners to carefully observe the detailed structure of the equipment, the packaging labels of the goods, etc.; the zoom-out function allows owners to view the layout and process of the entire workshop logistics system from a macro perspective; the shuttle function allows owners to move freely in the virtual space, simulating the walking path in the actual warehouse, and experience the logistics connection between different areas; the teleportation function allows owners to quickly reach the designated location or scene, improving viewing efficiency.

[0184] Owners should prioritize confirming whether the workshop logistics solution meets their business needs and expected goals. Regarding production efficiency, they should check whether the system's capacity, efficiency, and energy consumption meet the expected production pace. Regarding equipment configuration, they should review whether the equipment selection and layout are reasonable and can meet actual operational needs. Regarding personnel operations, they should assess whether the design of manual operations complies with actual workflows and safety regulations.

[0185] If any issues or questions arise during the owner's confirmation process, they can communicate with relevant parties in real time through the Metaverse platform's online communication function. All parties can hold meetings in a virtual space to conduct in-depth discussions and analysis on the issues raised by the owner.

[0186] In the specific implementation, as described in step S7, it includes: digital delivery of the workshop logistics system, specifically,

[0187] After the owner confirms that the workshop logistics solution design meets the requirements, the solution provider will take the lead in initiating digital delivery work on the joint R&D platform.

[0188] S7-1: Collaborative development of digital twin systems

[0189] Equipment suppliers and civil engineering design institutes grant logistics solution providers access to interfaces for digital twin models of equipment or plants. With this access, logistics solution providers can directly develop digital twin systems for workshop logistics using digital twin system development tools on this joint R&D platform without having to request digital twin models from equipment suppliers or civil engineering design institutes, thus preventing technical leaks caused by model sharing. Furthermore, solution providers can invite equipment suppliers to collaborate on digital twin system development, providing basic functional module components and integrating them into the digital twin system to improve system development efficiency.

[0190] S7-2: Forward and Reverse Digital Delivery

[0191] After the development of the workshop logistics digital twin system is completed, the logistics integrator collaborates with equipment suppliers and civil engineering design institutes to package digital assets such as workshop element digital twin models, simulation data, intelligent algorithms, and operation and maintenance knowledge bases into the workshop logistics digital twin system. Based on the owner's actual needs and application scenarios, the workshop logistics digital system is deployed to the owner's local terminal, local area network or metaverse platform to guide the implementation, production and operation and maintenance of the logistics system, and realize the positive digital delivery of the workshop logistics system based on the digital twin system.

[0192] If system maintenance and updates are required, the owner connects the Metaverse Joint R&D Platform to the workshop logistics digital twin system via a data interface to download the update package. Simultaneously, the owner can upload system operation and maintenance data to the Joint R&D Platform through the workshop logistics digital twin system. The Joint R&D Platform automatically analyzes the system data and distributes it to relevant departments, promoting product optimization and improvement, and achieving reverse digital delivery.

[0193] For specific implementation, please refer to Figure 3 , Figure 3 1 is a schematic diagram showing the system composition of a joint research and development of a workshop logistics system based on the Metaverse according to an exemplary embodiment. The system includes:

[0194] An acquisition module 30 is configured to acquire first request information from a preset logistics solution provider;

[0195] The first processing module 31 is configured to use the first request information of the logistics solution provider to build a virtual joint R&D space for workshop logistics, and use the virtual joint R&D space for workshop logistics to allocate permissions to target users;

[0196] The second processing module 32 is used to obtain the second request information of the preset logistics solution provider, and use the second request information of the logistics solution provider and the results of the target user's authority allocation in the workshop logistics virtual joint R&D space to allow the relevant target users to participate in the docking requirements according to the digital human role, and use the preset large model to process the docking requirements content, thereby generating a real-time updated digital requirement document encrypted and stored in the Metaverse distributed data center;

[0197] The third processing module 33 is configured to convert the encrypted digital requirement document stored in the Metaverse distributed data center, which is updated in real time, into a digital drawing that supports multiple interactive operations and reflects layout information, using a preset algorithm;

[0198] A fourth processing module 34 is configured to collaboratively model a preset workshop logistics system according to fields using the real-time updated digital drawings that support multiple interactive operations and reflect layout information;

[0199] A fifth processing module 35 is configured to utilize the collaborative modeling results of the preset workshop logistics system and utilize the preset digital twin model to simulate and optimize the preset workshop logistics solution through distributed joint dynamic simulation.

[0200] The sixth processing module 36 is used to realize digital delivery of the workshop logistics system by utilizing the results of simulating and optimizing the preset workshop logistics plan.

[0201] Furthermore, the present invention mainly includes the following beneficial effects:

[0202] Enhanced immersion and collaboration, reducing the risk of leaks: This invention integrates multiple technologies, including metaverse virtual space management, XR, and digital humans, to create a highly realistic virtual joint R&D space. Personnel from all parties enter the space as digital humans, and with the help of auxiliary tools such as digital drawings and virtual guidance elements, they can achieve real-life interactive collaboration. When discussing the layout of workshop logistics equipment, VR equipment allows all parties to experience the layout firsthand, intuitively identify problems, and make real-time corrections. This immersive experience greatly enhances participation and promotes close collaboration. Furthermore, compared to the traditional frequent exchange of technical information and models, the platform utilizes permission management and blockchain data encryption technology to strictly restrict data access. Different units and roles can only access authorized information, fundamentally reducing the risk of technical leaks.

[0203] Comprehensive simulation analysis enhances design scientificity: Plant structure simulation and human operation simulation are introduced to comprehensively simulate the workshop logistics system solution. Plant structure simulation accurately analyzes the mechanical properties and stability of the plant under various operating conditions, such as cargo loading, equipment vibration, and natural disasters. This allows for pre-emptive design optimization and mitigates potential safety hazards in actual operation. Human operation simulation involves actual workers wearing XR devices and simulating their operations. This fully considers the impact of factors such as operator habits and fatigue on the logistics system, making the logistics solution more tailored to actual operational scenarios. This further enhances the scientific nature and rationality of system design and reduces operational issues.

[0204] Improving simulation efficiency and ensuring data security: Distributed joint dynamic simulation and blockchain data encryption technologies, combined with a simulation domain allocation mechanism, disperse complex simulation computing tasks across local hardware terminals. Each sub-domain, such as the logistics dynamic simulation domain and the equipment dynamic simulation domain, is managed by a different unit. Parallel computing utilizes the edge computing capabilities of local terminals, avoiding the bottlenecks of centralized computing, significantly reducing computing overhead and costs, and significantly improving R&D efficiency. During data transmission, blockchain encryption technologies, such as the elliptic curve encryption algorithm (ECC), are used to encrypt simulation data. Only the recipient with the corresponding private key can decrypt it, effectively ensuring data security and preventing theft or tampering during transmission.

[0205] Achieve two-way digital delivery and enhance delivery capabilities: Through the collaborative development and deployment of the workshop logistics digital twin system, a data transmission mechanism between the platform and the digital twin system will be established to achieve forward and reverse digital delivery. During forward delivery, digital assets such as the workshop element digital twin model, simulation data, and intelligent algorithms are packaged into the system and deployed to the corresponding platform according to the owner's needs, providing comprehensive guidance for the implementation, production, and operation and maintenance of the logistics system. In reverse delivery, the owner uploads the system usage and operation data to the joint R&D platform through the data interface. The platform automatically analyzes and distributes the data to relevant units, promoting continuous product optimization and improvement, effectively improving the delivery capability of the workshop logistics system, and meeting the owner's needs for long-term use and system upgrades.

[0206] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0207] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" is at least two.

[0208] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0209] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0210] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0211] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0212] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0213] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0214] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for joint development of a workshop logistics system based on the Metaverse, characterized in that: The method comprises: Obtain the first request information of the preset logistics solution provider; Using the first request information of the logistics solution provider, constructing a workshop logistics virtual joint R&D space, and using the workshop logistics virtual joint R&D space to allocate permissions to target users; Obtain the second request information from the preset logistics solution provider, use the second request information from the logistics solution provider and the results of the target user's authority allocation in the workshop logistics virtual joint R&D space, require the relevant target users to participate in the docking requirements according to the digital human role, and use the preset large model to process the demand docking content, and generate a real-time updated digital demand document that is encrypted and stored in the Metaverse distributed data center; Using a preset algorithm, the encrypted digital requirement document that is updated in real time and stored in the Metaverse distributed data center is converted into a digital drawing that is updated in real time and supports multiple interactive operations and reflects layout information; By utilizing the real-time updated digital drawings that support multiple interactive operations and reflect layout information, collaborative modeling of a preset workshop logistics system is performed according to fields; Using the results of the collaborative modeling of the preset workshop logistics system, the preset digital twin model is used to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation; Using the results of the simulation and optimization of the preset workshop logistics plan, digital delivery of the workshop logistics system is achieved; The method utilizes the real-time updated digital drawings that support multiple interactive operations and reflect layout information to collaboratively model the preset workshop logistics system according to the field, including: Using the real-time updated digital drawings that support multiple interactive operations and reflect layout information, virtual guidance elements are constructed in the workshop logistics virtual joint R&D space based on computer graphics and spatial positioning technology; Utilizing the virtual guiding elements, a collaborative modeling assistance mode based on digital drawings is constructed; Based on the collaborative modeling assistance mode of the digital drawings, each unit is used to concurrently build and upload digital twin models of their respective fields, and the digital twin models are arranged according to the virtual guiding elements; The digital twin model is adjusted and optimized using a preset bounding box conflict detection algorithm to obtain the result of collaborative modeling of the preset workshop logistics system according to the field.

2. The method according to claim 1, characterized in that The step of using the first request information of the logistics solution provider to construct a virtual joint R&D space for workshop logistics and using the virtual joint R&D space for workshop logistics to allocate permissions to target users includes: Using the first request information of the logistics solution provider, using space modeling technology and virtual environment generation algorithm, constructing a virtual joint R&D space for workshop logistics; By utilizing the results of constructing a virtual joint R&D space for workshop logistics, access rights are allocated according to the roles and responsibilities of different participants in the project based on the RBAC model and dynamic permission allocation strategy.

3. The method according to claim 1, characterized in that The method utilizes a preset algorithm to convert the encrypted digital requirement document stored in the Metaverse distributed data center, which is updated in real time, into a digital drawing that supports multiple interactive operations and reflects layout information, including: Using pre-set system engineering analysis tools and logistics system planning algorithms, determine the interrelationships between the various functional areas of the pre-set workshop logistics system and the spatial layout principles, and generate pre-set workshop logistics system CAD drawings containing quantitative and qualitative information, precise dimensions, locations, and annotations; The interactive function is developed by utilizing the principles of human-computer interaction and virtual reality interaction to convert the preset workshop logistics system CAD drawings containing quantitative and qualitative information, precise dimensions, positions and annotations into digital drawings that reflect workshop layout information and support multiple interactive operations.

4. The method according to claim 1, wherein The construction process of the digital twin model includes: Using 3D modeling software to create a 3D geometric model of the logistics unit, and using the 3D geometric model to accurately characterize the shape, size and appearance characteristics of the logistics unit; Using the creation results of the three-dimensional geometric model, finite element simulation software is used to analyze the physical performance of the logistics unit under different working conditions and construct a physical dimension model; Also, use algorithm simulation analysis software to model and analyze the logistics flow patterns, storage characteristics, and scheduling algorithms in the workshop logistics system to build a mechanism dimension model; The data fusion algorithm is used to fuse models of different dimensions to obtain a digital twin model.

5. The method according to claim 1, wherein The digital twin model is adjusted and optimized using a preset bounding box conflict detection algorithm to obtain the result of collaborative modeling of the preset workshop logistics system according to the field, including: Compare the bounding box of each model in the actual scene layout with the bounding box in the preset scene layout information to determine whether there is a conflict in the model layout; If a large positional or dimensional deviation is detected in the layout, the model location of the error will be prompted using voice and visual elements, and the error area and deviation value will be clearly marked on the digital drawing; The model is adjusted through various interactive methods. After the adjustment is completed, the system performs layout detection again until it meets the requirements.

6. The method according to claim 1, characterized in that The method utilizes the results of the collaborative modeling of the preset workshop logistics system and utilizes the preset digital twin model to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation, including: Constructing a joint dynamic simulation task domain of a workshop logistics system; the joint dynamic simulation task domain of the workshop logistics system includes: a joint simulation domain and several sub-simulation domains; The digital twin models of each sub-simulation domain dynamically adjust and calculate according to the received preset simulation data stream and the actual workshop logistics operation logic to obtain a first processing result; Each sub-simulation domain receives data from other sub-simulation domains in real time, performs calculations and updates based on the data and its own model logic, and then feeds the generated new data back into the simulation data stream, which is then used by other sub-simulation domains to obtain a second processing result. Utilizing the first and second processing results, executing a distributed computing model driven by simulation data streams, having the computing tasks of each sub-simulation domain performed by local hardware terminals of relevant units, utilizing edge computing capabilities and communication interfaces to achieve data interaction and collaboration, and utilizing blockchain technology combined with the elliptic curve cryptography algorithm (ECC) to encrypt various transmission data exchanged between the sub-simulation domains during the joint simulation of the workshop logistics system, thereby obtaining a third processing result; Utilizing the third processing result, the simulation process and results are dynamically presented in real time in the joint R&D space through three-dimensional visualization technology. Each sub-simulation domain feeds back the results to the Metaverse platform in real time. The platform conducts comprehensive analysis and evaluation. If any anomalies are found, adjustment instructions are sent to the corresponding sub-simulation domain, prompting it to adjust model parameters or run logic before continuing the simulation, thereby accurately simulating and optimizing the logistics plan, thereby obtaining the fourth processing result. The fourth processing result is used to prepare a simulation report and confirm the simulation results.

7. The method according to claim 6, characterized in that Also includes: The joint simulation domain is the coupling of sub-simulation domains, which is expressed by the formula: J= （1） J represents the joint simulation domain; Represents a sub-simulation domain; each sub-simulation domain has its own specific task objectives. Data flows between sub-simulation domains, and each is responsible for different units, and the hardware terminals of the simulation calculations are set in different units. Each unit is responsible for the simulation tasks of the corresponding sub-simulation domain, and can also further subdivide the sub-simulation domain it is responsible for to meet the task requirements of its simulation domain.

8. The method according to claim 7, characterized in that The elliptic curve encryption algorithm ECC is used to encrypt various transmission data exchanged between sub-simulation domains during the joint simulation of the workshop logistics system, including: In the data encryption process, the elliptic curve encryption algorithm is used. For the simulation data to be transmitted, the joint simulation data encryption process is expressed as: （2） in is the public key, It is encrypted simulation data; only the recipient with the corresponding private key can decrypt the encrypted data, effectively preventing the data from being stolen or tampered with during transmission.

9. A system for joint development of a pre-set workshop logistics system based on a metaverse, applied to a method for joint development of a pre-set workshop logistics system based on a metaverse as claimed in any one of claims 1 to 8, characterized in that: The system comprises: An acquisition module, used to obtain the first request information of a preset logistics solution provider; A first processing module is configured to use the first request information of the logistics solution provider to build a virtual joint R&D space for workshop logistics, and use the virtual joint R&D space for workshop logistics to allocate permissions to target users; The second processing module is used to obtain the second request information of the preset logistics solution provider, use the second request information of the logistics solution provider and the results of the target user's authority allocation in the workshop logistics virtual joint R&D space, and require the relevant target users to participate in the docking requirements according to the digital human role, and use the preset large model to process the docking requirements content, and generate a real-time updated digital requirement document that is encrypted and stored in the Metaverse distributed data center; A third processing module is configured to convert the encrypted digital requirement document stored in the Metaverse distributed data center, which is updated in real time, into a digital drawing that supports multiple interactive operations and reflects layout information, which is updated in real time, using a preset algorithm; A fourth processing module is configured to collaboratively model a preset workshop logistics system according to fields using the real-time updated digital drawings that support multiple interactive operations and reflect layout information; a fifth processing module, configured to utilize the collaborative modeling results of the preset workshop logistics system and utilize the preset digital twin model to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation; The sixth processing module is used to realize digital delivery of the workshop logistics system by utilizing the results of simulating and optimizing the preset workshop logistics plan.

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