Universe-based workshop logistics system joint research and development method and system

Abstract

The invention relates to the technical field of joint research and development of workshop logistics systems, in particular to a method and a system for joint research and development of a workshop logistics system based on meta universe. The method comprises the following steps: acquiring request information of a logistics solution provider, constructing a virtual joint research and development space and allocating authority, thereby enabling a target user to meet a demand to generate an encrypted digital demand document, converting the encrypted digital demand document into a digital drawing, carrying out collaborative modeling, carrying out simulation optimization by using a digital twinborn model, and finally realizing a digital delivery process. According to the method, multiple technologies of the meta universe are fused, the immersion and collaboration of research and development are improved, and the risk of technology leakage is reduced; the system is comprehensively simulated and analyzed, and the design rationality is improved; a distributed joint dynamic simulation and encryption technology is adopted, so that the simulation efficiency and the data security are improved; bidirectional digital delivery is realized, delivery capability is enhanced, and a workshop logistics system research and development mode is innovated.

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 methods for researching and developing workshop logistics systems face many challenges, mainly including: ① High cost and low efficiency: Traditional research and development methods that rely on two-dimensional drawings and on-site testing are not only time-consuming and laborious, but also costly. Each design change requires remaking physical models and conducting on-site tests, which greatly extends the research and development cycle.

[0003] ② Information silos and difficult collaboration: Workshop logistics systems involve multiple parties, including the owner, logistics solution providers, equipment suppliers, and architectural design institutes. Different parties often use different tools and platforms, resulting in untimely and inaccurate information transmission, forming information silos, which seriously affects the efficiency of collaborative research and development.

[0004] ③ Lack of comprehensive simulation and optimization: Existing simulation tools mainly focus on the simulation of single equipment or local processes, lacking comprehensive coverage and dynamic interaction simulation of the entire workshop logistics system. This makes it difficult to comprehensively evaluate the performance of the system during the design phase, resulting in many problems in actual operation, such as unreasonable equipment layout and unoptimized logistics paths.

[0005] ④ Challenges in digital delivery and maintenance: Traditional system delivery models lack effective digital asset delivery and reverse feedback mechanisms, making it difficult to maintain and update the system, which affects the long-term stable operation of the system.

[0006] To solve the above problems and improve the research and development efficiency and quality of workshop logistics systems, there is an urgent need for an innovative research and development platform and method that can achieve efficient collaborative modeling, joint simulation, and digital delivery among all parties, while ensuring information security and consistency. Furthermore, existing collaborative research and development technologies mostly adopt a collaborative research and development mode based on two-dimensional web pages, with weak user immersion and participation, and poor collaborative effects. At the same time, in existing collaborative research and development work, technical materials and models are often transmitted to each other, posing a risk of technical leakage; In addition, existing simulation optimization technologies based on digital twins mostly focus on the modeling and simulation of logistics production lines and equipment, lacking comprehensive factor dynamic simulation and analysis of aspects such as workers and workshops in workshop logistics systems, making it difficult to accurately optimize logistics plans; Moreover, existing logistics system modeling and simulation are mainly concentratedly modeled and simulated by logistics solution providers, with a long modeling cycle, large computational overhead, and computational bottlenecks, resulting in low simulation efficiency; In addition, the existing technology lacks methods and means for seamless connection from R & D to digital delivery, and has poor delivery capabilities. Summary of the Invention

[0007] In view of this, the purpose of the present invention is to provide a method and system for joint R & D of a workshop logistics system based on the metaverse, so as to solve the technical problems in the existing technology such as poor immersion in the collaborative R & D of the workshop logistics system, incomplete simulation, long R & D cycle, poor technical confidentiality, and poor delivery capabilities. According to the first aspect of the embodiments of the present invention, a method for joint R & D of a workshop logistics system based on the metaverse is provided. The method includes: Obtain the first request information of a preset logistics solution provider; Utilize the first request information of the logistics solution provider to construct a virtual joint R & D space for the workshop logistics, and allocate permissions to target users using the virtual joint R & D space for the workshop logistics; Obtain the second request information of a preset logistics solution provider, and use the second request information of the logistics solution provider and the result of permission allocation to target users using the virtual joint R & D space for the workshop logistics, so that relevant target users participate in the meeting and dock requirements according to the digital human role, and use a preset large model to process the requirement docking content, and generate a digital requirement document that is encrypted and stored in real-time in the metaverse distributed data center; Use a preset algorithm to convert the digital requirement document that is encrypted and stored in real-time in the metaverse distributed data center into a digital drawing that supports various interactive operations and reflects layout information in real-time; Use the digital drawing that supports various interactive operations and reflects layout information in real-time to perform collaborative modeling on a preset workshop logistics system according to the field; Use the result of the collaborative modeling on the preset workshop logistics system, and use a preset digital twin model to simulate and optimize the preset workshop logistics plan through distributed joint dynamic simulation; Use the result of the simulation and optimization of the preset workshop logistics plan to achieve digital delivery of the workshop logistics system.

[0008] Further, the step of using the first request information of the logistics solution provider to construct a virtual joint R & D space for the workshop logistics and allocate permissions to target users using the virtual joint R & D space for the workshop logistics includes: Utilize the first request information of the logistics solution provider, and use space modeling technology and virtual environment generation algorithms to construct a virtual joint R & D space for the workshop logistics; Using the results of building a virtual joint R & D space for workshop logistics, based on the RBAC model and dynamic permission allocation strategy, access permissions are allocated according to the roles and responsibilities of different participants in the project.

[0009] Furthermore, using a preset algorithm to convert the encrypted digital requirement documents stored in the metaverse distributed data center with real-time updates into digital drawings that support multiple interactive operations and reflect layout information, including: Using a preset systems engineering analysis tool and logistics system planning algorithm, determine the interrelationships and spatial layout principles of each functional area of the preset workshop logistics system, and generate CAD drawings of the preset workshop logistics system that contain quantitative and qualitative information, precise dimensions, positions, and annotations; Develop an interactive function using the principles of human-computer interaction and virtual reality interaction, and convert the CAD drawings of the preset workshop logistics system that contain quantitative and qualitative information, precise dimensions, positions, and annotations into digital drawings that reflect the workshop layout information and support multiple interactive operations.

[0010] Furthermore, using the digital drawings that support multiple interactive operations and reflect layout information with real-time updates to perform collaborative modeling on the preset workshop logistics system according to the domain, including: Using the digital drawings that support multiple interactive operations and reflect layout information with real-time updates, construct virtual guiding elements in the virtual joint R & D space of the workshop logistics based on computer graphics and spatial positioning technology; Using the virtual guiding elements, construct a collaborative modeling assistance mode based on the digital drawings; Based on the collaborative modeling assistance mode of the digital drawings, use each unit to construct and upload digital twin models of their respective domains in parallel, and arrange the digital twin models according to the virtual guiding elements; Use a preset bounding box collision detection algorithm to adjust and optimize the digital twin models, and obtain the results of collaborative modeling of the preset workshop logistics system according to the domain.

[0011] Furthermore, the construction process of the digital twin model includes: Use 3D modeling software to create a 3D geometric model of the logistics unit, and use the 3D geometric model to accurately represent the shape, size, and appearance characteristics of the logistics unit; Using the creation results of the 3D geometric model, use finite element simulation software to analyze the physical properties of the logistics unit under different working conditions, and construct a physical dimension model; And, use algorithm simulation analysis software to model and analyze the logistics flow law, storage characteristics, and scheduling algorithm in the workshop logistics system, and construct a mechanism dimension model; Use a data fusion algorithm to fuse models of different dimensions to obtain a digital twin model.

[0012] Furthermore, use the preset bounding box collision detection algorithm to adjust and optimize the digital twin model to obtain the result of collaborative modeling of the preset workshop logistics system according to the domain, including: Compare the bounding boxes of each model in the actual scene layout with the bounding boxes in the preset scene layout information to determine whether there is a conflict in the model layout; If a large position deviation or size deviation is detected in the layout, use voice and visual elements to prompt the model position where the error is located, and at the same time clearly mark the error area and deviation value on the digital drawing; Adjust the model through various interaction methods. After the adjustment is completed, the system performs layout detection again until the requirements are met.

[0013] Furthermore, use the result of collaborative modeling of the preset workshop logistics system, and use the preset digital twin model to simulate and optimize the preset workshop logistics plan through a distributed joint dynamic simulation method, including: Construct a joint dynamic simulation task domain for the workshop logistics system; the joint dynamic simulation task domain for the workshop logistics system includes: 1 joint simulation domain and several sub-simulation domains; The digital twin models of each sub-simulation domain are dynamically adjusted and calculated according to the received preset simulation data stream according to 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 according to these data and its own model logic, and then feeds the generated new data back into the simulation data stream for use by other sub-simulation domains to obtain a second processing result; Use the first processing result and the second processing result to execute a distributed computing mode driven by the simulation data stream. The calculation tasks of each sub-simulation domain are executed by the local hardware terminals of relevant units. Use edge computing capabilities and communication interfaces to achieve data interaction and collaboration, and use blockchain technology combined with the elliptic curve encryption algorithm ECC to encrypt various transmission data exchanged between sub-simulation domains during the joint simulation of the workshop logistics system to obtain a third processing result; Use the third processing result to present the simulation process and results in real time and dynamically in the joint R & D space through 3D visualization technology. Each sub-simulation domain feeds back the results to the metaverse platform in real time. The platform comprehensively analyzes and evaluates. If abnormalities are found, adjustment instructions are sent to the corresponding sub-simulation domains to prompt them to adjust the model parameters or operation logic and then continue the simulation to accurately simulate and optimize the logistics plan to obtain a fourth processing result; Using the fourth processing result, a simulation report is made and the simulation result is confirmed.

[0014] Furthermore, it further 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 the sub-simulation domain; each sub-simulation domain has its specific task objective, there is data flow between sub-simulation domains, and they are respectively responsible for different units, and the hardware terminals for simulation calculation are respectively set in different units; each unit is responsible for the simulation task of the corresponding sub-simulation domain, and can also further subdivide the responsible sub-simulation domain to meet the task requirements of its simulation domain.

[0015] Furthermore, the combination of the elliptic curve encryption algorithm ECC is used to encrypt various transmission data exchanged between sub-simulation domains during the joint simulation process of the workshop logistics system, including: During the data encryption process, the elliptic curve encryption algorithm is adopted. For the simulation data to be transmitted, the joint simulation data encryption process is expressed as: (2) Where is the public key, is the encrypted simulation data; only the receiving party with the corresponding private key can decrypt the encrypted data, effectively preventing the data from being stolen or tampered with during the transmission process.

[0016] According to the second aspect of the embodiments of the present invention, a system for joint research and development of a preset workshop logistics system based on the metaverse is provided, which is applied to the method for joint research and development of a preset workshop logistics system based on the metaverse described in any one of the above, and the system includes: An acquisition module, configured to acquire the first request information of a preset logistics solution provider; A first processing module, configured to use the first request information of the logistics solution provider to construct a virtual joint research and development space for the workshop logistics, and perform permission allocation for target users by using the virtual joint research and development space for the workshop logistics; A second processing module, configured to acquire the second request information of a preset logistics solution provider, use the second request information of the logistics solution provider and the result of permission allocation for target users by using the virtual joint research and development space for the workshop logistics, enable relevant target users to participate in the meeting docking requirements according to the digital human role, and use a preset large model to process the content of the requirement docking, and generate a digital requirement document that is encrypted and stored in the metaverse distributed data center in real time; A third processing module, configured to use a preset algorithm to convert the encrypted digital requirement document stored in the distributed data center of the metaverse, which is updated in real time, into a digital drawing that is updated in real time, supports various interaction operations, and reflects layout information; A fourth processing module, configured to use the digital drawing that is updated in real time, supports various interaction operations, and reflects layout information to perform collaborative modeling on a preset workshop logistics system according to fields; A fifth processing module, configured to use the result of performing collaborative modeling on a preset workshop logistics system, and use a preset digital twin model to simulate and optimize a preset workshop logistics plan through distributed joint dynamic simulation; A sixth processing module, configured to use the result of simulating and optimizing a preset workshop logistics plan to achieve digital delivery of the workshop logistics system.

[0017] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: ① By integrating technologies such as metaverse virtual space management, permission management, XR, digital twin, digital human, and human-computer interaction, and with the help of auxiliary tools such as digital drawings and virtual guiding elements, the immersion of the research and development work of the workshop logistics system is enhanced, close collaboration among all parties is promoted, and at the same time, the risk of technology leakage can be effectively reduced; ② By introducing simulations of factory building structures and personnel operations during the operation of the logistics system, a comprehensive simulation analysis of the workshop logistics system plan is carried out to further improve the scientificity and rationality of system design; ③ By adopting distributed joint dynamic simulation and blockchain data encryption technology, and using a simulation domain allocation mechanism, cross-regional and cross-field distributed computing and simulation are realized, the computing overhead and cost are reduced, the R & D efficiency is improved, and data security is guaranteed; ④ By collaboratively developing and deploying a workshop logistics digital twin system, and establishing a data transmission mechanism for the workshop logistics system joint R & D platform and the workshop logistics digital twin system, forward and reverse digital delivery of the workshop logistics system can be realized, effectively improving the delivery ability of the workshop logistics system.

[0018] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. Description of the Drawings

[0019] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0020] Figure 1 It is a schematic diagram of the steps of a method for joint R & D of a workshop logistics system based on the metaverse shown according to an exemplary embodiment; Figure 2 It is a schematic diagram of the implementation process steps jointly developed for a metaverse-based workshop logistics system shown according to an exemplary embodiment; Figure 3 It is a schematic diagram of the system composition jointly developed for a metaverse-based workshop logistics system shown according to an exemplary embodiment. Detailed implementation manners

[0021] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0022] Embodiment 1 Please refer to Figure 1 , Figure 1 It is a schematic diagram of the steps of a method jointly developed for a metaverse-based workshop logistics system shown according to an exemplary embodiment. The method includes: S1. Obtain the first request information of a preset logistics solution provider; S2. Utilize the first request information of the logistics solution provider to construct a virtual joint R & D space for workshop logistics, and allocate permissions for target users using the virtual joint R & D space for workshop logistics; S3. Obtain the second request information of a preset logistics solution provider, and use the second request information of the logistics solution provider and the result of permission allocation for target users using the virtual joint R & D space for workshop logistics to enable relevant target users to participate in the meeting and dock requirements according to the digital human role, and use a preset large model to process the requirement docking content to generate a digitally encrypted demand document that is stored in the metaverse distributed data center and updated in real time; S4. Use a preset algorithm to convert the digitally encrypted demand document stored in the metaverse distributed data center and updated in real time into a digitally encrypted drawing that supports multiple interactive operations and reflects layout information and is updated in real time; S5. Use the digitally encrypted drawing that supports multiple interactive operations and reflects layout information and is updated in real time to perform collaborative modeling on a preset workshop logistics system according to the field; S6. Use the result of collaborative modeling on a preset workshop logistics system and use a preset digital twin model to simulate and optimize a preset workshop logistics plan through distributed joint dynamic simulation; S7. Use the result of simulating and optimizing a preset workshop logistics plan to achieve digital delivery of the workshop logistics system.

[0023] In specific implementation, the joint R & D method for workshop logistics based on the metaverse is initiated by a logistics solution provider based on a preset platform, and units such as the owner, equipment supplier, and architectural design institute jointly participate, enabling the docking of workshop logistics system requirements, the creation of digital drawings, collaborative modeling, joint simulation, and digital delivery.

[0024] In specific implementation, the preset platform architecture includes: Basic resource layer, data management layer, core function layer, application service layer.

[0025] L1: Basic resource layer This layer includes platform-provided software and hardware resources such as edge servers, specialized software (modeling, simulation, management, monitoring types), network communication facilities, interactive terminal devices (XR / PC / mobile), and workshop data acquisition devices.

[0026] L2: Data management layer This layer includes data management-related modules or components such as data interfaces, data buses, data processing algorithms, data encryption algorithms, and distributed databases, providing data management functions for platform operation.

[0027] L3: Core function layer The core function layer includes a virtual space construction management module, a model management module, a distributed simulation module, and a collaborative communication and collaboration module.

[0028] 1) Virtual space management module The virtual space management module supports the creation of a virtual joint R & D space using 3D modeling and virtual reality technology, and supports obtaining models and data from the basic resource layer to present scene elements such as warehouses, equipment, materials, and operating personnel, and provides scene editing tools.

[0029] 2) Model management module Supports the construction, upload, combination, inspection, and modification of models related to the digital twin of workshop logistics, and supports the creation of user digital human roles, endowing them with appearance, actions, and behavior logic, and realizing natural action simulation through motion capture or preset animations.

[0030] 3) Permission management module Supports permission management such as user access permission allocation, user identity authentication, and role, model, and data access permission setting.

[0031] 4) Distributed simulation module This module generates data streams according to the logistics plan to drive model operations, coordinates local hardware terminals of all parties to execute computing tasks, and combines blockchain encryption and intelligent scheduling algorithms to ensure data security and improve simulation efficiency.

[0032] 5) Communication and Collaboration Module The communication and collaboration module provides various communication methods such as text chat, voice call, video conferencing, and virtual meeting, facilitating users to quickly exchange information and deeply discuss issues. At the same time, it has file sharing and collaborative editing functions, supports users to upload and download project materials, provides collaborative data interaction interfaces, and enables multiple users to collaboratively participate in tasks such as the modeling, simulation, and delivery of the workshop logistics system.

[0033] L4: Platform Service Layer The platform service layer mainly includes intelligent auxiliary services, collaborative modeling services, joint simulation services, and digital delivery services.

[0034] 1) Intelligent Auxiliary Service Based on intelligent algorithms such as large language models, systems engineering analysis algorithms, logistics planning algorithms, and spatial detection and positioning algorithms, it is used to realize the intelligent assistance of joint R & D work. The large language model assists in requirement analysis and meeting records, the systems engineering analysis tool and logistics planning algorithms help with the functional analysis and solution design of the workshop logistics system, and the spatial detection algorithm ensures the rationality of the model layout, providing intelligent decision-making support for R & D work.

[0035] 2) Collaborative Modeling Service Using CAD drawing and human-computer interaction technologies to create digital drawings of the workshop logistics system containing detailed quantitative and qualitative information, and endowing them with rich interactive operation functions such as zooming, panning, and click query, facilitating all parties to view and use, and effectively managing the impact of requirement changes on the drawings and solutions, laying a solid foundation for subsequent R & D work.

[0036] 3) Joint Simulation Service Provides a simulation start and monitoring interface. Users can set simulation parameters to start joint simulation, and real-time display the operation status and key data of the sub-simulation domain. It has a result analysis and evaluation function, generating statistical charts and reports, intuitively presenting the changes of indicators such as logistics efficiency and equipment utilization rate, providing a basis for optimizing the logistics solution. It supports providing the owner with access rights to the metaverse space and diverse interactive functions, facilitating them to confirm whether the solution meets the requirements.

[0037] 4) Digital Delivery Service Supports digital asset packaging, digital twin system development, deployment and update, as well as data reverse delivery.

[0038] Specifically, as described in steps S1 - S2, in specific implementation, it includes: Obtain the first request information of the preset logistics solution provider, and use the request information to create a virtual joint R & D space for workshop logistics in the metaverse joint R & D platform, and allocate access rights, including the access and use rights of this space for units such as the owner, logistics solution provider, equipment supplier, and architectural design institute, and support entering this space area through an interactive terminal in the role of a digital human to participate in the relevant work of joint R & D of workshop logistics.

[0039] S2-1: Creation of virtual joint R & D space Please refer to Figure 2 , the logistics solution provider uses space modeling technology and virtual environment generation algorithms to construct a virtual joint R & D space for workshop logistics. This space can accurately simulate the digital ecosystem of the real workshop logistics environment, covering various aspects such as the building structure of the warehouse, the layout of logistics equipment, the storage and flow paths of goods, etc. At the same time, this space is equipped with a virtual meeting room to provide a meeting and communication place for R & D participating units. Personnel from units such as the owner, logistics solution provider, equipment supplier, and architectural design institute can enter this area in the role of a digital human through an interactive terminal (such as VR\AR\PC and other devices).

[0040] S2-2: Allocation of access rights for the created virtual joint R & D space After the creation of the virtual joint R & D space is completed, the logistics solution provider, based on the RBAC model and dynamic permission allocation strategy, assigns access rights according to the roles and responsibilities of different participating parties in the project. Each user entering this virtual joint R & D space must go through a strict identity authentication process. The identity authentication uses multi-factor authentication technology, combining multiple methods such as the user's account password, biometric identification, and dynamic verification code to ensure that only legally authorized users can enter the system. Once the identity authentication is passed, the system will automatically assign corresponding access rights according to the unit and role to which the user belongs.

[0041] The above 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 leakage of joint R & D technology. Among the non-general permissions, the owner has the simulation permission for operating personnel so as to deeply understand the actual performance of the manual operation link in the system; as the organizer and coordinator of the project, the logistics solution provider has multiple key permissions such as space development, solution design, and task allocation, and can control the overall direction and promotion rhythm of the project from a macro level; the civil engineering design institute and equipment supplier respectively focus on the key permissions for R & D in the sub-fields related to the plant and equipment, including product design modeling, model layout, and simulation optimization in their respective fields.

[0042] In specific implementation, as described in step S3, it includes: research and development requirement docking and management of the workshop logistics system, which specifically includes the following implementation steps: S3-1: Requirement Docking After the creation and permission allocation of the virtual joint research and development space are completed, the logistics solution provider invites units such as the owner, architectural design institute, and equipment supplier for requirement docking. To improve efficiency and reduce costs, the requirement docking can be carried out in the virtual meeting room of the joint research and development space. Each unit can send personnel to conduct meeting discussions through digital human roles to fully understand the usage requirements of the owner for the workshop logistics system, as well as the design resource requirements of the logistics solution provider, architectural design institute, and equipment supplier.

[0043] S3-2: Requirement Management Apply a large model to record the requirement docking meeting and purify the meeting content to form a structured and visual digital requirement document, which is stored in the metaverse distributed data center and encrypted through blockchain technology to prevent the content from being tampered with. When the requirements change, multiple parties need to conduct meeting discussions again. After reaching a consensus, update the requirement document, and broadcast the changed requirements to relevant units through mobile phones and computers via the metaverse platform, so that all participating parties can timely understand the latest information. At the same time, store the changed requirements in the version management library for subsequent reference and traceability.

[0044] In specific implementation, as described in step S4, it includes: Process of creating digital drawings of the workshop logistics system: After obtaining the requirements of all parties, the logistics solution provider needs to transform these requirements into specific and interactive digital drawings of the workshop logistics system solution. Creating digital drawings depends on the integration of logistics planning knowledge, CAD drawing drawing, human-computer interaction, and virtual reality technology, etc. When the requirements of the owner change, update the digital drawings in a timely manner to ensure that the digital drawings are consistent with the latest system solution, and archive the historical versions at the same time. The creation of digital drawings of the workshop logistics system mainly includes the following processes: S4-1: Overall System Scheme Design The solution provider needs to use system engineering analysis tools and logistics system planning algorithms to decompose the functions and analyze the processes of the workshop logistics system, and determine the mutual relationships and spatial layout principles of the functional areas (such as storage area, sorting area, loading and unloading area, etc.) of the workshop logistics system.

[0045] S4-2: Drawing of Scheme CAD Drawings Based on these analysis results, use software such as CAD to create CAD drawings of the workshop logistics system with precise dimensions, positions, and annotations, including quantitative information in the requirements (such as total output, production efficiency, cargo storage volume, number of equipment, energy consumption, etc.) and qualitative information (such as operation process priorities, space utilization preferences, etc.).

[0046] S4-3: Interactive enabling of the drawings After completing the digital drawing, the logistics solution provider uploads it to the joint R & D space, and through human-computer interaction technology and virtual reality interaction principles, develops interactive functions to transform the CAD drawing into a digital drawing that meets the interactive requirements, enabling it to reflect information such as the workshop plan layout and process specifications, and also supporting interactive operations such as interface retrieval, hiding, zooming in, zooming out, panning, rotating, clicking, alarming, and transparency adjustment.

[0047] In specific implementation, as described in step S5, it includes: the processing process of collaborative modeling of the workshop logistics system. Specifically, after the digital drawing is created, the workshop logistics system is collaboratively modeled by domain to improve the modeling efficiency, while reducing the model transfer between units and preventing technology leakage.

[0048] S5-1: Construct virtual guiding elements for collaborative modeling of workshop logistics The logistics solution provider constructs virtual guiding elements in the joint R & D space based on computer graphics and spatial positioning technology, providing an intuitive and accurate reference basis for the subsequent layout of the workshop digital twin model.

[0049] The virtual guiding elements include various types of visualization elements, such as three-dimensional dimension lines, reference planes, center points, dimension data, mounting surfaces, three-dimensional scene names, layout description frames, etc. Among them, the three-dimensional dimension lines visually display the spatial distances and positional relationships between various components by precisely drawing line segments in the three-dimensional space and annotating corresponding dimension information such as length and angle; the reference plane serves as a fixed reference plane to provide a reference for the placement and alignment of the model; the center point is used to identify the key positions or central coordinates of components, facilitating positioning during the layout process; the dimension data details the specific dimension parameters of each part to ensure that the size of the model conforms to the design requirements; the mounting surface clarifies the installation position and direction of the equipment or components; the three-dimensional scene name and layout description frame provide text descriptions of the entire scene and layout. Among them, the layout description frame includes not only the layout description of the three-dimensional scene, but also the data interface specifications and model storage locations.

[0050] S5-2: Develop collaborative modeling auxiliary functions based on digital drawings To quickly realize the construction of the workshop logistics digital twin scenario, develop collaborative modeling auxiliary functions based on digital drawings, including operation interaction, positioning transmission, and alarm prompts.

[0051] ①Operation interaction Develop the operation interaction function of digital drawings, enabling users to interact with digital drawings through various interaction methods. Users can perform operations such as zooming in, zooming out, and rotating on digital drawings through specific gestures (such as pinching, stretching, rotating, etc.) to view the details of the workshop logistics plan more clearly and accurately guide the modeling of the workshop logistics system. When users need to view the detailed dimensions and installation requirements of a certain device, they can zoom in on the corresponding area on the digital drawing through gestures to obtain the required information.

[0052] ②Positioning and transmission Based on the spatial positioning algorithm and associating the three-dimensional spatial position with two-dimensional coordinate information, develop the real-time positioning and position transmission functions of digital drawings. Among them, the real-time positioning function means that the user's current position can be marked and located on the digital drawing in real time. By tracking the position information of the user in the metaverse space and matching it with the coordinate system in the digital drawing, accurate positioning can be achieved, which can help users quickly confirm their positions. In addition, the digital drawing also supports the position transmission function. When the user clicks on any point on the digital drawing, the system will quickly transmit the user to the corresponding virtual scene position according to the coordinate information of this point, improving the user's browsing efficiency.

[0053] ③Alarm prompt Develop the alarm promotion function. When the layout of the workshop logistics system model does not meet the design requirements, the digital drawing will give an alarm prompt at the corresponding position. The alarm promotion function is developed based on preset layout rules and constraint conditions. By comparing the actual layout with the design requirements, when it is found that the deviation exceeds the allowable range, the alarm will be automatically triggered. The alarm prompt can be in the form of eye-catching color markings, flashing effects, or sound prompts, etc., to attract the user's attention and facilitate the user to discover and solve the layout problem in time.

[0054] S5-3: Parallel construction of the digital twin model of the workshop logistics system Each unit constructs and uploads the digital twin models of their respective fields of the workshop logistics system in parallel and arranges the accurate models according to the virtual guiding elements. At the same time, for models with technical secrets, each unit can set permissions such as prohibiting downloading, measuring, and disassembling to protect the relevant technologies of the enterprise to the greatest extent.

[0055] The logistics solution provider is responsible for building a logistics digital twin model. During the construction process, first use 3D modeling software to create a 3D geometric model of the logistics unit, accurately depicting the shape, size, and appearance characteristics of the logistics unit. Then, with the help of finite element simulation software, analyze the physical properties of the logistics unit under different working conditions, such as force deformation, stability, etc., to build a physical dimension model. At the same time, use algorithm simulation analysis software to model and analyze the logistics flow law, storage characteristics, scheduling algorithm, etc. in the workshop logistics system to build a mechanism dimension model. Finally, configure certain data or software interfaces and use data fusion algorithms to fuse models of different dimensions to form a complete logistics digital twin model.

[0056] The architectural design institute is responsible for building a digital twin model of the civil engineering structure of the logistics plant. Based on the architectural design drawings and relevant specifications, use professional architectural modeling software to create a 3D geometric model of the plant, including details such as the building's exterior shape, internal structure, walls, and doors and windows. Use finite element analysis software to analyze the mechanical properties of the plant structure, such as structural strength, seismic performance, etc., to build a physical dimension model. Considering the thermal performance, ventilation performance, etc. of the plant under different environmental conditions, use relevant simulation software to build a mechanism dimension model. Similarly, fuse these models through data interfaces and fusion algorithms to obtain a digital twin model that accurately reflects the civil engineering structure of the plant.

[0057] The equipment supplier is responsible for building an equipment digital twin model. First, according to the design drawings and technical parameters of the equipment, use 3D modeling software to create a geometric model of the equipment, ensuring that the model is highly consistent with the actual equipment in terms of shape and structure. Then, use the performance data provided by the equipment manufacturer and simulation software to simulate and analyze the operating principle, working performance, etc. of the equipment to build physical dimension and mechanism dimension models. Integrate the models of each dimension into an equipment digital twin model through data fusion technology.

[0058] The owner needs to create a digital twin model of the operating personnel, which is driven by data collected from devices such as XR devices, motion capture, smart bracelets, cameras, etc., and supports the simulation of human actions and heart rate collection in operation scenarios such as manual picking and manual loading and unloading, comprehensively evaluating the working efficiency and intensity of workers in the logistics solution.

[0059] After the preliminary construction of the digital twin models in their respective fields is completed, it is necessary to conduct preliminary simulations on each type of field model to check whether there are interferences in the internal space, whether the structural design meets the performance requirements, whether the operating rules meet the expectations, etc. For example, for the equipment digital twin model, through individual simulation, the processes of equipment startup, operation, and shutdown can be simulated to check whether there are collisions and interferences between the components of the equipment, and whether the operating parameters of the equipment are within the normal range.

[0060] After the preliminary simulation meets the requirements, each unit uploads its digital twin model in its respective field to the joint R & D space and stores it in the distributed database of the metaverse according to the system prompt. At the same time, each unit sets the access rights of the digital twin model and opens the data interface of the model.

[0061] S5-4: Workshop Logistics System Model Layout Detection and Adjustment During the construction of the workshop logistics system model, the bounding box collision detection algorithm is used to detect whether the three-dimensional model layout of the workshop and equipment is correct by comparing the actual scene layout with the preset scene layout information, and to adjust and optimize the model.

[0062] When there are large position and size deviations in the layout of the workshop or equipment model, the system will promptly use voice and visual elements to prompt the model position where the error is located. At the same time, the area where the error exists and the deviation value will also be clearly prompted on the digital drawing, facilitating users to quickly locate the problem. When the model layout deviates, users can adjust the model through various interaction 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 enable users to adjust the model by speaking commands; the UI click method provides an intuitive operation interface, and users can complete model adjustment by clicking buttons on the interface or entering specific parameters.

[0063] After the adjustment is completed, the system will perform layout detection again. If the detection result meets the requirements, it will prompt that the adjustment is completed, and the digital drawing will no longer prompt the existence of errors. In addition, different units can cooperate to adjust the layout in the virtual joint R & D space to achieve collaborative optimization of the layout. Finally, each unit broadcasts the content of its adjustment in the metaverse space.

[0064] In specific implementation, as described in step S6, it includes: the processing process of the joint simulation of the workshop logistics system. Specifically, after the construction of the digital twin model of the workshop logistics is completed, in order to verify whether the workshop logistics plan meets the design requirements and reduce the situations of redundant design and under-design, it is necessary to simulate and optimize the workshop logistics plan based on the digital twin model. To reduce the computational overhead of the simulation of the complex workshop logistics system and improve the simulation efficiency, the present invention adopts the method of distributed joint dynamic simulation, and the specific process is as follows: S6-1: Simulation Task Domain Division The entire joint dynamic simulation task domain of the workshop logistics system can be divided into 1 joint simulation domain and several sub-simulation domains. The sub-simulation domains include the material flow dynamic simulation domain, the equipment dynamic simulation domain, the workshop structure dynamic simulation domain, the manual operation simulation domain, etc. The joint simulation domain J is the coupling of the sub-simulation domains which is expressed by the formula: J = (1) Each sub-simulation domain has its specific task objectives. There is data flow between sub-simulation domains, and they are respectively responsible for different units, and the hardware terminals for simulation calculations are respectively set in different units. Each unit is responsible for the simulation tasks of the corresponding sub-simulation domain, and can also further subdivide the responsible sub-simulation domain to meet the task requirements of its simulation domain.

[0065] The physical flow dynamic simulation domain focuses on the physical flow process of goods in the workshop logistics system, including links such as goods inbound, storage, sorting, and outbound. This simulation domain needs to consider factors such as the types, quantities, flow rate changes of goods, and the transfer logic between different goods to simulate the dynamic flow of goods in the system and the logistics scheduling algorithm.

[0066] The equipment dynamic simulation domain mainly focuses on the operating status and performance of various logistics equipment, such as forklifts, conveyors, automated sorting equipment, etc. In this sub-simulation domain, the working processes of equipment such as startup, operation, and stop need to be carefully simulated, and performance indicators such as the working efficiency, energy consumption, and probability of failure of the equipment are analyzed.

[0067] The plant structure dynamic simulation domain focuses on studying the mechanical properties and stability of the civil engineering structure of the logistics plant under different working conditions. Analyze the structural stress distribution, deformation, and seismic performance of the plant under external forces such as bearing goods, equipment operation vibration, and natural disasters to ensure the safety and reliability of the plant structure.

[0068] The manual operation simulation domain emphasizes the role of human factors in workshop logistics operations. By allowing the client to select actual operators to wear XR devices and enter the metaverse space for simulation interaction, manual operation links such as manual picking of goods and manual operation of forklifts for handling are simulated, considering factors such as the operating habits, fatigue levels, and fluctuations in work efficiency of personnel on the entire workshop logistics system.

[0069] Data interaction interfaces are configured between simulation domains to ensure the simulation data and collaborative interaction between the digital twin models of different simulation domains, and finally achieve joint dynamic simulation and optimization.

[0070] S6-2: Simulation Data Driven and Interactive Collaboration Create a simulation data stream according to the workshop logistics plan , and the logistics solution provider initiates a joint simulation on the platform. When performing the simulation, the digital twin models of each sub-simulation domain perform dynamic adjustment and operation according to the received simulation data stream and perform the simulation according to the actual workshop logistics operation logic. For example, when the goods flow rate in the physical flow dynamic simulation domain changes, the corresponding data will pass through the simulation data stream It is passed to the equipment dynamic simulation domain, and the equipment digital twin model in the equipment dynamic simulation domain will adjust its own operating parameters according to the change of the cargo flow, such as accelerating or decelerating the conveying speed, to adapt to the new logistics requirements.

[0071] There is a close data flow and collaborative interaction relationship between each sub-simulation domain to achieve joint dynamic simulation, ensuring that each sub-simulation domain 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, performs calculations and updates according to these data and its own model logic, and then feeds the generated new data back into the simulation data stream for other sub-simulation domains to use. For example, the factory building structure dynamic simulation domain analyzes the impact of the vibration generated by equipment operation and the weight distribution of cargo storage on the factory building structure, and feeds the structure stress and deformation data back into the simulation data stream ; the operation behavior data of the operators in the manual operation simulation domain will also affect the cargo flow speed and path selection in the material flow dynamic simulation domain. Under such data interaction and cooperation of each sub-simulation domain, a comprehensive and dynamic simulation of the workshop logistics system is realized.

[0072] S6-3: Distributed Computing and Data Encryption Driven by the simulation data stream start the distributed computing mode, that is, the simulation calculation tasks of each sub-simulation domain are respectively responsible for execution by the local hardware terminals of relevant units. These local terminals have independent edge computing capabilities and realize data interaction and collaborative work with other sub-simulation domains through the communication interface with the metaverse platform, avoiding the computing bottleneck and single point of failure problems that may be brought by centralized computing, improving the reliability and scalability of the entire joint simulation system, and thus improving the simulation efficiency of complex systems.

[0073] At the same time, to ensure the privacy of data transmission, the responsible units of each simulation domain use blockchain technology for encryption to ensure data security. In the data encryption process, the elliptic curve encryption algorithm ECC is used. For the simulation data to be transmitted , the joint simulation data encryption process is expressed as: (2) where is the public key, is the encrypted simulation data. Only the receiving party with the corresponding private key can decrypt the encrypted data, effectively preventing the data from being stolen or tampered with during transmission.

[0074] S6-4: Simulation Visualization and Feedback Optimization Through 3D visualization technology, the simulation process and results are presented in real-time dynamically in 3D in the joint R & D space, enabling the digital twin model of the workshop logistics system in the metaverse to intuitively simulate the real production situation.

[0075] During the joint dynamic simulation process, each sub-simulation domain real-time feeds back the simulation results to the metaverse platform. The platform comprehensively analyzes and evaluates these feedback data to determine whether the operation of the logistics system meets the design requirements. If it is found that the simulation results of a certain sub-simulation domain are abnormal or do not meet expectations, the platform will promptly send adjustment instructions to the corresponding sub-simulation domain. The sub-simulation domain adjusts its model parameters or operation logic according to the instructions and then continues the simulation to ensure that the entire joint dynamic simulation process can accurately simulate the actual operation of the workshop logistics system and continuously optimize the logistics plan.

[0076] S6-5: Simulation report production After completing all joint simulation work, the logistics solution provider produces a detailed simulation result report. This report is a comprehensive summary of the simulation process and results of the entire workshop logistics system, covering multiple important aspects, including performance index analysis, production capacity evaluation, equipment utilization analysis, energy consumption analysis, etc., and uses a combination of charts, data tables, and text descriptions to ensure that the owner can intuitively and clearly understand the simulation results. At the same time, on the metaverse platform, various types of data generated during the simulation process are integrated and optimized to ensure the accuracy and integrity of the data, and a data query terminal is set up in the virtual space. The owner can click on the terminal to select the data category to view, and the system will present the relevant data in a visual way (such as dynamic data annotation on the 3D model, virtual chart display, etc.).

[0077] S6-6: Simulation result confirmation After the owner obtains the permission to enter the metaverse joint R & D space, he can use a variety of interaction modes to comprehensively confirm the integration and simulation results of the logistics system.

[0078] In terms of the application of interaction modes, through the zoom-in function, the owner can carefully observe the detailed structure of the equipment, the packaging labels of the goods, etc.; the zoom-out function enables the owner to view the layout and process of the entire workshop logistics system from a macroscopic perspective; the shuttle function allows the owner to freely move in the virtual space, simulate the walking path in the actual warehouse, and experience the logistics connection between different areas; the teleportation function enables the owner to quickly reach the specified location or scene, improving the viewing efficiency.

[0079] The client party focuses on confirming whether the design of the workshop logistics solution meets its own business needs and expected goals. In terms of production efficiency, check whether the system capacity, efficiency, and energy consumption conform to the expected production rhythm; in terms of equipment configuration, check whether the equipment selection and layout are reasonable and can meet the actual operation requirements; in terms of personnel operation, evaluate whether the design of the manual operation link conforms to the actual work process and safety specifications.

[0080] During the client's confirmation process, if any problems are found or any questions arise, real-time communication can be carried out with the relevant parties through the online communication function of the metaverse platform. All parties can hold meetings in the virtual space to conduct in-depth discussions and analyses on the issues raised by the client party.

[0081] In specific implementation, as described in step S7, it includes: digital delivery of the workshop logistics system. Specifically, After the client party confirms that the design of the workshop logistics solution meets the requirements, the solution provider takes the lead in initiating digital delivery work on the joint R & D platform.

[0082] S7-1: Collaborative development of the digital twin system The equipment supplier and the civil engineering design institute open the interface call permission of the digital twin model of the equipment or workshop to the logistics solution provider. Based on this permission, the logistics solution provider can directly develop the workshop logistics digital twin system on this joint R & D platform using the digital twin system development tool, and there is no need to ask the equipment supplier and the civil engineering design institute for the digital twin model, avoiding technology leakage caused by model transmission. At the same time, the solution provider can invite the equipment supplier to participate in the collaborative development of the digital twin system, provide basic functional module components, and integrate them into the digital twin system to improve the system development efficiency.

[0083] S7-2: Forward and reverse digital delivery After the development of the workshop logistics digital twin system is completed, the logistics integrator collaborates with the equipment supplier and the civil engineering design institute to package digital assets such as the digital twin model of workshop elements, simulation data, intelligent algorithms, and operation and maintenance knowledge bases into the workshop logistics digital twin system, and deploy the workshop logistics digital system to the local end, local area network, or metaverse platform of the client party according to the actual needs and application scenarios of the client party, for guiding the implementation, production, and operation and maintenance of the logistics system, and realizing the forward digital delivery of the workshop logistics system based on the digital twin system.

[0084] If system maintenance and update are required, the client party connects the metaverse joint R & D platform with the workshop logistics digital twin system through the data interface to download the update package. At the same time, the client party can upload the system usage and 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 the data to relevant units to promote product optimization and improvement, and realizes reverse digital delivery.

[0085] In specific implementation, please refer to Figure 3 , Figure 3 which is a schematic diagram of the system composition jointly developed for the metaverse-based workshop logistics system shown according to an exemplary embodiment. The system includes: An acquisition module 30, configured to acquire first request information of a preset logistics solution provider; A first processing module 31, configured to utilize the first request information of the logistics solution provider to construct a virtual joint R & D space for workshop logistics, and perform permission allocation for target users by using the virtual joint R & D space for workshop logistics; A second processing module 32, configured to acquire second request information of a preset logistics solution provider, and use the second request information of the logistics solution provider and the result of permission allocation for target users by using the virtual joint R & D space for workshop logistics, to enable relevant target users to participate in the meeting and dock requirements according to the digital human role, and apply a preset large model to process the requirement docking content, and generate a digitally demanded document that is encrypted and stored in the metaverse distributed data center in real time; A third processing module 33, configured to convert the digitally demanded document that is encrypted and stored in the metaverse distributed data center in real time into a digital drawing that supports various interactive operations and reflects layout information in real time by using a preset algorithm; A fourth processing module 34, configured to perform collaborative modeling on a preset workshop logistics system according to the field by using the digital drawing that supports various interactive operations and reflects layout information in real time; A fifth processing module 35, configured to utilize the result of collaborative modeling on a preset workshop logistics system, and simulate and optimize a preset workshop logistics plan by using a preset digital twin model through a distributed joint dynamic simulation method; A sixth processing module 36, configured to realize digital delivery of the workshop logistics system by using the result of simulating and optimizing a preset workshop logistics plan.

[0086] Furthermore, the present invention mainly includes the following beneficial effects: Enhance immersion and collaboration, reduce the risk of information leakage: The present invention integrates multiple technologies such as metaverse virtual space management, XR, and digital humans to construct a highly realistic virtual joint R & D space. Personnel from all parties enter it in the form of digital human characters and can achieve interactive collaboration as in the real world with the help of auxiliary tools such as digital drawings and virtual guiding elements. When discussing the layout of workshop logistics equipment, through VR devices, all parties can feel the layout effect immersive, intuitively point out problems and modify them in real time. This immersive experience greatly improves participation and promotes close collaboration. At the same time, compared with the traditional frequent transmission of technical materials and models, the platform adopts permission management and blockchain data encryption technology to strictly restrict data access. Different units and roles can only obtain authorized information, fundamentally reducing the risk of technology leakage.

[0087] Comprehensive simulation analysis to improve the scientificity of design: Introduce factory building structure simulation and personnel operation simulation to comprehensively simulate the workshop logistics system solution. In terms of factory building structure simulation, it can accurately analyze the mechanical properties and stability of the factory building under different working conditions such as carrying goods, equipment vibration, and natural disasters, optimize the design in advance, and avoid potential safety hazards in actual use. Personnel operation simulation allows actual operators to wear XR devices to simulate operations, fully considering the influence of factors such as personnel operation habits and fatigue levels on the logistics system, making the logistics plan more in line with the actual operation scenario, further improving the scientificity and rationality of system design, and reducing problems in actual operation.

[0088] Improve simulation efficiency and ensure data security: Adopt distributed joint dynamic simulation and blockchain data encryption technology, combined with the simulation domain allocation mechanism, to disperse complex simulation calculation tasks to local hardware terminals of all parties for execution. Each sub-simulation domain, such as the material flow dynamic simulation domain and the equipment dynamic simulation domain, is responsible for different units, and uses the edge computing capabilities of local terminals for parallel computing, avoiding the bottleneck of centralized computing, greatly reducing the computing overhead and cost, and significantly improving the R & D efficiency. During data transmission, use blockchain encryption technology, such as the elliptic curve encryption algorithm ECC, to encrypt simulation data, and only the receiving party with the corresponding private key can decrypt it, effectively ensuring data security and preventing data from being stolen or tampered with during transmission.

[0089] Implement two-way digital delivery and enhance delivery capabilities: By jointly developing and deploying a digital twin system for workshop logistics, establish a data transmission mechanism between the platform and the digital twin system to achieve forward and reverse digital delivery. During forward delivery, digital assets such as digital twin models of workshop elements, simulation data, and intelligent algorithms are packaged into the system and deployed to the corresponding platform according to the needs of the owner, 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 and maintenance data to the joint R & D platform through the data interface, and the platform automatically analyzes and distributes the data to relevant units, promoting continuous optimization and improvement of the product, effectively improving the delivery capabilities of the workshop logistics system, and meeting the long-term usage and system upgrade needs of the owner.

[0090] It can be understood that the same or similar parts in the above embodiments can be referred to each other, and the content not detailed in some embodiments can be referred to the same or similar content in other embodiments.

[0091] It should be noted that in the description of the present invention, terms such as "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "a plurality of" refers to at least two.

[0092] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in a reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the technical field of the embodiments of the present invention.

[0093] It should be understood that each part of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following well-known technologies in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0094] Those of ordinary skill in the technical field of the present invention can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant 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 embodiments.

[0095] In addition, each functional unit in various embodiments of the present invention may be integrated into a processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0096] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, or the like.

[0097] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0098] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to 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 research and development space, and using the workshop logistics virtual joint research and development space to allocate permissions to target users; Obtain the second request information of the preset logistics solution provider, and use the second request information of the logistics solution provider and the result of the authority allocation of the target user 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 demand docking content, and generate a real-time updated digital demand document encrypted and stored in the Metaverse distributed data center; Using a preset algorithm, the real-time updated encrypted digital requirement document stored in the Metaverse distributed data center is converted into a real-time updated digital drawing that supports multiple interactive operations and reflects layout information; By 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 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; By utilizing the results of simulating and optimizing the preset workshop logistics plan, digital delivery of the workshop logistics system is achieved.

2. The method according to claim 1, characterized in that The using the first request information of the logistics solution provider to construct a workshop logistics virtual joint research and development space, and using the workshop logistics virtual joint research and development space to allocate rights 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 workshop logistics virtual joint R&D space; By utilizing the results of constructing a virtual joint R&D space for workshop logistics, based on the RBAC model and dynamic permission allocation strategy, access rights are allocated according to the roles and responsibilities of different participants in the project.

3. The method according to claim 1, characterized in that: The method uses a preset algorithm to convert the encrypted digital requirement document stored in the Metaverse distributed data center and updated in real time into a digital drawing that supports multiple interactive operations and reflects layout information and is updated in real time, including: Using the preset system engineering analysis tools and logistics system planning algorithms, determine the interrelationships and spatial layout principles of the various functional areas of the preset workshop logistics system, and generate the preset workshop logistics system CAD drawings containing quantitative and qualitative information, precise dimensions, locations and annotations; The interactive function is developed by utilizing the human-computer interaction and virtual reality interaction principles 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, characterized in that 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, construct virtual guidance elements in the workshop logistics virtual joint R&D space based on computer graphics and space positioning technology; By using 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 build and upload the digital twin models of their respective fields in parallel, 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.

5. The method according to claim 4, characterized in that 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 result 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 to construct a physical dimension model; Also, use algorithm simulation analysis software to model and analyze the logistics flow rules, 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.

6. The method according to claim 4, characterized in that The digital twin model is adjusted and optimized by 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 deviation or size deviation is detected in the layout, the model position where the error is located will be prompted by voice and visual elements, and the error area and deviation value will be clearly marked on the digital drawing; The model is adjusted through a variety of interactive methods. After the adjustment is completed, the system performs layout detection again until it meets the requirements.

7. The method according to claim 1, characterized in that The method utilizes the result of collaborative modeling of the preset workshop logistics system and utilizes the preset digital twin model to simulate and optimize the preset workshop logistics solution 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 a plurality of sub-simulation domains; The digital twin models of each sub-simulation domain are dynamically adjusted and calculated 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, and performs calculations and updates based on these data and its own model logic, and then feeds the generated new data back to the simulation data stream, and uses the simulation data stream for use by other sub-simulation domains to obtain a second processing result; Using the first processing result and the second processing result, a distributed computing mode driven by simulation data flow is executed, and the computing tasks of each sub-simulation domain are executed by the local hardware terminals of the relevant units. The edge computing capabilities and communication interfaces are used to realize data interaction and collaboration, and blockchain technology is combined with the elliptic curve encryption algorithm ECC to encrypt various transmission data exchanged between the sub-simulation domains during the joint simulation of the workshop logistics system, so as to obtain a third processing result; Using 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 an abnormality is found, an adjustment instruction is sent to the corresponding sub-simulation domain to urge it to adjust the model parameters or run the logic and continue the simulation, so as to accurately simulate and optimize the logistics plan and obtain the fourth processing result. The fourth processing result is used to prepare a simulation report and confirm the simulation result.

8. The method according to claim 7, 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, there is data flow between the sub-simulation domains, and they are each 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 to meet the task requirements of its simulation domain.

9. 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 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.

10. A system for joint development of a preset workshop logistics system based on a metaverse, applied to a method for joint development of a preset workshop logistics system based on a metaverse as described in any one of claims 1 to 9, characterized in that: The system comprises: An acquisition module, used to acquire first request information of a preset logistics solution provider; A first processing module is used to construct a workshop logistics virtual joint research and development space by using the first request information of the logistics solution provider, and to allocate rights to target users by using the workshop logistics virtual joint research and development space; The second processing module 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 result of the authority allocation of the target user in the workshop logistics virtual joint R&D space to enable 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 encrypted and stored in the Metaverse distributed data center; A third processing module is used to convert the encrypted digital requirement document stored in the Metaverse distributed data center and updated in real time into a digital drawing that supports multiple interactive operations and reflects layout information and is updated in real time using a preset algorithm; A fourth processing module is used to collaboratively model the preset workshop logistics system according to the field by using the real-time updated digital drawings that support multiple interactive operations and reflect layout information; A fifth processing module is used to utilize the result of collaborative modeling 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; The sixth processing module is used to realize the digital delivery of the workshop logistics system by utilizing the results of simulating and optimizing the preset workshop logistics plan.

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