Mine engineering design data management method and device based on structured flow tree

Abstract

The application discloses a mine engineering design data management method and device based on a structured flow tree, relates to the technical field of data processing, and constructs a digital design flow tree based on a preset professional template, and no longer relies on manual establishment; a data model is established for each flow node, which not only contains information of a design task itself, but also contains input and output data and a dependency relationship, isolated design tasks are converted into logical units with definite data interfaces, efficient data circulation is realized, and the data acquisition cost of cross-department is reduced. When new data is output by a certain flow node, the downstream flow nodes affected are determined according to the dependency relationship, the data model is updated, and the corresponding designers are informed, so that the downstream flow nodes always refer to the latest upstream output results, and design conflicts and version confusion caused by data lag are eliminated. Through complete recording of the whole process from data generation to use, the circulation efficiency and collaborative accuracy of mine design data are significantly improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method and apparatus for managing mining engineering design data based on a structured process tree. Background Technology

[0002] As mining engineering transforms towards digitalization and intelligence, mine design has gradually evolved from traditional two-dimensional CAD drawing to three-dimensional digital collaborative design. A complete mine design project typically involves multiple disciplines such as geology, mining, surveying, ventilation, transportation, water supply and drainage, and power supply and distribution. There are complex process connections and data dependencies between these disciplines, and a large amount of structured and unstructured data are generated simultaneously during the design process.

[0003] In related technologies, the following solutions are mainly adopted for mine design processes and data management: First, a file directory-based management solution, where each discipline creates folders on a shared server according to project, discipline, and stage, classifying and storing design deliverables, and relying on manual agreements for data transfer; second, a solution based on general project management software, using Gantt charts or network diagrams to display task schedules and dependencies, but the management object is tasks rather than data; third, the introduction of manufacturing PDM / PLM systems, but their data models are geared towards product BOMs and are difficult to adapt to the process organization needs of mine engineering based on spatial areas and disciplines. The applicant recognizes that the file directory-based or general project management software-based management models require designers to switch between multiple systems to find the required data when performing tasks, resulting in low data acquisition efficiency; in multi-disciplinary parallel design scenarios, existing solutions are prone to version confusion, design conflicts, and data overwriting, failing to guarantee data consistency and accuracy, and making it difficult for project managers to effectively control and trace the design process, resulting in problems such as low mine engineering design efficiency, poor data consistency, and poor progress visualization. Summary of the Invention

[0004] In view of this, this application provides a method and apparatus for managing mine engineering design data based on a structured process tree, the main purpose of which is to solve the problems of low design efficiency, poor data consistency and poor progress visualization in existing mine engineering designs.

[0005] According to the first aspect of this application, a method for managing mine engineering design data based on a structured process tree is provided, the method comprising: Obtain design data for mining engineering projects, and construct a digital design process tree for the mining engineering projects based on a pre-set professional template library. The design data is used to build a data model for each process node in the digital design process tree. The data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison index role information. The output deliverable list is used to index the structured and unstructured data output by the process node. The dependency reference list is used to record the directed acyclic dependencies between the process node and other process nodes. When an update to the output deliverables list of a certain process node is detected, at least one downstream process node of the process node is determined based on the dependency reference list of other process nodes in the digital design process tree. The data model of the at least one downstream process node is updated, and a change notification is pushed to the designer of each downstream process node.

[0006] According to a second aspect of this application, a mine engineering design data management device based on a structured process tree is provided, the device comprising: The process tree construction module is used to acquire design data for mining engineering projects and, based on a preset professional template library, construct a digital design process tree for the mining engineering project using the design data. The data model building module is used to build a data model for each process node in the digital design process tree using the design data. The data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison index role information. The output deliverable list is used to index the structured and unstructured data output by the process node, and the dependency reference list is used to record the directed acyclic dependencies between the process node and other process nodes. The data update module is used to determine at least one downstream process node of a process node based on the dependency reference list of other process nodes in the digital design process tree when an update is detected in the output deliverable list of a certain process node, update the data model of the at least one downstream process node, and push a change notification to the designer of each downstream process node.

[0007] By employing the above-described technical solution, the technical solution provided in this application has at least the following advantages: This application provides a method and apparatus for managing mine engineering design data based on a structured process tree. This method eliminates the reliance on manually creating folders or task lists. Instead, it uses a pre-set professional template library to construct a visualized digital design process tree based on the design data of the mine engineering project, building a standardized digital skeleton for the entire mine design project. Then, based on the design data, a data model is established for each process node within the digital design process tree. This data model not only includes information about the design task itself but also input data, output data, and dependencies, transforming previously isolated design tasks into logical units with clearly defined data interfaces. Through clear input and output interface definitions, designers from various disciplines can intuitively see the location and provider of their required data through the digital design process tree, achieving efficient data flow and significantly reducing cross-departmental data acquisition costs. Furthermore, the data model incorporates professional category information and node information, allowing for optimization specifically for the multi-disciplinary and strongly spatially dependent characteristics of mines, perfectly meeting the actual needs of the digital and intelligent transformation of mine engineering. When an update to the output deliverables list of a certain process node is detected, this application determines at least one downstream process node based on the dependency reference list of other process nodes in the digital design process tree. The data model of the downstream process node is then updated, and a change notification is pushed to the designers of each downstream process node. This automatic update mechanism ensures that downstream process nodes always reference the latest upstream output deliverables, eliminating numerous design conflicts and version confusion caused by data lag. Simultaneously, because a complete dependency reference list is established in the data model, the system can fully record the entire process from data generation to use. Managers can clearly trace the source of any design deliverable through the digital design process tree, achieving refined project progress management and clear definition of design responsibilities. This significantly improves the efficiency and accuracy of mine design data flow and collaboration, enhancing the overall project progress speed and management transparency.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1A flowchart illustrating a mine engineering design data management method based on a structured process tree, provided in an embodiment of this application, is shown. Figure 2 This paper illustrates a flowchart of another mine engineering design data management method based on a structured process tree, as provided in an embodiment of this application. Figure 3 This illustration shows a structural schematic diagram of a mine engineering design data management device based on a structured process tree, as provided in an embodiment of this application. Figure 4 This invention provides a schematic diagram of another mine engineering design data management device based on a structured process tree, as illustrated in an embodiment of this application. Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of this application is shown. Detailed Implementation

[0010] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0011] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0012] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0013] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0014] A complete mine design project typically covers multiple disciplines and design stages, including geological exploration and modeling, selection of mining methods, design of development and transportation systems, design of ventilation systems, design of water supply and drainage systems, design of power supply and distribution systems, layout of surface industrial sites, infrastructure schedule, and mining production plan. There are close data dependencies between these disciplines. For example, the design of development and transportation systems depends on the determination of geological models and mining methods, and the design of ventilation systems depends on the layout of roadways in the development system.

[0015] With the popularization of digital technology in the field of engineering design, mine design is gradually transforming from traditional two-dimensional CAD drawing to three-dimensional digital design. Currently, widely used mine design software such as Surpac, DIMINE, and 3DMine have functions such as three-dimensional geological modeling, ore body model construction, and mining design. However, these software mainly focus on the functional implementation of a single discipline or a single design stage, lacking the ability to uniformly organize and manage data for the entire mine engineering design process.

[0016] In the field of building engineering, BIM (Building Information Modeling) technology has largely solved the information integration problem in multi-disciplinary collaborative design. Inspired by this, the mining industry has also begun to explore the concepts and methods of MIM (Mine Information Modeling). However, due to significant differences between mining engineering and building engineering in terms of design objects, design processes, and data types, mature BIM solutions cannot be directly transferred to mining engineering design.

[0017] Existing technical solutions include mine design data management solutions based on file directory management, mine design process management solutions based on project management software, and engineering data management solutions based on PDM / PLM systems.

[0018] File directory-based mining design data management solutions are currently the most common practice in the industry. Each design specialty establishes a hierarchical folder directory structure on a shared file server or local disk, categorized by project number, specialty name, design stage, etc., storing design deliverables such as drawings, documents, and model files in corresponding folders. This allows project managers to organize and locate design materials through the directory structure. For example, a three-level directory structure of "Project Name / Specialty Name / Design Stage" can be established on the file server. Designers from each specialty store completed design files in the corresponding directories according to agreed-upon naming rules. Data transfer between specialties is achieved through file copying or reading from the shared directory. However, the file directory structure can only reflect the static classification and storage relationship of data, and cannot express the dynamic logical sequence of the design process and the data dependencies between disciplines. Designers cannot intuitively know from the directory structure "which results of the previous steps are required as input for the current step" and "which subsequent steps will be used as input for the results of the current step". Secondly, structured data such as parameter tables and statistical data are scattered in different forms in the file directory with unstructured data such as models, drawings and documents. The two lack a connection and binding mechanism under the same logical node, and designers need to rely on experience to find the required data in multiple places. In addition, when multiple people operate in parallel, problems such as file overwriting and version confusion are prone to occur, and there is a lack of effective version management and data consistency guarantee mechanisms.

[0019] Some mining design institutes use general-purpose project management software, such as Microsoft Project and Primavera P6, to manage their design processes. While these software programs can display the timeline and dependencies of design tasks using Gantt charts and network diagrams, their management focus is on tasks and time, not design data and tools. Therefore, these programs can only specify when to complete which task, but cannot directly link the required input data, design tools, or outputs. Designers need to frequently switch between project management software and various specialized design software programs. Furthermore, these programs lack the ability to identify and manage data specific to the mining design field, such as 3D geological models and ore body models.

[0020] Product Data Management (PDM) and Product Lifecycle Management (PLM) systems are widely used in manufacturing, managing documents, bills of materials (BOMs), workflows, and other content related to the product design process. Currently, some literature and practices have attempted to introduce PDM / PLM systems into the field of mining engineering design. However, the data models and workflow models of general PDM / PLM systems are primarily geared towards manufacturing product design, while the process logic of mining engineering design differs fundamentally from that of manufacturing product design: the BOM-oriented data organization in manufacturing product design is unsuitable for the process organization requirements of mining engineering design, which is based on spatial regions and design specialties; mining design places greater emphasis on multi-scheme comparison under spatial relationships and geological constraints, and the proportion of unstructured data such as 3D geological models and large CAD atlases is far higher than in manufacturing. These characteristics result in insufficient adaptability of general PDM / PLM systems in mining design scenarios.

[0021] To address this issue, this application proposes a mine engineering design data management method based on a structured process tree. This method organizes the design processes of various mine engineering disciplines into a unified tree-like hierarchical structure. Each process node is associated with corresponding design tool interfaces, input data references, and output deliverable references, allowing designers to intuitively grasp and execute the entire design process through a tree-like navigation interface. Under the same process node, it achieves unified association management of structured design data and unstructured design deliverables, eliminating data silos. Relying on a unified cloud-based data management architecture, it maintains data consistency and achieves real-time sharing in multi-disciplinary parallel design scenarios through dependency identification and data synchronization mechanisms between process nodes. The status markers of process tree nodes enable visual display of design progress and traceability of the design process. The implementing entity of this application can be a mine engineering design data management system based on a structured process tree. This system relies on the computing power of a server to provide services to users. The server can be an independent server or a server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0022] This application provides a method for managing mine engineering design data based on a structured process tree, such as... Figure 1 As shown, the method includes: 101. Obtain the design data of the mining project, and construct a digital design process tree for the mining project based on the pre-set professional template library.

[0023] In this embodiment, the design data for a mining project refers to various basic information and raw data generated or collected during the project's early planning, feasibility study, preliminary design, and construction drawing design stages. The pre-established professional template library is a standardized database that stores standard workflow templates for different mining specialties, categorized by specialty such as mining, geology, ventilation, electromechanical, and mineral processing. Each template defines the standard design procedures, logical relationships between procedures, required input conditions, and standard deliverables for that specialty. For example, the mining specialty sequentially includes development design, stope design, and longwall mining process design.

[0024] A digital design process tree is a model that visually reconstructs a mine design project in a software system according to professional division of labor and the logical sequence of procedures, using a hierarchical tree structure. It is not simply a task list, but a dynamic digital skeleton: the root node corresponds to the entire mine project, first-level branches correspond to various specialties, second-level branches correspond to specific stages of each specialty, and leaf nodes correspond to specific individual design tasks. Collected actual design data is used as node filler, filling the preset framework in the template with specific task nodes and connecting them into a network, ultimately generating a digital design process tree specific to the project. Project managers can clearly grasp the overall picture of the project, the intersections of various specialties, and the current progress bottlenecks; at the same time, it ensures that different projects and different design teams follow unified quality standards and procedural logic when executing the same type of design, reducing human error and eliminating the need to plan the project process from scratch, greatly shortening the preparation and planning time in the early stages of the project. It adapts to the characteristics of multi-disciplinary collaboration in mines and solves the pain point of traditional mine design processes' difficulty in global control.

[0025] 102. Use design data to build a data model for each process node in the digital design process tree.

[0026] In this embodiment, the data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison index role information. Specifically, the professional category information distinguishes mining specialties such as geology, mining, ventilation, transportation, and electromechanical engineering; the design tool reference information binds the software required to complete the design task of this process node, such as mining 3D modeling software, ventilation simulation software, and CAD; the output deliverable list indexes the structured and unstructured data output by the process node; and the dependency reference list records the directed acyclic dependencies between the current process node and other process nodes. This model transforms design procedures that originally only had business significance into computer-recognizable, searchable, and interconnected data objects, completely encapsulating the full-dimensional information of a single process node's input, output, tools, specialties, dependencies, and status. The data model thoroughly solves the problems of unclear data ownership and version confusion, allowing for precise traceability of the input source and output destination of each process node, providing underlying data support for subsequent automatic reminders, automatic task distribution, and automatic status updates. In addition, this data model is specifically designed for the multi-disciplinary and strongly coupled characteristics of mining engineering, and can effectively handle the complex data dependencies between spatial regions and disciplines.

[0027] 103. When an update to the output deliverables list of a certain process node is detected, determine at least one downstream process node of the process node based on the dependency reference list of other process nodes in the digital design process tree, update the data model of at least one downstream process node, and push a change notification to the designer of each downstream process node.

[0028] In this embodiment, an update to the output deliverables list typically refers to a file being overwritten and saved, a new version being uploaded, or key parameters being modified and confirmed. Upon detecting an update event at any process node, the system retrieves the dependency reference list of all process nodes within the digital design process tree, filters out all downstream process nodes that use the current process node as an input source, updates the data model of each downstream process node, and then matches the designer's account corresponding to the downstream node, sending a targeted change notification to inform the upstream process of the changes. This mechanism can replace manual communication, solving the problem of missed changes during multi-disciplinary collaboration in mines; simultaneously, by automating process updates, it ensures the consistency and timeliness of the data flow throughout the project, avoiding major design errors or rework caused by using old versions of data. Furthermore, managers can view in real time which process nodes have undergone state transitions due to upstream changes, thereby accurately controlling the dynamic risks of the project.

[0029] This application provides a method for managing mine engineering design data based on a structured process tree. Compared with existing technologies, this application eliminates the need for manually creating folders or task lists. Instead, it uses a pre-set professional template library to construct a visualized digital design process tree based on the design data of the mine engineering project, building a standardized digital skeleton for the entire mine design project. Then, a data model is established for each process node within the digital design process tree based on the design data. This data model includes not only information about the design task itself but also input data, output data, and dependencies, transforming previously isolated design tasks into logical units with clearly defined data interfaces. Through clear input and output interface definitions, designers from various disciplines can intuitively see the location and provider of their required data through the digital design process tree, achieving efficient data flow and significantly reducing cross-departmental data acquisition costs. Furthermore, the data model incorporates professional category information and node information, specifically optimized for the multi-disciplinary and strongly spatially dependent characteristics of mines, perfectly meeting the actual needs of the digital and intelligent transformation of mine engineering. When an update to the output deliverables list of a certain process node is detected, this application determines at least one downstream process node based on the dependency reference list of other process nodes in the digital design process tree. The data model of the downstream process node is then updated, and a change notification is pushed to the designers of each downstream process node. This automatic update mechanism ensures that downstream process nodes always reference the latest upstream output deliverables, eliminating numerous design conflicts and version confusion caused by data lag. Simultaneously, because a complete dependency reference list is established in the data model, the system can fully record the entire process from data generation to use. Managers can clearly trace the source of any design deliverable through the digital design process tree, achieving refined project progress management and clear definition of design responsibilities. This significantly improves the efficiency and accuracy of mine design data flow and collaboration, enhancing the overall project progress speed and management transparency.

[0030] Furthermore, as a refinement and extension of the specific implementation methods of the above embodiments, and in order to fully illustrate the specific implementation process of this embodiment, this application provides another method for mine engineering design data management based on a structured process tree, such as... Figure 2 As shown, the method includes: 201. Obtain design data for mining engineering projects.

[0031] In this embodiment, the design data for a mining project may specifically include: geological exploration data, such as borehole columnar sections, geological profiles, ore body models, rock mechanics parameters, and hydrogeological data; surveying and mapping data, such as topographic maps of the mining area, control point coordinates, and measured data from mining operations; mining design parameters, such as mining plans, mining methods, development and transportation systems, and stope structure parameters; mineral processing data, such as ore beneficiation test reports, mineral processing flow charts, equipment selection parameters, and tailings disposal plans; and transportation data, such as the overall layout plan of the industrial site, road parameters, pipeline routes, power supply line routes, and transportation... Transportation methods and capacity configurations; building structure data, such as structural design drawings and load parameters for buildings like factories, office buildings, and mine shafts; electromechanical equipment data, such as lists of major equipment, equipment technical specifications, and control system configurations; ventilation data, such as mine ventilation system design data and ventilation network diagrams; water supply and drainage data, such as drainage system design data, water supply system design data, and waterproofing / drainage measures; power supply and distribution data, such as power supply system design data, protection and control data, and electrical equipment parameters; and project information, such as basic project information, personnel organization information, design specifications, and project management information. This data is typically stored in structured formats such as structured Excel spreadsheets, or unstructured file formats such as CAD drawings, PDF documents, and 3D models.

[0032] 202. Based on a pre-set professional template library, construct a digital design process tree for mining engineering projects using design data.

[0033] In this embodiment of the application, a list of professional categories is extracted from the design data. The list of professional categories includes multiple professional categories involved in the mining engineering project, such as geology, mining, surveying, ventilation, transportation, water supply and drainage, power supply and distribution, and surface construction.

[0034] Next, the template subtree corresponding to each professional category is extracted from the preset professional template library. The template subtree consists of multiple nodes with entity attribute labels and is a predefined standard framework containing specific parent-child node hierarchical relationships.

[0035] Subsequently, multiple template subtrees are attached to the root node of the mining engineering project to form an initial process tree skeleton. The root node records the basic information of the mining engineering project, including the project number, project name, and design phase identifier. The root node of each template subtree serves as a first-level branch node of the initial process tree skeleton. At this point, the initial process tree skeleton is not yet linked to actual business data and is in a state of pending activation.

[0036] Finally, adjustments are performed on the initial process tree skeleton based on the design data to generate a digital design process tree. These adjustments include at least one of the following: pruning, disabling, and expanding. Pruning involves deleting nodes corresponding to design tasks not covered by the design data from the initial process tree skeleton. For example, if the project does not involve backfill mining, the "backfill system" node is directly deleted. Disabling marks nodes corresponding to design tasks that are not currently needed in the initial process tree skeleton as disabled, rather than permanently deleting them, to allow for later restoration or traceability. Expanding inserts nodes corresponding to newly added design tasks from the design data into the initial process tree skeleton to accommodate specific or new project requirements.

[0037] After the above adjustments, a digital design process tree is finally generated that perfectly matches the actual situation of the current mining project. This process tree not only has a structured hierarchy, but also establishes a dynamic relationship with actual design data instances. Whether it is conventional open-pit mining or complex underground backfilling mining, it can be quickly adapted through tailoring and expansion, perfectly solving the differences in professional focus of different mining projects.

[0038] In this embodiment, the entire process of mine engineering design is abstracted as a multi-level tree structure, which includes three levels: root node, branch nodes, and leaf nodes. The root node corresponds to the entire mine engineering project and includes top-level basic information such as project number, project name, and design stage identifiers. Design stage identifiers can include feasibility study, preliminary design, and construction drawing design, etc. First-level branch nodes correspond to various professional categories within the mine engineering project. Second-level and lower-level branch nodes correspond to specific design sub-processes and design tasks within each specialty. For example, when the first-level branch node is underground mining, the second-level and lower-level branch nodes include geological models, spatial data, underground mining plans, underground mining methods, underground mining production capacity, underground mining development and transportation systems, shaft and tunnel engineering, filling systems, ventilation systems, underground mining drainage and sludge removal systems, compressed air and water supply systems, auxiliary facilities, underground mining infrastructure quantities, underground mining infrastructure schedules, and underground mining production schedules, etc.

[0039] In one alternative implementation, a directed acyclic graph (DAG) network structure can be used to organize the design process nodes. Compared to a tree structure, a pure DAG structure can more flexibly express many-to-many dependencies between nodes, but its visualization is less intuitive and user-friendly than a tree structure. In practical applications, a hybrid approach can be adopted, using a tree structure as the primary display format and a DAG as the underlying dependency recording format.

[0040] 203. Use design data to build a data model for each process node in the digital design process tree.

[0041] In this embodiment, the data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison indicator role information. The output deliverable list is used to index the structured and unstructured data output by the process nodes, and the dependency reference list is used to record the directed acyclic dependencies between process nodes and other process nodes. The specific construction process is as follows: Traverse each process node in the digital design process tree, and obtain the entity attribute tags for each process node. Entity attribute tags include professionalCategory, taskType, requiredInputType (input data type set), outputArtifactType (output artifact type set), designToolType (design tool type), and comparisonRole (comparison indicator role). For example, the entity attribute tags for the development transportation system design process node are: professionalCategory=Mining, taskType=System Layout, requiredInputType={Mining Scheme, Mining Method}, outputArtifactType={Tunneling Engineering Model, Engineering Quantity Statistics Table, Development System Diagram}.

[0042] For each process node, the node identifier (nodeId), node name (nodeName), node type (nodeType), and parent node identifier (parentNodeId) are determined based on the digitally designed process tree, serving as the node information for the process node. The node name is as shown in the main / auxiliary shaft scheme, the node type is root node / branch node / leaf node, and the parent node identifier is used to construct the tree hierarchy.

[0043] Obtain the professional category, task type, and comparison indicator role contained in the entity attribute tags of the process node. Use the professional category, task type, and comparison indicator role as the professional category information, task type information, and comparison indicator role information of the process node, respectively. The comparison indicator role includes role type and comparison indicator weight coefficient sequence.

[0044] The system retrieves the design tool type contained in the entity attribute tags of the process node, searches for the corresponding design tool reference information (designToolRef) in the configuration tool library, and assigns specific business meaning and execution capabilities to the process node. The design tool reference information includes the design tool name, design tool type, startup parameters, and API call address. The design tool type indicates the category of design tools used for the design task of the process node.

[0045] Obtain the set of output artifact types contained in the entity attribute tags of the process node, generate an empty artifact entry for each output artifact type in the set, and obtain the output artifact list outputArtifacts of the process node. The artifact entry is used to record the entry identifier, output artifact name, output artifact type, data type tag, format storage address and local cache version number. The data type tag is either structured or unstructured.

[0046] It should be noted that the output deliverables of each process node need to be categorized and labeled according to type, so that structured and unstructured data within the same process node can be uniformly indexed and bound to the same source. Structured data, such as sets of design parameters, engineering quantity statistics tables, coordinate data sets, and scheme comparison and scoring tables, are stored in JSON / XML format or relational database tables; unstructured data, such as .dm / .dtm format 3D geological model files, 3D engineering model files, .dwg format CAD drawing files, .docx / .pdf format design specification documents, and development system diagrams, are stored in their original file formats in a cloud object storage service.

[0047] Within each process node, all data is indexed through a unified output artifact reference list, `outputArtifacts`. Each artifact contains a unique identifier, name, type marker, file format, cloud storage address, version number, and update timestamp, and can be associated with structured data such as quantities and design parameters. Furthermore, to ensure the stability of data generation, during the process tree construction phase, the system pre-generates empty slots with entry identifiers based on the artifact type. These slots are then filled in after the actual artifacts are generated, using ID parsing. Simultaneously, once structured and unstructured entries describing the same design object are written under the same process node, the system automatically inherits the same-source binding relationship, ensuring that empty slots return to a "pending output" state when accessed by downstream process nodes and can participate normally in dependency graph operations. For example, an artifact object may contain the following information: {"artifactId":"ART-2025-001", “artifactName”: “3D model of the main and auxiliary shaft development tunnel project” “dataTypeTag”: “Semi-structured” "fileFormat": ".dsm", "storageUrl": "cloud: / / project-DT2501 / mining / shaft-model-v3.dsm", "version": "3.0" "lastModified": "2025-06-15T14:30:00Z", "relatedStructuredData": { "engineeringQuantity": "cloud: / / project-DT2501 / mining / shaft-eq-stats.json", "designParameters":"cloud: / / project-DT2501 / mining / shaft-params.json"}} Based on a dependency determination rule base, at least one preceding dependent process node is matched and determined for each process node. A directed acyclic dependency relationship is constructed using the process node and at least one preceding dependent process node. A dependency reference list `dependencyNodes` for each process node is generated using the directed acyclic dependency relationship and the node identifier of each preceding dependent process node. The dependency determination rule base includes intra-professional dependency determination rules and cross-professional dependency determination rules. Specifically, intra-professional dependency determination involves reading a preset task type sequence from the intra-professional dependency determination rules, determining the logical position of the process node's task type within the preset task type sequence, and taking the task type preceding that logical position as the preceding dependent task type. In the digital design process tree, the process subtree corresponding to the professional category to which the process node belongs is determined, and process nodes within the process subtree whose task type is the preceding dependent task type are taken as preceding dependent process nodes, thus obtaining at least one preceding dependent process node for each process node. For example, the "Development and Transportation System Design" process node depends on the "Geological Mining Scheme" process node and the "Geological Mining Method" process node because the layout of the development system needs to be based on the determined mining scheme and mining method.

[0048] Cross-disciplinary dependency determination: Based on cross-disciplinary dependency determination rules, at least one input data type is obtained from the input data type set. For each input data type, it is matched with the output result type set of other process nodes in the digital design process tree. Process nodes in the output result type set containing the input data type are taken as predecessor dependent process nodes, thus obtaining at least one predecessor dependent process node for each process node. For example, the "Geological Model" process node of the mining discipline uses the 3D geological body model produced by the geology discipline as input data; the "Ventilation Network Model" process node of the ventilation discipline uses the 3D tunnel model produced by the "Shaft and Tunnel Engineering Model" process node of the mining discipline as input data.

[0049] It's important to note that dependencies are recorded in the `dependencyNodes` field of each process node using a Directed Acyclic Graph (DAG). During runtime, the system traverses the DAG to determine the executable status of process nodes and the data update propagation path. A DAG is a graph structure without circular dependencies, ensuring a clear sequence of operations during system execution, preventing deadlocks, and supporting parallel computing or concurrent execution of multiple tasks. Furthermore, within the same discipline, dependencies are generated based on the rule of "matching within the same discipline and task type"; between different disciplines, dependencies are generated based on the rule of "matching requirement type and output type". Different disciplines can configure their own dependency determination rule bases, and all subsequent projects can reuse this logic to ensure the standardization and professionalism of process execution across different projects. For example, in mining, system layout depends on scheme determination, quantity statistics depend on modeling, and schedule planning depends on quantity statistics; in ventilation, network modeling depends on the shaft engineering model, calculation depends on the network model, and equipment selection depends on the calculation results. In the traditional model, engineers need to manually specify the prerequisites for each process node, which is very easy to miss or connect incorrectly. However, by automatically generating input / output references and dependencies through a dependency determination rule base, logical deadlocks or data gaps caused by human configuration errors can be avoided.

[0050] The process involves obtaining the set of input data types contained in the entity attribute tags of each process node, determining at least one input data type included in the set, and obtaining the output deliverable list for each preceding dependent process node. For each input data type, the process matches the input data type against the output deliverable list of each preceding dependent process node, selecting deliverable entries whose output deliverable type matches the input data type as preceding deliverable entries. In this way, by matching each input data type, multiple preceding deliverable entries are obtained. These multiple preceding deliverable entries are then used to generate the input data reference list `inputDataRef` for the process node.

[0051] Initialize the status information nodeStatus for each process node, where the status can be any of the following: Not Started, In Progress, Completed, or Needing Update. The status information of each process node is visualized using an icon nodeIcon. In the visualization interface of the digital design process tree, process nodes in different statuses are distinguished by different icons, enabling project managers to intuitively grasp the completion progress of each discipline and design step of the entire project.

[0052] The "Not Started" status indicates that the design task for the process node has not been initiated, and the output deliverables are empty. Triggering scenarios include project initialization and new node creation. This status is marked with a gray icon in the visual interface of the digital design process tree.

[0053] The "In Progress" status indicates that the design task for the process node has started, some deliverables have been generated, but the design task is not yet complete. This is marked with a yellow icon in the visualization interface of the digital design process tree. In the "In Progress" status, some deliverables can be incrementally added to the corresponding deliverable entries in the deliverable list as drafts, with the draft flag `isDraft=true` and an undecided version number set. Draft deliverables are only visible within this process node or authorized scope and do not trigger downstream change propagation. Once the process node is completed and approved, the draft deliverables will be used as the final deliverables. Then, based on the dependency reference list, the status of downstream referencing nodes will be updated to "Needs Update" and a notification will be sent.

[0054] The "Completed" status indicates that the design task for the process node has been completed, all expected outputs have been generated and passed review and verification, and it is marked with a green icon in the visualization interface of the digital design process tree.

[0055] An update status indicates that the list of output deliverables of the process nodes that are prerequisites of the process node has changed, and the current process node needs to be re-executed to ensure data consistency. This status is marked with a red icon in the visualization interface of the digital design process tree.

[0056] Finally, the data model of the process nodes is generated using node information, professional category information, task type information, comparison indicator role information, design tool reference information, input data reference list, output deliverable list, dependency reference list, and status information.

[0057] It should be noted that the system maintains a version history for each deliverable object at each process node, including the timestamp of each update, operator identification, and version description. Project managers can trace the modification process of a design step by querying the version history of a specific process node. Project managers can also trace the impact of a design decision on downstream professional designs by examining the dependencies between process nodes.

[0058] 204. When an update to the output deliverables list of a certain process node is detected, at least one downstream process node of the process node is determined based on the dependency reference list of other process nodes in the digital design process tree. The data model of at least one downstream process node is updated, and a change notification is pushed to the designer of each downstream process node.

[0059] In this embodiment of the application, when an update to the output results list of a certain process node is detected, the node identifier is read from the data model of the process node, other process nodes in the digital design process tree are traversed, and the process nodes containing the node identifier in the dependency reference list are taken as downstream process nodes, thus obtaining at least one downstream process node.

[0060] For each downstream process node, the input data reference list is read from the data model of the downstream process node, the target prerequisite deliverable item is determined from the input data reference list, and the format storage address and local cache version number indicated by the target prerequisite deliverable item are updated using the updated output deliverable list of the process node. Here, the target prerequisite deliverable item refers to the prerequisite deliverable item that references the output deliverable of the process node.

[0061] In the data model of downstream process nodes, the status information of downstream process nodes is updated to the status that needs to be updated, and marked with a red icon in the visualization interface of the digital design process tree. At the same time, a structured change log is generated, which includes the change timestamp, the node identifier of the process node, the list of output deliverables after the process node is updated, and the node identifier of the downstream process node. The structured change log is stored in the data model of the downstream process node.

[0062] The system identifies the designer information associated with downstream process nodes, generates a node identifier for each process node, a list of updated output deliverables for each process node, and a change notification for the node identifier of the downstream process nodes. This change notification is then pushed to the designers via a pre-defined communication method. The pre-defined communication method uses in-system notifications, but can also integrate with message push interfaces from instant messaging tools such as WeChat Work and DingTalk, or use email notifications to achieve cross-platform push of change information.

[0063] This embodiment breaks through the traditional manual hierarchical notification mode and builds a full-chain intelligent response system. It not only greatly improves the efficiency of cross-departmental and cross-professional collaboration and eliminates data silos and duplication of work caused by information lag, but also ensures the real-time consistency and accuracy of the overall project design data through mandatory status synchronization, thereby reducing the risk of rework from the source and ensuring the overall quality and progress of the engineering design.

[0064] 205. When a user access operation to a certain process node in the digital design process tree is detected, a synchronization operation from the cloud to the local machine is performed.

[0065] In this embodiment, in response to a user's access operation to a process node in the digital design process tree, the input data reference list is read from the data model of the process node. The upstream process node indicated by each preceding deliverable entry in the input data reference list is determined, and the format storage address and local cache version number indicated by each preceding deliverable entry in the input data reference list are obtained.

[0066] For each upstream process node, the system requests the latest version number of the output deliverable from the cloud server and compares it with the local cache version number. If the latest version number matches the local cache version number, the local data is up-to-date, and the system retrieves the corresponding local cache file for the upstream process node's output deliverable based on the format storage address. If the latest version number does not match the local cache version number, the upstream data has been updated, and the system downloads the latest version file for the upstream process node's output deliverable from the cloud server, overwrites the local cache file indicated by the format storage address with the latest version file, and updates the local cache version number to the latest version number. By comparing the version numbers in the cloud and the local cache, the system achieves automatic data updates and accurate synchronization, ensuring that designers always work based on the latest version and avoiding rework or logical conflicts caused by using outdated data.

[0067] This embodiment employs a proactive synchronization method based on version number comparison. Alternative solutions include real-time synchronization, similar to the real-time push mechanism of collaborative document editing tools, or timed polling synchronization. Real-time synchronization places high demands on network bandwidth and server performance, while timed polling may suffer from insufficient data timeliness. The proactive synchronization method based on version number comparison achieves a better balance between performance and timeliness.

[0068] Optionally, the design tool reference information of the process node is read from the data model of the process node, and the design tool type, startup parameters, and call interface address are obtained from the design tool reference information. The design tool used for the design task of the process node is called according to the startup parameters and call interface address, and the format storage addresses indicated by multiple prerequisite deliverable items are passed to the design tool as initialization parameters. When it is detected that the designer has completed the design task and performed a save operation in the design tool according to the initialization parameters, at least one newly generated output deliverable of the process node is collected, and a deliverable item is generated for each output deliverable, resulting in at least one deliverable item. At least one deliverable item is added to the output deliverable list of the process node, and the updated output deliverable list is used to update the data model of the process node. The system can automatically parse the design tool configuration in the process node data model and automatically pass in the prerequisite dependent outputs as initialization parameters, achieving seamless connection from data preparation to tool startup. This highly automated integration can eliminate tedious manual operations, ensure the accuracy of input data, and achieve automated and efficient processing by capturing new deliverables generated by the tool and updating the data model.

[0069] This embodiment achieves integrated invocation of design tools by configuring references and invocation interfaces for design tools in process nodes. Alternatively, a plug-in architecture can be used, embedding the process tree management module as a plug-in into various professional design tools, or a microservice architecture can be used to encapsulate the design tools as remotely invoked services.

[0070] 206. When it is detected that the designer of a certain process node has completed the design task of the process node locally and performed the finalization operation, perform the synchronization operation from local to cloud.

[0071] In this embodiment of the application, when it is detected that the designer of a certain process node has completed the design task of the process node locally and performed the finalization operation, multiple output deliverables generated by the process node are collected, and a deliverable entry is generated for each output deliverable to obtain a list of output deliverables of the process node. The deliverable entry includes an entry identifier, output deliverable name, output deliverable type, data type tag, format storage address and local cache version number, and the data type tag is a structured type or an unstructured type.

[0072] Multiple output deliverables are uploaded to the storage layer of the cloud server. The final storage address and cloud version number of each output deliverable are obtained from the cloud server. Structured data is stored in the structured data storage layer, and unstructured data is stored in the unstructured data storage layer. The structured data storage layer uses a relational database to store structured data such as design parameters and engineering quantity statistics. The unstructured data storage layer uses object storage services to store unstructured data such as model files, drawing files, and document files, and maintains a version chain for each file.

[0073] This embodiment preferably adopts a unified cloud-based data storage architecture. Alternative solutions include centralized server deployment on a local area network (LAN) or a distributed file system for unified data storage. The advantage of a cloud-based architecture lies in its support for remote collaboration and elastic scaling; however, for mining projects with limited network conditions, a LAN deployment may be more suitable. It should be noted that the core process tree data model and data management methods remain unchanged regardless of the deployment architecture.

[0074] Iterate through the output list of process nodes. For each output item, determine the final storage address and cloud version number corresponding to the output item from the final storage address and cloud version number of multiple output items. Update the format storage address in the output item to the final storage address corresponding to the output item, and update the local cache version number in the output item to the cloud version number corresponding to the output item.

[0075] The updated output deliverable list of the process node is stored in the data model of the process node. The status information of the process node is updated to the completed status in the data model of the process node. A finalized structured log is generated, which includes the finalized operator information, the finalized completion timestamp, the node identifier of the process node, and the updated output deliverable list of the process node. The finalized structured log is stored in the data model of the process node.

[0076] Traverse the dependency reference list of other process nodes in the digital design process tree, and designate process nodes containing node identifiers in the dependency reference list as subsequent process nodes, thus obtaining at least one subsequent process node. Update the status information of each subsequent process node in its data model to the required state. Update the data model of at least one subsequent process node and push a change notification to the designer of each subsequent process node.

[0077] When the system detects a local finalization operation, it automatically collects and structures various output results to distinguish between structured and unstructured data, ensuring accurate correspondence between metadata and file entities. Simultaneously, through intelligent comparison and differentiated updates between cloud and local caches, it guarantees data consistency and version control accuracy across multiple terminals. Furthermore, the finalization action triggers automatic cascading updates and real-time notifications to subsequent dependent nodes, breaking down information barriers between disciplines and ensuring the entire design team collaborates based on the same data version, effectively avoiding large-scale rework caused by information lag.

[0078] It should be noted that the system can also refresh and load the latest data status of each process node in the digital design process tree within the same client. When a designer switches to a specific professional view or expands a branch process node, the system will automatically check the data version information of all process nodes under that branch and compare it with the cloud, refreshing the process tree interface display with the latest status information.

[0079] 207. When it is detected that the role information of the comparison indicator in the data model of a certain process node contains a non-empty role type, execute the scheme comparison operation.

[0080] In this embodiment, multiple process nodes in the digital design process tree are traversed. When a process node is detected to have a non-empty role type in its data model's comparison indicator role information, the process node is designated as a solution comparison process node. A dependency reference list is read from the data model of the solution comparison process node, and multiple preceding process nodes are determined based on this list.

[0081] The parent node identifier of each preceding process node is read from the data model of the preceding process node, and the parent node identifier of the scheme comparison process node is read from the data model of the scheme comparison process node. Among multiple preceding process nodes, the preceding process node whose parent node identifier matches that of the scheme comparison process node is selected as the parallel scheme branch process node, resulting in multiple parallel scheme branch process nodes. For example, when the "development and transportation system" is determined as the scheme comparison node, the "main and auxiliary shaft scheme" and the "belt inclined shaft scheme" are further determined as parallel scheme branch process nodes.

[0082] The system continuously monitors the status information of multiple parallel scheme branch process nodes. When it is determined that the status information of multiple parallel scheme branch process nodes is all in the "completed" state, the weight coefficient sequence of the selection indicators is read from the selection indicator role information of the scheme selection process node. This weight coefficient sequence includes multiple selection indicator types and the corresponding weight coefficient for each type. Selection indicator types can include infrastructure investment, engineering quantity, time to reach full production capacity, operating costs, production capacity, and safety scores, etc. These selection indicator types have attributes such as name, dimensions, weight, and value source. This indicator system supports flexible configuration according to project needs and can adapt to the selection focus at different stages.

[0083] For each parallel scheme branch process node, the output result list is read from the data model of the parallel scheme branch process node. The value corresponding to each comparison index type is extracted according to the output result list. Normalization processing is performed on the value and weight coefficient corresponding to each comparison index type to eliminate the difference in units. Then, weighted calculation is performed to obtain the weighted comprehensive score of the parallel scheme branch process node.

[0084] Multiple parallel scheme branch process nodes are sorted in descending order of weighted comprehensive score to generate a recommended sequence of preferred schemes. The recommended sequence and the weighted comprehensive score of each parallel scheme branch process node are used as the output of the scheme selection process node. The output of the scheme selection process node is used to generate an output list and stored in the data model of the scheme selection process node. This embodiment overcomes the efficiency bottleneck of traditional manual scheme selection by automatically aggregating complex multi-disciplinary data to generate a "scheme × index" matrix, and then using preset weight coefficients to complete normalization and weighted scoring, achieving quantitative ranking and selection of schemes. This not only transforms judgments based on subjective experience into objective data-driven scientific decision-making, significantly improving the objectivity and reliability of the selection results, but also significantly reduces the cost and error rate of manual data integration through automated data processing and log traceability, providing efficient and transparent decision support for the design optimization of complex projects.

[0085] Taking the digital design data management of a preliminary design project for an underground metal mine as an example, this application illustrates the specific implementation process. Project number: DT2501; Project name: Preliminary design of underground mining for a gold mine; Involving disciplines: geology, mining, surveying, ventilation, water supply and drainage, power supply and distribution, and surface construction, totaling 8 disciplines.

[0086] Based on the relevant specialties involved in the project, template subtrees for geology, mining, surveying, ventilation, water supply and drainage, power supply and distribution, and ground construction are retrieved from the professional template library and automatically attached to the project root node. Subsequently, entity attribute tags such as professional category, task type, input type, and output deliverable type are populated into each node. DependencyNodes and inputDataRef are automatically generated based on the dependency determination rule library, and deliverable slots and their source binding relationships are pre-generated based on outputArtifactType. The specific process is as follows: (1) Create the project root node “MIM Design DT2501” in the system; (2) Create 8 first-level branch nodes under the root node, each corresponding to one of the 8 majors, and set the professionalCategory attribute for each major node; (3) Taking mining as an example, create secondary nodes under the mining node, including: project overview, settings, geological model, spatial data, mining plan, mining method, mining production capacity, mining development and transportation system, development and transportation system design, shaft and tunnel engineering, filling system, ventilation system, mining drainage and sludge removal system, compressed air and water supply system, auxiliary facilities, mining infrastructure engineering quantity, mining infrastructure schedule, and mining production schedule. (4) Create three level-four nodes under the “Development and Transportation System Design” node: “Main and Auxiliary Shaft Scheme”, “Belt Inclined Shaft Scheme” and “Comparison of Development and Transportation Schemes”; (5) Create leaf nodes under the “Main and Auxiliary Shaft Scheme” node: “Shaft and Tunnel Engineering Model”, “Engineering Quantity Statistics”, “Development System Diagram”, “Hoisting and Transportation Equipment”, and “Data Statistics”; (6) Configure the designToolRef property for each node. For example, the “Tunnel Engineering Model” node is associated with the 3D tunnel modeling tool, the “Quantity Statistics” node is associated with the automatic quantity statistics module, and the “Development System Diagram” node is associated with the CAD drawing tool. (7) Establish dependencies: Set the dependencyNodes of the “Development and Transportation System Design” node to the “Ground Mining Scheme” node and the “Ground Mining Method” node; set the inputDataRef of the “Ventilation System” node to reference the shaft and tunnel engineering model results in the “Development and Transportation System Design” node.

[0087] Geological designers first complete the design of the geological model nodes, uploading the 3D geological model file to the cloud via data synchronization, and updating the node status to "Completed." Mining designers then open the workflow tree interface, switch to the "Mining" professional view, and obtain the latest geological model through data refresh. Clicking on the 3D model leaf node under the "Geological Model" node automatically downloads the latest geological model file from the cloud and loads it using 3D visualization tools. Mining designers then sequentially complete the design steps such as determining the mining scheme, selecting the mining method, and demonstrating production capacity, triggering data synchronization and uploading upon completion of each node. Entering the development and transportation system design phase, mining designers conduct designs under two branches: "Main and Auxiliary Shaft Scheme" and "Belt Conveyor Inclined Shaft Scheme." Clicking the "Main and Auxiliary Shaft Schemes" → "Shaft and Tunnel Engineering Model" node, the system automatically calls the 3D tunnel modeling tool and loads existing geological models and spatial data as the design base map. After the designer completes the shaft and tunnel modeling and saves it, the system automatically generates and updates the engineering quantity statistics (structured data) and the 3D model file (unstructured data). After the two schemes are designed, the designer clicks the "Development and Transportation Scheme Comparison" node, and the system automatically summarizes the engineering quantity statistics, investment estimates, and other structured data of the two schemes, generating a scheme comparison table to assist the designer in making the optimal scheme decision. After the development system scheme is determined, the system automatically updates the status of the "Ventilation Network Model" node of the ventilation profession to "Needs Update" and notifies the ventilation professionals. The ventilation designers obtain the latest tunnel engineering model by refreshing the data and carry out the ventilation system design based on it.

[0088] After project managers expand the process tree, they can intuitively grasp the overall design progress of the project by viewing the status marker colors of each specialty and node. For example, most nodes in the geology and mining specialties are displayed as completed and marked in green; nodes in the ventilation specialties are displayed as in progress and marked in yellow; and nodes in the power supply and distribution specialties are displayed as not started and marked in gray.

[0089] This application provides a method for managing mine engineering design data based on a structured process tree. Compared with existing technologies, this application eliminates the need for manually creating folders or task lists. Instead, it uses a pre-set professional template library to construct a visualized digital design process tree based on the design data of the mine engineering project, building a standardized digital skeleton for the entire mine design project. Then, a data model is established for each process node within the digital design process tree based on the design data. This data model includes not only information about the design task itself but also input data, output data, and dependencies, transforming previously isolated design tasks into logical units with clearly defined data interfaces. Through clear input and output interface definitions, designers from various disciplines can intuitively see the location and provider of their required data through the digital design process tree, achieving efficient data flow and significantly reducing cross-departmental data acquisition costs. Furthermore, the data model incorporates professional category information and node information, specifically optimized for the multi-disciplinary and strongly spatially dependent characteristics of mines, perfectly meeting the actual needs of the digital and intelligent transformation of mine engineering. When an update to the output deliverables list of a certain process node is detected, this application determines at least one downstream process node based on the dependency reference list of other process nodes in the digital design process tree. The data model of the downstream process node is then updated, and a change notification is pushed to the designers of each downstream process node. This automatic update mechanism ensures that downstream process nodes always reference the latest upstream output deliverables, eliminating numerous design conflicts and version confusion caused by data lag. Simultaneously, because a complete dependency reference list is established in the data model, the system can fully record the entire process from data generation to use. Managers can clearly trace the source of any design deliverable through the digital design process tree, achieving refined project progress management and clear definition of design responsibilities. This significantly improves the efficiency and accuracy of mine design data flow and collaboration, enhancing the overall project progress speed and management transparency.

[0090] Furthermore, as Figure 1 In a specific implementation of the method, this application provides a mine engineering design data management device based on a structured process tree, such as... Figure 3 As shown, the device includes: a process tree construction module 301, a data model construction module 302, and a data update module 303.

[0091] The process tree construction module 301 is used to acquire design data of mining engineering projects and construct a digital design process tree of the mining engineering project based on a preset professional template library. The data model building module 302 is used to build a data model for each process node in the digital design process tree using the design data. The data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison index role information. The output deliverable list is used to index the structured and unstructured data output by the process node. The dependency reference list is used to record the directed acyclic dependencies between the process node and other process nodes. The data update module 303 is used to determine at least one downstream process node of the process node according to the dependency reference list of other process nodes in the digital design process tree when an update is detected in the output result list of a certain process node, update the data model of the at least one downstream process node, and push a change notification to the designer of each downstream process node.

[0092] In a specific application scenario, the process tree construction module 301 is used to extract a list of professional categories from the design data, the list of professional categories containing multiple professional categories involved in the mining engineering project; extract a template subtree corresponding to each professional category from the preset professional template library, the template subtree consisting of multiple nodes with entity attribute tags; attach multiple template subtrees to the root node of the mining engineering project to form an initial process tree skeleton, the root node being used to record the basic information of the mining engineering project, the basic information including project number, project name, and design stage identifier, the root node of each template subtree serving as a first-level branch node of the initial process tree skeleton; perform adjustment operations on the initial process tree skeleton according to the design data to generate the digital design process tree, wherein the adjustment operations include at least one of pruning, disabling, and expanding operations, the pruning operation deleting nodes corresponding to design tasks not involved in the design data from the initial process tree skeleton, the disabling operation marking nodes corresponding to design tasks that are temporarily not needed in the initial process tree skeleton as disabled, and the expanding operation inserting nodes corresponding to newly added design tasks from the design data into the initial process tree skeleton.

[0093] In a specific application scenario, the data model construction module 302 is used to traverse each process node in the digital design process tree, obtain the entity attribute tags of each process node, and the entity attribute tags include professional category, task type, input data type set, output deliverable type set, design tool type, and comparison index role; for each process node, the node identifier, node name, node type, and parent node identifier of the process node are determined according to the digital design process tree, which serve as the node information of the process node; the professional category, task type, and comparison index role contained in the entity attribute tags of the process node are obtained, and the professional category, task type, and comparison index role are set together. The roles are respectively used for the professional category information, task type information, and selection indicator role information of the process node. The selection indicator role includes role type and selection indicator weight coefficient sequence. The design tool type contained in the entity attribute tags of the process node is obtained, and the design tool reference information corresponding to the design tool type is searched in the configuration tool library. The design tool reference information includes design tool name, design tool type, startup parameters, and calling interface address. The design tool type represents the category of design tools used in the design task of the process node. The set of output deliverable types contained in the entity attribute tags of the process node is obtained, and a set of output deliverable types is generated for each output deliverable type in the set. An empty deliverable entry is created to obtain the output deliverable list of the process node. Each deliverable entry records the entry identifier, output deliverable name, output deliverable type, data type flag, format storage address, and local cache version number. The data type flag is either structured or unstructured. Based on a dependency determination rule base, at least one preceding dependent process node of the process node is matched and determined. A directed acyclic dependency relationship is constructed using the process node and the at least one preceding dependent process node. A dependency reference list of the process node is generated using the directed acyclic dependency relationship and the node identifier of each preceding dependent process node. The dependency determination rule base includes professional internal dependencies. Dependency determination rules and cross-disciplinary dependency determination rules; obtain the input data type set contained in the entity attribute tags of the process node, determine at least one input data type included in the input data type set, and obtain the output deliverable list of each of the preceding dependent process nodes; for each input data type, match the input data type in the output deliverable list of each of the preceding dependent process nodes, and take the deliverable entries whose output deliverable type is consistent with the input data type as the preceding deliverable entries; by matching each input data type, obtain multiple preceding deliverable entries, and use the multiple preceding deliverable entries to generate the input data reference list of the process node;Initialize the status information of the process node. The status information can be any one of the following: Not Started, In Progress, Completed, or Needs Update. The "Not Started" status indicates that the design task of the process node has not been initiated, and is marked with a gray icon in the visualization interface of the digital design process tree. The "In Progress" status indicates that the design task of the process node has been initiated, and is marked with a yellow icon in the visualization interface of the digital design process tree. The "Completed" status indicates that the design task of the process node has been completed, and is marked with a green icon in the visualization interface of the digital design process tree. The "Needs Update" status indicates that the output deliverable list of the process node's preceding dependent process nodes has changed, and is marked with a red icon in the visualization interface of the digital design process tree. Use the node information, the professional category information, the task type information, the comparison indicator role information, the design tool reference information, the input data reference list, the output deliverable list, the dependency reference list, and the status information to generate the data model of the process node.

[0094] In specific application scenarios, the data model construction module 302 is used to read a preset task type sequence from the professional dependency determination rules, determine the logical position of the task type of the process node in the preset task type sequence, take the task type preceding the logical position as the pre-dependent task type, determine the process subtree corresponding to the professional category to which the process node belongs in the digital design process tree, take the process node in the process subtree whose task type is the pre-dependent task type as the pre-dependent process node, and obtain at least one pre-dependent process node of the process node; and / or, based on the cross-professional dependency determination rules, obtain at least one input data type included in the input data type set, and for each input data type, match the input data type with the output result type set of other process nodes in the digital design process tree, take the process node in the output result type set containing the input data type as the pre-dependent process node, and obtain at least one pre-dependent process node of the process node.

[0095] In a specific application scenario, the data update module 303 is used to read node identifiers from the data model of the process node, traverse other process nodes in the digital design process tree, and take process nodes containing the node identifiers in the dependency reference list as downstream process nodes to obtain at least one downstream process node; for each downstream process node, the input data reference list is read from the data model of the downstream process node, the target prerequisite deliverable item is determined from the input data reference list, and the format storage address and local cache version number indicated by the target prerequisite deliverable item are updated using the updated output deliverable list of the process node. The target prerequisite deliverable item refers to the one that references the process node. The process node's output deliverables are listed as prerequisite deliverable entries; the downstream process node's status information is updated to a state requiring updating in the downstream process node's data model, generating a structured change log containing a change timestamp, the process node's node identifier, the updated output deliverable list of the process node, and the downstream process node's node identifier, and storing the structured change log in the downstream process node's data model; the designer information associated with the downstream process node is determined, a change notification containing the process node's node identifier, the updated output deliverable list of the process node, and the downstream process node's node identifier is generated, and the change notification is pushed to the designer through a preset communication method.

[0096] In specific application scenarios, such as Figure 4 As shown, the device also includes: a data access module 304, a task finalization module 305, and a scheme comparison module 306.

[0097] The data access module 304 is configured to respond to a user's access operation to a process node in the digital design process tree by reading an input data reference list from the data model of the process node; determining the upstream process node indicated by each preceding deliverable entry in the input data reference list, and obtaining the format storage address and local cache version number indicated by each preceding deliverable entry in the input data reference list; for each upstream process node, requesting the latest version number of the output deliverable of the upstream process node from the cloud server, and comparing the latest version number with the local cache version number; if the latest version number matches the local cache version number, obtaining the local cache file corresponding to the output deliverable of the upstream process node according to the format storage address; if the latest version number does not match the local cache version number, downloading the latest version file corresponding to the output deliverable of the upstream process node from the cloud server, overwriting the local cache file indicated by the format storage address with the latest version file, and updating the local cache version number to the latest version number.

[0098] The task finalization module 305 is used to collect multiple output deliverables generated by a process node when it is detected that a designer has completed the design task of a process node locally and performed a finalization operation. It generates a deliverable entry for each output deliverable, resulting in a list of output deliverables for the process node. Each deliverable entry includes an entry identifier, output deliverable name, output deliverable type, data type flag, format storage address, and local cache version number. The data type flag is either structured or unstructured. The module then uploads the multiple output deliverables to the storage layer of a cloud server, obtaining the final storage address and cloud version number of each output deliverable returned by the cloud server. Structured data is stored in a structured data storage layer, and unstructured data is stored in an unstructured data storage layer. The structured data storage layer uses a relational database, and the unstructured data storage layer uses an object storage service. Finally, the module iterates through the output deliverable list of the process node, and for each deliverable entry, it checks the final storage address and cloud version number of the multiple output deliverables. The final storage address and cloud version number corresponding to the deliverable item are determined. The format storage address in the deliverable item is updated to the final storage address corresponding to the deliverable item, and the local cache version number in the deliverable item is updated to the cloud version number corresponding to the deliverable item. The updated output deliverable list of the process node is stored in the data model of the process node, and the status information of the process node is updated to the completed state in the data model of the process node. A finalized structured log containing the finalization operator information, the finalization completion timestamp, the node identifier of the process node, and the updated output deliverable list of the process node is generated, and the finalized structured log is stored in the data model of the process node. The dependency reference list of other process nodes in the digital design process tree is traversed, and the process node containing the node identifier in the dependency reference list is taken as the subsequent process node to obtain at least one subsequent process node. The status information of each subsequent process node is updated to the update-required state in the data model of each subsequent process node. The data model of the at least one subsequent process node is updated, and a change notification is pushed to the designer of each subsequent process node.

[0099] The scheme comparison module 306 is used to traverse multiple process nodes in the digital design process tree. When it is detected that the comparison indicator role information of a certain process node contains a non-empty role type, the process node is designated as a scheme comparison process node. The module reads a dependency reference list from the data model of the scheme comparison process node and determines multiple preceding process nodes based on the dependency reference list. It reads the parent node identifier of each preceding process node from its data model and the parent node identifier of the scheme comparison process node from its data model. It selects a preceding process node whose parent node identifier matches that of the scheme comparison process node as a parallel scheme branch process node, thus obtaining multiple parallel scheme branch process nodes. It continuously monitors the status information of the multiple parallel scheme branch process nodes. When it is determined that the status information of all multiple parallel scheme branch process nodes is in a completed state, the module... The process involves reading the weight coefficient sequence of the selection indicators from the role information of the selection indicators in the scheme selection process node. This sequence includes multiple selection indicator types and a corresponding weight coefficient for each type. For each parallel scheme branch process node, the output result list is read from the data model of that node. Values ​​corresponding to each selection indicator type are extracted from the output result list, and a weighted calculation is performed based on these values ​​and the weight coefficients to obtain the weighted comprehensive score of the parallel scheme branch process node. The parallel scheme branch process nodes are then sorted in descending order of their weighted comprehensive scores to generate a preferred scheme recommendation sequence. This preferred scheme recommendation sequence and the weighted comprehensive score of each parallel scheme branch process node are used as the output results of the scheme selection process node. Finally, the output results of the scheme selection process node are used to generate an output result list, which is stored in the data model of the scheme selection process node.

[0100] In a specific application scenario, the data access module 304 is used to read the design tool reference information of the process node from the data model of the process node, and obtain the design tool type, startup parameters, and call interface address from the design tool reference information; call the design tool used by the design task of the process node according to the startup parameters and the call interface address, and pass the format storage address indicated by multiple pre-deliverable items as initialization parameters to the design tool; when it is detected that the designer completes the design task and performs a save operation in the design tool according to the initialization parameters, at least one newly generated output deliverable of the process node is collected, and a deliverable item is generated for each output deliverable, resulting in at least one deliverable item; the at least one deliverable item is added to the output deliverable list of the process node, and the updated output deliverable list is used to update the data model of the process node.

[0101] This application provides an apparatus that, compared to existing technologies, eliminates the need for manually creating folders or task lists. Instead, it constructs a visualized digital design process tree based on a pre-set professional template library and design data from mining engineering projects, building a standardized digital framework for the entire mining design project. Subsequently, a data model is established for each process node within the digital design process tree based on the design data. This data model includes not only information about the design task itself but also input data, output data, and dependencies, transforming previously isolated design tasks into logical units with clearly defined data interfaces. Through explicit input / output interface definitions, designers from various disciplines can intuitively see the location and provider of their required data through the digital design process tree, achieving efficient data flow and significantly reducing cross-departmental data acquisition costs. Furthermore, the data model incorporates professional category information and node information, specifically optimized for the multi-disciplinary and spatially dependent characteristics of mining, perfectly meeting the actual needs of the digital and intelligent transformation of mining engineering. When an update to the output deliverables list of a certain process node is detected, this application determines at least one downstream process node based on the dependency reference list of other process nodes in the digital design process tree. The data model of the downstream process node is then updated, and a change notification is pushed to the designers of each downstream process node. This automatic update mechanism ensures that downstream process nodes always reference the latest upstream output deliverables, eliminating numerous design conflicts and version confusion caused by data lag. Simultaneously, because a complete dependency reference list is established in the data model, the system can fully record the entire process from data generation to use. Managers can clearly trace the source of any design deliverable through the digital design process tree, achieving refined project progress management and clear definition of design responsibilities. This significantly improves the efficiency and accuracy of mine design data flow and collaboration, enhancing the overall project progress speed and management transparency.

[0102] It should be noted that other corresponding descriptions of the functional units involved in the mine engineering design data management device based on a structured process tree provided in this application embodiment can be found in the following references. Figure 1 and Figure 2 The corresponding descriptions in [the document] will not be repeated here.

[0103] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0104] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0105] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

[0106] In an exemplary embodiment, see Figure 5 The system also provides a computer device including a bus, a processor, a memory, and a communication interface. It may also include an input / output interface and a display device. The various functional units can communicate with each other via the bus. The memory stores computer programs, and the processor executes the programs stored in the memory, performing the mine engineering design data management method based on a structured process tree as described in the above embodiments. The memory is divided into four layers from top to bottom: the top layer consists of application software modules that directly address functional requirements; the second layer is the application programming interface (API) that provides the application layer with an interface to call underlying functions; the third layer is middleware that provides general services and connects software components at the upper and lower layers; and the bottom layer is the kernel, the foundational core of the software system, responsible for underlying functions such as hardware resource management and process scheduling.

[0107] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the mining engineering design data management method based on a structured process tree.

[0108] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented in hardware or by using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0109] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application.

[0110] Those skilled in the art will understand that the modules in the apparatus of the implementation scenario can be distributed within the apparatus of the implementation scenario as described, or they can be located in one or more apparatuses different from this implementation scenario, with corresponding changes. The modules of the above-described implementation scenario can be combined into one module, or they can be further divided into multiple sub-modules.

[0111] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of the implementation scenario.

[0112] The above disclosures are only a few specific implementation scenarios of this application. However, this application is not limited to these. Any variations that can be conceived by those skilled in the art should fall within the protection scope of this application.

Claims

1. A method for managing mine engineering design data based on a structured process tree, characterized in that, include: Obtain design data for mining engineering projects, and construct a digital design process tree for the mining engineering projects based on a pre-set professional template library. The design data is used to build a data model for each process node in the digital design process tree. The data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison index role information. The output deliverable list is used to index the structured and unstructured data output by the process node. The dependency reference list is used to record the directed acyclic dependencies between the process node and other process nodes. When an update to the output deliverables list of a certain process node is detected, at least one downstream process node of the process node is determined based on the dependency reference list of other process nodes in the digital design process tree. The data model of the at least one downstream process node is updated, and a change notification is pushed to the designer of each downstream process node.

2. The method according to claim 1, characterized in that, The process of constructing a digital design flow tree for the mining engineering project based on a pre-set professional template library and the design data includes: Extract a list of professional categories from the design data, which contains multiple professional categories involved in the mining engineering project; Extract the template subtree corresponding to each professional category from the preset professional template library. The template subtree consists of multiple nodes with entity attribute labels. Multiple template subtrees are attached to the root node of the mining project to form an initial process tree skeleton. The root node is used to record the basic information of the mining project, including project number, project name, and design stage identifier. The root node of each template subtree serves as a first-level branch node of the initial process tree skeleton. The initial process tree skeleton is adjusted based on the design data to generate the digital design process tree. The adjustment operation includes at least one of the following: pruning, disabling, and expansion. The pruning operation deletes nodes corresponding to design tasks not involved in the design data from the initial process tree skeleton. The disabling operation marks nodes corresponding to design tasks that are not currently needed in the initial process tree skeleton as disabled. The expansion operation inserts nodes corresponding to newly added design tasks from the design data into the initial process tree skeleton.

3. The method according to claim 1, characterized in that, The step of using the design data to establish a data model for each process node within the digital design process tree includes: Traverse each process node in the digital design process tree and obtain the entity attribute label for each process node. The entity attribute label includes professional category, task type, input data type set, output deliverable type set, design tool type, and comparison index role. For each process node, the node identifier, node name, node type, and parent node identifier of the process node are determined according to the digital design process tree, which serve as the node information of the process node. Obtain the professional category, task type, and comparison indicator role contained in the entity attribute tag of the process node, and use the professional category, task type, and comparison indicator role as the professional category information, task type information, and comparison indicator role information of the process node, respectively. The comparison indicator role includes role type and comparison indicator weight coefficient sequence. Obtain the design tool type contained in the entity attribute tag of the process node, and search for the design tool reference information corresponding to the design tool type in the configuration tool library. The design tool reference information includes the design tool name, design tool type, startup parameters, and call interface address. The design tool type indicates the category of design tools used by the design task of the process node. Obtain the set of output result types contained in the entity attribute tags of the process node, generate an empty result entry for each output result type in the set of output result types, and obtain the output result list of the process node. The result entry is used to record the entry identifier, output result name, output result type, data type tag, format storage address and local cache version number. The data type tag is a structured type or an unstructured type. Based on the dependency determination rule base, at least one preceding dependent process node of the process node is matched and determined. A directed acyclic dependency relationship is constructed using the process node and the at least one preceding dependent process node. A dependency reference list of the process node is generated using the directed acyclic dependency relationship and the node identifier of each preceding dependent process node. The dependency determination rule base includes intra-professional dependency determination rules and cross-professional dependency determination rules. Obtain the set of input data types contained in the entity attribute tags of the process node, determine at least one input data type included in the set of input data types, and obtain the list of output deliverables for each of the preceding dependent process nodes; For each input data type, the input data type is matched against the output result list of each preceding dependent process node, and the result item whose output result type matches the input data type is taken as the preceding result item. By matching each of the input data types, multiple prerequisite result items are obtained, and the input data reference list of the process node is generated using the multiple prerequisite result items. Initialize the status information of the process node. The status information is any one of not started, in progress, completed, and needs updating. The not started state indicates that the design task of the process node has not been started, and is marked with a gray icon in the visualization interface of the digital design process tree. The in progress state indicates that the design task of the process node has been started, and is marked with a yellow icon in the visualization interface of the digital design process tree. The completed state indicates that the design task of the process node has been completed, and is marked with a green icon in the visualization interface of the digital design process tree. The needs updating state indicates that the output deliverable list of the process node's predecessor dependent process nodes has changed, and is marked with a red icon in the visualization interface of the digital design process tree. The data model of the process node is generated using the node information, the professional category information, the task type information, the comparison indicator role information, the design tool reference information, the input data reference list, the output deliverable list, the dependency reference list, and the status information.

4. The method according to claim 3, characterized in that, The process of matching and determining at least one preceding dependent process node of the process node based on the dependency determination rule base includes: Read the preset task type sequence from the professional dependency determination rules, determine the logical position of the task type of the process node in the preset task type sequence, take the task type preceding the logical position as the pre-dependent task type, determine the process subtree corresponding to the professional category to which the process node belongs in the digital design process tree, and take the process nodes in the process subtree whose task type is the pre-dependent task type as pre-dependent process nodes, thus obtaining at least one pre-dependent process node of the process node; and / or, Based on the cross-disciplinary dependency determination rule, at least one input data type is obtained from the input data type set. For each input data type, the input data type is matched with the output result type set of other process nodes in the digital design process tree. The process nodes in the output result type set containing the input data type are taken as the preceding dependent process nodes, thus obtaining at least one preceding dependent process node of the process node.

5. The method according to claim 1, characterized in that, The process of determining at least one downstream process node of a process node based on the dependency reference list of other process nodes in the digital design process tree, updating the data model of the at least one downstream process node, and pushing change notifications to the designers of each downstream process node includes: Read the node identifier from the data model of the process node, traverse other process nodes in the digital design process tree, and take the process node containing the node identifier in the dependency reference list as the downstream process node to obtain the at least one downstream process node. For each downstream process node, the input data reference list is read from the data model of the downstream process node, the target preceding result item is determined from the input data reference list, and the format storage address and local cache version number indicated by the target preceding result item are updated using the updated output result list of the process node. The target preceding result item refers to the preceding result item that references the output result of the process node. In the data model of the downstream process node, the status information of the downstream process node is updated to the state that needs to be updated, and a change structured log is generated, which includes the change timestamp, the node identifier of the process node, the list of output results of the updated process node, and the node identifier of the downstream process node. The change structured log is stored in the data model of the downstream process node. The designer information associated with the downstream process node is determined, a change notification is generated that includes the node identifier of the process node, the list of output deliverables after the update of the process node, and the node identifier of the downstream process node, and the change notification is pushed to the designer through a preset communication method.

6. The method according to claim 1, characterized in that, The method further includes: In response to a user's access operation to a certain process node in the digital design process tree, the input data reference list is read from the data model of the process node; Determine the upstream process node indicated by each preceding result item in the input data reference list, and obtain the format storage address and local cache version number indicated by each preceding result item in the input data reference list; For each upstream process node, request the latest version number of the output product of the upstream process node from the cloud server, and compare the latest version number with the local cache version number; If the latest version number is consistent with the local cache version number, then the local cache file corresponding to the output product of the upstream process node is obtained according to the format storage address; If the latest version number is inconsistent with the local cache version number, then download the latest version file corresponding to the output of the upstream process node from the cloud server, overwrite the local cache file indicated by the format storage address with the latest version file, and update the local cache version number to the latest version number.

7. The method according to claim 6, characterized in that, The method further includes: Read the design tool reference information of the process node from the data model of the process node, and obtain the design tool type, startup parameters and call interface address from the design tool reference information; The design tool used by the design task of the process node is invoked according to the startup parameters and the calling interface address, and the storage address of the format indicated by multiple prerequisite deliverables is passed to the design tool as an initialization parameter. When it is detected that the designer has completed the design task and performed the save operation in the design tool according to the initialization parameters, at least one newly generated output product of the process node is collected, and a product entry is generated for each output product to obtain at least one product entry. Add the at least one outcome item to the output outcome list of the process node, and update the data model of the process node using the updated output outcome list.

8. The method according to claim 1, characterized in that, The method further includes: When it is detected that the designer of a certain process node has completed the design task of the process node locally and performed the finalization operation, multiple output deliverables generated by the process node are collected, and a deliverable entry is generated for each output deliverable to obtain the output deliverable list of the process node. The deliverable entry includes an entry identifier, output deliverable name, output deliverable type, data type tag, format storage address and local cache version number. The data type tag is either structured or unstructured. The multiple output products are uploaded to the storage layer of the cloud server, and the final storage address and cloud version number of each output product returned by the cloud server are obtained. Among them, the structured data of the output products are stored in the structured data storage layer, and the unstructured data of the output products are stored in the unstructured data storage layer. The structured data storage layer uses a relational database for data storage, and the unstructured data storage layer uses an object storage service for data storage. Traverse the output result list of the process node. For each result item, determine the final storage address and cloud version number corresponding to the result item from the final storage address and cloud version number of the multiple output result items. Update the format storage address in the result item to the final storage address corresponding to the result item. Update the local cache version number in the result item to the cloud version number corresponding to the result item. The updated output list of the process node is stored in the data model of the process node, and the status information of the process node is updated to the completed status in the data model of the process node. Generate a finalized structured log containing information on the finalized personnel, a finalized completion timestamp, the node identifier of the process node, and a list of output deliverables updated by the process node; store the finalized structured log in the data model of the process node. Traverse the dependency reference list of other process nodes in the digital design process tree, take the process node containing the node identifier in the dependency reference list as the subsequent process node, and obtain at least one subsequent process node. In the data model of each subsequent process node, update the state information of each subsequent process node to the state that needs to be updated. The data model of the at least one post-process node is updated, and a change notification is pushed to the designer of each post-process node.

9. The method according to claim 1, characterized in that, The method further includes: Traverse multiple process nodes in the digital design process tree. When it is detected that the comparison indicator role information of a certain process node contains a non-empty role type in the data model of a certain process node, the process node is used as the solution comparison process node. Read the dependency reference list from the data model of the solution comparison process node, and determine multiple preceding process nodes of the solution comparison process node based on the dependency reference list; Read the parent node identifier of each of the preceding process nodes in the data model of each preceding process node, and read the parent node identifier of the scheme comparison process node in the data model of the scheme comparison process node; Among the multiple preceding process nodes, the preceding process node whose parent node identifier is consistent with the parent node identifier of the scheme comparison process node is selected as the parallel scheme branch process node, thus obtaining multiple parallel scheme branch process nodes. The status information of the multiple parallel scheme branch process nodes is continuously monitored. When it is determined that the status information of the multiple parallel scheme branch process nodes is all in the completed state, the weight coefficient sequence of the comparison index is read from the comparison index role information of the scheme comparison process node. The weight coefficient sequence of the comparison index includes multiple comparison index types and the weight coefficient corresponding to each comparison index type. For each of the parallel scheme branch process nodes, the output result list is read from the data model of the parallel scheme branch process node, the value corresponding to each of the comparison index types is extracted according to the output result list, and a weighted calculation is performed according to the value corresponding to each of the comparison index types and the weight coefficient to obtain the weighted comprehensive score of the parallel scheme branch process node. The multiple parallel scheme branch process nodes are sorted in descending order of weighted comprehensive score to generate a preferred scheme recommendation sequence. The preferred scheme recommendation sequence and the weighted comprehensive score of each parallel scheme branch process node are used as the output of the scheme comparison process node. The output results of the scheme comparison process node are used to generate a list of output results of the scheme comparison process node and store it in the data model of the scheme comparison process node.

10. A mining engineering design data management device based on a structured process tree, characterized in that, include: The process tree construction module is used to acquire design data for mining engineering projects and, based on a preset professional template library, construct a digital design process tree for the mining engineering project using the design data. The data model building module is used to build a data model for each process node in the digital design process tree using the design data. The data model includes node information, professional category information, task type information, design tool reference information, input data reference list, output deliverable list, dependency reference list, status information, and comparison index role information. The output deliverable list is used to index the structured and unstructured data output by the process node, and the dependency reference list is used to record the directed acyclic dependencies between the process node and other process nodes. The data update module is used to determine at least one downstream process node of a process node based on the dependency reference list of other process nodes in the digital design process tree when an update is detected in the output deliverable list of a certain process node, update the data model of the at least one downstream process node, and push a change notification to the designer of each downstream process node.

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