Civil aircraft model data management process customizing and real-time monitoring system

Abstract

The invention discloses a civil aircraft model data management process customizing and real-time monitoring system, which comprises a Flowable process engine module, a dynamic attribute configuration interface expanded on the basis of a standard BPMN 2.0, a data storage layer module, a PostgreSQL-based design business basic table structure, a multi-level approval system module, an RBAC model-based definition multi-dimensional permission label and a real-time monitoring module, a process instance state is captured by utilizing a HistoryService interface of Flowable, a CEP technology and a user interaction interface module are integrated, and a visual process designer is developed based on BPMN.js. According to the method, the problem of process stiffness is solved, real-time synchronization of a process state and PLM / ERP service data is ensured by utilizing PostgreSQL logic copying and Camel middleware, a data island is eliminated, abnormity can be automatically detected and alarmed by combining a real-time monitoring module of CEP, the process reliability is remarkably improved, modeling and management thresholds are reduced by a visual designer and a Gantt chart, and the process reliability is improved. And the cross-department collaboration transparency is enhanced.

Description

Technical Field

[0001] This invention belongs to the field of civil aircraft model data management technology, specifically a civil aircraft model data management process customization and real-time monitoring system. Background Technology

[0002] Existing technologies primarily rely on mainstream workflow engines such as Activiti and Camunda to build process management systems (e.g., patents CN109841234A and CN110884567B). While these technologies have achieved basic automation of business processes, they have revealed significant technical shortcomings when dealing with dynamic scenarios involving the parallel development of multiple civil aircraft models, complex processes, and frequent adjustments.

[0003] First, the dynamic adaptability of processes is severely lacking. The process models of existing engines tend to become fixed once deployed. For example, in a system based on Activiti, when a new quality review node needs to be inserted or the approval path needs to be adjusted, the entire process definition must be shut down and redeployed, resulting in business interruption and failing to meet the real-time requirements of rapid iteration across multiple models.

[0004] Secondly, there is a disconnect between process and business data. Existing solutions lack an efficient real-time data synchronization mechanism. When the Bill of Materials (BOM) data in the Product Lifecycle Management (PLM) system changes, the process engine often fails to detect it, causing approval processes to run based on outdated data, leading to decision-making errors and management chaos, and creating "data silos."

[0005] Furthermore, the system lacks real-time monitoring and proactive early warning capabilities. Existing systems lag behind in monitoring the execution status of processes, generally relying on manual log checks to detect anomalies (such as task timeouts and verification failures). The lack of automatic detection and real-time alerting mechanisms for process blockages leads to delayed problem response and affects overall development efficiency.

[0006] Finally, cross-departmental collaboration lacks visualization. Existing tools struggle to intuitively display the dependencies and overall progress of tasks across multiple departments, including design, process, and manufacturing. Critical paths remain opaque, inter-departmental collaboration heavily relies on offline communication, resulting in low efficiency and slowing down data release and production preparation cycles.

[0007] In summary, the shortcomings of existing technologies in terms of process flexibility, real-time data synchronization, intelligent monitoring, and collaborative visualization have become key bottlenecks restricting the efficiency and reliability of civil aircraft model data management. Summary of the Invention

[0008] The technical solution adopted in this invention is as follows: A customizable and real-time monitoring system for civil aircraft model data management processes, comprising:

[0009] The Flowable workflow engine module extends the dynamic attribute configuration interface on top of the standard BPMN 2.0.

[0010] The data storage layer module is designed with the basic business table structure based on PostgreSQL.

[0011] The multi-level approval system module defines multi-dimensional permission tags based on the RBAC model.

[0012] The real-time monitoring module uses Flowable's HistoryService interface to capture the status of process instances and integrates CEP technology.

[0013] The user interface module is a visual process designer developed based on BPMN.js.

[0014] The Flowable workflow engine module is connected to the data storage layer module via signal connections, the Flowable workflow engine module is connected to the multi-level approval system module via signal connections, the Flowable workflow engine module is connected to the real-time monitoring module via signal connections, and the Flowable workflow engine module is connected to the user interface module via signal connections.

[0015] Furthermore, in the Flowable process engine module, the dynamic attribute configuration interface adds "nodes can be dynamically inserted" and "condition triggering rules" fields, supporting the definition or modification of process templates through a visual interface. Java reflection technology is used to achieve hot updates of process instances, dynamically loading modified process definition files. A lightweight DSL interpreter is also built-in to convert multi-level conditions into Boolean logic paths.

[0016] Furthermore, in the data storage layer module, the basic business table structure based on PostgreSQL includes:

[0017] The process instance table is used to store process status and node execution logs.

[0018] A business data mapping table is used to associate process instances with business entities in PLM / ERP systems.

[0019] Furthermore, the data storage layer module listens for data change events in the business system through the PostgreSQL logical replication mechanism to trigger process engine state synchronization. It also builds Apache Camel middleware to uniformly map heterogeneous system data formats to standard process parameters.

[0020] Furthermore, the multi-level approval system module dynamically matches approvers and generates task queues using the multi-dimensional permission tags defined by the RBAC model. It also maintains historical rule compatibility through a process version controller, ensuring that older process instances execute correctly after rule iterations.

[0021] Furthermore, the real-time monitoring module combines CEP technology to define anomaly rules, which include "task timeout > 2 hours" and "data verification failure ≥ 3 times", used to trigger alarms in real time and push them to the initiator.

[0022] Furthermore, the real-time monitoring module integrates a chart library to build a visual monitoring panel, dynamically displaying process execution heatmaps and resource load status. Monitoring data persistence is achieved through a PostgreSQL streaming processing framework.

[0023] Furthermore, in the user interface module, the visual process designer developed based on BPMN.js supports drag-and-drop node configuration and condition rule binding.

[0024] Furthermore, the user interface module also includes a task management panel, which displays pending, completed, and delegated tasks in separate columns, and provides fuzzy search and batch operation functions.

[0025] Furthermore, the user interface module displays cross-departmental task dependencies in real time using a Gantt chart and highlights critical path nodes.

[0026] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0027] (1) This invention realizes the modification and dynamic adjustment of the running civil aircraft data management process without downtime by using the Java reflection hot update technology and dynamic attribute configuration interface of the Flowable process engine module. It fundamentally solves the problem of rigid approval path caused by the solidification of model in traditional process engines, and significantly improves the flexibility of process response and reconstruction in multi-model and multi-task parallel scenarios.

[0028] (2) This invention achieves real-time and accurate synchronization between the process engine status and external business system (such as PLM / ERP) data through the PostgreSQL logical replication mechanism and business data mapping table design of the data storage layer module. This effectively eliminates information silos and decision biases caused by data lag and ensures that process execution is always based on the latest business data.

[0029] (3) This invention integrates CEP complex event processing technology through a real-time monitoring module, which can intelligently analyze the process execution status and define abnormal rules (such as task timeout, verification failure), realize automatic detection and real-time alarm of process blockage and data anomaly, greatly shorten the problem response and handling time, and improve the reliability and control capability of the whole process.

[0030] (4) The present invention provides a visual process designer based on BPMN.js, a multi-functional task management panel and a Gantt chart through the user interaction interface module, which greatly reduces the technical threshold of process modeling and management, improves the intuitiveness and operational efficiency of task processing and cross-departmental collaboration, and enhances the transparency of the entire work progress.

[0031] (5) This invention achieves unified mapping and conversion of multi-source data formats in heterogeneous systems by building Apache Camel middleware, and realizes accurate matching of permissions and smooth evolution of process rules under complex organizational structures through the RBAC model and process version control of multi-level approval system modules. While improving the system integration and automation level, it ensures business continuity and historical compatibility. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the overall system architecture of the present invention.

[0033] In the diagram: 1. Flowable workflow engine module; 2. Data storage layer module; 3. Multi-level approval system module; 4. Real-time monitoring module; 5. User interface module. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0035] Example 1

[0036] Reference Figure 1 A customizable and real-time monitoring system for civil aircraft model data management processes, comprising:

[0037] Flowable Process Engine Module 1

[0038] For process modeling and dynamic adjustment, a visual process designer is built using the Modeler component provided by Flowable (based on the BPMN 2.0 standard). Designers define basic process templates by dragging and dropping nodes (such as "User Tasks" and "Gateway"), and configure extended fields such as "Nodes can be dynamically inserted" and "Conditional triggering rules" in the property panel.

[0039] Develop a dynamically updated service by extending the RuntimeService interface of Flowable. Utilize Java reflection to implement hot updates of the process instance, dynamically loading the modified process definition file (.bpmn). Example code is as follows:

[0040] DeploymentBuilderdeployment=repositoryService.createDeployment();

[0041] deployment.addInputStream("process.bpmn",newFileInputStream("modified_process.bpmn"));

[0042] deployment.enableDuplicateFiltering();

[0043] deployment.deploy();

[0044] Running process instances automatically associate with the new version of the process definition by listening to the Deployment event. Existing instances continue to execute unfinished nodes, while newly initiated instances run according to the updated rules, thus achieving process adjustment without downtime.

[0045] Rule parsing and execution involve embedding conditional expressions (such as ${auditExceed>10%}) in the process definition file, which are then parsed into executable logic by Flowable's ExpressionManager during deployment. A built-in lightweight DSL (Domain-Specific Language) interpreter converts multi-level business conditions into Boolean logic paths, driving the dynamic route generation of the approval process.

[0046] Data storage layer module 2

[0047] Database design and integration: Based on PostgreSQL, the business table structure was designed, with key tables including:

[0048] ACT_RU_TASK (Process Task Table): Stores information such as task ID, execution status, and creation time, used for real-time tracking of task progress.

[0049] BIZ_DATA_MAP (Business Data Mapping Table): Contains fields such as process_instance_id (process instance ID) and bom_id (BOM document ID), establishing a strong association between process instances and entities in business systems such as PLM / ERP.

[0050] Data mapping and synchronization are achieved through PostgreSQL's logical replication mechanism. This involves monitoring change events in business system (such as PLM) data tables (based on WAL logs) and triggering state synchronization in the process engine. An Apache Camel middleware routing mechanism is built to achieve unified mapping and forwarding of heterogeneous system data formats (XML, JSON) to standard process parameters. An example routing configuration is shown below:

[0051] <route>

[0052] <from uri="postgresql: / / bo_db?initialDelay=3000" / >

[0053] <process ref="dataChangeProcessor" / >

[0054] <to uri="activemq:queue:flowable_trigger" / >

[0055] < / route>

[0056] Multi-level approval system module 3

[0057] Role-based access control (RBAC) configuration defines multi-dimensional permission tags (such as "department" and "job level"). Roles are bound to process nodes to enable dynamic task assignment. Example SQL is as follows:

[0058] INSERT INTO ACT_RU_IDENTITYLINK(TASK_ID_,GROUP_ID_,TYPE_)VALUES('task123','data_auditor','candidate');

[0059] Automated task assignment and version control are implemented by embedding task assignment rules into the process definition. TaskService automatically assigns tasks to appropriate users based on preset priority weights. A process version controller manages the iteration of the process definition, ensuring that historical process instances can still execute correctly after rule updates, maintaining compatibility.

[0060] Real-time monitoring module 4

[0061] Data capture and alerting utilize Flowable's HistoryService interface to capture the real-time status of process instances (such as task completion rate and blocked node information). It combines CEP (Complex Event Processing) technology to define exception rules (such as "task timeout > 2 hours" and "data verification failure ≥ 3 times"). When a rule is triggered, the system generates an alert in real time and pushes it to the to-do center of the process initiator and administrators via a message queue.

[0062] Visualization and auditing: Integrate with charting libraries (such as ECharts) to build visual monitoring dashboards, dynamically displaying process execution heatmaps and resource load status, helping managers quickly locate bottlenecks. All monitoring data is persistently stored through a PostgreSQL streaming framework, ensuring full lifecycle audit traceability.

[0063] User interaction interface module 5

[0064] A visual process designer, developed based on the BPMN.js library, is a web-based visual process designer that allows users to configure nodes and bind condition rules via drag and drop, lowering the barrier to entry for process modeling. The designer supports exporting processes to the standard BPMN 2.0 XML format.

[0065] const modeler=new BpmnJS({container:'#canvas'});

[0066] modeler.importXML(bpmnXml);

[0067] Task management and a global view: The front end retrieves a list of user-to-do and completed tasks via a REST API and renders it as a task management panel, providing fuzzy search and batch operation functions. A Gantt chart displays cross-departmental task dependencies and critical paths in real time, enhancing collaborative transparency in the parallel development of multiple models.

[0068] System Workflow Example

[0069] Taking the civil aircraft flight test data management process as an example:

[0070] Process Initiation and Conditional Flow: During the flight test data integrity verification phase, the process engine makes a judgment based on the conditional gateway set in the BPMN. If the verification passes (approved == true), the system automatically triggers the "Data Analysis" task; if it fails (approved == false), it jumps to the "Data Supplementation" node.

[0071] Real-time monitoring and intervention: The real-time monitoring module tracks the status of "data analysis" tasks. If the task execution time exceeds a predetermined threshold, the system automatically issues an alarm and notifies relevant personnel to handle the situation.

[0072] Data synchronization: Once the "data supplementation" is completed and approved, the system automatically updates the flight test data status in the data warehouse through the synchronization mechanism of the data storage layer and synchronizes it to the data analysis platform to ensure that downstream processes obtain the latest data.

[0073] Working principle:

[0074] Process definition, instantiation, and intelligent conditional routing:

[0075] Users define process models based on the BPMN 2.0 standard using a visual designer and set business condition rules at key nodes (such as the approval gateway). After the process starts, the Flowable process engine module 1 creates a process instance (ProcessInstance). When execution reaches the condition gateway, the engine's built-in DSL interpreter parses the current business data in real time (such as the test flight data verification result "approved") and automatically calculates the Boolean logic path. For example, if the verification passes (approved == true), the engine automatically routes to the "Data Analysis" task node; if it fails (approved == false), it jumps to the "Data Supplementation" node, thereby achieving dynamic and automated process branch control based on business logic.

[0076] Real-time status tracking and anomaly monitoring throughout the entire lifecycle:

[0077] After the process instance runs, the real-time monitoring module 4 continuously captures the real-time status (such as start time, handler, and completion status) of the instance and its various tasks by calling the Flowable's HistoryService interface. This status data is streamed. Simultaneously, the CEP (Complex Event Processing) engine integrated into the monitoring module performs real-time analysis of the data stream, comparing it against preset anomaly rules (such as "task time > 2 hours"). Once an event matching the rules is detected (e.g., a data validation task timeout), the system immediately and automatically triggers an alarm, notifying relevant personnel via message, enabling immediate detection and intervention of process blockages and anomalies.

[0078] Two-way real-time synchronization of process and business data:

[0079] Throughout the entire process execution, data storage layer module 2 ensures strong consistency between the process status and backend business data. On one hand, every action in the process (such as task completion or gateway redirection) updates the status in the process instance table in real time and links it to specific business objects (such as BOM numbers) through a business data mapping table. On the other hand, through the PostgreSQL logical replication mechanism, the system monitors data changes in business systems (such as PLM). When external business data is updated (such as design document revisions), this change event is captured in real time and triggers status synchronization or task response for associated process instances, ensuring that process decisions are always based on the latest business data, thus achieving data-driven processes.

[0080] Dynamic adjustment and hot update of processes:

[0081] When business rules change and processes need to be adjusted, administrators modify the process definition (.bpmn file) through the designer and submit it. The Flowable process engine module 1 uses Java reflection technology to dynamically load the new version of the process definition, achieving hot updates. For already running process instances, the current node is usually completed according to the original definition, and subsequent nodes can be executed according to the new rules; newly initiated instances directly adopt the new process. This process does not require service interruption or restart, realizing online and dynamic optimization of business processes.

[0082] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A customizable and real-time monitoring system for civil aircraft model data management processes, characterized in that, include: The Flowable process engine module (1) extends the dynamic attribute configuration interface on the basis of the standard BPMN 2.0; Data storage layer module (2), based on PostgreSQL, designs the basic business table structure; The multi-level approval system module (3) defines multi-dimensional permission tags based on the RBAC model; The real-time monitoring module (4) uses the Flowable's HistoryService interface to capture the status of process instances and integrates CEP technology; User interaction interface module (5), a visual process designer is developed based on BPMN.js; The Flowable process engine module (1) is connected to the data storage layer module (2) by signal, the Flowable process engine module (1) is connected to the multi-level approval system module (3) by signal, the Flowable process engine module (1) is connected to the real-time monitoring module (4) by signal, and the Flowable process engine module (1) is connected to the user interaction interface module (5) by signal.

2. The civil aircraft model data management process customization and real-time monitoring system according to claim 1, characterized in that, In the Flowable process engine module (1), the dynamic attribute configuration interface adds the fields "nodes can be dynamically inserted" and "condition triggering rules", supports defining or changing process templates through a visual interface, uses Java reflection technology to realize hot updates of process instances, dynamically loads the modified process definition file, and has a built-in lightweight DSL interpreter to convert multi-level conditions into Boolean logic paths.

3. The civil aircraft model data management process customization and real-time monitoring system according to claim 1, characterized in that, In the data storage layer module (2), the basic business table structure based on PostgreSQL includes: The process instance table is used to store process status and node execution logs. A business data mapping table is used to associate process instances with business entities in PLM / ERP systems.

4. The civil aircraft model data management process customization and real-time monitoring system according to claim 3, characterized in that, The data storage layer module (2) listens for data change events in the business system through the PostgreSQL logical replication mechanism to trigger the synchronization of the process engine state, and builds the Apache Camel middleware to uniformly map the data format of heterogeneous systems to standard process parameters.

5. The civil aircraft model data management process customization and real-time monitoring system according to claim 1, characterized in that, The multi-level approval system module (3) dynamically matches approvers and generates task queues through the multi-dimensional permission tags defined by the RBAC model, and retains historical rule compatibility through the process version controller to ensure that old process instances are executed normally after rule iteration.

6. The civil aircraft model data management process customization and real-time monitoring system according to claim 1, characterized in that, The real-time monitoring module (4) defines anomaly rules in conjunction with CEP technology. The anomaly rules include "task timeout > 2 hours" and "data verification failure ≥ 3 times", which are used to trigger alarms in real time and push them to the initiator.

7. A customizable and real-time monitoring system for civil aircraft model data management process according to claim 1 or 6, characterized in that, The real-time monitoring module (4) integrates a chart library to build a visual monitoring panel, dynamically displaying the process execution heatmap and resource load status, and uses the PostgreSQL streaming processing framework to persist the monitoring data.

8. The civil aircraft model data management process customization and real-time monitoring system according to claim 1, characterized in that, In the user interface module (5), the visual process designer based on BPMN.js supports drag-and-drop node configuration and condition rule binding.

9. A customizable and real-time monitoring system for civil aircraft model data management process according to claim 1, characterized in that, The user interface module (5) also includes a task management panel, which displays pending, completed, and delegated tasks in columns and provides fuzzy search and batch operation functions.

10. A customizable and real-time monitoring system for civil aircraft model data management process according to claim 1 or 9, characterized in that, The user interface module (5) displays cross-departmental task dependencies in real time through a Gantt chart and highlights critical path nodes.

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