Workflow condition node management method based on dynamic rule engine

Abstract

The invention provides a workflow condition node management method based on a dynamic rule engine, and the method comprises the steps: obtaining a business circulation demand, configuring a task node attribute, and carrying out the adaptation of the business circulation demand according to the task node attribute, and obtaining a process template model; setting rule conditions, binding the rule conditions with the task nodes, and processing the flow template model; generating a process instance according to the updated process template model, analyzing rule conditions, initializing task allocation logic, and pushing a to-do task to a user; the user executes a to-do task, triggers the rule engine to carry out condition judgment, and updates a process instance state to obtain an updated process instance state; and according to the updated process instance state, generating a visual interface to display the process progress, and carrying out real-time early warning on an overtime or abnormal task to obtain a monitoring report and the process instance state after abnormal processing. Tasks can be decomposed, so that complex tasks are easier to manage, and the execution difficulty is reduced.

Description

Technical Field

[0001] The present invention relates to the field of office automation, and particularly to a method for managing workflow condition nodes based on a dynamic rule engine. Background Art

[0002] A workflow engine is a software system designed to automate, manage, and optimize business processes. It defines, executes, and monitors a series of interrelated tasks or activities that flow according to preset rules and conditions to achieve specific business goals. The core value of a workflow engine lies in improving business efficiency, reducing human errors, ensuring process consistency and compliance, while providing process transparency and traceability. With the acceleration of digital transformation, workflow engines have become key components in enterprise application architectures, supporting a wide range of requirements from simple approval processes to complex cross-departmental collaborations.

[0003] Existing process engines in the market lack flexibility, cannot respond to changes in a timely manner, lack interoperability with each other, cannot quickly provide operation and maintenance information, have relatively single functions, simple UI interfaces, and limited advanced functions.

[0004] For complex and ever-changing business scenarios, it is necessary to develop highly standardized products and consider subsequent flexible expansion. In the architecture design, it is necessary to distinguish between standard functions and business functions, decouple and integrate the code. At the design level, the user experience needs to be considered. Summary of the Invention

[0005] In view of the above situation, the main purpose of the present invention is to propose a method and system for managing workflow condition nodes based on a dynamic rule engine to solve the above technical problems.

[0006] The present invention proposes a method for managing workflow condition nodes based on a dynamic rule engine, and the method includes the following steps: Step 1: Obtain business flow requirements, configure task node attributes, and adapt the business flow requirements according to the task node attributes to obtain a process template model; Step 2: Set rule conditions, bind the rule conditions to the task nodes, and update the process template model to obtain an updated process template model; Step 3: Generate a process instance according to the updated process template model, parse the rule conditions, initialize the task assignment logic, and push the to-do tasks to the user; Step 4: The user executes the to-do tasks, triggers the rule engine to perform condition judgment, and updates the process instance status to obtain an updated process instance status; Step 5: Generate a visual interface based on the updated process instance status to display the process progress, and issue real-time warnings for overdue or abnormal tasks, obtaining a monitoring report and the process instance status after exception handling.

[0007] Compared with the prior art, the beneficial effects of the present invention are as follows: 1) Improve efficiency: Task decomposition makes complex tasks easier to manage and reduces the execution difficulty. Optimizing the task order streamlines the execution process and avoids duplication or omission. Task allocation ensures the rational use of resources and improves the overall efficiency.

[0008] 2) Promote collaboration: The workflow clarifies everyone's responsibilities and reduces communication costs. Team members can coordinate better, enhancing the overall collaboration effect.

[0009] 3) Complete functions: Existing process engines mostly focus on basic approval functions, while the present invention realizes the integration of "rule-driven + approval execution" through the in-depth cooperation between conditional nodes and approval nodes (such as the approval result triggering a branch process), solving the problem of "function fragmentation" in traditional systems.

[0010] 4) User experience: Traditional systems rely on code development to adjust the process. The present invention greatly reduces the usage threshold for non-technical personnel through a graphical configuration interface and real-time visual monitoring.

[0011] 5) Traceability and room for improvement: The workflow records the execution of each step, facilitating post-event analysis. By storing process execution data, users can analyze historical data through native SQL, APIs, or custom reporting tools. Common analysis scenarios include process performance analysis, task processing efficiency analysis, process exception analysis, etc. It can be seen from actual cases that the analysis based on historical data can help users identify process bottlenecks and optimize task allocation strategies, thereby improving the efficiency and quality of business processes.

[0012] 6) Standardization and consistency: The workflow ensures consistent execution results each time through a standardized process. It reduces the impact of human factors on the results and improves reliability.

[0013] The process engine supports multiple approval operations and can more flexibly handle various business scenarios and requirements. In case of abnormal situations during the approval process, the administrator can also perform emergency handling through the backend system, improving the adaptability and reliability of the process.

[0014] Process modeling driven by business requirements and dynamic binding of rules; realizing automated conditional judgment and task assignment based on a rule engine; improving the efficiency of exception handling by combining visual monitoring and real-time warning; supporting multi-dimensional data analysis to promote continuous process optimization. It can quickly respond to business changes, reduce manual configuration costs, ensure the consistency and compliance of process execution, and significantly improve the agility and reliability of enterprise business processes through a closed-loop feedback mechanism Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the embodiments of the present invention Description of the Drawings

[0015] Figure 1 It is a flowchart of a method for managing workflow conditional nodes based on a dynamic rule engine proposed by the present invention Detailed Embodiments

[0016] The embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention

[0017] These and other aspects of the embodiments of the present invention will be clear with reference to the following description and drawings. In these descriptions and drawings, some specific embodiments of the embodiments of the present invention are specifically disclosed to represent some ways of implementing the principles of the embodiments of the present invention, but it should be understood that the scope of the embodiments of the present invention is not limited thereto

[0018] Please refer to Figure 1 , this embodiment provides a method for managing workflow conditional nodes based on a dynamic rule engine, and the method includes the following steps Step 1: Obtain business transfer requirements, configure task node attributes (such as approvers, rule conditions, timeout policies), and adapt the business transfer requirements according to the task node attributes to obtain a process template model As a preferred embodiment of the present invention, obtaining business transfer requirements, configuring task node attributes, and adapting the business transfer requirements according to the task node attributes to obtain a process template model specifically includes the following steps Extract task nodes and business logic from the business transfer requirements. The task nodes include approval nodes and conditional nodes Configure attribute parameters for the approval nodes According to the business logic, associate the approval nodes with the conditional nodes after configuring the attribute parameters to generate a process template model including the transfer relationship and rule logic between the nodes After performing syntax verification and node logic conflict detection on the process template model to ensure its executability, store the process template model in the template library.

[0019] Step 2: Set rule conditions, bind the rule conditions to task nodes, and update the process template model to obtain an updated process template model; As a preferred embodiment of the present invention, setting rule conditions, binding the rule conditions to task nodes, and updating the process template model to obtain an updated process template model specifically includes the following steps: Locate condition nodes in the process template model and input rule condition expressions through a rule editor; Configure priority weights and conflict resolution strategies for multiple rule conditions; Bind the rule conditions to the condition nodes to generate metadata that can be parsed by the rule engine; Simulate the execution of the verification approval process and the coordination of conditional branches for the metadata to update the rule logic in the process template model.

[0020] As a preferred embodiment of the present invention, binding the rule conditions to the condition nodes to generate metadata that can be parsed by the rule engine specifically includes the following steps: Preset a business field comparison table and extract business fields from the business field comparison table; Parse the mathematical operators and logical relationships in the rule condition expression, and decompose the parallel relationship in the logical relationship into independent judgment conditions to obtain rule elements; Combine the business fields with the rule elements to form a structured rule element list; Locate the target nodes in the condition nodes, and based on the judgment rules in the structured rule element list, establish a forward flow association when the rule conditions are met; when the conditions are not met, set a reverse flow association to obtain a node binding relationship record table; According to the priority weights and conflict resolution strategies, assign priorities to the next condition nodes in the forward flow association or reverse flow association to obtain a node binding relationship record table with priorities; Perform machine-readable processing on the node binding relationship record table with priorities and encapsulate it to obtain metadata that can be parsed by the rule engine.

[0021] Step 3: Generate a process instance according to the updated process template model, parse the rule conditions, initialize the task assignment logic, and push the to-do tasks to the user; As a preferred embodiment of the present invention, generating a process instance according to the updated process template model, parsing the rule conditions, initializing the task assignment logic, and pushing the to-do tasks to the user specifically includes the following steps: Load the updated process template model from the template library and generate a process instance by associating business data (such as contract number, amount); Call the rule engine to parse the rule expressions in the conditional nodes of the process instance and dynamically calculate the task assignment path; Based on the task assignment path, push the to-do tasks to the to-do list of the target user or system interfaces, such as emails, API callbacks, etc.; Record the initial state of the process instance and the task queue information, and synchronize them to the database and cache layer.

[0022] To better reduce the access pressure on the database, the data during the process execution is separated and stored in the form of hot data and cold data, and the cache mechanism is combined to optimize the data access efficiency, generating real-time processing data and historical archived data. Among them, optimizing the data access efficiency and generating real-time processing data and historical archived data specifically include the following steps: Identify the frequently accessed data (hot data) and infrequently accessed data (cold data) in the process instance through the data classification module; Store the hot data in the in-memory database and set multiple-level caches to respond to the process status query and operation requests in real time; Compress the cold data and archive it to generate archive logs and historical execution records; Ensure the consistency of the hot data and the database through the cache synchronization mechanism to reduce the access pressure on the main database.

[0023] As a preferred embodiment of the present invention, calling the rule engine to parse the rule expressions in the conditional nodes of the process instance and dynamically calculate the task assignment path specifically includes the following steps: Obtain the business data, approver role, and the current number of to-do tasks of the approver during the process instantiation stage; According to the timeliness information of the business data, obtain the urgency coefficient; according to the approver role, obtain the role base score; according to the current number of to-do tasks of the approver and the task processing ability of the approver, obtain the load pressure value; Convert the urgency coefficient into a gain multiple, and adjust the role base score according to the gain multiple and the load pressure value to obtain a candidate node dynamic scoring table; Set an admission threshold, and screen the candidate node dynamic scoring table according to the admission threshold to generate a preliminary selection path list; Construct a risk timeliness weight by using the timeliness information of the business data and the project risk level; Statistical historical approval efficiency and the current rule trigger frequency, and dynamically and adaptively adjust the risk timeliness weight according to the historical approval efficiency and the current rule trigger frequency to generate a dynamic risk timeliness weight; The initial selection path list is weighted and adjusted using dynamic risk time - effect weights to obtain a final selection path ranking list, and task allocation is performed based on the final selection path ranking list.

[0024] In the above solution, the present invention designs a multi - dimensional dynamic decision - making mechanism. Through the dynamic coupling calculation of five - dimensional data including role permissions, real - time load, time - effect pressure, risk level, and historical efficiency, the task allocation path can automatically adapt to changes in the business scenario (such as automatically diverting tasks during the business peak period), effectively preventing resource idleness or overload problems caused by fixed thresholds. And it can automatically adjust the weight ratio of risk and time - effect. Compared with the traditional method that requires manual regular calibration of parameters, this feature enables the system to have the ability of continuous evolution.

[0025] Step 4: The user executes the to - do task, triggers the rule engine for condition judgment, updates the process instance status, and obtains the updated process instance status. As a preferred embodiment of the present invention, when the user executes the to - do task, triggers the rule engine for condition judgment, and updates the process instance status, obtaining the updated process instance status specifically includes the following steps: The user receives the to - do task through the front - end interface and performs approval, rejection, or transfer operations. Trigger the rule engine to perform condition judgment on the current operation (such as "re - submission to the previous node is required after rejection"); update the process instance status according to the judgment result (such as "approval passed" or "returned for modification"), and trigger the task allocation of the next node. Write the status change information of the process instance status into the execution log and synchronize it to the database and message queue for the monitoring module to call.

[0026] As a preferred embodiment of the present invention, triggering the rule engine to perform condition judgment on the current operation (such as "re - submission to the previous node is required after rejection"); updating the process instance status according to the judgment result (such as "approval passed" or "returned for modification"), and triggering the task allocation of the next node specifically includes the following steps: Parse the user operation type, obtain the type flag, and extract the risk characteristic data of the current contract and the load status of the target approver. Perform shunt processing according to the operation type flag. If it is an approval - passed operation, jump to the risk review branch; if it is a rejection operation, enter the rejection reason analysis branch; if it is a transfer operation, start the path conflict detection branch. If in the risk review branch, perform risk quantification analysis on the risk characteristic data of the current contract based on historical approval records to obtain a dynamic risk score report. Set the basic weight according to the current approver's rank, and adjust the basic weight using the impact of the current to - do task on the approval efficiency to obtain the actually effective weight. According to the actual effective weight and the dynamic risk scoring report, generate a parallel alternative approval path for the approver of the department collaboration relationship, obtain an approval path decision instruction to update the process instance status; If in the rejection analysis branch, obtain the rejection reason text and identify the cause keywords in the rejection reason text; According to the cause keywords, retrieve the occurrence frequency of historical rejections of the same type to calculate the severity index of the current rejection reason, and obtain a rejection feature analysis report; According to the number of rejections of the same type and the severity index in the rejection feature analysis report, assign identifiers for different emergency situations to the current approval, obtain a process upgrade decision letter, and overwrite the original approval path with the process upgrade decision letter to update the process instance status; If in the path conflict detection branch, generate an initial priority ranking according to the approver's rank and dynamically adjust the initial priority ranking according to the current load of the target approver to obtain a dynamic priority matrix; Detect the repeated occupation of approvers in multiple alternative paths in the dynamic priority matrix. According to the repeated occupation situation of approvers, select the combination of approvers with the highest priority and the lowest load, generate a new approval path to avoid resource conflicts, and replace the original conflict path with the new approval path to avoid resource conflicts to update the process instance status.

[0027] In the above solution, the present invention performs three-dimensional coupling analysis on user behavior data (operation type), business feature data (contract risk), and system resource data (approver load). This design enables the decision-making logic to simultaneously meet the triple requirements of business compliance, operation rationality, and system stability, and can effectively reduce the error rate of judgment. And the designed dynamic priority matrix prevents resource deadlocks by pre-calculating the following parameters: the probability of approval path cross-conflict, the predicted value of approver task saturation, and the estimated cross-departmental collaboration delay.

[0028] Step 5: Generate a visual interface according to the updated process instance status to display the process progress, and real-time warning of overtime or abnormal tasks, obtain a monitoring report and the process instance status after exception handling.

[0029] As a preferred embodiment of the present invention, generating a visual interface according to the updated process instance status to display the process progress, and real-time warning of overtime or abnormal tasks, obtaining a monitoring report and the process instance status after exception handling specifically includes the following steps: Obtain the real-time status data of the process instance from the front-end monitoring interface and render it in the form of a flowchart to display the progress of node completion; According to the progress of node completion, scan for overtime tasks (such as unapproved overtime) or abnormal status (such as being rejected three times in a row) through the warning module, and trigger SMS or in-site message notifications; Generate a monitoring report based on the aggregated log data, where the monitoring report includes the task processing time limit, the rule trigger frequency, and the abnormal event distribution; Generate optimization suggestions (such as adjusting the rule threshold or adding parallel approval nodes) according to the report analysis results, and update them to the template library.

[0030] In this embodiment, the present invention adopts a front-end and back-end separated development mode. The front end uses vue.js, and the back end uses the Java language for development, supporting Sass-based deployment. It is built based on the process engine flowable and complies with the process function design and implementation of the BPMN2.0 specification.

[0031] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0032] It should be understood that each part of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiment, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following well-known technologies in the art can be used: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0033] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0034] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

Claims

1. A method for managing workflow condition nodes based on a dynamic rule engine, characterized in that, The method includes the following steps: Step 1: Obtain the business process flow requirements, configure the task node attributes, and adapt the business process flow requirements according to the task node attributes to obtain a process template model; Step 2: Set rule conditions, bind the rule conditions to the task nodes, and update the process template model to obtain an updated process template model; Step 3: Generate a process instance according to the updated process template model, parse the rule conditions, initialize the task assignment logic, and push the to-do tasks to the users; Step 4: The user executes the to-do tasks, triggers the rule engine to perform condition judgment, and updates the process instance status to obtain an updated process instance status; Step 5: Generate a visual interface according to the updated process instance status to display the process progress, and real-time warn of overdue or abnormal tasks to obtain a monitoring report and the process instance status after exception handling.

2. The workflow condition node management method based on a dynamic rule engine according to claim 1, characterized in that In the said Step 1, obtaining the business process flow requirements, configuring the task node attributes, and adapting the business process flow requirements according to the task node attributes to obtain a process template model specifically includes the following steps: Extract task nodes and business logics from the business process flow requirements, where the task nodes include approval nodes and condition nodes; Configure attribute parameters for the approval nodes; According to the business logic, associate the approval nodes with configured attribute parameters with the condition nodes to generate a process template model including the flow relationship and rule logic between nodes; Perform syntax verification and node logic conflict detection on the process template model, and store the process template model in the template library.

3. The workflow condition node management method based on a dynamic rule engine according to claim 2, characterized in that, In the said Step 2, setting rule conditions, binding the rule conditions to the task nodes, and updating the process template model to obtain an updated process template model specifically includes the following steps: Locate the condition nodes from the process template model, and input the rule condition expressions through a rule editor; Configure priority weights and conflict resolution strategies for multiple rule conditions; Bind the rule conditions to the condition nodes to generate metadata that can be parsed by the rule engine; Simulate and execute the verification of the coordination between the approval flow and the condition branches for the metadata, and update the rule logic in the process template model.

4. The workflow condition node management method based on a dynamic rule engine according to claim 3, characterized in that Binding the rule conditions to the condition nodes to generate metadata that can be parsed by the rule engine specifically includes the following steps: Preset a business field comparison table, and extract the business fields in the business field comparison table; Parse the mathematical operators and logical relationships in the rule condition expressions, and decompose the parallel relationships in the logical relationships into independent judgment conditions to obtain rule elements; Combine the business fields with the rule elements to form a structured rule element list; Locate the target nodes in the condition nodes, and based on the judgment rules in the structured rule element list, establish a forward flow association when the rule conditions are met; When the conditions are not met, set a reverse flow association to obtain a node binding relationship record table; According to the priority weights and conflict resolution strategies, assign priorities to the next condition nodes in the forward flow association or the reverse flow association to obtain a node binding relationship record table with priorities; Perform machine-readable processing on the node binding relationship record table with priorities, and perform encapsulation to obtain metadata that can be parsed by the rule engine.

5. The workflow condition node management method based on a dynamic rule engine according to claim 4, wherein In step 3, a process instance is generated according to the updated process template model, the rule conditions are parsed, the task assignment logic is initialized, and the to-do tasks are pushed to the user, which specifically includes the following steps: Load the updated process template model from the template library and generate a process instance by associating business data; Call the rule engine to parse the rule expressions in the condition nodes of the process instance and dynamically calculate the task assignment path; Based on the task assignment path, push the to-do tasks to the to-do list of the target user or the system interface; Record the initial state of the process instance and the task queue information, and synchronize them to the database and cache layer.

6. The workflow condition node management method based on a dynamic rule engine according to claim 5, wherein Calling the rule engine to parse the rule expressions in the condition nodes of the process instance and dynamically calculate the task assignment path specifically includes the following steps: Obtain the business data, approver role, and the current number of to-do tasks of the approver during the process instantiation phase; According to the timeliness information of the business data, obtain the urgency coefficient; according to the approver role, obtain the role base score; according to the current number of to-do tasks of the approver and the task processing ability of the approver, obtain the load pressure value; Convert the urgency coefficient into a gain multiple, and adjust the role base score according to the gain multiple and the load pressure value to obtain a candidate node dynamic scoring table; Set an admission threshold, and filter the candidate node dynamic scoring table according to the admission threshold to generate a preliminary selection path list; Construct a risk timeliness weight using the timeliness information of the business data and the project risk level; Statistical historical approval efficiency and the current rule trigger frequency, and dynamically and adaptively adjust the risk timeliness weight according to the historical approval efficiency and the current rule trigger frequency to generate a dynamic risk timeliness weight; Use the dynamic risk timeliness weight to perform weighted adjustment on the preliminary selection path list to obtain a final selection path sorting table, and perform task assignment based on the final selection path sorting table.

7. The workflow condition node management method based on a dynamic rule engine according to claim 6, characterized in that In step 4, the user executes the to-do task, triggers the rule engine to perform condition judgment, and updates the process instance state to obtain the updated process instance state, which specifically includes the following steps: The user receives the to-do task through the front-end interface and performs approval, rejection, or transfer operations; Trigger the rule engine to perform condition judgment on the current operation; update the process instance state according to the judgment result, and trigger the task assignment of the next node; Write the status change information of the process instance state into the execution log, and synchronize it to the database and message queue for the monitoring module to call.

8. The workflow condition node management method based on a dynamic rule engine according to claim 7, wherein, Trigger the rule engine to perform condition judgment on the current operation; update the process instance state according to the judgment result, and trigger the task assignment of the next node, which specifically includes the following steps: Parse the user operation type, obtain the type flag, and extract the risk characteristic data of the current contract and the load status of the target approver; Perform shunt processing according to the operation type flag. If it is an approval passed operation, jump to the risk review branch; If it is a rejection operation, enter the rejection reason analysis branch; If it is a transfer operation, start the path conflict detection branch; If in the risk review branch, perform risk quantification analysis on the risk characteristic data of the current contract according to the historical approval records to obtain a dynamic risk scoring report; Set the basic weight according to the current approver's rank, and adjust the basic weight by using the impact of the current to-do task on the approval efficiency to obtain the actually effective weight; According to the actually effective weight and the dynamic risk scoring report, generate a parallel alternative approval path for the approver of the department collaboration relationship, obtain the approval path decision instruction, and update the process instance status; If in the rejection analysis branch, obtain the rejection reason text and identify the cause keywords in the rejection reason text; According to the cause keywords, retrieve the occurrence frequency of historical rejections of the same type to calculate the severity index of the current rejection reason, and obtain the rejection feature analysis report; According to the number of rejections of the same type and the severity index in the rejection feature analysis report, assign different emergency situation identifiers to the current approval, obtain the process upgrade decision letter, and overwrite the original approval path with the process upgrade decision letter to update the process instance status; If in the path conflict detection branch, generate an initial priority ranking according to the approver's rank, and dynamically adjust the initial priority ranking according to the current load of the target approver to obtain the dynamic priority matrix; Detect the repeated occupation of approvers in multiple alternative paths in the dynamic priority matrix. According to the repeated occupation of approvers, select the approver combination with the highest priority and the lowest load, generate a new approval path to avoid resource conflicts, and replace the original conflict path with the new approval path to avoid resource conflicts to update the process instance status.

9. The workflow condition node management method based on a dynamic rule engine according to claim 8, wherein, In the step 5, generate a visual interface according to the updated process instance status to display the process progress, and give a real-time warning for overtime or abnormal tasks, and obtain the monitoring report and the process instance status after exception handling, which specifically includes the following steps: Obtain the real-time status data of the process instance from the front-end monitoring interface and render it in the form of a flowchart to display the node completion progress; According to the node completion progress, scan for overtime tasks or abnormal status through the warning module to trigger SMS or in-site message notifications; Generate a monitoring report according to the aggregated log data, and the monitoring report includes task processing timeliness, rule trigger frequency, and abnormal event distribution; Generate optimization suggestions according to the report analysis results and update them to the template library.

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