A process engine implementation method based on a multi-dimensional approver computing engine

Abstract

The application discloses a kind of process engine implementation method based on multidimensional approver computing engine, it is related to enterprise management technical field, to Camunda process engine bit as foundation, this kind of process engine implementation method based on multidimensional approver computing engine, by the method, based on Camunda process engine core builds stable and reliable engine layer, on it new approval person configuration, personnel analysis and rule matching etc. Core extension component, user is configured by process designer to select person type and parameter, when process flows to corresponding node, flexible person selection extension layer is driven by event in real time to receive and process signal, by the operation of routing of person decision maker, each resolver query extraction information, program script engine calculation and personnel result summary processor de-duplication and merging, obtain accurate approval person list and pass to basic engine allocation task, flow process, until end, the method improves the flexibility and adaptability of process engine, ensure that process is smoothly and efficiently executed.

Description

Technical Field

[0001] This invention relates to the field of enterprise management technology, specifically to a process engine implementation method based on a multi-dimensional approver calculation engine. Background Technology

[0002] As a core support tool for enterprise digital business processes, the process engine is responsible for defining, executing, monitoring and assigning tasks to processes. In actual business operations, the logic for determining approvers is often complex and diverse, requiring dynamic generation based on multiple dimensions such as department affiliation, job functions, and role permissions. However, existing open-source process engines (such as Camunda and Activity) only support fixed personnel configuration modes, which cannot meet the enterprise's need for "dynamic calculation on demand" of approvers. This results in rigid process configuration, poor adaptability, and increases the complexity and maintenance costs of enterprise process management.

[0003] Open-source workflow engines typically have fixed approvers, and the system only supports fixed user IDs or fixed roles by default. They cannot dynamically select approvers based on business changes, which is not flexible enough to meet the real approval needs of enterprises. Enterprises often need to extend the code themselves, which is highly intrusive, has high maintenance costs, and is difficult to reuse. Summary of the Invention

[0004] The purpose of this invention is to provide a process engine implementation method based on a multi-dimensional approver calculation engine to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for implementing a process engine based on a multi-dimensional approver calculation engine, the method comprising the following steps: S1: Based on the Camunda process engine, build a basic engine layer, a flexible personnel selection extension layer, and an application layer; The basic engine layer is based on the Camunda process engine core and provides basic capabilities for process execution and task scheduling. The flexible personnel selection extension layer uses the new approver configuration module, personnel parsing module and rule matching module as core extension components. The application layer uses the interactive interface of the process designer and process management portal to provide a visual configuration entry and process operation. S2: Users can select the target person selection type and fill in the corresponding configuration parameters in the user node configuration interface through the visual process designer; S3: The process flows to the user node, where the flexible selection extension layer receives the trigger signal and calls the parsing logic for the corresponding selection type; S4: Based on the configuration type of the newly added approver configuration module, query the personnel corresponding to the department or position through the organizational structure service, extract the personnel associated with the specified fields from the form data, execute the program script to calculate the target personnel, and obtain the accurate list of approvers; S5: Pass the parsed list of approvers to the Camunda base engine, which then assigns tasks to be done, and the process continues until it ends.

[0006] Preferably, the approver configuration module includes seven configuration types: fixed personnel, department affiliation, job level, custom grouping, role association, form data transmission, and program script calculation.

[0007] Preferably, after receiving the configuration parameters, the personnel parsing module dynamically parses and obtains the target approver list through the organizational structure service, form data service, and script execution engine.

[0008] Preferably, the rule matching module supports configurations for repeated processing by approvers and fallback configurations for cases without approvers.

[0009] Preferably, in step S2, the user sets multi-dimensional node approvers through visual operation, constructs a multi-dimensional approver designer, and forms a structured configuration.

[0010] Preferably, in step S3, the trigger signal received by the flexible selection extension layer is a request and result from the approver calculation engine, and the request and result of the calculation engine form a multi-dimensional approver calculation engine layer.

[0011] Preferably, the multidimensional approver calculation engine layer includes a personnel selection decision-maker, a job configuration parser, a department configuration parser, a program script engine, and a personnel result summary processor; The personnel selection decision-maker develops a rule routing component that receives request parameters from approval nodes and routes them to the corresponding parser based on the rule type. The job configuration parser development interface connects to the personnel proxy service, which identifies all valid personnel under the job code. The department configuration parser development interface connects with the personnel agent service, allowing users to query the department head, member list, and designated personnel based on the department code; The role configuration parser development interface connects to the personnel agent service to query all persons who own the role based on the personnel code; The program script engine integrates an open-source script execution framework, supporting the execution of custom scripts; The personnel results summary processor developed deduplication algorithms, merging logic, and fallback strategies.

[0012] Preferably, if the accurate list of approvers is not obtained in step S4, approver proxy configuration is supported. The target approver sets up a proxy, and the task is automatically assigned to the proxy.

[0013] Preferably, in step S5, the flow rules connect the previous node and the next node through node flow to achieve the continuity of the process.

[0014] Preferably, the fallback strategy in the personnel result summary processor is to return the process initiator's superior when there are no personnel.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention utilizes a method to build a stable and reliable engine layer based on the core of the Camunda workflow engine. Core extension components such as approver configuration, personnel parsing, and rule matching are added on top of this layer. Users configure the selection type and parameters through the workflow designer. When the workflow reaches the corresponding node, the flexible personnel selection extension layer receives and processes signals in real time using an event-driven architecture. Through operations such as routing by the personnel selection decision-maker, information extraction by various parsers, calculation by the program script engine, and deduplication and merging by the personnel result summary processor, an accurate list of approvers is obtained and transmitted to the basic engine for task allocation and workflow transition until completion. This method improves the flexibility and adaptability of the workflow engine, ensuring smooth and efficient workflow execution. Attached Figure Description

[0016] Figure 1 This is a diagram illustrating the interaction architecture between the multi-dimensional approver calculation engine and process nodes of this invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example: Please refer to Figure 1 This invention provides a technical solution: a method for implementing a process engine based on a multi-dimensional approver calculation engine, the method comprising the following steps: S1: Based on the Camunda process engine, build a basic engine layer, a flexible personnel selection extension layer, and an application layer; The basic engine layer is based on the Camunda process engine core, providing basic capabilities for process execution and task scheduling. The flexible personnel selection extension layer uses the new approver configuration module, personnel parsing module and rule matching module as core extension components. The application layer uses the interactive interface of the process designer and process management portal to provide a visual configuration entry and process operation. S2: Users can select the target person selection type and fill in the corresponding configuration parameters in the user node configuration interface through the visual process designer; S3: The process flows to the user node, where the flexible selection extension layer receives the trigger signal and calls the parsing logic for the corresponding selection type; S4: Based on the configuration type of the newly added approver configuration module, query the personnel corresponding to the department or position through the organizational structure service, extract the personnel associated with the specified fields from the form data, execute the program script to calculate the target personnel, and obtain the accurate list of approvers; S5: Pass the parsed list of approvers to the Camunda base engine, which then assigns tasks to be done, and the process continues until it ends.

[0019] The approver configuration module includes seven configuration types: fixed personnel, department affiliation, job level, custom grouping, role association, form data transfer, and program script calculation.

[0020] After receiving the configuration parameters, the personnel parsing module dynamically parses and obtains the target approver list through the organizational structure service, form data service, and script execution engine.

[0021] The rule matching module supports configurations for duplicate processing by approvers and fallback configurations for cases without approvers.

[0022] In step S2, users set up multi-dimensional node approvers through visual operations, build a multi-dimensional approver designer, and form a structured configuration.

[0023] In step S3, the flexible selection of the extension layer receives the trigger signal. The trigger signal is mostly the request and result of the approver calculation engine. The request and result of the calculation engine form a multi-dimensional approver calculation engine layer.

[0024] The multidimensional approver calculation engine layer includes a personnel selection decision-maker, a job configuration parser, a department configuration parser, a program script engine, and a personnel result aggregation processor; The personnel selection decision-maker develops a rule routing component that receives request parameters from approval nodes and routes them to the corresponding parser based on the rule type. The job configuration parser development interface connects to the personnel proxy service, which identifies all valid personnel under the job code. The department configuration parser development interface connects with the personnel agent service, allowing users to query the department head, member list, and designated personnel based on the department code; The role configuration parser development interface connects to the personnel agent service to query all persons who own the role based on the personnel code; The program script engine integrates an open-source script execution framework, supporting the execution of custom scripts; The personnel results summary processor developed deduplication algorithms, merging logic, and fallback strategies.

[0025] For those who did not obtain the accurate list of approvers in step S4, approver proxy configuration is supported. The target approver sets up a proxy, and the task is automatically assigned to the proxy.

[0026] In step S5, the flow rules connect the previous node and the next node through node flow, thus achieving the continuity of the process.

[0027] The fallback strategy in the personnel result summary processor is to return to the superior of the process initiator when there are no personnel.

[0028] The specific implementation method of this embodiment is as follows: Based on the Camunda workflow engine core, an engine layer is built to provide basic capabilities for workflow execution and task scheduling, ensuring its stable operation and providing a reliable workflow execution environment for upper layers. Above the basic engine layer, three new core extension components are added: an approver configuration module, a personnel parsing module, and a rule matching module. These modules are responsible for handling the dynamic configuration and parsing of approvers. Users log into the workflow designer and enter the user node configuration interface. In the configuration interface, they select the target personnel selection type and fill in the corresponding configuration parameters. When the workflow reaches a user node configured with flexible personnel selection, that node sends a trigger signal to the flexible personnel selection extension layer. After receiving the signal, the flexible personnel selection extension layer parses the request parameters of the approval node. An event-driven architecture is adopted to ensure real-time signal reception and processing. The data is parsed and validated to provide an accurate data foundation for subsequent processing. The personnel selection decision-maker routes the request to the corresponding parser based on the rule type in the request parameters. Each parser queries personnel information corresponding to departments or positions by calling components such as organizational structure service and form data service, or extracts personnel information associated with specified fields from form data. If a program script calculation type is configured, the program script engine is called to execute a custom script to calculate the target approver. The personnel result summary processor performs deduplication and merging on the parsed approver list to ensure the accuracy and uniqueness of the approver list. The parsed approver list is then passed to the Camunda basic engine. The Camunda basic engine assigns pending tasks based on the approver list and moves the process to the next node, repeating the above steps until the process ends.

[0029] Taking the "procurement approval process" as an example, the specific operational logic is shown below: In the process design phase: Configure a department configuration parser at the "Procurement Department Preliminary Review" node with the parameter "Procurement Department"; configure a position configuration parser at the "CFO Review" node with the parameter "CFO"; configure a program script engine at the "Legal Compliance Verification" node with the script logic "Based on the contract amount, if it exceeds 500,000, it requires joint approval from Legal Manager A and Legal Manager B"; Process initiation stage: The procurement personnel submit a procurement application, and the process flows to the "procurement department preliminary review" node, which initiates a proxy request to the multi-dimensional approver calculation engine; Execution phase of the computing engine: The personnel selection decision-maker identifies the rule type of "preliminary review by the procurement department" as "department" and calls the department configuration parser; The department configuration parser calls the personnel agent service to query the list of responsible persons in the "Purchasing Department" and returns the results to the personnel result summary processor. After deduplication by the aggregate processor, the data is returned to the head of the purchasing department as the initial reviewer and approver. After the initial review is completed, the process moves to the "CFO review" node, repeats the above logic, and obtains the "CFO" as the reviewer through the job configuration parser; After the review is completed, the process flows to the "Legal Compliance Verification" node. The personnel selection decision-maker calls the program script engine to execute the custom script and calculates legal managers A and B as compliance verification approvers. Process completion stage: After all approvers have completed their tasks, the process moves to the next node until the process ends.

[0030] Abnormal scenario handling: No approver scenario: If no matching personnel are found after calculation for a certain node, the personnel result summary processor triggers the fallback strategy, automatically assigning the task to the process administrator or returning it to the initiator; Multi-parser collaboration scenario: Supports calling multiple parsers on the same node (such as "department head + job expert"); the personnel result aggregation processor merges the results of multiple parsers and removes duplicates. Agency relationship scenario: The personnel agency service supports the configuration of approver agents. When the target approver sets up an agent, the task will be automatically assigned to the agent.

[0031] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for implementing a workflow engine based on a multi-dimensional approver calculation engine, characterized in that: The method includes the following steps: S1: Based on the Camunda process engine, build a basic engine layer, a flexible personnel selection extension layer, and an application layer; The basic engine layer is based on the Camunda process engine core and provides basic capabilities for process execution and task scheduling. The flexible personnel selection extension layer uses the new approver configuration module, personnel parsing module and rule matching module as core extension components. The application layer uses the interactive interface of the process designer and process management portal to provide a visual configuration entry and process operation. S2: Users can select the target person selection type and fill in the corresponding configuration parameters in the user node configuration interface through the visual process designer; S3: The process flows to the user node, where the flexible selection extension layer receives the trigger signal and calls the parsing logic for the corresponding selection type; S4: Based on the configuration type of the newly added approver configuration module, query the personnel corresponding to the department or position through the organizational structure service, extract the personnel associated with the specified fields from the form data, execute the program script to calculate the target personnel, and obtain the accurate list of approvers; S5: Pass the parsed list of approvers to the Camunda base engine, which then assigns tasks to be done, and the process continues until it ends.

2. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: The approver configuration module includes seven configuration types: fixed personnel, department affiliation, job level, custom grouping, role association, form data transmission, and program script calculation.

3. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: After receiving the configuration parameters, the personnel parsing module dynamically parses and obtains the target approver list through the organizational structure service, form data service, and script execution engine.

4. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: The rule matching module supports configurations for repeated processing by approvers and fallback configurations for cases without approvers.

5. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: In step S2, the user sets up multi-dimensional node approvers through visual operation, builds a multi-dimensional approver designer, and forms a structured configuration.

6. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: In step S3, the flexible selection of the extension layer receives the trigger signal. The trigger signal is mostly the request and result of the approver calculation engine. The request and result of the calculation engine form a multi-dimensional approver calculation engine layer.

7. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: The multidimensional approver calculation engine layer includes a personnel selection decision-maker, a job configuration parser, a department configuration parser, a program script engine, and a personnel result aggregation processor. The personnel selection decision-maker develops a rule routing component that receives request parameters from approval nodes and routes them to the corresponding parser based on the rule type. The job configuration parser development interface connects to the personnel proxy service, which identifies all valid personnel under the job code. The department configuration parser development interface connects with the personnel agent service, allowing users to query the department head, member list, and designated personnel based on the department code; The role configuration parser development interface connects to the personnel agent service to query all persons who own the role based on the personnel code; The program script engine integrates an open-source script execution framework, supporting the execution of custom scripts; The personnel results summary processor developed deduplication algorithms, merging logic, and fallback strategies.

8. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: If no accurate list of approvers is obtained in step S4, approver proxy configuration is supported. The target approver sets up a proxy, and the task is automatically assigned to the proxy.

9. The method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 1, characterized in that: In step S5, the flow rules connect the previous node and the next node through node flow, thereby achieving the continuity of the process.

10. A method for implementing a workflow engine based on a multi-dimensional approver calculation engine according to claim 7, characterized in that: The fallback strategy in the personnel result summary processor is to return the process initiator's superior when there are no personnel.

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