MOM scenario component identification method, system, device and medium based on dynamic chain flow

Abstract

The application discloses a MOM scene component identification method, system, device and medium based on a dynamic chain process, relates to the technical field of intelligent manufacturing, and comprises the following steps: acquiring a natural language requirement of a user under a current MOM scene, analyzing the natural language requirement, and constructing a corresponding dynamic chain process graph; performing scene unit identification according to the dynamic chain process graph to obtain at least one scene unit, wherein the scene unit is a minimum business action logic unit that can be reused; for each scene unit, a corresponding scene unit description model is constructed according to the scene unit, wherein the scene unit description model is used to represent the scene attribute of the scene unit; and for each scene unit, the scene unit description model is matched in a historical component library based on a predefined matching rule to determine a corresponding implementation component. The application has the effect of improving the development efficiency of a MOM system.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of intelligent manufacturing, in particular to a MOM scene component identification method, system, device and medium based on a dynamic chain process. BACKGROUND

[0002] In the process of intelligent manufacturing and digital workshop construction, a manufacturing operation management system (MOM) plays a key role in connecting business and execution, is the core system for realizing digital, visual and automatic workshop management, and is widely used in the fields of production planning, quality management, equipment management and logistics execution.

[0003] With the rapid changes in enterprise needs and the continuous evolution of business scenarios, the traditional MOM platform faces the following challenges in custom development for complex scenarios: it is difficult to structure the requirement description, that is, business personnel often express requirements in natural language or semi-structured ways, lack standardized and structured expression means, and it is difficult for developers to understand and develop efficiently; lack of abstraction ability of scene components, that is, the custom development of the MOM system lacks effective abstraction and identification of scene components, which easily causes repeated construction and code redundancy, and it is difficult to fully reuse existing execution units; and the matching of dynamic chain processes and execution units is insufficient, that is, it is difficult to establish an efficient intelligent matching and association between existing execution units and new requirements in the custom development process, resulting in low development efficiency and low reuse rate.

[0004] To improve the development efficiency of the MOM system, the application provides a MOM scene component identification method, system, device and medium based on a dynamic chain process. SUMMARY

[0005] To improve the development efficiency of the MOM system, the application provides a MOM scene component identification method, system, device and medium based on a dynamic chain process.

[0006] In a first aspect, the application provides a MOM scene component identification method based on a dynamic chain process, which adopts the following technical scheme:

[0007] The MOM scene component identification method based on a dynamic chain process comprises the following steps:

[0008] Obtaining a natural language requirement of a user under a current MOM scene, and analyzing the natural language requirement to construct a corresponding dynamic chain process diagram;

[0009] Identifying a scene unit according to the dynamic chain process diagram to obtain at least one scene unit, wherein the scene unit is a reusable minimum business action logic unit;

[0010] For each of the scene units, a corresponding scene unit description model is constructed according to the scene unit, wherein the scene unit description model is used to represent the scene attribute of the scene unit;

[0011] For each of the scene units, the scene unit description model is matched in a historical component library based on a predefined matching rule to determine a corresponding implementation component.

[0012] By adopting the technical solution, the natural language requirement of a user under a current MOM scene is obtained, the natural language requirement is parsed, a corresponding dynamic chain flowchart is constructed, scene unit recognition is performed according to the dynamic chain flowchart, at least one scene unit is obtained, the scene unit is a reusable minimum business action logic unit, for each of the scene units, a corresponding scene unit description model is constructed according to the scene unit, the scene unit description model is used to represent the scene attribute of the scene unit, for each of the scene units, the scene unit description model is matched in a historical component library based on a predefined matching rule to determine a corresponding implementation component. In the above method, the fuzzy natural language requirement is structured (dynamic chain flowchart), the business scene is accurately decomposed (scene unit recognition), the standardized component description model (scene unit description model) and the intelligent matching mechanism are used to efficiently reuse the historical assets (historical component library), thereby systematically solving the core pain points of difficult requirement understanding, weak component abstraction and low reuse rate in traditional MOM customized development, improving the development efficiency of the MON system, reducing the development cost, and enhancing the flexibility and maintainability of the system.

[0013] Optionally, the step of parsing the natural language requirement and constructing a corresponding dynamic chain flowchart comprises:

[0014] The natural language requirement is structured according to a MOM scene requirement based on a predefined node structure to obtain at least one business node, wherein the business node comprises a role unit, a scene unit, a trigger condition unit and an execution operation unit.

[0015] The at least one business node is semantically connected based on a predefined semantic connection type to obtain a corresponding dynamic chain flowchart.

[0016] By adopting the technical solution, in order to construct the dynamic chain flowchart, the natural language requirement is structured according to a MOM scene requirement based on a predefined node structure to obtain at least one business node, wherein the business node comprises at least one of a role unit, a scene unit, a trigger condition unit and an execution operation unit, and the at least one business node is semantically connected based on a predefined semantic connection type to obtain a corresponding dynamic chain flowchart.

[0017] Optionally, the step of identifying a scene unit according to the dynamic chain flowchart comprises:

[0018] Obtaining scene semantics in the dynamic chain flowchart, and constructing a corresponding behavior chain flowchart according to the scene semantics, wherein the behavior chain flowchart comprises action nodes and state nodes;

[0019] Performing state node stripping on the behavior chain flowchart to obtain a corresponding scene unit.

[0020] By using the above technical solution, in order to realize the identification of the scene unit, the scene semantics in the dynamic chain flowchart is obtained, and a corresponding behavior chain flowchart is constructed according to the scene semantics, wherein the behavior chain flowchart comprises action nodes and state nodes, and then the state node stripping is performed on the behavior chain flowchart to obtain a corresponding scene unit.

[0021] Optionally, the step of matching the scene unit description model with the historical component library based on a predefined matching rule to determine a corresponding implementation component comprises:

[0022] Obtaining component attributes of each historical component in the historical component library, and determining scores of the historical components according to the scene attributes and the component attributes, wherein the scores are used to represent matching degrees of the historical components and the scene unit;

[0023] Taking a historical component corresponding to a maximum value in the scores as an implementation component of the scene unit.

[0024] By using the above technical solution, in order to realize the matching of the scene unit description model and the historical component, the component attributes of each historical component in the historical component library are obtained, and the scores of the historical components are determined according to the scene attributes and the component attributes, wherein the scores are used to represent the matching degrees of the historical components and the scene unit, and then the historical component corresponding to the maximum value in the scores is taken as the implementation component of the scene unit.

[0025] Optionally, the scene attributes comprise scene unit description, scene unit name, scene unit classification, and scene unit IO, the component attributes comprise component description, component name, component classification, and component IO, and the step of determining the scores of the historical components according to the scene attributes and the component attributes comprises:

[0026] Determining a description similarity according to the scene unit description and the component description;

[0027] Determining a name similarity according to the scene unit name and the component name;

[0028] determine a category similarity according to the scene unit category and the component category, wherein the category similarity is used to represent whether the categories are consistent or the similarity of the category labels;

[0029] determine an IO similarity according to the scene unit IO and the component IO, wherein the IO similarity is used to represent the similarity of the input parameters and the output parameters in type, structure or keyword;

[0030] obtain the weight of each of the description similarity, the name similarity, the category similarity and the IO similarity, and determine a corresponding score according to the weight, the description similarity, the name similarity, the category similarity and the IO similarity.

[0031] By adopting the technical solution, in order to obtain the score of each historical component, the description similarity is determined according to the scene unit description and the component description, the name similarity is determined according to the scene unit name and the component name, the category similarity is determined according to the scene unit category and the component category, wherein the category similarity is used to represent whether the categories are consistent or the similarity of the category labels, the IO similarity is determined according to the scene unit IO and the component IO, wherein the IO similarity is used to represent the similarity of the input parameters and the output parameters in type, structure or keyword, then the weight of each of the description similarity, the name similarity, the category similarity and the IO similarity is obtained, and a corresponding score is determined according to the weight, the description similarity, the name similarity, the category similarity and the IO similarity.

[0032] Optionally, the scene attribute further includes a scene unit number, a preceding scene unit name, a following scene unit name, an upstream scene, an associated business scene, a start state, an end state, an associated business object and an external interface.

[0033] Optionally, after the step of matching the scene unit description model in the historical component library based on a predefined matching rule to determine the corresponding implementation component for each scene unit, the method further includes:

[0034] binding the corresponding implementation component with the corresponding scene unit.

[0035] By adopting the technical solution, the corresponding implementation component is bound with the corresponding scene unit, and when all the scene units are bound with a customized implementation component, a customizable and executable MOM system function module is automatically assembled.

[0036] In a second aspect, the application further provides a MOM scene component identification system based on a dynamic chain flow, which adopts the following technical solution:

[0037] The MOM scene component identification system based on the dynamic chain flow includes:

[0038] a dynamic chain flowchart construction module configured to acquire a natural language requirement of a user in a current MOM scenario, and to parse the natural language requirement and construct a corresponding dynamic chain flowchart;

[0039] a scenario unit identification module configured to identify scenario units according to the dynamic chain flowchart, and obtain at least one scenario unit, wherein the scenario unit is a minimum business action logic unit that can be reused;

[0040] a scenario unit description model construction module configured to, for each of the scenario units, construct a corresponding scenario unit description model according to the scenario unit, wherein the scenario unit description model is used to represent a scenario attribute of the scenario unit;

[0041] a component matching module configured to, for each of the scenario units, match the scenario unit description model in a historical component library based on a predefined matching rule, and determine a corresponding implementation component.

[0042] In a third aspect, the present application also provides a computer device, which adopts the technical scheme as follows:

[0043] A computer device includes a memory and a processor, the memory has a computer program capable of running on the processor, and the processor implements the method in the first aspect when executing the computer program.

[0044] In a fourth aspect, the present application also provides a computer readable storage medium, which adopts the technical scheme as follows:

[0045] A computer readable storage medium stores a computer program capable of being loaded and executed by a processor to implement the method in the first aspect.

[0046] In summary, this application includes at least the following beneficial technical effects: It acquires the natural language requirements of users in the current MOM scenario, parses these requirements, constructs a corresponding dynamic chain flowchart, identifies scenario units based on the dynamic chain flowchart to obtain at least one scenario unit, where each scenario unit is a reusable minimum business action logic unit. For each scenario unit, a corresponding scenario unit description model is constructed, representing the scenario attributes of the scenario unit. For each scenario unit, the scenario unit description model is matched against a historical component library based on predefined matching rules to determine the corresponding implementation component. In this method, by structuring fuzzy natural language requirements (dynamic chain flowchart), accurate decomposition of business scenarios (scenario unit identification) is achieved. Based on a standardized component description model (scenario unit description model) and an intelligent matching mechanism, historical assets (historical component library) are efficiently reused. This systematically solves the core pain points of difficult requirement understanding, weak component abstraction, and low reusability in traditional MOM customized development, improving the development efficiency of the MON system, reducing development costs, and enhancing system flexibility and maintainability. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the overall process of an embodiment of this application.

[0048] Figure 2 Dynamic chain flowcharts collected for factory business processes.

[0049] Figure 3 This is a behavioral chain flowchart for the execution scenario of process inspection tasks.

[0050] Figure 4 This is a schematic diagram of the system structure of this application.

[0051] Figure 5 This is a structural block diagram of the computer device described in this application. Detailed Implementation

[0052] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1-5 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0053] This application discloses a method for identifying MOM scene components based on a dynamic chain process.

[0054] Reference Figure 1 A method for identifying MOM scene components based on a dynamic chain process includes:

[0055] Step S11, obtain the natural language requirement of the user in the current MOM scenario, and parse the natural language requirement to construct a corresponding dynamic chain flowchart.

[0056] It should be noted that the natural language requirement of the user can be the words said by the user when describing the requirement. In step S11, the user's fuzzy natural language requirement is structured and disassembled into structured multiple tuples (for example, a four-tuple <role, scenario, trigger condition, execution operation>), and these multiple tuples are connected to form a structured graph chain that meets the user's MOM requirement, i.e., a dynamic chain flowchart. For example, Figure 2 The dynamic chain flowchart collected for the factory business process is specifically: process production → process inspection: dynamic chain flowchart <role: production personnel, scenario: process submission, trigger condition: part process completion, execution operation: process submission>, <role: inspector, scenario: process inspection, trigger condition: process submission completion, execution operation: verify task>; inspection qualified → qualified certificate issued, dynamic chain flowchart <role: qualified certificate issuer, scenario: qualified certificate processing, trigger condition: inspection qualified, execution operation: feedback inspection>, and inspection unqualified → fault handling, dynamic chain flowchart <role: fault handling personnel, scenario: fault handling, trigger condition: inspection failure, execution operation: feedback inspection>. Through step S11, the problem of "difficulty in structuring requirement description" is solved, and the developer clearly understands the business logic.

[0057] Step S12, scene unit identification is performed according to the dynamic chain flowchart, and at least one scene unit is obtained.

[0058] Among them, the scene unit is the smallest business action logic unit that can be reused.

[0059] It should be noted that the at least one scene unit corresponds to a specific business activity or a specific business scenario (such as a process inspection task execution scenario), and each scene unit corresponds to a specific business action (such as "inspection task" and "qualified certificate issuance"). The flow of the specific business activity or the specific business scenario is represented by a behavior chain flowchart, and the behavior chain flowchart contains reusable atomic business actions (i.e., scene units) and does not contain state nodes. For example, Figure 3 The behavior chain flowchart for the process inspection task execution scenario contains state nodes such as "task receiving", "inspection qualified", and "inspection unqualified", and does not contain state nodes such as "inspection in progress", "qualified certificate pending", and "qualified certificate pending confirmation". In addition, when the at least one scene unit involves multiple specific business activities or specific business scenarios, multiple behavior chain flowcharts are required to represent them respectively. Through step S12, the problem of "lack of abstraction ability of scene components" is solved to facilitate the reuse of function blocks in the subsequent implementation.

[0060] Step S13, for each scene unit, a corresponding scene unit description model is constructed according to the scene unit.

[0061] The scene unit description model is used to represent the scene attributes of the scene unit.

[0062] It should be noted that in step S13, the scene unit description model can be represented by a standardized scene unit dictionary. By such a setting, each scene unit has a detailed "specification" that clearly defines the functions, context, data requirements, interfaces, and other scene attributes of each scene unit, so as to facilitate subsequent intelligent matching. For example, the scene unit description model received by the task is as follows:

[0063] Table 1

[0064]

[0065] Step S14, for each scene unit, the scene unit description model is matched in the historical component library based on a predefined matching rule to determine the corresponding implementation component.

[0066] It should be noted that the standardized "scene unit description model" created in step S13 automatically finds the most suitable component to implement the scene unit in the existing historical component library (previously developed, reusable code modules / services); when all scene units of a complete requirement (behavior chain flowchart composed of multiple scene units) are bound to the corresponding historical components, a customizable and executable MOM system function module is automatically assembled, thereby solving the problem of "lack of matching mechanism for dynamic chain flow and execution unit" and greatly improving the development efficiency and reusability.

[0067] In the above embodiment, the natural language requirement of the user in the current MOM scenario is acquired, the natural language requirement is parsed, a corresponding dynamic chain flowchart is constructed, scene unit recognition is performed according to the dynamic chain flowchart, at least one scene unit is obtained, wherein the scene unit is a reusable minimum business action logic unit, then for each scene unit, a corresponding scene unit description model is constructed according to the scene unit, wherein the scene unit description model is used to represent the scene attribute of the scene unit, then for each scene unit, the scene unit description model is matched in the historical component library based on a predefined matching rule to determine a corresponding implementation component; in the above method, the fuzzy natural language requirement is structured (dynamic chain flow), the business scenario is accurately decomposed (scene unit recognition), and the historical assets (historical component library) are efficiently reused based on the standardized component description model (scene unit description model) and the intelligent matching mechanism, thereby systematically solving the core pain points of difficult requirement understanding, weak component abstraction and low reuse rate in traditional MOM customized development, improving the development efficiency of the MON system, reducing the development cost, and enhancing the system flexibility and maintainability.

[0068] As a further embodiment of the method, the step of parsing the natural language requirement and constructing a corresponding dynamic chain flowchart comprises:

[0069] In step S21, the MOM scenario requirement of the natural language requirement is structured based on a predefined node structure to obtain at least one business node, wherein the business node includes at least one of a role unit, a scene unit, a trigger condition unit and an execution operation unit.

[0070] In step S22, at least one business node is semantically connected based on a predefined semantic connection type to obtain a corresponding dynamic chain flowchart.

[0071] In the above embodiment, in order to implement the construction of the dynamic chain flowchart, the MOM scenario requirement of the natural language requirement is structured based on a predefined node structure to obtain at least one business node, wherein the business node includes at least one of a role unit, a scene unit, a trigger condition unit and an execution operation unit, and then at least one business node is semantically connected based on a predefined semantic connection type to obtain a corresponding dynamic chain flowchart.

[0072] As a further embodiment of the method, the step of performing scene unit recognition according to the dynamic chain flowchart to obtain at least one scene unit comprises:

[0073] In step S31, the scene semantics in the dynamic chain flowchart are acquired, and a corresponding behavior chain flowchart is constructed according to the scene semantics, wherein the behavior chain flowchart includes action nodes and state nodes.

[0074] It should be noted that the behavior chain flow chart includes input nodes, output nodes, state nodes and action nodes, wherein the state node is a special node in the behavior chain flow chart, representing an intermediate state or a condition judgment result in the business activity execution process, for example, in the "process inspection" flow chart, the state node can be "inspection in progress", "waiting for audit", "qualified judgment in progress", "unqualified judgment in progress", etc., and the action node can be "issue a qualified certificate", "qualified certificate confirmation", "fault single confirmation", etc.

[0075] In step S32, the state nodes of the behavior chain flow chart are stripped to obtain the corresponding scene units.

[0076] It should be noted that the state nodes are process markers, which only represent temporary states of the flow chart (such as "waiting for audit"), and do not contain executable operation logic; the scene units focus on "actions", and the reusable components must be operation units (such as "issue a qualified certificate") that can independently complete a certain business function, rather than intermediate states. In step S32, the reusable atomic business actions (i.e. scene units) are extracted by stripping and removing the state nodes, solving the pain points of "repeated development and inability to reuse" in traditional MOM systems.

[0077] In the above embodiment, in order to realize the identification of the scene unit, the scene semantics in the dynamic chain flow chart are obtained, and the corresponding behavior chain flow chart is constructed according to the scene semantics, wherein the behavior chain flow chart includes action nodes and state nodes, and then the state nodes of the behavior chain flow chart are stripped to obtain the corresponding scene unit.

[0078] As a further embodiment of the method, the step of matching the scene unit description model in the historical component library based on the pre-defined matching rule to determine the corresponding implementation component, includes:

[0079] In step S41, the component properties of each historical component in the historical component library are obtained, and the scores of each historical component are determined according to the scene properties and the component properties, wherein the score is used to express the matching degree of the historical component and the scene unit.

[0080] In step S42, the historical component corresponding to the maximum value in the score is taken as the implementation component of the scene unit.

[0081] In the above embodiment, in order to realize the matching of the scene unit description model and the historical construction, the component properties of each historical component in the historical component library are obtained, and the scores of each historical component are determined according to the scene properties and the component properties, wherein the score is used to express the matching degree of the historical component and the scene unit, and then the historical component corresponding to the maximum value in the score is taken as the implementation component of the scene unit.

[0082] As a further implementation of the method, the scene attributes include scene unit description, scene unit name, scene unit category and scene unit IO, the component attributes include component description, component name, component category and component IO, the step of determining the score of each historical component according to the scene attributes and the component attributes includes:

[0083] In step S51, the description similarity is determined according to the scene unit description and the component description.

[0084] In step S52, the name similarity is determined according to the scene unit name and the component name.

[0085] In step S53, the category similarity is determined according to the scene unit category and the component category, wherein the category similarity is used to represent whether the categories are consistent or the similarity of the category labels.

[0086] In step S54, the IO similarity is determined according to the scene unit IO and the component IO, wherein the IO similarity is used to represent the similarity of the input parameters and the output parameters in type, structure or keyword.

[0087] In step S55, the weights of the description similarity, the name similarity, the category similarity and the IO similarity are obtained, and the corresponding scores are determined according to the weights, the description similarity, the name similarity, the category similarity and the IO similarity.

[0088] It should be noted that the weighted comprehensive score function for calculating the scores through steps S51 to S55 can be represented as: Score=α*name similarity+β*description similarity+γ*category similarity+δ*IO similarity, wherein α, β, γ and δ represent the weights; the name similarity and the description similarity can be calculated by a text semantic similarity function sim_text(), the category similarity can be calculated by a function sim_category(), and the IO similarity can be calculated by a function sim_io().

[0089] In the above implementation, in order to obtain the score of each historical component, the description similarity is determined according to the scene unit description and the component description, the name similarity is determined according to the scene unit name and the component name, the category similarity is determined according to the scene unit category and the component category, wherein the category similarity is used to represent whether the categories are consistent or the similarity of the category labels, the IO similarity is determined according to the scene unit IO and the component IO, wherein the IO similarity is used to represent the similarity of the input parameters and the output parameters in type, structure or keyword, then the weights of the description similarity, the name similarity, the category similarity and the IO similarity are obtained, and the corresponding scores are determined according to the weights, the description similarity, the name similarity, the category similarity and the IO similarity.

[0090] As a further implementation of the method, the scenario attribute further comprises a scenario unit number, a preceding scenario unit name, a following scenario unit name, an upstream scenario, an associated business scenario, a start state, an end state, an associated business object, and an external interface.

[0091] As a further implementation of the method, after the step of determining the corresponding implementation component by matching the scenario unit description model with the historical component library based on a predefined matching rule for each scenario unit, the method comprises:

[0092] Binding the corresponding implementation component with the corresponding scenario unit.

[0093] In the above implementation, the corresponding implementation component is bound with the corresponding scenario unit, and after all the scenario units are bound with a customized implementation component, a customizable and executable MOM system function module is automatically assembled.

[0094] The embodiment of the application further discloses a MOM scenario component identification system based on a dynamic chained flow.

[0095] Reference Figure 4 The MOM scenario component identification system based on the dynamic chained flow comprises:

[0096] A dynamic chained flow chart construction module is configured to acquire a natural language requirement of a user in a current MOM scenario, and analyze and construct a corresponding dynamic chained flow chart based on the natural language requirement.

[0097] A scenario unit identification module is configured to identify scenario units based on the dynamic chained flow chart, and obtain at least one scenario unit, wherein the scenario unit is a minimum business action logic unit that can be reused.

[0098] A scenario unit description model construction module is configured to construct a corresponding scenario unit description model for each scenario unit based on the scenario unit, wherein the scenario unit description model is used to represent scenario attributes of the scenario unit.

[0099] A component matching module is configured to match the scenario unit description model with a historical component library based on a predefined matching rule for each scenario unit, and determine a corresponding implementation component.

[0100] The MOM scenario component identification system based on the dynamic chained flow of the application can implement any one of the MOM scenario component identification methods based on the dynamic chained flow, and the specific working process of the MOM scenario component identification system based on the dynamic chained flow of the application can refer to the corresponding process in the above-mentioned MOM scenario component identification method based on the dynamic chained flow.

[0101] The embodiment of the application further discloses a computer device.

[0102] Reference Figure 5 A computer device includes a memory and a processor, the memory has a computer program stored thereon, the computer program is capable of being run on the processor, and the processor implements any one of the above-mentioned MOM scene component identification methods based on a dynamic chain flow when executing the computer program.

[0103] The embodiments of the present application further disclose a computer readable storage medium.

[0104] A computer readable storage medium stores a computer program capable of being loaded and executed by a processor to perform any one of the above-mentioned MOM scene component identification methods based on a dynamic chain flow.

[0105] The computer readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, device or apparatus; the program code contained in the computer readable medium can be transmitted by any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any appropriate combination of the above.

[0106] The above are preferred embodiments of the present application, and are not intended to limit the protection scope of the present application; any feature disclosed in the specification (including the abstract and the drawings) can be replaced by other equivalent or similar features unless specifically described, or can be replaced by other equivalent or similar features having the same purpose. That is, unless specifically described, each feature is only an example of a series of equivalent or similar features.

Claims

1. A MOM scenario component identification method based on dynamic chain flow, characterized in that, The method comprises the following steps: acquiring natural language requirements of a user in a current MOM scenario, and parsing the natural language requirements to construct a corresponding dynamic chain flowchart; identifying a scenario unit according to the dynamic chain flowchart to obtain at least one scenario unit, wherein the scenario unit is a minimum business action logic unit that can be reused; for each scenario unit, constructing a corresponding scenario unit description model according to the scenario unit, wherein the scenario unit description model is used to represent scenario attributes of the scenario unit; for each scenario unit, matching the scenario unit description model in a historical component library based on a predefined matching rule to determine a corresponding implementation component; the step of parsing the natural language requirements to construct a corresponding dynamic chain flowchart comprises the following steps: structuring MOM scenario requirements of the natural language requirements based on a predefined node structure to obtain at least one business node, wherein the business node comprises at least one of a role unit, a scenario unit, a trigger condition unit and an execution operation unit; performing semantic connection on the at least one business node based on a predefined semantic connection type to obtain a corresponding dynamic chain flowchart; the step of identifying a scenario unit according to the dynamic chain flowchart to obtain at least one scenario unit comprises the following steps: acquiring scenario semantics in the dynamic chain flowchart, and constructing a corresponding behavior chain flowchart according to the scenario semantics, wherein the behavior chain flowchart comprises action nodes and state nodes; performing state node stripping on the behavior chain flowchart to obtain a corresponding scenario unit.

2. The MOM scenario component identification method based on dynamic chained flow according to claim 1, characterized in that, the step of matching the scenario unit description model in a historical component library based on a predefined matching rule to determine a corresponding implementation component comprises the following steps: acquiring component attributes of each historical component in the historical component library, and determining scores of the historical components according to the scenario attributes and the component attributes, wherein the scores are used to represent matching degrees of the historical components and the scenario unit; taking a historical component corresponding to a maximum value in the scores as an implementation component of the scenario unit.

3. The MOM scenario component identification method based on dynamic chain flow according to claim 2, characterized in that, The scenario attributes comprise scenario unit description, scenario unit name, scenario unit classification and scenario unit IO, the component attributes comprise component description, component name, component classification and component IO, and the step of determining the scores of the historical components according to the scenario attributes and the component attributes comprises the following steps: determining a description similarity according to the scenario unit description and the component description; determining a name similarity according to the scenario unit name and the component name; determining a category similarity according to the scenario unit classification and the component classification, wherein the category similarity is used to represent whether the categories are consistent or a similarity of category labels; determining an IO similarity according to the scenario unit IO and the component IO, wherein the IO similarity is used to represent a similarity of input parameters and output parameters in terms of type, structure or keywords. Obtaining weights of the description similarity, the name similarity, the category similarity and the IO similarity respectively, and determining a corresponding score according to the weights, the description similarity, the name similarity, the category similarity and the IO similarity.

4. The MOM scenario component identification method based on dynamic chain flow according to claim 3, characterized in that, The scene attribute further comprises a scene unit number, a preceding scene unit name, a following scene unit name, an upstream scene, an associated business scene, a start state, an end state, an associated business object and an external interface.

5. The MOM scenario component identification method based on dynamic chained flow according to claim 1, characterized in that, After the step of matching the scene unit description model with a historical component library based on a predefined matching rule to determine a corresponding implementation component for each of the scene units, the method further comprises: Binding the corresponding implementation component with the corresponding scene unit.

6. A MOM scenario component identification system based on dynamic chain flow, characterized in that, The method comprises: a dynamic chained flowchart construction module configured to obtain a natural language requirement of a user under a current MOM scene, and parse the natural language requirement to construct a corresponding dynamic chained flowchart; a scene unit identification module configured to identify scene units according to the dynamic chained flowchart to obtain at least one scene unit, wherein the scene unit is a minimum business action logic unit that can be reused; a scene unit description model construction module configured to construct a corresponding scene unit description model for each of the scene units according to the scene unit, wherein the scene unit description model is used to represent scene attributes of the scene unit; a component matching module configured to match the scene unit description model with a historical component library based on a predefined matching rule to determine a corresponding implementation component for each of the scene units; the step of parsing the natural language requirement to construct a corresponding dynamic chained flowchart comprises: performing MOM scene requirement structuring on the natural language requirement based on a predefined node structure to obtain at least one business node, wherein the business node comprises at least one of a role unit, a scene unit, a trigger condition unit and an execution operation unit; performing semantic connection on the at least one business node based on a predefined semantic connection type to obtain a corresponding dynamic chained flowchart; the step of identifying scene units according to the dynamic chained flowchart to obtain at least one scene unit comprises: obtaining scene semantics in the dynamic chained flowchart, and constructing a corresponding behavior chained flowchart according to the scene semantics, wherein the behavior chained flowchart comprises an action node and a state node; performing state node stripping on the behavior chained flowchart to obtain a corresponding scene unit.

7. A computer device, comprising: A computer program is stored in a memory and executable on a processor, and the processor executes the computer program to implement the method in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, A computer program is stored in a memory and executable on a processor, and the processor executes the computer program to implement the method in any one of claims 1 to 5.

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