ERP Management Method and System Based on Low-Code Platform

Abstract

This application relates to the technical field of ERP management, and specifically discloses an ERP management method and system based on a low-code platform. The method includes: constructing a template library, the template library includes various ERP category templates, each ERP category template has a data flow diagram, and the data flow diagram includes multiple processing nodes; merging the data flow diagrams of the same type of ERP category templates into an integrated flow diagram, and obtaining the functional requirements and process requirements of the user; selecting the corresponding integrated flow diagram based on the functional requirements, and extracting the corresponding basic flow diagram from the integrated flow diagram based on the process requirements; marking the parts to be modified in the basic flow diagram; obtaining a complete flow diagram after completing the adjustment of the parts to be modified, verifying each processing node in the complete flow diagram based on an intelligent recognition model, defining the processing nodes that fail the verification as abnormal nodes, and generating a risk reminder pointing to the abnormal nodes. The present invention helps developers quickly produce an ERP system.

Description

Technical Field

[0001] This application relates to the technical field of ERP management, and particularly to an ERP management method and system based on a low-code platform. Background Art

[0002] An ERP (Enterprise Resource Planning) system is an integrated management information system that optimizes enterprise resource allocation and business operations by integrating various business processes within the enterprise. A low-code platform (Low-Code Development Platform, LCDP) is a digital technology tool platform that is driven by both business personnel and IT personnel. It can achieve functions such as rapid construction, data orchestration, connection to the ecosystem, and middleware services through efficient methods such as graphical drag-and-drop and parameterized configuration. Applying a low-code platform to an ERP system can make the customization and extension of the ERP system more flexible and rapid.

[0003] For example, the Chinese patent document with the publication number CN118012396A discloses a method and system for implementing ERP functions for book publishing in a low-code manner. This method greatly simplifies the development process and method through a low-code platform, builds relevant pages, operation logics, approval processes, data calculation models, etc. of an ERP system for the book industry through the low-code platform, improving the development efficiency of the ERP system; and supports quick adjustment and modification, greatly reducing the technical threshold and reducing the dependence on programming.

[0004] Currently, to further accelerate the development speed, multiple ERP system templates are prepared in advance, and development is carried out by selecting a suitable template and building on it. However, when there are a large number of templates, developers need to search for suitable system templates one by one according to customer requirements, which will consume a lot of time. Summary of the Invention

[0005] To solve the problems raised in the above background art, this application provides an ERP management method and system based on a low-code platform.

[0006] To achieve the above invention purpose, the present invention proposes an ERP management method based on a low-code platform, including:

[0007] Construct a template library, where the template library includes multiple ERP category templates, and each ERP category template has a data flow diagram, and the data flow diagram includes multiple processing nodes;

[0008] Merge the data flow diagrams of the same type of ERP category templates into an integrated flow diagram;

[0009] Obtain the functional requirements and process requirements of the user, select the corresponding integration flow chart based on the functional requirements, and extract the corresponding basic flow chart from the integration flow chart based on the process requirements;

[0010] Mark the parts to be modified in the basic flow chart, where the parts to be modified are the parts that need to be modified in the basic flow chart;

[0011] Build an intelligent recognition model. After completing the adjustment of the parts to be modified, obtain the complete flow chart. Based on the intelligent recognition model, verify each processing node in the complete flow chart, define the processing nodes that fail the verification as abnormal nodes, and generate a risk reminder pointing to the abnormal nodes.

[0012] Furthermore, merging the data flow charts into the integration flow chart includes the following steps:

[0013] Data flow lines are marked between the processing nodes in the data flow chart. Number each processing node based on the data flow lines, and divide the data flow chart into multiple levels based on the numbers;

[0014] Take the data flow charts corresponding to the same type of ERP category modules as the aggregation targets, take the aggregation target with the largest number of levels among them as the main target, the processing nodes included in the main target as the main nodes, locate the reference nodes in each of the remaining aggregation targets, start from the reference nodes, and correspondingly merge the processing nodes of each level of the aggregation target into the main target. When merging, if the main node and the processing node meet the fusion conditions, merge the processing node into the main node; if not, chain the processing node into the main target as a branch node.

[0015] Furthermore, locating the reference nodes includes the following steps:

[0016] Locate the level with the smallest value in the aggregation target, and take the processing node in it as the first node. If a main node that meets the fusion conditions with the first node is found in the main target, determine the first node as the reference node; otherwise, continue to extract the processing node in other levels of the aggregation target as the second node, and judge whether the second node is the reference node. Repeat this step until the reference node is located.

[0017] Furthermore, extracting the corresponding basic flow chart from the integration flow chart includes the following steps:

[0018] Obtain a requirements flowchart based on the user's process requirements, locate the initial node and the termination node in the requirements flowchart, and at the same time locate the processing nodes in the integration flowchart that can be fused with the initial node and the termination node, and use them as the top node and the bottom node respectively. Generate multiple alternative flowcharts in the integration flowchart with the top node and the bottom node as the starting point and the ending point, calculate the similarity between the requirements flowchart and each alternative flowchart, and use the alternative flowchart with the maximum similarity as the basic flowchart.

[0019] Further, locating the initial node and the termination node includes the following steps:

[0020] The requirements flowchart includes multiple process nodes. Starting from both ends of the requirements flowchart, sequentially determine whether each process node is a target node in the requirements flowchart. Among them, if there is a processing node in the integration flowchart that meets the fusion condition with the process node, then determine the process node as the target node, and define the target nodes first determined at both ends in the requirements flowchart as the initial node and the termination node respectively.

[0021] Further, determining whether it meets the fusion condition includes the following steps:

[0022] Set attribute data for each processing node. The attribute data includes its own function label, the function label of the data source node, and the function label of the data output node. When the function labels of the main node and the reference node are the same, and at least one of the function labels of the data source node and the data output node is the same, then define that the main node and the processing node meet the fusion condition.

[0023] Further, calculating the similarity includes the following steps:

[0024] Generate a corresponding hash value based on the function label of the processing node itself. Take the processing node adjacent to the initial node or the top node as the first neighbor node, perform an exclusive OR operation on the hash values of the first neighbor node and the initial node itself, and perform an exclusive OR operation on the hash values of the first neighbor node and the top node itself to obtain the label values of the initial node and the top node;

[0025] Obtain the second neighbor node of the first neighbor node. The second neighbor node does not include the initial node or the top node. Perform an exclusive OR operation on the hash values of the first neighbor node and the second neighbor node to obtain the label value of the first neighbor node. Repeat this step until all the processing nodes in the flowchart are traversed;

[0026] Generate a first tag set and a second tag set corresponding to the requirement flow chart and the alternative flow chart based on the tag values, and calculate the similarity based on the number of the same tag values included in the first tag set and the second tag set.

[0027] Further, the intelligent recognition model is constructed based on a neural network. Input the attribute data of the adjusted processing node into the intelligent recognition model, and the intelligent recognition model outputs the error probability of the processing node. When the error probability is greater than the critical threshold, determine that the processing node is the abnormal node.

[0028] The present invention also provides an ERP management system based on a low-code platform for implementing the above-mentioned ERP management method based on a low-code platform. The system includes:

[0029] A template unit, including a template library. The template library includes multiple ERP category templates. Each ERP category template has a data flow chart, and the data flow chart includes multiple processing nodes. The template unit combines the data flow charts of the same type of ERP category templates into an integrated flow chart;

[0030] An initialization unit, which obtains the functional requirements and process requirements of the user, selects the corresponding integrated flow chart based on the functional requirements, and extracts the corresponding basic flow chart from the integrated flow chart based on the process requirements;

[0031] An editing unit, which marks the part to be modified in the basic flow chart. The part to be modified is the part that needs to be modified in the basic flow chart;

[0032] An inspection unit, which is used to construct an intelligent recognition model. After the adjustment of the part to be modified is completed, a complete flow chart is obtained. Based on the intelligent recognition model, each processing node in the complete flow chart is verified, and the processing node that fails the verification is defined as an abnormal node, and a risk reminder pointing to the abnormal node is generated.

[0033] Beneficial effects:

[0034] By constructing a template library containing multiple ERP category templates, combining the data flow charts of the same type of templates into an integrated flow chart, then selecting the corresponding integrated flow chart according to the functional requirements of the user, and automatically extracting the basic flow chart from the integrated flow chart according to the process requirements, the development of the ERP system can not only closely meet the actual needs of the user, but also help developers quickly locate and select the appropriate template, avoiding searching one by one among a large number of templates and saving time. Description of the drawings

[0035] Figure 1Schematic diagram of the steps of an ERP management method based on a low-code platform in this application;

[0036] Figure 2 Schematic diagram of the principle for generating an integration flowchart in this application;

[0037] Figure 3 Schematic diagram of the principle for generating a basic flowchart in this application;

[0038] Figure 4 Schematic diagram of the structure of an ERP management system based on a low-code platform in this application. Detailed implementation manners

[0039] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0040] As Figure 1 shown, an ERP management method based on a low-code platform includes:

[0041] S1: Construct a template library, the template library includes various ERP category templates, and each ERP category template has a data flow diagram, and the data flow diagram includes multiple processing nodes.

[0042] Specifically, the ERP category templates include material management category, human resources category, equipment maintenance category, purchase order category, data analysis category, etc., and there is at least one of each type of template. Each ERP category template has a data flow diagram, and the data flow diagram is as Figure 2 shown. The data flow diagram A of an ERP category module under material management includes multiple processing nodes, and there are data flow lines between the processing nodes. The direction of the data flow line indicates that data flows from one processing node to another processing node. For example, for the material management category, the processing nodes represent the main warehouse and the sub-warehouses in each area. For the human resources category, the processing nodes include the transaction approval sequence and the carbon copy sequence. For the data analysis type, the processing nodes include the data processing sequence, such as missing value supplementation, outlier removal, etc.

[0043] S2: Merge the data flow diagrams of the same type of ERP category templates into an integration flowchart.

[0044] For example, there are 10 templates under the material management category, and each template has a corresponding data flow diagram. Then, the data flow diagrams corresponding to the 10 templates are merged into an integrated flow diagram. The merging method will be introduced in the following content. Before development, the previous business personnel obtain the user's functional requirements and process requirements. The functional requirements are what functions the customer needs, such as material management functions, data analysis functions, etc. The process requirements are the specific processes under each functional requirement, such as the inbound and outbound processes of materials, the material distribution process, etc.

[0045] S3: Obtain the user's functional requirements and process requirements, select the corresponding integrated flow diagram based on the functional requirements, and extract the corresponding basic flow diagram from the integrated flow diagram based on the process requirements.

[0046] S4: Mark the parts to be modified in the basic flow diagram. The parts to be modified are the parts that need to be modified in the basic flow diagram.

[0047] As mentioned above, an integrated flow diagram corresponds to the data processing flow of all templates under one type. First, select the corresponding integrated flow diagram according to the user's functional requirements, and then extract the appropriate basic flow diagram from the integrated flow diagram according to the user's process requirements. However, the extracted basic flow diagram may not fully meet the customer's needs and needs to be modified specifically. The parts that do not meet the customer's needs are defined as the parts to be modified. The parts to be modified include the disorder of the order of processing nodes or the absence of a processing node somewhere.

[0048] S5: Build an intelligent recognition model. After completing the adjustment of the parts to be modified to obtain a complete flow diagram, verify each processing node in the complete flow diagram based on the intelligent recognition model, define the processing nodes that fail the verification as abnormal nodes, and generate a risk reminder pointing to the abnormal nodes.

[0049] The intelligent recognition model is built based on a neural network. Input the attribute data of the adjusted processing nodes into the intelligent recognition model. The intelligent recognition model outputs the error probability of the processing nodes. When the error probability is greater than the critical threshold, the processing node is determined to be an abnormal node.

[0050] The intelligent recognition model is built based on a neural network. Each processing node has attribute data, and the attribute data includes the function label of the processing node, such as the function label is missing value supplementation, the function labels of the processing nodes before and after this processing node. The intelligent recognition model automatically captures the attribute data of each processing node to determine whether there is an abnormality in this processing node. For example, the intelligent recognition model finds that the function label of the current processing node is missing value supplementation, and the function label of the previous processing node is data statistical analysis, and the order of the two is reversed, so it is listed as an abnormal node. After determining that there are no process errors in the complete flow diagram, the subsequent development of the software interface can be continued.

[0051] In the present invention, a template library containing various ERP category templates is constructed, and the data flowcharts of the same type of templates are merged into an integrated flowchart. Then, according to the functional requirements of the user, the corresponding integrated flowchart is selected, and based on the process requirements, the basic flowchart is automatically extracted from the integrated flowchart, enabling the development of the ERP system to not only closely meet the actual needs of the user, but also help developers quickly locate and select the appropriate templates, avoiding searching one by one among a large number of templates and saving time.

[0052] In the present invention, the parts to be modified are marked in the basic flowchart, enabling developers to clearly understand which places need to be adjusted, increasing the directivity and improving work efficiency. Finally, in the present invention, by constructing an intelligent recognition model to verify each processing node in the complete flowchart, abnormal nodes can be automatically identified and risk reminders can be generated, helping developers timely discover and solve potential problems in the process and ensuring the correctness and reliability of the process.

[0053] In this embodiment, merging the data flowcharts into an integrated flowchart includes the following steps:

[0054] Data flow lines are marked between the processing nodes in the data flowchart. Each processing node is numbered based on the data flow lines, and the data flowchart is divided into multiple levels based on the numbers.

[0055] Continue to refer to Figure 2 , in the data flowchart, each processing node is marked with 1, 2, 3 in the order of data flow, representing that the data reaches processing node 2 from processing node 1 and then reaches processing node 3 from processing node 2. And since there are 3 numbers in the data flowchart, the data flowchart is divided into 3 levels. For example, in the data flowchart B in Figure 2 , from top to bottom are the first level, the second level, and the third level respectively.

[0056] Taking the data flowcharts corresponding to the same type of ERP category modules as the aggregation targets, taking the aggregation target with the largest number of levels included as the main target, the processing nodes included in the main target as the main nodes, locating the reference nodes in each of the remaining aggregation targets, starting from the reference nodes, corresponding processing nodes of each level of the aggregation target are merged into the main target. And when merging, if the main node and the processing node meet the fusion conditions, the processing node is merged into the main node; if not, the processing node is chained into the main target as a branch node.

[0057] As described above, there are 10 templates under the material management category. Then, the data flowcharts corresponding to the 10 templates are taken as the aggregation targets. Among the aggregation targets, the one with the largest number of hierarchical levels is taken as the main target, which is convenient for subsequent merging. Before aggregation, first locate the reference nodes in each aggregation target. The reference node is the root node for merging the aggregation target and the main target. For example Figure 2 in the data flowchart A is the main target, and the data flowchart B is the aggregation target. It is necessary to merge the data flowchart B into the data flowchart A.

[0058] The processing node 1 of the data flowchart B is the reference target. When merging, if the processing node 1 of the data flowchart A and the processing node 1 of the data flowchart B meet the fusion conditions, then the two are merged into one. However, if the processing node 2 of the data flowchart A and the processing node 2 of the data flowchart B do not meet the fusion conditions, then the processing node 2 is chained into the main target as a branch node and still maintains the connection relationship with the original processing node. The merged result refers to Figure 2 the data flowchart C in.

[0059] Specifically, determining whether it meets the fusion conditions includes the following steps:

[0060] Set attribute data for each processing node. The attribute data includes its own function label, the function label of the data source node, and the function label of the data output node. When the function labels of the main node and the reference node are the same, and at least one of the function labels of the data source node and the data output node is the same, then it is defined that the main node and the processing node meet the fusion conditions.

[0061] Continue to refer to Figure 2 For the processing node 1 in the data flowcharts A and B, the function labels of the two are the same, and the function labels of the data source nodes are the same. For example, the function labels are all material out of the warehouse. Although the function labels of the data output nodes are different, they meet the fusion conditions and can be fused. For the processing node 2 in the data flowcharts A and B, the function labels of the two are different, such as material price approval and material quantity approval respectively, then they do not meet the fusion conditions.

[0062] The steps for locating the reference node in this embodiment include the following:

[0063] Locate the level with the smallest value in the aggregation target, and take the processing node therein as the first node. If a main node with fusion conditions with the first node is found in the main target, then the first node is determined as the reference node. Otherwise, continue to extract processing nodes in other levels of the aggregation target as the second node, and determine whether the second node is the reference node. Repeat this step until the reference node is located.

[0064] Continue to refer to Figure 2, as before, the data flow diagram B is used as the aggregation target. The lowest level in terms of value is the first level, which includes processing node 1. Processing node 1 is taken as the first node. In the data flow diagram A (main target), search from top to bottom for the main node that is the same as processing node 1 (the first node). Since processing node 1 in data flow diagram A and processing node 1 in data flow diagram B meet the fusion conditions, processing node 1 in data flow diagram B is taken as the reference node. Otherwise, in the second level of data flow diagram B, extract processing node 2 again. If there is a processing node in data flow diagram A that can be fused with processing node 2 in data flow diagram B, then processing node 2 is taken as the reference node.

[0065] In this embodiment, generating the basic flow chart includes the following steps:

[0066] Based on the user's process requirements to obtain the requirements flow chart, locate the initial node and the termination node in the requirements flow chart. At the same time, locate the processing nodes in the integrated flow chart that can be fused with the initial node and the termination node, and use them as the top node and the bottom node respectively. Generate multiple alternative flow charts in the integrated flow chart with the top node and the bottom node as the starting point and the ending point. Calculate the similarity between the requirements flow chart and each alternative flow chart, and take the alternative flow chart with the largest similarity as the basic flow chart.

[0067] Specifically, locating the initial node and the termination node includes the following steps:

[0068] The requirements flow chart includes multiple process nodes. Starting from both ends of the requirements flow chart in turn, determine whether the process node is a target node in the requirements flow chart. Among them, if there is a processing node in the integrated flow chart that meets the fusion conditions with the process node, then the process node is determined as the target node. The target nodes first determined at both ends in the requirements flow chart are defined as the initial node and the termination node respectively.

[0069] The following is an example to explain the above steps. Currently, the integrated flow chart D is stored in the system, and the requirements flow chart E has been obtained. Now it is necessary to locate the initial node and the termination node in the requirements flow chart E. The specific method is as follows. First, obtain the processing nodes at the upper and lower ends of the requirements flow chart E, that is, processing node 1 and processing node 4. Then determine whether there are nodes in the integrated flow chart that can be fused with processing node 1 and 4. Suppose that processing node 1 in the integrated flow chart D can be fused with processing node 1 in the requirements flow chart E, and processing node 6 in the integrated flow chart D can be fused with processing node 4 in the requirements flow chart E. Then processing node 1 and processing node 4 in the requirements flow chart E are taken as the target nodes. And processing node 1 in the requirements flow chart E is at the head end of its entire process, so it is taken as the initial node. Similarly, processing node 4 is taken as the termination node.

[0070] Based on the above introduction, in the integrated flowchart D, taking processing node 1 as the top node and processing node 6 as the bottom node, multiple filing flowcharts are generated with the two as the starting point and the ending point respectively. In Figure 3 two alternative flowcharts can be generated. The first one includes processing nodes 1 - 2 - 4 - 6, and the second one includes processing nodes 1 - 2 - 3 - 5 - 6. Then, the similarity between the requirement flowchart E and the two alternative flowcharts is calculated, and the alternative flowchart with a greater similarity is selected as the base flowchart.

[0071] Calculating the similarity in this embodiment includes the following steps:

[0072] Generate corresponding hash values based on the function tags of the processing nodes themselves. Take the processing nodes adjacent to the initial node or the top node as the first neighbor nodes, and perform exclusive OR operations on the hash values of the first neighbor nodes and the initial node itself, and on the hash values of the first neighbor nodes and the top node itself to obtain the label values of the initial node and the top node.

[0073] Obtain the second neighbor nodes of the first neighbor nodes. The second neighbor nodes do not include the initial node or the top node. Perform exclusive OR operations on the hash values of the first neighbor nodes and the second neighbor nodes to obtain the label values of the first neighbor nodes. Repeat this step until all the processing nodes in the flowchart are traversed.

[0074] In a computer, the function tags are binary values. Based on the hash algorithm, convert the binary values into hash values. For example, taking processing node 2 in the requirement flowchart E as the first neighbor node, perform exclusive OR operations on the hash values of processing node 1 and processing node 2 to obtain the label value of processing node 1.

[0075] Similarly, continue to obtain the second neighbor nodes of the first neighbor nodes. In the requirement flowchart E, the second neighbor node of processing node 2 (the first neighbor node) is processing node 3. Then perform exclusive OR operations on the hash values of processing node 2 and processing node 3 to obtain the hash value of processing node 2. Repeat this process until reaching processing node 4.

[0076] Generate the first label set and the second label set corresponding to the requirement flowchart and the alternative flowchart based on the label values, and calculate the similarity based on the number of the same label values included in the first label set and the second label set.

[0077] For the requirement flowchart and the alternative flowchart, if the function tags of processing node 1 and processing node 2 are the same, then the calculated label values of processing node 1 and processing node 2 are also the same. Then the similarity can be calculated through the following first formula. The first formula is: , where P is the similarity between the requirement flowchart and the alternative flowchart. is the number of identical tag values in the first tag set and the second tag set, is the number of tag values included in the first tag set, is the number of tag values included in the second tag set. For example, if the alternative flowchart includes processing nodes 1-2-3-5-6, four tag values will be calculated, which are obtained based on 1-2, 2-3, 3-5, and 5-6 respectively. The requirement flowchart includes processing nodes 1-2-3-4, and there are three tag values, which are obtained based on 1-2, 2-3, and 3-4 respectively. If three of these tag values are the same, the similarity is 3 / 4 = 0.75.

[0078] As Figure 4 shown, the present invention also provides an ERP management system based on a low-code platform for implementing the above-mentioned ERP management method based on a low-code platform. The system includes:

[0079] A template unit, including a template library. The template library includes various ERP category templates. Each ERP category template has a data flow diagram, and the data flow diagram includes multiple processing nodes. The template unit combines the data flow diagrams of the same type of ERP category templates into an integrated flow diagram;

[0080] An initialization unit, which obtains the functional requirements and process requirements of the user, selects the corresponding integrated flow diagram based on the functional requirements, and extracts the corresponding basic flow diagram from the integrated flow diagram based on the process requirements;

[0081] An editing unit, which marks the part to be modified in the basic flow diagram. The part to be modified is the part that needs to be modified in the basic flow diagram;

[0082] An inspection unit, which is used to build an intelligent recognition model. After the adjustment of the part to be modified is completed, a complete flow diagram is obtained. Based on the intelligent recognition model, each processing node in the complete flow diagram is verified. The processing nodes that fail the verification are defined as abnormal nodes, and a risk reminder pointing to the abnormal nodes is generated.

[0083] It should be understood that the technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combinations of these technical features do not conflict, they should be considered to be within the scope described in this specification.

[0084] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An ERP management method based on a low-code platform, characterized in that: Building a template library, the template library includes multiple ERP category templates, each ERP category template has a data flow diagram, and the data flow diagram includes multiple processing nodes; Merge the data flow diagrams of the same type of ERP category templates into an integrated flow diagram, which includes: Data flow lines are marked between the processing nodes in the data flow diagram, and each processing node is numbered based on the data flow lines. The data flow diagram is divided into multiple levels based on the numbers; The data flow diagram corresponding to the same type of ERP category module is taken as the aggregation target, the aggregation target with the largest number of levels is taken as the main target, the processing node included in the main target is taken as the main node, and the reference node is located in the remaining aggregation targets. Starting from the reference node, the processing nodes of each level of the aggregation target are merged into the main target. When merging, if the main node and the processing node meet the fusion condition, the processing node is merged into the main node. If not, the processing node is linked to the main target as a branch node; Obtain the user's functional requirements and process requirements, select the corresponding integrated flowchart based on the functional requirements, and extract the corresponding basic flowchart from the integrated flowchart based on the process requirements; Mark the part to be modified in the basic flowchart. The part to be modified is the part that needs to be modified in the basic flowchart. Build an intelligent recognition model, obtain a complete flow chart after completing the adjustment of the part to be modified, verify each processing node in the complete flow chart based on the intelligent recognition model, define the processing nodes that fail the verification as abnormal nodes, and generate risk reminders pointing to the abnormal nodes.

2. The ERP management method based on the low-code platform according to claim 1 is characterized in that: Locating a reference node involves the following steps: Locate the level with the smallest value in the aggregate target, and use the processing node therein as the first node. If a main node that meets the fusion conditions with the first node is found in the main target, the first node is determined as the reference node. Otherwise, continue to extract processing nodes in other levels of the aggregate target as the second node, and determine whether the second node is a reference node. Repeat this step until the reference node is located.

3. The ERP management method based on the low-code platform according to claim 1 is characterized in that: Extracting the corresponding basic flowchart from the integrated flowchart includes the following steps: Based on the user's process requirements, the demand flow chart is obtained, the initial node and the terminal node in the demand flow chart are located, and the processing nodes that can be integrated with the initial node and the terminal node are located in the integrated flow chart, and used as the top node and the bottom node respectively. In the integrated flow chart, multiple alternative flow charts are generated with the top node and the bottom node as the starting point and the end point, and the similarity between the demand flow chart and each alternative flow chart is calculated, and the alternative flow chart with the largest similarity is used as the basic flow chart.

4. The ERP management method based on the low-code platform according to claim 3 is characterized in that: Locating the initial node and the terminal node includes the following steps: The demand flow chart includes multiple process nodes, which start from the two ends of the demand flow chart respectively. In the demand flow chart, it is determined in turn whether the process node is a target node. Among them, if there are processing nodes and process nodes in the integrated flow chart that meet the fusion conditions, the process node is determined as the target node, and the target nodes first determined at the two ends of the demand flow chart are defined as the initial node and the terminal node respectively.

5. The ERP management method based on the low-code platform according to claim 1 is characterized in that: Determining whether the fusion conditions are met includes the following steps: Attribute data is set for each processing node, and the attribute data includes its own function label, the function label of the data source node, and the function label of the data output node. When the function label of the main node is the same as that of the reference node, and at least one function label of the data source node and the data output node is the same, the main node and the processing node are defined to meet the fusion conditions.

6. The ERP management method based on the low-code platform according to claim 4 is characterized in that: Calculating similarity involves the following steps: Generate a corresponding hash value based on the function label of the processing node itself, take the processing node adjacent to the initial node or the top node as the first neighbor node, perform an XOR operation on the hash value of the first neighbor node and the initial node itself, and perform an XOR operation on the hash value of the first neighbor node and the top node itself, and obtain the label value of the initial node and the top node; Obtain the second neighbor node of the first neighbor node, where the second neighbor node does not include the initial node or the top node, perform an XOR operation on the hash values ​​of the first neighbor node and the second neighbor node to obtain the label value of the first neighbor node, and repeat this step until all processing nodes in the flowchart are traversed; A first label set and a second label set corresponding to the required flowchart and the alternative flowchart are generated based on the label values, and similarity is calculated based on the number of identical label values ​​contained in the first label set and the second label set.

7. The ERP management method based on the low-code platform according to claim 6 is characterized in that: The intelligent recognition model is built based on a neural network. The attribute data of the adjusted processing node is input into the intelligent recognition model. The intelligent recognition model outputs the error probability of the processing node. When the error probability is greater than the critical threshold, the processing node is determined to be an abnormal node.

8. An ERP management system based on a low-code platform, used to implement an ERP management method based on a low-code platform as claimed in any one of claims 1 to 7, characterized in that: include: The template unit includes a template library, which includes a plurality of ERP category templates. Each ERP category template has a data flow diagram, and the data flow diagram includes a plurality of processing nodes. The template unit merges the data flow diagrams of the same type of ERP category templates into an integrated flow diagram, which includes: Data flow lines are marked between the processing nodes in the data flow diagram, and each processing node is numbered based on the data flow lines. The data flow diagram is divided into multiple levels based on the numbers; The data flow diagram corresponding to the same type of ERP category module is taken as the aggregation target, the aggregation target with the largest number of levels is taken as the main target, the processing node included in the main target is taken as the main node, and the reference node is located in the remaining aggregation targets. Starting from the reference node, the processing nodes of each level of the aggregation target are merged into the main target. When merging, if the main node and the processing node meet the fusion condition, the processing node is merged into the main node. If not, the processing node is linked to the main target as a branch node; Initialization unit, obtains the user's functional requirements and process requirements, selects the corresponding integrated flowchart based on the functional requirements, and extracts the corresponding basic flowchart from the integrated flowchart based on the process requirements; The editing unit marks the part to be modified in the basic flowchart, and the part to be modified is the part of the basic flowchart that needs to be modified; The inspection unit is used to build an intelligent recognition model, obtain a complete flow chart after completing the adjustment of the part to be modified, verify each processing node in the complete flow chart based on the intelligent recognition model, define the processing nodes that fail the verification as abnormal nodes, and generate risk reminders pointing to the abnormal nodes.

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