ERP management method and system based on low-code platform

Abstract

The invention relates to the technical field of ERP management, and particularly discloses an ERP management method and system based on a low-code platform. The method comprises the steps that a template library is constructed, the template library comprises a plurality of ERP category templates, each ERP category template is provided with a data flow chart, and the data flow chart comprises a plurality of processing nodes; combining the data flow charts of the same type of ERP category templates into an integrated flow chart, and obtaining function requirements and flow requirements of the user; selecting a corresponding integrated flow chart based on the function demand, and extracting a corresponding basic flow chart from the integrated flow chart based on the flow demand; marking a to-be-modified part in the basic flow chart; and obtaining a complete flow chart after the adjustment of the to-be-modified part is completed, verifying each processing node in the complete flow chart based on the intelligent identification model, defining the processing node which does not pass the verification as an abnormal node, and generating a risk prompt pointing to the abnormal node. According to the invention, developers are helped to quickly manufacture the ERP system.

Description

Technical Field

[0001] The present application relates to the field of ERP management technology, and in particular to an ERP management method and system based on a low-code platform. Background Art

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

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

[0004] Currently, in order to further speed up the development, a variety of ERP system templates are prepared in advance, and development is carried out by selecting appropriate templates based on them. However, when there are a large number of templates, developers need to search for appropriate system templates one by one according to customer needs, which will take a lot of time. Summary of the invention

[0005] In order to solve the problems raised in the above background technology, the present application provides an ERP management method and system based on a low-code platform.

[0006] In order to achieve the above-mentioned purpose of the invention, the present invention proposes an ERP management method based on a low-code platform, comprising:

[0007] Building a template library, the template library includes a plurality of ERP category templates, each of the ERP category templates has a data flow diagram, and the data flow diagram includes a plurality of processing nodes;

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

[0009] Acquire 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;

[0010] Mark the part to be modified in the basic flowchart, where the part to be modified is the part of the basic flowchart that needs to be modified;

[0011] An intelligent recognition model is constructed to obtain a complete flow chart after completing the adjustment of the part to be modified. Each processing node in the complete flow chart is verified based on the intelligent recognition model, and the processing nodes that fail the verification are defined as abnormal nodes, and risk reminders pointing to the abnormal nodes are generated.

[0012] Further, merging the data flow diagram into the integrated flow diagram comprises the following steps:

[0013] Data flow lines are marked between the processing nodes in the data flow diagram, each processing node is numbered based on the data flow lines, and the data flow diagram is divided into multiple levels based on the numbers;

[0014] The data flow diagram corresponding to the ERP category module of the same type is taken as the aggregation target, the aggregation target containing 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 each of 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.

[0015] Further, locating the reference node comprises the following steps:

[0016] Locate the level with the smallest value in the aggregate target, and use the processing node therein as the first node. If the main node that has the fusion condition with the first node is found in the main target, the first node is determined as the reference node. Otherwise, continue to extract the processing node as the second node in other levels of the aggregate target, and determine whether the second node is the reference node. Repeat this step until the reference node is located.

[0017] Furthermore, extracting the corresponding basic flowchart from the integrated flowchart comprises the following steps:

[0018] Based on the process requirements of the user, a demand flow chart is obtained, the initial node and the terminal node in the demand flow chart are located, and at the same time, the processing node that can be integrated with the initial node and the terminal node is located in the integrated flow chart, and used as the top node and the bottom node respectively, and multiple alternative flow charts are generated in the integrated flow chart with the top node and the bottom node as the starting point and end point, and the similarity between the demand flow chart and each of the alternative flow charts is calculated, and the alternative flow chart with the largest similarity is used as the basic flow chart.

[0019] Further, locating the initial node and the terminal node comprises the following steps:

[0020] 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 the processing node and the process node in the integrated flow chart meet the fusion condition, 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.

[0021] Furthermore, determining whether the fusion condition is met includes the following steps:

[0022] 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, it is defined that the main node and the processing node meet the fusion conditions.

[0023] Furthermore, calculating the similarity comprises 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 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, to obtain the label values ​​of the initial node and the top node;

[0025] Obtain a 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 the processing nodes in the flowchart are traversed;

[0026] 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 the similarity is calculated based on the number of identical label values ​​contained in the first label set and the second label set.

[0027] Furthermore, the intelligent recognition model is constructed based on a neural network, and 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 a critical threshold, the processing node is determined to be the abnormal node.

[0028] The present invention also provides an ERP management system based on a low-code platform, which is used to implement the above-mentioned ERP management method based on a low-code platform, and the system includes:

[0029] A template unit, comprising a template library, wherein the template library comprises a plurality of ERP category templates, each of the ERP category templates has a data flow diagram, the data flow diagram comprises a plurality of processing nodes, and the template unit merges the data flow diagrams of the ERP category templates of the same type into an integrated flow diagram;

[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, marking a part to be modified in the basic flowchart, wherein the part to be modified is a part of the basic flowchart that needs to be modified;

[0032] 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 node that fails the verification as an abnormal node, and generate a risk reminder pointing to the abnormal node.

[0033] Beneficial effects:

[0034] The present invention constructs a template library containing multiple ERP category templates, merges the data flow diagrams of the same type of templates into an integrated flow diagram, then selects the corresponding integrated flow diagram according to the user's functional requirements, and then automatically extracts the basic flow diagram from the integrated flow diagram according to the process requirements, so that the development of the ERP system can not only closely meet the actual needs of users, but also help developers quickly locate and select suitable templates, avoid searching one by one in a large number of templates, and save time. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1A schematic diagram of the steps of an ERP management method based on a low-code platform is provided for this application;

[0036] Figure 2 A schematic diagram of the principle of generating an integrated flow chart for this application;

[0037] Figure 3 A schematic diagram of the principles for generating a basic flow chart for this application;

[0038] Figure 4 This application provides a structural diagram of an ERP management system based on a low-code platform. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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 intended to limit the present invention.

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

[0041] S1: Build a template library, the template library includes a variety of ERP category templates, each ERP category template has a data flow diagram, and the data flow diagram includes a plurality of processing nodes.

[0042] Specifically, ERP category templates include material management category, human resources category, equipment maintenance category, purchase order category, data analysis category, etc. Each category template includes at least one, and each ERP category template has a data flow diagram. The data flow diagram is as follows: Figure 2 As shown in FIG. 1 , a 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 lines indicates that data flows from one processing node to another processing node. For example, for the material management category, the processing nodes represent the general warehouse and the sub-warehouses in each region. For the human resources category, the processing nodes include the transaction approval order and the copy order. For the data analysis type, the processing nodes include the data processing order, 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 integrated flow diagram.

[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 subsequent content. Before development, the early 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 material warehousing, outbound processes, and material distribution processes.

[0045] S3: 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.

[0046] S4: Mark the part to be modified in the basic flowchart. The part to be modified is the part of the basic flowchart that needs to be modified.

[0047] As mentioned above, one integrated flowchart corresponds to the data processing flow of all templates under one type. First, the corresponding integrated flowchart is selected according to the user's functional requirements, and then the appropriate basic flowchart is extracted from the integrated flowchart according to the user's process requirements. However, the extracted basic flowchart may not completely meet the customer's needs, and it is necessary to make targeted modifications. The part that does not meet the customer's needs is defined as the part to be modified. The part to be modified includes the disorder of the order of processing nodes, or the missing of processing nodes somewhere.

[0048] S5: Build an intelligent recognition model, obtain a complete flowchart after completing the adjustment of the part to be modified, verify each processing node in the complete flowchart 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.

[0049] 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.

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

[0051] The present invention constructs a template library containing multiple ERP category templates, merges the data flow diagrams of the same type of templates into an integrated flow diagram, then selects the corresponding integrated flow diagram according to the user's functional requirements, and then automatically extracts the basic flow diagram from the integrated flow diagram according to the process requirements, so that the development of the ERP system can not only closely meet the actual needs of users, but also help developers quickly locate and select suitable templates, avoid searching one by one in a large number of templates, and save time.

[0052] The present invention marks the parts to be modified in the basic flowchart, so that developers can clearly understand which parts need to be adjusted, increase directionality, and improve work efficiency. Finally, the present invention verifies each processing node in the complete flowchart by constructing an intelligent recognition model, which can automatically identify abnormal nodes and generate risk reminders, helping developers to promptly discover and solve potential problems in the process and ensure the correctness and reliability of the process.

[0053] In this embodiment, merging the data flow diagrams into an integrated flow diagram includes the following steps:

[0054] Data flow lines are marked between the processing nodes in the data flow diagram, each processing node is numbered based on the data flow line, and the data flow diagram is divided into multiple levels based on the number.

[0055] Continue to refer to Figure 2 In the data flow diagram, each processing node is marked 1, 2, and 3 according to the data flow order, which means that the data goes from processing node 1 to processing node 2, and then from processing node 2 to processing node 3. And because there are 3 numbers in the data flow diagram, the data flow diagram is divided into 3 levels, such as Figure 2 The data flow diagram B in Figure 1 shows the first level, the second level, and the third level from top to bottom.

[0056] The data flow diagram corresponding to the same type of ERP category modules is taken as the aggregation target, the aggregation target with the largest number of levels is taken as the main target, the processing nodes included in the main target are taken as the main nodes, and the reference nodes are located in the remaining aggregation targets. Starting from the reference nodes, the processing nodes of each level of the aggregation targets are merged into the main target. When merging, if the main node and the processing node meet the fusion conditions, the processing node will be merged into the main node. If not, the processing node will be linked to the main target as a branch node.

[0057] As before, there are 10 templates under the material management category. The data flow diagrams corresponding to the 10 templates are used as aggregation targets. Among the aggregation targets, the one with the largest number of levels is used as the main target, which is convenient for subsequent merging. Before aggregation, first locate the reference node in each aggregation target. The reference node is the root node for merging the aggregation target with the main target. For example Figure 2 In the data flow diagram, data flow diagram A is the main target, data flow diagram B is the aggregation target, and data flow diagram B needs to be merged into data flow diagram A.

[0058] Processing node 1 of data flow diagram B is the reference target. When merging, if processing node 1 of data flow diagram A and processing node 1 of data flow diagram B meet the fusion conditions, the two will be merged into one. If processing node 2 of data flow diagram A and processing node 2 of data flow diagram B do not meet the fusion conditions, processing node 2 will be linked to the main target as a branch node, and the connection relationship with the original processing node will still be maintained. The result after merging is referenced. Figure 2 The data flow diagram in C.

[0059] Specifically, determining whether the fusion conditions are met includes the following steps:

[0060] 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.

[0061] Continue to refer to Figure 2 For processing node 1 in data flow diagram A and data flow diagram B, the function labels of the two are the same, and the function labels of the data source nodes are the same, such as the function label is material out of the warehouse. Although the function labels of the data output nodes are different, they meet the fusion conditions and the two can be merged. For processing node 2 in data flow diagram A and data flow diagram B, the function labels of the two are different, such as material price approval and material quantity approval, which do not meet the fusion conditions.

[0062] This embodiment of locating the reference node includes the following steps:

[0063] 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.

[0064] Continue to refer to Figure 2As before, data flow graph B is used as the aggregation target, where the level with the smallest value is the first level, which includes processing node 1. Processing node 1 is used as the first node. In data flow graph A (main target), the main node that is the same as processing node 1 (first node) is searched from top to bottom. Since processing node 1 of data flow graph A and processing node 1 of data flow graph B meet the fusion condition, processing node 1 of data flow graph B is used as the reference node. Otherwise, in the second level of data flow graph B, processing node 2 is extracted again. If there is a processing node in data flow graph A that can be fused with processing node 2 of data flow graph B, processing node 2 is used as the reference node.

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

[0066] 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.

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

[0068] 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.

[0069] The following example explains the above steps. Currently, the system stores an integrated flowchart D, and has obtained the demand flowchart E. Now it is necessary to locate the initial node and the terminal node in the demand flowchart E. The following method is specifically used. First, the processing nodes at the upper and lower ends of the demand flowchart E are obtained, namely, processing node 1 and processing node 4. Then, it is determined whether there are nodes in the integrated flowchart that can be merged with processing nodes 1 and 4. If processing node 1 in the integrated flowchart D can be merged with processing node 1 in the demand flowchart E, and processing node 6 in the integrated flowchart D can be merged with processing node 4 in the demand flowchart E, then processing node 1 and processing node 4 in the demand flowchart E are used as target nodes, and processing node 1 in the demand flowchart E is at the beginning of its entire process, so it is used as the initial node. Similarly, processing node 4 is used as the terminal node.

[0070] Based on the above introduction, in the integrated flow chart D, processing node 1 is used as the top node and processing node 6 is used as the bottom node, and multiple filing flow charts are generated with the two as the starting point and the end point respectively. Figure 3 In the example, two alternative flowcharts can be generated, wherein 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 demand flowchart E and the two alternative flowcharts is calculated, and the alternative flowchart with the larger similarity is selected as the basic flowchart.

[0071] In this embodiment, calculating the similarity includes the following steps:

[0072] Generate a corresponding hash value based on the functional 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 XOR operation on the hash value of the first neighbor node and the initial node itself, and perform XOR operation on the hash value of the first neighbor node and the top node itself to obtain the label values ​​of the initial node and the top node.

[0073] Get 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 XOR operation on the hash values ​​of the first neighbor node and the second neighbor node, obtain the label value of the first neighbor node, and repeat this step until all processing nodes in the flowchart are traversed.

[0074] In computers, function labels are binary values, which are converted into hash values ​​based on hash algorithms. For example, processing node 2 in demand flow chart E is used as the first neighbor node, and the hash values ​​of processing nodes 1 and 2 are XORed to obtain the label value of processing node 1.

[0075] Similarly, continue to obtain the second neighbor node of the first neighbor node. In the requirement flow chart E, the second neighbor node of processing node 2 (the first neighbor node) is processing node 3. Then, perform an XOR operation 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] 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.

[0077] For the required flowchart and the alternative flowchart, the function labels of processing node 1 and processing node 2 are the same, and the calculated label values ​​of processing node 1 and processing node 2 are also the same. Then the similarity can be calculated by the following first formula, which is: , where P is the similarity between the demand flowchart and the alternative flowchart, is the number of identical label values ​​in the first label set and the second label set, is the number of label values ​​included in the first label set, is the number of label values ​​included in the second label set. For example, if the alternative flowchart includes processing nodes 1-2-3-5-6, 4 label values ​​will be calculated, which are calculated based on 1-2, 2-3, 3-5, and 5-6 respectively. If the required flowchart includes processing nodes 1-2-3-4, there are 3 label values, which are calculated based on 1-2, 2-3, and 3-4 respectively. If 3 of the label values ​​are the same, the similarity is 3 / 4=0.75.

[0078] like Figure 4 As shown, the present invention also provides an ERP management system based on a low-code platform, which is used to implement the above-mentioned ERP management method based on a low-code platform, and the system includes:

[0079] A template unit includes a template library, the template library includes a plurality of ERP category templates, each ERP category template has a data flow diagram, the data flow diagram includes a plurality of processing nodes, and the template unit merges the data flow diagrams of the same type of ERP category templates into an integrated flow diagram;

[0080] 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;

[0081] 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;

[0082] 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.

[0083] It should be understood that the various technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0084] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in 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; 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: Merging data flow diagrams into an integrated flow diagram involves the following steps: 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 modules is taken as the aggregation target, the aggregation target with the largest number of levels is taken as the main target, the processing nodes included in the main target are taken as the main nodes, and the reference nodes are located in the remaining aggregation targets. Starting from the reference nodes, the processing nodes of each level of the aggregation targets are merged into the main target. When merging, if the main node and the processing node meet the fusion conditions, the processing node will be merged into the main node. If not, the processing node will be linked to the main target as a branch node.

3. The ERP management method based on the low-code platform according to claim 2 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.

4. The ERP management method based on the low-code platform according to claim 2 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.

5. The ERP management method based on the low-code platform according to claim 4 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.

6. The ERP management method based on the low-code platform according to claim 2 is characterized in that: Determining whether the integration 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.

7. The ERP management method based on the low-code platform according to claim 5 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.

8. 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.

9. 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 8, characterized in that: include: A template unit includes a template library, the template library includes a plurality of ERP category templates, each ERP category template has a data flow diagram, the data flow diagram includes a plurality of processing nodes, and the template unit merges the data flow diagrams of the same type of ERP category templates into an integrated flow diagram; 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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