Preposed traceability early warning method and system

Abstract

The invention provides a front traceability early warning method and system, and the method comprises the steps: S1, obtaining sales order data in real time based on a kafka technology, and converting the sales order data into a message object after screening; s2, analyzing and extracting SKU information corresponding to the sales order from the message object; s3, performing verification according to the SKU information and the supplier list information, and outputting a verification result; and S4, extracting field information from the verification result, and pushing the field information to a purchasing system. According to the invention, the procurement channel is checked and optimized through the preposed traceability technology, so that the purchaser can monitor the state of the supply chain in real time, predict the potential risk and select the optimal procurement channel, the efficiency and accuracy of the procurement process are improved, and the method has good practicability.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain procurement, and in particular to a method and system for pre-tracing early warning. Background Art

[0002] With the rapid development of the global economy, supply chain management on the procurement side has become a key factor in the core competitiveness of enterprises. In a volatile market environment, enterprises are faced with challenges such as supply chain disruptions, cost control and supplier risk management. Effective supply chain management can ensure the smoothness of the procurement process, reduce operational risks, and improve the ability of enterprises to respond to market changes.

[0003] However, traditional procurement traceability methods have many limitations. The opacity of information and delayed updates make it difficult for companies to monitor the status of the supply chain in real time and predict potential risks. In addition, the diversity and complexity of suppliers increase management difficulties, making it difficult for companies to quickly respond to abnormal situations in the supply chain.

[0004] To solve these problems, the industry has begun to explore the use of advanced technologies to improve the traceability warning system. Big data technology can process and analyze massive amounts of data and provide in-depth insights; artificial intelligence and machine learning algorithms can predict market trends and consumer behavior and optimize inventory management; blockchain technology provides a decentralized, tamper-proof data storage method, enhancing the transparency and trust of the supply chain. Summary of the invention

[0005] In view of the defects in the prior art, the object of the present invention is to provide a method and system for pre-tracing warning.

[0006] A method for pre-tracing warning provided by the present invention includes:

[0007] Step S1: Based on Kafka technology, obtain sales order data in real time, filter it and convert it into message objects;

[0008] Step S2: parse and extract the SKU information corresponding to the sales order from the message object;

[0009] Step S3: Verify according to the SKU information and supplier list information, and output the verification result;

[0010] Step S4: Extract field information from the verification result and push it to the procurement system.

[0011] Preferably, step S1 includes subscribing to a sales order-related topic in a Kafka cluster, receiving and parsing sales order data in real time, and converting the data into a format supported by the procurement system.

[0012] Preferably, step S3 includes the following sub-steps:

[0013] Step S3.1: Take the SKU information as input and use the SORT interface of the preset procurement traceability strategy to obtain the supplier list;

[0014] Step S3.2: Input the SKU information and supplier list into the CheckSupplier interface for verification to obtain the verification result.

[0015] Preferably, the SORT interface includes sorting the supplier list according to timeliness, cost or different scenarios, and supports custom sorting rules, allowing users to adjust the sorting strategy according to actual needs.

[0016] Preferably, the step S3.2 includes calling the CheckSupplier interface, returning a supplier of the corresponding SKU and providing an abnormal data prompt; the abnormal data includes invalid supplier brand authorization, invalid price, invalid supplier status and supplier products are not supported for sale.

[0017] A pre-source tracing warning system provided by the present invention includes:

[0018] Module M1: Based on Kafka technology, it obtains sales order data in real time and converts it into message objects after filtering;

[0019] Module M2: parse and extract the SKU information of the corresponding sales order from the message object;

[0020] Module M3: Verify based on SKU information and supplier list information, and output verification results;

[0021] Module M4: Extract field information from the verification results and push it to the procurement system.

[0022] Preferably, the module M1 includes subscribing to sales order-related topics in the Kafka cluster, receiving and parsing sales order data in real time, and converting the data into a format supported by the procurement system.

[0023] Preferably, the module M3 includes the following submodules:

[0024] Module M3.1: Take SKU information as input and use the SORT interface of the preset procurement traceability strategy to obtain the supplier list;

[0025] Module M3.2: Input the SKU information and supplier list into the CheckSupplier interface for verification and obtain the verification result.

[0026] Preferably, the SORT interface includes sorting the supplier list according to timeliness, cost or different scenarios, and supports custom sorting rules, allowing users to adjust the sorting strategy according to actual needs.

[0027] Preferably, the module M3.2 includes calling the CheckSupplier interface, returning a supplier of the corresponding SKU and providing an abnormal data prompt; the abnormal data includes invalid supplier brand authorization, invalid price, invalid supplier status and supplier products are not supported for sale.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. The present invention checks and optimizes procurement channels through pre-tracing technology, so that the purchaser can monitor the supply chain status in real time, predict potential risks and select the best procurement channel, thereby improving the efficiency and accuracy of the procurement process and having good practicality.

[0030] 2. The present invention significantly improves the transparency of the supply chain through online data monitoring and analysis, allowing enterprises to clearly understand the entire process of the product from the source to the consumption point; through advanced data analysis technology, it identifies potential risks of outdated supply chain information in advance and issues early warnings, thereby reducing the possibility of supply chain disruptions.

[0031] 3. The present invention can automatically evaluate the performance and compliance of suppliers, help enterprises quickly identify and select the best suppliers, simplify the supplier management process, and respond quickly when abnormal data is detected to reduce losses; it reduces operating costs by optimizing inventory management and reducing supply chain disruptions.

[0032] 4. The present invention uses automated tools and intelligent algorithms to improve the efficiency of the supply chain process, reduce manual intervention, and greatly improve accuracy.

[0033] Other beneficial effects of the present invention will be explained in the specific implementation manner through the introduction of specific technical features and technical solutions. Through the introduction of these technical features and technical solutions, those skilled in the art should be able to understand the beneficial technical effects brought about by the technical features and technical solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0035] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0036] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0037] Reference Figure 1 As shown, a method for pre-tracing and early warning includes:

[0038] First, use Kafka technology to filter out the current sales order data in real time and convert it into a message object:

[0039] Filter the SKU sales information data in the sales order, filter the information of the supplier that sells the SKU in the supplier and product correspondence table, use the traceability strategy SORT strategy to return the TOP5 suppliers, that is, return the SKU-supplier object, and then input the SKU-supplier object into the CheckSupplier interface.

[0040] By subscribing to sales order-related topics in the Kafka cluster, sales order data is received and parsed in real time, and the data is converted into a format supported by the procurement system. The SKU information corresponding to the sales order is filtered out, and the corresponding supplier list is returned using the SORT interface of the procurement traceability strategy; in one embodiment, the SORT interface sorts the suppliers by cost, timeliness or different scenarios, returns the TOP5 of the corresponding supplier list, and then inputs the SKU and supplier objects into the CheckSupplier interface. The SORT interface supports custom sorting rules and allows users to adjust the sorting strategy according to actual needs.

[0041] Call the supplier interface for verification. The underlying principle of the CheckSupplier interface verification is: obtain the verification supplier's status, brand authorization information, price validity period information, and whether it is sold from the database. If the supplier is a valid supplier, the supplier brand is authorized, the price is within the valid price period, and the sales conditions are met, the supplier is valid.

[0042] Based on the verification results, a supplier abnormal data prompt for the corresponding SKU can be returned, such as invalid supplier brand authorization, invalid price, invalid supplier status, whether the supplier's products are sold, and other necessary information.

[0043] Filter this information according to requirements and return the corresponding fields to the procurement system:

[0044] After the top five suppliers are ranked, each SKU is checked against its corresponding supplier. This process is implemented by calling the CheckSupplier interface. During the verification process, it is necessary to ensure that the supplier meets the following conditions: it is a valid supplier, has brand authorization, is in a saleable state, and the price provided by the supplier is valid. If the supplier of a SKU fails to meet any of the above conditions, it will be considered that there is an abnormality in the supplier channel of the SKU. Once such an abnormality is detected, the abnormal information will be sent to the corresponding supplier relationship management system (SRM) and marked as a to-do item. These to-do items will be assigned to the person responsible for the relevant brand and the supplier responsible person. Subsequently, the relevant personnel will manually review and process the abnormal information to ensure the stability and compliance of the supply chain. This process is designed to ensure that the supplier channels of all SKUs are reliable and effective, thereby maintaining product quality and customer satisfaction.

[0045] The present invention checks and optimizes procurement channels through pre-tracing technology, enabling the purchaser to monitor the supply chain status in real time, predict potential risks and select the best procurement channel, thereby improving the efficiency and accuracy of the procurement process and having good practicality.

[0046] The present invention also provides a system for pre-traceability warning, which can be implemented by executing the process steps of the pre-traceability warning method, that is, those skilled in the art can understand the pre-traceability warning method as a preferred implementation of the system for pre-traceability warning.

[0047] Specifically, a pre-tracing warning system includes:

[0048] Module M1: Based on Kafka technology, it obtains sales order data in real time and converts it into message objects after filtering;

[0049] Module M2: parse and extract the SKU information of the corresponding sales order from the message object;

[0050] Module M3: Verify based on SKU information and supplier list information, and output verification results;

[0051] Module M4: Extract field information from the verification results and push it to the procurement system.

[0052] The module M1 includes subscribing to sales order-related topics in the Kafka cluster, receiving and parsing sales order data in real time, and converting the data into a format supported by the procurement system.

[0053] The module M3 includes the following submodules:

[0054] Module M3.1: Take SKU information as input and use the SORT interface of the preset procurement traceability strategy to obtain the supplier list;

[0055] Module M3.2: Input the SKU information and supplier list into the CheckSupplier interface for verification and obtain the verification result.

[0056] The SORT interface includes sorting the supplier list according to timeliness, cost or different scenarios, and supports custom sorting rules, allowing users to adjust the sorting strategy according to actual needs.

[0057] The module M3.2 includes calling the CheckSupplier interface, returning a supplier of the corresponding SKU and providing an abnormal data prompt; the abnormal data includes invalid supplier brand authorization, invalid price, invalid supplier status and supplier products are not supported for sale.

[0058] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0059] In the description of the present application, it should be understood that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0060] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for pre-tracing early warning, It is characterized in that include: Step S1: Based on Kafka technology, obtain sales order data in real time, filter it and convert it into message objects; Step S2: parse and extract the SKU information corresponding to the sales order from the message object; Step S3: Verify according to the SKU information and supplier list information, and output the verification result; Step S4: Extract field information from the verification result and push it to the procurement system.

2. The method for pre-tracing and early warning according to claim 1, It is characterized in that The step S1 includes subscribing to a sales order-related topic in the Kafka cluster, receiving and parsing sales order data in real time, and converting the data into a format supported by the procurement system.

3. The method for pre-tracing and early warning according to claim 1, It is characterized in that The step S3 comprises the following sub-steps: Step S3.1: Take the SKU information as input and use the SORT interface of the preset procurement traceability strategy to obtain the supplier list; Step S3.2: Input the SKU information and supplier list into the CheckSupplier interface for verification to obtain the verification result.

4. The method for pre-tracing and warning according to claim 3, It is characterized in that The SORT interface includes sorting the supplier list according to timeliness, cost or different scenarios, and supports custom sorting rules, allowing users to adjust the sorting strategy according to actual needs.

5. The method for pre-tracing and warning according to claim 3, It is characterized in that The step S3.2 includes calling the CheckSupplier interface, returning a supplier of the corresponding SKU and providing an abnormal data prompt; the abnormal data includes invalid supplier brand authorization, invalid price, invalid supplier status, and supplier products are not supported for sale.

6. A system for early warning of source tracing, It is characterized in that include: Module M1: Based on Kafka technology, it obtains sales order data in real time and converts it into message objects after filtering; Module M2: parse and extract the SKU information of the corresponding sales order from the message object; Module M3: Verify based on SKU information and supplier list information, and output verification results; Module M4: Extract field information from the verification results and push it to the procurement system.

7. The system for pre-tracing and early warning according to claim 6, It is characterized in that The module M1 includes subscribing to sales order-related topics in the Kafka cluster, receiving and parsing sales order data in real time, and converting the data into a format supported by the procurement system.

8. The system for pre-tracing and early warning according to claim 6, It is characterized in that The module M3 includes the following submodules: Module M3.1: Take SKU information as input and use the SORT interface of the preset procurement traceability strategy to obtain the supplier list; Module M3.2: Input the SKU information and supplier list into the CheckSupplier interface for verification and obtain the verification result.

9. The system for pre-tracing and early warning according to claim 8, It is characterized in that The SORT interface includes sorting the supplier list according to timeliness, cost or different scenarios, and supports custom sorting rules, allowing users to adjust the sorting strategy according to actual needs.

10. The system for pre-tracing and early warning according to claim 8, It is characterized in that The module M3.2 includes calling the CheckSupplier interface, returning a supplier of the corresponding SKU and providing an abnormal data prompt; the abnormal data includes invalid supplier brand authorization, invalid price, invalid supplier status and supplier products are not supported for sale.

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