Material purchasing management system

Abstract

The invention discloses a material purchasing management system. The system comprises a supplier management and evaluation module; the system is responsible for collecting and analyzing supplier basic information, historical performance, quality evaluation, after-sales service data structured data, social media data and industry news unstructured data in real time, and dynamically evaluating suppliers. The supplier management and evaluation module transmits an evaluation result to the purchase order and quality standard docking module and the product quality verification and detection module; and the product quality verification and detection module is responsible for carrying out intelligent quality verification and detection on samples or preliminary batches provided by the recommended suppliers before purchase decision making by adopting the Internet of Things technology and automatic detection equipment. The product quality verification and detection module carries out quality verification and detection on samples or preliminary batches provided by recommended suppliers before purchase decision making, it is ensured that products meet the set quality standard, and subsequent problems caused by substandard product quality are effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of procurement and management, and in particular to a material procurement management system. Background Art

[0002] With the rapid development of information technology, enterprises pay more and more attention to the application of information technology in the management field to improve management efficiency and accuracy. Modern enterprises face many challenges in procurement management, such as cumbersome processes, opaque information, and low efficiency. The emergence of the material procurement management system provides enterprises with a new solution to standardize and simplify the material procurement process and improve management efficiency. The material procurement management system is a tool for comprehensive management of enterprise material procurement. It covers a series of links from demand planning, supplier selection, purchase order generation, contract signing, order tracking, arrival acceptance, inventory management, to financial settlement. By integrating advanced information technology and data analysis tools, the material procurement management system can significantly improve procurement efficiency, reduce procurement costs, optimize inventory structure, and provide strong support for enterprise decision-making.

[0003] After searching, the invention patent with Chinese patent number CN111539020B discloses a material procurement management system, including a client and a server, the client includes a login module and an encryption module, the login module is used to input the user's account and password, the encryption module is used to convert the user's account and password into corresponding user ciphertext and transmit the user ciphertext to the server, the server verifies the account and password input by the user according to the user ciphertext, if the verification is successful, the client is authorized to connect to the database and access the database, otherwise the client is denied access to the data and feedback is given a verification failure prompt. The present invention performs elliptical encryption on the user's account and password when registering through the encryption module, converts it into the corresponding user ciphertext, and then the server receives the user ciphertext and stores it in the server, which can improve the security of user data and avoid user privacy leakage. Correspondingly, the present invention also provides a material procurement management method.

[0004] However, in actual use, the evaluation of the above systems often relies on limited and static data sources, such as financial statements and historical transaction records, which may not fully reflect the actual capabilities and potential risks of suppliers. At the same time, the evaluation cycle is long and it is difficult to adapt to the rapidly changing market environment. Therefore, a material procurement management system is proposed. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art that evaluation often relies on limited and static data sources, such as financial statements, historical transaction records, etc., which may not fully reflect the actual capabilities and potential risks of suppliers. At the same time, the evaluation cycle is long and it is difficult to adapt to the rapidly changing market environment. A material procurement management system is proposed.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A material procurement management system, comprising:

[0008] Supplier management and evaluation module: responsible for real-time collection and analysis of supplier basic information, historical performance, quality evaluation, after-sales service data, structured data, social media data, and unstructured data of industry news, and dynamic evaluation of suppliers. The supplier management and evaluation module transmits the evaluation results to the purchase order and quality standard docking module and the product quality verification and testing module;

[0009] Product quality verification and testing module: responsible for using Internet of Things technology and automated testing equipment to conduct intelligent quality verification and testing on samples or preliminary batches provided by recommended suppliers before purchasing decisions are made. The product quality verification and testing module transmits the quality verification and testing results to the purchase order and quality standard docking module and the supplier management and evaluation module;

[0010] Purchase order and quality standard docking module: responsible for automatically matching suppliers through intelligent matching algorithms based on big data analysis technology, according to procurement needs and historical data, and intelligently docking purchase orders with product quality standards. The purchase order and quality standard docking transmits the procurement standards to the real-time quality monitoring and tracking module;

[0011] Real-time quality monitoring and tracking module: responsible for using Internet of Things technology and big data analysis to monitor the production, transportation and storage of materials in real time, and set up quality abnormality alarms. The real-time quality monitoring and tracking module transmits the monitoring results to the acceptance and rework management module;

[0012] Acceptance and rework management module: responsible for the acceptance of qualified materials and initiating the rework or return process for unqualified materials. The acceptance and rework management module feeds back the material acceptance status to the supplier management and evaluation module.

[0013] The above technical solution further includes:

[0014] Preferably, the supplier management and evaluation module includes an intelligent evaluation unit, a supplier grading management unit, a risk assessment and early warning unit, a supplier information management unit and a supplier cooperation record unit. The intelligent evaluation unit performs dynamic evaluation on suppliers. The supplier grading management unit divides suppliers into different grades according to the output results of the intelligent evaluation unit and formulates corresponding management strategies. The risk assessment and early warning unit establishes a supplier risk assessment model to predict and warn of potential risks. When certain key indicators of the supplier are abnormal, the early warning mechanism is automatically triggered. The supplier information management unit is responsible for the entry, update and maintenance of the basic information of the supplier. The supplier cooperation record unit records the cooperation history with the supplier.

[0015] Preferably, the product quality verification and testing module includes a quality standard definition unit, a sample collection and management unit, a physical test and performance test unit, a test data analysis and report generation unit, a pass and fail judgment unit, and a quality feedback and communication unit. The quality standard definition unit is responsible for defining the quality standards of purchased materials according to the production needs and product characteristics of the enterprise, including dimensional tolerances, material composition, performance requirements, etc., to ensure that all quality standards can be closely integrated with procurement needs. The sample collection and management unit is responsible for collecting samples from recommended suppliers and managing the warehousing and storage information of samples to ensure that the received samples are consistent with the order requirements. The physical test and performance test unit is responsible for performing physical tests on samples as well as functional and performance tests. Physical tests such as size measurement, weight measurement, strength test, wear resistance test, etc., ensure that it meets the specific physical performance requirements. Function and performance tests are to check its actual performance in the use environment. For example, it may include performance tests such as strength, durability, and heat treatment effects of precision parts to ensure that it meets the production process requirements. The test data analysis and report generation unit is responsible for data analysis of the test results and generating a test report, including error range, pass rate, performance comparison, etc. The report makes a clear judgment on whether the sample meets the quality standards. The qualified and unqualified judgment unit is responsible for judging whether the sample is qualified according to the quality standards and test results. The quality feedback and communication unit is responsible for feeding back the test results to the supplier management and evaluation module and notifying the purchaser.

[0016] Preferably, the purchase order and quality standard docking module includes a purchase demand analysis unit, a quality standard matching unit, a purchase order generation and quality requirement binding unit, an intelligent supplier recommendation unit and a quality monitoring standard transmission unit. The purchase demand analysis unit is responsible for analyzing and defining the purchase demand according to the specific purpose, production requirements and quality standards of the purchased materials, comparing the existing quality standards and purchase demand, and clarifying the key performance indicators of the materials, such as dimensional tolerance, material properties, durability, etc. The quality standard matching unit is responsible for matching product quality requirements, such as dimensional tolerance range, material requirements, performance testing, etc., according to the purchase demand and predefined quality standards. The purchase order generation and quality requirement binding unit is responsible for generating a purchase order and binding the quality standards related to the order to ensure that all relevant quality standards are followed during the procurement process. The intelligent supplier recommendation unit is responsible for recommending suppliers based on the purchase order, quality requirement analysis and the evaluation results of the supplier management and evaluation module. The quality monitoring standard transmission unit is responsible for transmitting the purchase standards and quality requirements to the real-time quality monitoring and tracking module to ensure real-time monitoring of quality during the procurement process.

[0017] Preferably, the real-time quality monitoring and tracking module includes a production process monitoring unit, a transportation process monitoring unit, a storage process monitoring unit, a quality abnormality alarm and response unit, a data analysis and report generation unit, and a monitoring result feedback unit. The production process monitoring unit is responsible for real-time monitoring of various quality indicators in the supplier's production process, docking with the supplier's production line data system, and collecting key data of product production in real time, such as size, process, production speed, etc. The transportation process monitoring unit is responsible for monitoring the quality of materials during transportation, including tracking whether the transportation conditions (such as temperature, humidity, vibration, etc.) meet the requirements. The storage process monitoring unit is responsible for monitoring the quality of materials in the warehousing link to ensure that the storage environment (such as humidity, temperature, storage method, etc.) will not have adverse effects on the materials. The quality abnormality alarm and response unit is responsible for immediately issuing an alarm and notifying relevant responsible personnel when quality abnormalities or non-compliance with requirements are found during monitoring. It can classify and prioritize abnormal situations and start a preset response process, such as timely notifying suppliers, adjusting transportation routes, adjusting storage conditions, etc. The monitoring result feedback unit is responsible for timely feedback of real-time monitoring results to the acceptance and rework management module.

[0018] Preferably, the acceptance and rework management module includes a material acceptance unit, a quality anomaly detection and feedback unit, a rework and return process management unit, a supplier feedback and collaboration unit, and a quality report and analysis unit. The material acceptance unit is responsible for acceptance inspection of the received purchased materials, including size, appearance, quantity, packaging, etc., to ensure that the materials meet the quality standards and quantity requirements in the purchase order. The quality anomaly detection and feedback unit is responsible for detecting and analyzing unqualified materials, determining the type of quality problem, and feeding back relevant anomalies to the supplier management and evaluation module. The rework and return process management unit is responsible for initiating the rework or return process after unqualified materials are found during the acceptance process, and supervising the execution of relevant processes. The supplier feedback and collaboration unit is responsible for feeding back the acceptance results, rework or return processing results to the supplier, and collaborating with the supplier to improve the quality of materials. The quality report and analysis unit is responsible for generating quality reports, providing analysis of material acceptance, rework, return and other data for management decision-making.

[0019] 10. Preferably, the specific process of the intelligent evaluation unit dynamically evaluating the supplier is:

[0020] Data collection and processing: Collect supplier financial data, historical cooperation records, product quality data, structured data, and social media data, industry news unstructured data;

[0021] Feature selection and extraction: Extracting features that have important influence on supplier evaluation from the collected data;

[0022] Model training and validation: Use neural network training to evaluate the model, and use the validation set to verify the performance of the model;

[0023] Evaluation and feedback: Apply the trained model to newly collected supplier data, conduct dynamic evaluation, and adjust management strategies based on the evaluation results.

[0024] Preferably, the risk assessment and early warning unit establishes a supplier risk assessment model to predict and warn of potential risks, and the specific steps are:

[0025] Risk assessment model establishment: Use random forest to establish a supplier risk assessment model;

[0026] Early warning mechanism setting: set early warning thresholds, and trigger the early warning mechanism when certain key indicators of suppliers are abnormal;

[0027] Development of response measures: Develop response measures based on the early warning results.

[0028] Preferably, the specific steps of immediately issuing an alarm when the quality abnormality alarm and response unit finds quality abnormality or non-compliance with requirements during monitoring are:

[0029] Collect various quality data in real time, set various quality index thresholds (such as upper and lower limits of dimensional tolerance, temperature and humidity range, etc.) according to the quality standards of purchased materials and historical data, and set the thresholds as: X min ≤X≤X max , where X represents the quality index value, X min and X max Represent the lowest and highest acceptable values ​​of the indicator respectively;

[0030] The data collected in real time is compared with the set threshold. When the data exceeds the threshold range, it is judged as quality abnormality and the system immediately triggers the alarm mechanism.

[0031] The present invention has the following beneficial effects:

[0032] In the present invention, the supplier management and evaluation module is used to collect and analyze the supplier's basic information, historical performance, quality evaluation, after-sales service data, structured data, social media data, and unstructured data of industry news, and dynamically evaluate the supplier. The product quality verification and testing module verifies and tests the quality of samples or preliminary batches provided by the recommended supplier before making a purchase decision to ensure that the product meets the established quality standards, effectively avoiding subsequent problems caused by substandard product quality. The real-time quality monitoring and tracking module is responsible for real-time monitoring of the production, transportation, and warehousing of materials, and setting quality abnormality alarms, so that the company can promptly discover and deal with potential quality problems, avoiding problematic materials from flowing into production lines or warehouses, and further reducing quality risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a system architecture diagram of a material procurement management system proposed by the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] like Figure 1 As shown, a material procurement management system includes:

[0036] Supplier management and evaluation module: responsible for real-time collection and analysis of supplier basic information, historical performance, quality evaluation, after-sales service data, structured data, social media data, and unstructured data of industry news, and dynamic evaluation of suppliers. The supplier management and evaluation module transmits the evaluation results to the purchase order and quality standard docking module and the product quality verification and testing module;

[0037] Product quality verification and testing module: responsible for using Internet of Things technology and automated testing equipment to conduct intelligent quality verification and testing on samples or preliminary batches provided by recommended suppliers before purchasing decisions are made. The product quality verification and testing module transmits the quality verification and testing results to the purchase order and quality standard docking module and the supplier management and evaluation module;

[0038] Purchase order and quality standard docking module: responsible for automatically matching suppliers through intelligent matching algorithms based on big data analysis technology, according to procurement needs and historical data, and intelligently docking purchase orders with product quality standards. The purchase order and quality standard docking transmits the procurement standards to the real-time quality monitoring and tracking module;

[0039] Real-time quality monitoring and tracking module: responsible for using Internet of Things technology and big data analysis to monitor the production, transportation and storage of materials in real time, and set up quality abnormality alarms. The real-time quality monitoring and tracking module transmits the monitoring results to the acceptance and rework management module;

[0040] Acceptance and rework management module: responsible for the acceptance of qualified materials and initiating the rework or return process for unqualified materials. The acceptance and rework management module feeds back the material acceptance status to the supplier management and evaluation module.

[0041] In an embodiment of the present invention, through dynamic evaluation, the system can timely identify suppliers with poor performance, so as to avoid enterprises relying solely on suppliers' promotional materials or samples and ignoring long-term quality performance. This multi-dimensional evaluation can reduce blindness and dependence in procurement decisions, thereby reducing procurement risks. The quality verification and testing module provides additional security to ensure that the quality of purchased materials meets strict requirements and avoids quality problems caused by relying on simple samples. By docking precise quality standards with order requirements, quality problems caused by mismatches between orders and quality requirements can be effectively avoided, such as the dimensional tolerance of precision parts not meeting requirements. Real-time monitoring and quality tracking can effectively control quality risks in the procurement process, detect problems in time and take remedial measures to avoid production stagnation or equipment failure due to quality problems. The acceptance and rework management module ensures that even if problems occur during production or transportation, they can be corrected in time to prevent enterprises from putting unqualified products into production.

[0042] In one embodiment, the supplier management and evaluation module includes an intelligent evaluation unit, a supplier grading management unit, a risk assessment and early warning unit, a supplier information management unit and a supplier cooperation record unit. The intelligent evaluation unit dynamically evaluates suppliers. The supplier grading management unit divides suppliers into different levels according to the output results of the intelligent evaluation unit and formulates corresponding management strategies. The risk assessment and early warning unit establishes a supplier risk assessment model to predict and warn of potential risks. When certain key indicators of the supplier are abnormal, the early warning mechanism is automatically triggered. The supplier information management unit is responsible for the entry, update and maintenance of the basic information of the supplier. The supplier cooperation record unit records the cooperation history with the supplier.

[0043] In one embodiment, the product quality verification and inspection module includes a quality standard definition unit, a sample collection and management unit, a physical test and performance test unit, a test data analysis and report generation unit, a pass and fail judgment unit, and a quality feedback and communication unit. The quality standard definition unit is responsible for defining the quality standards of purchased materials according to the production needs of the enterprise and product characteristics. The sample collection and management unit is responsible for collecting samples from recommended suppliers and managing the sample warehousing and storage information. The physical test and performance test unit is responsible for performing physical tests on samples as well as functional and performance tests. The test data analysis and report generation unit is responsible for performing data analysis on the test results and generating a test report. The pass and fail judgment unit is responsible for judging whether the sample is qualified according to the quality standards and test results. The quality feedback and communication unit is responsible for feeding back the test results to the supplier management and evaluation module and notifying the purchaser.

[0044] In the embodiment of the present invention, the basis for determining whether a product is qualified or unqualified is whether the product meets the pre-set quality standard. By calculating the qualified rate, defect rate, performance test results, etc., it is determined whether the product meets the procurement standard. When the unqualified rate exceeds the set threshold (such as 1%), the product is judged to be unqualified, and the purchasing department needs to decide whether to return the product or find an alternative supplier.

[0045] In one embodiment, the purchase order and quality standard docking module includes a purchase demand analysis unit, a quality standard matching unit, a purchase order generation and quality requirement binding unit, an intelligent supplier recommendation unit and a quality monitoring standard transmission unit. The purchase demand analysis unit is responsible for analyzing and defining purchase requirements according to the specific purpose, production requirements and quality standards of the purchased materials. The quality standard matching unit is responsible for matching product quality requirements according to purchase requirements and quality standards. The purchase order generation and quality requirement binding unit is responsible for generating purchase orders and binding the quality standards related to the order. The intelligent supplier recommendation unit is responsible for recommending suppliers based on the purchase order, quality requirement analysis and the evaluation results of the supplier management and evaluation module. The quality monitoring standard transmission unit is responsible for transmitting the purchase standards and quality requirements to the real-time quality monitoring and tracking module.

[0046] In one embodiment, the real-time quality monitoring and tracking module includes a production process monitoring unit, a transportation process monitoring unit, a warehousing process monitoring unit, a quality anomaly alarm and response unit, a data analysis and report generation unit, and a monitoring result feedback unit. The production process monitoring unit is responsible for real-time monitoring of various quality indicators in the supplier's production process, the transportation process monitoring unit is responsible for monitoring the quality of materials during transportation, the warehousing process monitoring unit is responsible for monitoring the quality of materials in the warehousing link, the quality anomaly alarm and response unit is responsible for immediately issuing an alarm and notifying relevant responsible personnel when quality anomalies or non-compliance with requirements are found during monitoring, and the monitoring result feedback unit is responsible for timely feedback of real-time monitoring results to the acceptance and rework management module.

[0047] In the embodiment of the present invention, through the quality monitoring and evaluation of the above-mentioned units, the quality risk of each link in the procurement can be fully grasped, and the increase of procurement risk due to reliance on samples or promotional materials provided by suppliers can be avoided. By combining the monitoring and evaluation of production, transportation, warehousing, quality abnormality warning and other links, enterprises can timely discover potential quality problems, take effective preventive and corrective measures, ensure that precision metal parts meet production requirements, thereby reducing procurement risks and ensuring the smooth operation of production equipment.

[0048] In one embodiment, the acceptance and rework management module includes a material acceptance unit, a quality anomaly detection and feedback unit, a rework and return process management unit, a supplier feedback and collaboration unit, and a quality report and analysis unit. The material acceptance unit is responsible for acceptance inspection of the received purchased materials. The quality anomaly detection and feedback unit is responsible for testing and analyzing unqualified materials, determining the type of quality problems, and feeding back relevant anomalies to the supplier management and evaluation module. The rework and return process management unit is responsible for initiating the rework or return process after unqualified materials are found during the acceptance process, and supervising the execution of related processes. The supplier feedback and collaboration unit is responsible for feeding back the acceptance results, rework or return processing results to the supplier, and collaborating with the supplier to improve the quality of materials. The quality report and analysis unit is responsible for generating quality reports.

[0049] In the embodiment of the present invention, the quality reporting and analysis unit is responsible for generating a detailed quality report, summarizing the quality status of the purchased materials, and providing data support for future purchasing decisions. The content of the report includes: summarizing the scores of various quality indicators, displaying the overall quality level, analyzing the types and causes of quality problems, finding the root causes and proposing improvement suggestions, analyzing the quality change trend based on historical data, and predicting the quality problems that may be encountered in future purchases. Based on historical procurement data, the weighted moving average method is used to perform trend analysis on each quality indicator to predict future quality changes: in, represents the predicted quality value of the i-th quality indicator, that is, the predicted future quality level, ω k is the weight coefficient, which indicates the influence of historical data points on the prediction results. Recent historical data points will be given higher weights, indicating that they have more influence on future quality predictions. i (k represents the quality value of the kth data point in the historical data, and represents the actual quality data of the ith indicator at time k.

[0050] In one embodiment, the specific process of the intelligent evaluation unit dynamically evaluating the supplier is as follows:

[0051] Data collection and processing: Collect supplier financial data, historical cooperation records, product quality data, structured data, and social media data, industry news unstructured data;

[0052] Feature selection and extraction: Extracting features that have important influence on supplier evaluation from the collected data;

[0053] Model training and validation: Use neural network training to evaluate the model, and use the validation set to verify the performance of the model;

[0054] Evaluation and feedback: Apply the trained model to newly collected supplier data, conduct dynamic evaluation, and adjust management strategies based on the evaluation results.

[0055] In one embodiment, the risk assessment and early warning unit establishes a supplier risk assessment model to predict and warn of potential risks. The specific steps are:

[0056] Risk assessment model establishment: Use random forest to establish a supplier risk assessment model;

[0057] Early warning mechanism setting: set early warning thresholds, and trigger the early warning mechanism when certain key indicators of suppliers are abnormal;

[0058] Development of response measures: Develop response measures based on the early warning results.

[0059] In one embodiment, when the quality abnormality alarm and response unit finds quality abnormality or non-compliance with requirements during monitoring, the specific steps of immediately issuing an alarm are:

[0060] Collect various quality data in real time, set various quality index thresholds according to the quality standards of purchased materials and historical data, and set the thresholds as: X min ≤X≤X max , where X represents the quality index value, X min and X max Represent the lowest and highest acceptable values ​​of the indicator respectively;

[0061] The data collected in real time is compared with the set threshold. When the data exceeds the threshold range, it is judged as quality abnormality and the system immediately triggers the alarm mechanism.

[0062] In the embodiment of the present invention, if the collected quality indicator data is X, it is necessary to detect whether X exceeds the set threshold range. If X <X min or X>X max It is judged as quality abnormality. If X min ≤X≤X max The judgment is normal.

[0063] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A material procurement management system, characterized in that: include: Supplier management and evaluation module: responsible for real-time collection and analysis of supplier basic information, historical performance, quality evaluation, after-sales service data, structured data, social media data, and unstructured data of industry news, and dynamic evaluation of suppliers. The supplier management and evaluation module transmits the evaluation results to the purchase order and quality standard docking module and the product quality verification and testing module; Product quality verification and testing module: responsible for using Internet of Things technology and automated testing equipment to conduct intelligent quality verification and testing on samples or preliminary batches provided by recommended suppliers before purchasing decisions are made. The product quality verification and testing module transmits the quality verification and testing results to the purchase order and quality standard docking module and the supplier management and evaluation module; Purchase order and quality standard docking module: responsible for automatically matching suppliers through intelligent matching algorithms based on big data analysis technology, according to procurement needs and historical data, and intelligently docking purchase orders with product quality standards. The purchase order and quality standard docking transmits the procurement standards to the real-time quality monitoring and tracking module; Real-time quality monitoring and tracking module: responsible for using Internet of Things technology and big data analysis to monitor the production, transportation and storage of materials in real time, and set up quality abnormality alarms. The real-time quality monitoring and tracking module transmits the monitoring results to the acceptance and rework management module; Acceptance and rework management module: responsible for the acceptance of qualified materials and initiating the rework or return process for unqualified materials. The acceptance and rework management module feeds back the material acceptance status to the supplier management and evaluation module.

2. A material procurement management system according to claim 1, characterized in that: The supplier management and evaluation module includes an intelligent evaluation unit, a supplier grading management unit, a risk assessment and early warning unit, a supplier information management unit and a supplier cooperation record unit. The intelligent evaluation unit performs dynamic evaluation on suppliers. The supplier grading management unit divides suppliers into different grades according to the output results of the intelligent evaluation unit and formulates corresponding management strategies. The risk assessment and early warning unit establishes a supplier risk assessment model to predict and warn of potential risks. When certain key indicators of the supplier are abnormal, the early warning mechanism is automatically triggered. The supplier information management unit is responsible for the entry, update and maintenance of the basic information of the supplier. The supplier cooperation record unit records the cooperation history with the supplier.

3. A material procurement management system according to claim 1, characterized in that: The product quality verification and inspection module includes a quality standard definition unit, a sample collection and management unit, a physical test and performance test unit, a test data analysis and report generation unit, a pass and fail judgment unit, and a quality feedback and communication unit. The quality standard definition unit is responsible for defining the quality standards of purchased materials according to the production needs of the enterprise and product characteristics. The sample collection and management unit is responsible for collecting samples from recommended suppliers and managing the sample warehousing and storage information. The physical test and performance test unit is responsible for performing physical tests on samples as well as functional and performance tests. The test data analysis and report generation unit is responsible for performing data analysis on the test results and generating a test report. The pass and fail judgment unit is responsible for judging whether the sample is qualified according to the quality standards and test results. The quality feedback and communication unit is responsible for feeding back the test results to the supplier management and evaluation module and notifying the purchaser.

4. A material procurement management system according to claim 1, characterized in that: The purchase order and quality standard docking module includes a purchase demand analysis unit, a quality standard matching unit, a purchase order generation and quality requirement binding unit, an intelligent supplier recommendation unit and a quality monitoring standard transmission unit. The purchase demand analysis unit is responsible for analyzing and defining purchase requirements according to the specific purpose, production requirements and quality standards of the purchased materials. The quality standard matching unit is responsible for matching product quality requirements according to purchase requirements and quality standards. The purchase order generation and quality requirement binding unit is responsible for generating purchase orders and binding the quality standards related to the order. The intelligent supplier recommendation unit is responsible for recommending suppliers based on the purchase order, quality requirement analysis and the evaluation results of the supplier management and evaluation module. The quality monitoring standard transmission unit is responsible for transmitting the purchase standards and quality requirements to the real-time quality monitoring and tracking module.

5. A material procurement management system according to claim 1, characterized in that: The real-time quality monitoring and tracking module includes a production process monitoring unit, a transportation process monitoring unit, a warehousing process monitoring unit, a quality anomaly alarm and response unit, a data analysis and report generation unit, and a monitoring result feedback unit. The production process monitoring unit is responsible for real-time monitoring of various quality indicators in the supplier's production process, the transportation process monitoring unit is responsible for monitoring the quality of materials during transportation, and the warehousing process monitoring unit is responsible for monitoring the quality of materials in the warehousing link. The quality anomaly alarm and response unit is responsible for immediately issuing an alarm and notifying relevant responsible personnel when quality anomalies or non-compliance with requirements are found during monitoring. The monitoring result feedback unit is responsible for timely feedback of real-time monitoring results to the acceptance and rework management module.

6. A material procurement management system according to claim 1, characterized in that: The acceptance and rework management module includes a material acceptance unit, a quality anomaly detection and feedback unit, a rework and return process management unit, a supplier feedback and collaboration unit, and a quality report and analysis unit. The material acceptance unit is responsible for acceptance inspection of the received purchased materials. The quality anomaly detection and feedback unit is responsible for detection and analysis of unqualified materials, determining the type of quality problems, and feeding back relevant anomalies to the supplier management and evaluation module. The rework and return process management unit is responsible for initiating the rework or return process after unqualified materials are found during the acceptance process, and supervising the execution of related processes. The supplier feedback and collaboration unit is responsible for feeding back the acceptance results, rework or return processing results to the supplier, and collaborating with the supplier to improve the quality of materials. The quality report and analysis unit is responsible for generating quality reports.

7. A material procurement management system according to claim 2, characterized in that: The specific process of the intelligent evaluation unit dynamically evaluating the supplier is as follows: Data collection and processing: Collect supplier financial data, historical cooperation records, product quality data, structured data, and social media data, industry news unstructured data; Feature selection and extraction: Extracting features that have important influence on supplier evaluation from the collected data; Model training and validation: Use neural network training to evaluate the model, and use the validation set to verify the performance of the model; Evaluation and feedback: Apply the trained model to newly collected supplier data, conduct dynamic evaluation, and adjust management strategies based on the evaluation results.

8. A material procurement management system according to claim 2, characterized in that: The risk assessment and early warning unit establishes a supplier risk assessment model to predict and warn of potential risks. The specific steps are as follows: Risk assessment model establishment: Use random forest to establish a supplier risk assessment model; Early warning mechanism setting: set early warning thresholds, and trigger the early warning mechanism when certain key indicators of suppliers are abnormal; Development of response measures: Develop response measures based on the early warning results.

9. A material procurement management system according to claim 5, characterized in that: When the quality abnormality alarm and response unit finds quality abnormality or non-compliance with requirements during monitoring, the specific steps of immediately issuing an alarm are: Collect various quality data in real time, set various quality index thresholds according to the quality standards of purchased materials and historical data, and set the thresholds as: X min ≤X≤X max , where X represents the quality index value, X min and X max Represent the lowest and highest acceptable values ​​of the indicator respectively; The data collected in real time is compared with the set threshold. When the data exceeds the threshold range, it is judged as quality abnormality and the system immediately triggers the alarm mechanism.

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