College purchase performance supervision comprehensive management system and management method

Abstract

The invention discloses a university purchase performance supervision comprehensive management system and management method, and the system comprises a purchase plan management module which makes a purchase plan according to the actual demands of a university, and carries out the verification of the purchase plan; the purchase execution management module is used for issuing purchase information, inviting suppliers to participate in bidding, performing qualification auditing and reputation evaluation on the suppliers, recording and tracking a purchase negotiation process, and performing electronic signing and management on contracts; the performance acceptance management module is used for supervising performance conditions of suppliers and is responsible for recording and tracking an acceptance process; the performance supervision and evaluation module is used for carrying out regular evaluation on purchasing activities, forming a performance evaluation report, providing rectification measures for problems found in evaluation, and tracking rectification conditions; and the information query and statistics module is used for providing a function of querying related information of purchasing activities and carrying out statistics and analysis on the purchasing data.

Description

Technical Field

[0001] The present invention relates to the technical field of university procurement management, and in particular to a comprehensive management system and method for university procurement performance supervision. Background Art

[0002] Procurement plays a crucial role in university operations, directly impacting the smooth functioning of teaching, research, administration, and other aspects of a university's operations. With the rapid development of information technology and the continuous improvement of university management, the demand for procurement performance monitoring is becoming increasingly stringent. The introduction of a comprehensive management system for university procurement performance monitoring will promote the modernization and standardization of university procurement management, enhance university management and competitiveness, and lay a solid foundation for the university's long-term development.

[0003] Traditional methods often only focus on a certain link or aspect, resulting in a lack of systematic and comprehensive supervision of university procurement performance. Therefore, a comprehensive management system and management method for university procurement performance supervision is proposed. Summary of the Invention

[0004] The purpose of the present invention is to solve the problem in the prior art that traditional methods often only focus on a certain link or aspect, resulting in a lack of systematicity and comprehensiveness in the supervision of university procurement performance, and to propose a comprehensive management system and management method for university procurement performance supervision.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A comprehensive management system for university procurement performance supervision, including:

[0007] Procurement plan management module: formulates procurement plans based on the actual needs of colleges and universities, including information such as purchased items, quantities, and budgets, and reviews procurement plans to ensure their rationality and necessity. Execution is only possible after approval;

[0008] Procurement Execution Management Module: Publishes procurement information, invites suppliers to bid, conducts supplier qualification and credit assessment, ensures supplier reliability and compliance, records and tracks procurement negotiation processes, and electronically signs and manages contracts. The procurement plan developed by the Procurement Plan Management Module forms the foundation of the Procurement Execution Management Module.

[0009] Contract performance and acceptance management module: monitors suppliers' contract performance to ensure they provide products and services in accordance with contract requirements, records and tracks the acceptance process, and ensures the quality and quantity of purchased items meet contract requirements;

[0010] Performance Monitoring and Evaluation Module: This module regularly evaluates the efficiency, quality, and cost of procurement activities, generates performance evaluation reports, proposes corrective measures for issues identified during the evaluation, and tracks the progress of these corrective measures. The execution of procurement plans in the Procurement Plan Management Module will be included as part of the performance evaluation in the Performance Monitoring and Evaluation Module.

[0011] Information query and statistics module: provides relevant information query function for procurement activities, allowing users to understand procurement progress and results at any time, conduct statistics and analysis on procurement data, and provide support for decision-making.

[0012] The above technical solution further includes:

[0013] Furthermore, the procurement plan management module formulates a procurement plan based on the actual needs of the university, with the following specific steps:

[0014] Demand analysis: Using data analysis tools, we conduct a comprehensive analysis of the university's historical procurement data, inventory data, and the needs of various departments to predict future procurement needs, ensure that procurement plans meet the actual needs of the university, and avoid over- or under-purchasing;

[0015] Supplier screening: Through electronic procurement platforms or supplier management systems, potential suppliers are reviewed for qualifications, reputation assessments, and price comparisons to select suppliers with high cost-effectiveness and high-quality services, thereby reducing procurement costs and improving procurement efficiency.

[0016] Budgeting: Use financial management software or budgeting tools to develop a procurement budget based on the market price and quantity of the items being purchased, as well as the university's financial budget, to ensure that the procurement plan is economically feasible and avoids exceeding the budget;

[0017] Plan development: Use project management software or spreadsheet software to integrate purchase items, quantities, budgets, and suppliers into a purchasing plan to create a purchase list.

[0018] Furthermore, in demand analysis, data analysis tools are used to conduct a comprehensive analysis of the university's historical procurement data, inventory data, and the needs of various departments to predict future procurement needs. Specific steps include:

[0019] Data collection: Collect historical procurement data, inventory data, and demand data from the university's procurement system, inventory management system, and demand declarations from various departments;

[0020] Data cleaning: pre-processing the collected data, including removing duplicate data, processing missing values, correcting erroneous data, etc., to ensure the accuracy and completeness of the data;

[0021] Data visualization: Use charts (such as line charts, bar charts, pie charts, etc.) to show the distribution, trends, and correlations of data, and identify patterns and outliers in the data;

[0022] Statistical analysis: Use descriptive statistics (such as mean, standard deviation, maximum, minimum, etc.) and inferential statistics (such as hypothesis testing, analysis of variance, etc.) to analyze the characteristics and patterns of data;

[0023] Model training and validation: Use historical data to train time series analysis models;

[0024] Demand forecasting: Use the trained time series analysis model to predict future procurement demand and obtain forecast results;

[0025] Results analysis: Analyze the forecast results, including the evaluation of forecast errors, the interpretation of forecast results, and the impact of forecast results on procurement plans.

[0026] Furthermore, the procurement execution management module publishes procurement information, invites suppliers to bid, and conducts qualification review and credit assessment on suppliers. The specific steps are as follows:

[0027] Publishing procurement information: Procurement personnel fill in procurement information according to the procurement plan, including procurement items, quantity, budget, technical requirements, etc. The procurement execution management module publishes the procurement information to designated platforms or channels, such as university official websites, government procurement websites, industry procurement platforms, etc., to ensure the wide dissemination of information;

[0028] Invite suppliers to bid: The procurement execution management module automatically sends bidding invitations to qualified suppliers based on procurement information, including bidding deadlines, bidding methods, bidding requirements, etc. After receiving the invitations, suppliers prepare and submit bidding documents as required;

[0029] Supplier qualification review: The procurement execution management module collects supplier qualification documents, such as business licenses, tax registration certificates, and industry qualification certificates, and conducts a preliminary review. For suppliers whose qualifications do not meet the requirements, the procurement execution management module automatically excludes them and notifies them of the reasons for non-compliance.

[0030] Supplier reputation assessment: The procurement execution management module assesses the reputation of suppliers, including analyzing suppliers' historical cooperation data, customer reviews, industry reputation, etc. Based on the assessment results, suppliers are scored or graded to provide reference for procurement personnel;

[0031] Preliminary screening and evaluation: Based on qualification review and reputation assessment, the procurement execution management module uses artificial intelligence technology to further conduct preliminary screening and evaluation of suppliers, analyzing the suppliers' multi-dimensional information, such as the suppliers' product quality, delivery capabilities, and after-sales service. Based on the screening and evaluation results, the procurement execution management module provides procurement personnel with a list of high-quality supplier candidates, greatly shortening the time for procurement personnel to screen suppliers and improving selection efficiency and accuracy.

[0032] Furthermore, the procurement execution management module uses support vector machines to further perform preliminary screening and evaluation of suppliers, specifically in the following steps:

[0033] Collect data: extract multi-dimensional information of suppliers;

[0034] Data cleaning: remove duplicate, erroneous or missing data to ensure data accuracy and completeness;

[0035] Feature extraction: Based on screening and evaluation requirements, extract key features that reflect the supplier's product quality, delivery capabilities, and after-sales service;

[0036] Input data: The pre-processed key features and corresponding supplier labels are input into the support vector machine model;

[0037] Learning algorithm: The support vector machine model uses SMO to find the best separating hyperplane, the separating hyperplane is in the form of w T x + b = 0, where w is the weight vector, x is the input feature vector, and b is the bias term, so that samples of different categories are classified as correctly as possible. The SMO algorithm is an iterative algorithm for solving the dual problem of support vector machines. In each iteration, the SMO algorithm selects two Lagrange multipliers to update to maintain the KKT condition, which is expressed as:

[0038] Calculate the gradient of L(α): Calculate the Lagrangian function L(α) with respect to a i and a j The gradient of the Lagrangian function L(α) is defined as Among them, K(x i ,x j ) is the kernel function used to calculate the similarity between two samples, y i and y j Is the label of the sample, used to determine the category of the sample in the gradient calculation, about a i and a j The gradient of

[0039] Here λ is the inverse of the regularization parameter C, that is, λ = 1 / C;

[0040] Solve the quadratic programming problem: Simplify the problem into a quadratic programming problem to find the new a i and a j values, which will maximize L(α) under the constraints. The quadratic programming problem is expressed as

[0041] Among them, the elements of the B matrix, B ii , B jj , B ij Related to the kernel function and the label, c is a constant, solve this quadratic programming problem and get the new a i and a j The value of

[0042] Update a i and a j : Update a with the new value found by the solver i and a j , the updated value must satisfy the constraints of SVM, which are expressed as

[0043] Calculate the new value of b: Update a i and a j After that, a support vector is selected (i.e., a i or a j samples greater than 0) to calculate the new value of b, w T x + b = 0, where w is the weight vector, expressed as Select a support vector x s , so that a s >0, then b=-w T x s +y x Substitute the expression of w into the above formula to get the new value of b;

[0044] Check KKT conditions and check the updated a i 、a i Do a and b meet the KKT condition? If not, continue to iterate; if so, the algorithm converges and finds the optimal separating hyperplane.

[0045] Model evaluation: After training is complete, use the test dataset to evaluate the performance of the model;

[0046] Model prediction: Input the multi-dimensional information of a new supplier into the trained support vector machine model to obtain the probability or category of the supplier being a high-quality supplier;

[0047] Result analysis: Based on the model's prediction results, suppliers are preliminarily screened and evaluated to generate a shortlist of high-quality supplier candidates.

[0048] Furthermore, the performance acceptance management module monitors the supplier's performance and records and tracks the acceptance process. Specific steps:

[0049] Performance supervision preparation: After the procurement contract is signed, the contract terms are reviewed to clarify the specific products and services that the supplier should provide, the delivery time and quality standards. Based on the contract content, a performance supervision plan is formulated, including the time nodes, content and methods of supervision;

[0050] Real-time contract performance monitoring: Track suppliers' contract performance progress to ensure they deliver products and services according to the timeframe agreed in the contract. During the contract performance process, monitor the quality of products and services provided by suppliers, including on-site inspections and sample testing, to ensure they meet the quality standards agreed in the contract.

[0051] Acceptance preparation: formulate acceptance standards based on the contract content, including acceptance content, methods, time, etc.;

[0052] Acceptance Implementation: Inspect the products and services provided by suppliers according to the acceptance standards to ensure that the products and services meet the quality and quantity requirements stipulated in the contract. Record the acceptance process, including the time, location, participants, and results of the acceptance, and follow up on any issues found during the acceptance process.

[0053] Acceptance summary and feedback: Summarize the acceptance work, form an acceptance report, clarify the acceptance results and existing problems, feedback the acceptance results to the supplier, and require the supplier to rectify the existing problems to ensure that the final products and services provided meet the contract requirements

[0054] Furthermore, the performance acceptance management module uses artificial intelligence technology to intelligently identify and judge the acceptance process. The specific steps are:

[0055] Data collection: Extract all data related to acceptance, including procurement contracts, product and service information provided by suppliers, historical acceptance records, etc.

[0056] Data cleaning: remove duplicate, erroneous or irrelevant data to ensure data accuracy and completeness;

[0057] Feature extraction: Based on the acceptance requirements, key features that reflect the quality of products and services are extracted, such as product specifications, quantity, performance indicators, etc. Correlation analysis is used to evaluate the features that have a significant impact on the quality of products and services. The correlation analysis calculation formula is: Among them, r is the correlation coefficient, x i and y i are the observed values of the characteristic and product and service quality variables, and are the means of the two sets of data respectively. The correlation coefficient r ranges from -1 to 1. The larger the absolute value, the stronger the correlation between the two sets of data.

[0058] Intelligent Identification and Judgment: Image Recognition: For physical products undergoing acceptance, image recognition technology is used to photograph and identify the products, and then compared with the product images in the contract to confirm whether the product's appearance, specifications, etc. meet the requirements; Natural Language Processing: For service projects, natural language processing technology is used to parse and understand the service description and contract terms to determine whether the service is performed in accordance with the contract requirements;

[0059] Data analysis and prediction: Combining historical acceptance data with current data, neural networks are used to predict and evaluate the quality of products and services and identify potential quality issues.

[0060] Automatically generate acceptance report: Generate acceptance report based on the results of intelligent identification and judgment, including acceptance time, location, participants, acceptance results and other information;

[0061] Real-time tracking and feedback: Leveraging technologies such as the Internet of Things and sensors to track and monitor the use of products and services in real time, identify problems promptly, and provide feedback to suppliers and relevant management departments;

[0062] Problem identification: Based on the results of intelligent recognition and judgment, the system automatically identifies existing problems and non-conforming items, issues rectification notices to suppliers, and requires them to make rectifications within a specified time. The system also tracks and evaluates the suppliers’ rectifications to ensure that the problems are effectively resolved.

[0063] A management method for a comprehensive management system for university procurement performance supervision includes the following steps:

[0064] Procurement plan formulation and review: Based on actual needs, a procurement application is submitted. The procurement plan management module collects and analyzes the actual needs and determines key information such as the type, quantity, and budget of the purchased items. Based on the demand analysis results, the procurement plan management module formulates a procurement plan, including a list of purchased items, quantity, budget allocation, procurement time, etc. The procurement plan is submitted and reviewed to ensure the rationality of the plan and the feasibility of the budget. After passing the review, the procurement plan is approved by the school leader or designated person in charge;

[0065] Procurement Execution and Supplier Management: The procurement execution management module publishes procurement information, including purchased items, quantities, budgets, bid deadlines, etc., invites suppliers to bid, and conducts qualification reviews on participating suppliers, checking their business licenses, tax registration certificates, and other relevant documents. The procurement execution management module evaluates the supplier's credibility, understands their historical cooperation records, customer reviews, and other information, and ensures the supplier's reliability and compliance. The procurement execution management module conducts procurement negotiations with selected suppliers to reach consensus on key terms such as price, delivery time, and after-sales service. The procurement execution management module records and tracks the procurement negotiation process to ensure transparency and traceability, and signs electronic contracts to clarify the rights and obligations of both parties, facilitating subsequent management and execution.

[0066] Contract performance supervision and acceptance management: The contract performance acceptance management module monitors suppliers' contract performance in real time to ensure they provide products and services in accordance with contract requirements. It regularly checks suppliers' production progress and quality control to ensure that products meet the quality standards stipulated in the contract. After the supplier delivers products or services, the contract performance acceptance management module conducts acceptance work. The system records and tracks the acceptance process, including information such as the acceptance time, location, participants, and acceptance results. The contract performance acceptance management module ensures that the quality and quantity of purchased items meet contract requirements. If there are any discrepancies, the module promptly communicates with the supplier and properly handles them.

[0067] Performance evaluation and problem rectification: The performance monitoring and evaluation module regularly evaluates the efficiency, quality, and cost of procurement activities, collects and analyzes relevant data, and generates performance evaluation reports to provide reference and improvement directions for subsequent procurement activities. The module proposes corrective measures for problems identified during the evaluation, tracks the progress of rectification to ensure that problems are effectively resolved, and verifies and evaluates rectification results to ensure the effectiveness of corrective measures.

[0068] Information query and data statistics: The information query and statistics module provides relevant information query functions for procurement activities, allowing users to understand procurement progress, results, supplier information, etc. at any time. Users can enter keywords or select relevant conditions to query through the information query and statistics module to obtain the required information.

[0069] The present invention has the following beneficial effects:

[0070] In the present invention, the system covers the entire procurement process, including budget preparation, procurement execution, contract signing, goods acceptance, fund payment, etc., and realizes comprehensive supervision of procurement performance. Through automated and intelligent means, the system can realize real-time monitoring and data analysis of the procurement process, greatly improving the efficiency and accuracy of supervision. Through clear standards and processes, procurement behavior is standardized, human intervention and corruption are reduced, and the transparency of procurement is improved, which enhances public trust. Through this system, colleges and universities can arrange procurement plans and budgets more scientifically and reasonably, avoid waste of resources and duplicate purchases, and thus improve the efficiency of fund use. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 This is a system block diagram of a comprehensive management system for university procurement performance supervision proposed by the present invention;

[0072] Figure 2 The present invention provides a flow chart of a management method for a comprehensive management system for university procurement performance supervision. DETAILED DESCRIPTION

[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0074] See also Figure 1-Figure 2 As shown, the present invention is a comprehensive management system for university procurement performance supervision, including:

[0075] Procurement plan management module: formulates procurement plans based on the actual needs of colleges and universities, including information such as purchased items, quantities, and budgets, and reviews procurement plans to ensure their rationality and necessity. Execution is only possible after approval;

[0076] Procurement Execution Management Module: Publishes procurement information, invites suppliers to bid, conducts supplier qualification and credit assessment, ensures supplier reliability and compliance, records and tracks procurement negotiation processes, and electronically signs and manages contracts. The procurement plan developed by the Procurement Plan Management Module forms the foundation of the Procurement Execution Management Module.

[0077] Contract performance and acceptance management module: monitors suppliers' contract performance to ensure they provide products and services in accordance with contract requirements, records and tracks the acceptance process, and ensures the quality and quantity of purchased items meet contract requirements;

[0078] Performance Monitoring and Evaluation Module: This module regularly evaluates the efficiency, quality, and cost of procurement activities, generates performance evaluation reports, proposes corrective measures for issues identified during the evaluation, and tracks the progress of these corrective measures. The execution of procurement plans in the Procurement Plan Management Module will be included as part of the performance evaluation in the Performance Monitoring and Evaluation Module.

[0079] Information query and statistics module: provides relevant information query function for procurement activities, allowing users to understand procurement progress and results at any time, conduct statistics and analysis on procurement data, and provide support for decision-making.

[0080] In one embodiment, the procurement plan management module formulates a procurement plan based on the actual needs of the university, specifically the following steps:

[0081] Demand analysis: Using data analysis tools, we conduct a comprehensive analysis of the university's historical procurement data, inventory data, and the needs of various departments to predict future procurement needs, ensure that procurement plans meet the actual needs of the university, and avoid over- or under-purchasing;

[0082] Supplier screening: Through electronic procurement platforms or supplier management systems, potential suppliers are reviewed for qualifications, reputation assessments, and price comparisons to select suppliers with high cost-effectiveness and high-quality services, thereby reducing procurement costs and improving procurement efficiency.

[0083] Budgeting: Use financial management software or budgeting tools to develop a procurement budget based on the market price and quantity of the items being purchased, as well as the university's financial budget, to ensure that the procurement plan is economically feasible and avoids exceeding the budget;

[0084] Plan development: Use project management software or spreadsheet software to integrate purchase items, quantities, budgets, and suppliers into a purchasing plan to create a purchase list.

[0085] In one embodiment, in demand analysis, data analysis tools are used to comprehensively analyze the university's historical procurement data, inventory data, and the needs of various departments to predict future procurement needs. Specific steps include:

[0086] Data collection: Collect historical procurement data, inventory data, and demand data from the university's procurement system, inventory management system, and demand declarations from various departments;

[0087] Data cleaning: pre-processing the collected data, including removing duplicate data, processing missing values, correcting erroneous data, etc., to ensure the accuracy and completeness of the data;

[0088] Data visualization: Use charts (such as line charts, bar charts, pie charts, etc.) to show the distribution, trends, and correlations of data, and identify patterns and outliers in the data;

[0089] Statistical analysis: Use descriptive statistics (such as mean, standard deviation, maximum, minimum, etc.) and inferential statistics (such as hypothesis testing, analysis of variance, etc.) to analyze the characteristics and patterns of data;

[0090] Model training and validation: Use historical data to train time series analysis models;

[0091] Demand forecasting: Use the trained time series analysis model to predict future procurement demand and obtain forecast results;

[0092] Results analysis: Analyze the forecast results, including the evaluation of forecast errors, the interpretation of forecast results, and the impact of forecast results on procurement plans.

[0093] In one embodiment, the procurement execution management module publishes procurement information, invites suppliers to bid, and conducts qualification review and reputation assessment on suppliers. The specific steps are as follows:

[0094] Publishing procurement information: Procurement personnel fill in procurement information according to the procurement plan, including procurement items, quantity, budget, technical requirements, etc. The procurement execution management module publishes the procurement information to designated platforms or channels, such as university official websites, government procurement websites, industry procurement platforms, etc., to ensure the wide dissemination of information;

[0095] Invite suppliers to bid: The procurement execution management module automatically sends bidding invitations to qualified suppliers based on procurement information, including bidding deadlines, bidding methods, bidding requirements, etc. After receiving the invitations, suppliers prepare and submit bidding documents as required;

[0096] Supplier qualification review: The procurement execution management module collects supplier qualification documents, such as business licenses, tax registration certificates, and industry qualification certificates, and conducts a preliminary review. For suppliers whose qualifications do not meet the requirements, the procurement execution management module automatically excludes them and notifies them of the reasons for non-compliance.

[0097] Supplier reputation assessment: The procurement execution management module assesses the reputation of suppliers, including analyzing suppliers' historical cooperation data, customer reviews, industry reputation, etc. Based on the assessment results, suppliers are scored or graded to provide reference for procurement personnel;

[0098] Preliminary screening and evaluation: Based on qualification review and reputation assessment, the procurement execution management module uses artificial intelligence technology to further conduct preliminary screening and evaluation of suppliers, analyzing the suppliers' multi-dimensional information, such as the suppliers' product quality, delivery capabilities, and after-sales service. Based on the screening and evaluation results, the procurement execution management module provides procurement personnel with a list of high-quality supplier candidates, greatly shortening the time for procurement personnel to screen suppliers and improving selection efficiency and accuracy.

[0099] In one embodiment, the procurement execution management module further uses a support vector machine to perform preliminary screening and evaluation of suppliers, specifically the following steps:

[0100] Collect data: extract multi-dimensional information of suppliers;

[0101] Data cleaning: remove duplicate, erroneous or missing data to ensure data accuracy and completeness;

[0102] Feature extraction: Based on screening and evaluation requirements, extract key features that reflect the supplier's product quality, delivery capabilities, and after-sales service;

[0103] Input data: The pre-processed key features and corresponding supplier labels are input into the support vector machine model;

[0104] Learning algorithm: The support vector machine model uses SMO to find the best separating hyperplane, the separating hyperplane is in the form of w T x + b = 0, where w is the weight vector, x is the input feature vector, and b is the bias term, so that samples of different categories are classified as correctly as possible. The SMO algorithm is an iterative algorithm for solving the dual problem of support vector machines. In each iteration, the SMO algorithm selects two Lagrange multipliers to update to maintain the KKT condition, which is expressed as:

[0105] Calculate the gradient of L(α): Calculate the Lagrangian function L(α) with respect to a i and a j The gradient of the Lagrangian function L(α) is defined as Among them, K(x i ,x j ) is the kernel function used to calculate the similarity between two samples, y i and y j Is the label of the sample, used to determine the category of the sample in the gradient calculation, about a i and a j The gradient of

[0106] Here λ is the inverse of the regularization parameter C, that is, λ = 1 / C;

[0107] Solve the quadratic programming problem: Simplify the problem into a quadratic programming problem to find the new a i and a j values, which will maximize L(α) under the constraints. The quadratic programming problem is expressed as

[0108] Among them, the elements of the B matrix, B ii , B jj , B ij Related to the kernel function and the label, c is a constant, solve this quadratic programming problem and get the new a i and a j The value of

[0109] Update a i and a j : Update a with the new value found by the solver i and a j , the updated value must satisfy the constraints of SVM, which are expressed as

[0110] Calculate the new value of b: Update a i and a j After that, a support vector is selected (i.e., a i or a j samples greater than 0) to calculate the new value of b, w T x + b = 0, where w is the weight vector, expressed as Select a support vector x s , so that a s >0, then b=-w T x s +y x Substitute the expression of w into the above formula to get the new value of b;

[0111] Check KKT conditions and check the updated a i 、a i Do a and b meet the KKT condition? If not, continue to iterate; if so, the algorithm converges and finds the optimal separating hyperplane.

[0112] Model evaluation: After training is complete, use the test dataset to evaluate the performance of the model;

[0113] Model prediction: Input the multi-dimensional information of a new supplier into the trained support vector machine model to obtain the probability or category of the supplier being a high-quality supplier;

[0114] Result analysis: Based on the model's prediction results, suppliers are preliminarily screened and evaluated to generate a shortlist of high-quality supplier candidates.

[0115] In one embodiment, the contract performance acceptance management module monitors the supplier's contract performance and records and tracks the acceptance process. Specific steps include:

[0116] Performance supervision preparation: After the procurement contract is signed, the contract terms are reviewed to clarify the specific products and services that the supplier should provide, the delivery time and quality standards. Based on the contract content, a performance supervision plan is formulated, including the time nodes, content and methods of supervision;

[0117] Real-time contract performance monitoring: Track suppliers' contract performance progress to ensure they deliver products and services according to the timeframe agreed in the contract. During the contract performance process, monitor the quality of products and services provided by suppliers, including on-site inspections and sample testing, to ensure they meet the quality standards agreed in the contract.

[0118] Acceptance preparation: formulate acceptance standards based on the contract content, including acceptance content, methods, time, etc.;

[0119] Acceptance Implementation: Inspect the products and services provided by suppliers according to the acceptance standards to ensure that the products and services meet the quality and quantity requirements stipulated in the contract. Record the acceptance process, including the time, location, participants, and results of the acceptance, and follow up on any issues found during the acceptance process.

[0120] Acceptance summary and feedback: Summarize the acceptance work, form an acceptance report, clarify the acceptance results and existing problems, feedback the acceptance results to the supplier, and require the supplier to rectify the existing problems to ensure that the final products and services provided meet the contract requirements.

[0121] In one embodiment, the performance acceptance management module uses artificial intelligence technology to intelligently identify and judge the acceptance process. The specific steps are:

[0122] Data collection: Extract all data related to acceptance, including procurement contracts, product and service information provided by suppliers, historical acceptance records, etc.

[0123] Data cleaning: remove duplicate, erroneous or irrelevant data to ensure data accuracy and completeness;

[0124] Feature extraction: Based on the acceptance requirements, key features that reflect the quality of products and services are extracted, such as product specifications, quantity, performance indicators, etc. Correlation analysis is used to evaluate the features that have a significant impact on the quality of products and services. The correlation analysis calculation formula is: Among them, r is the correlation coefficient, x i and y i are the observed values of the characteristic and product and service quality variables, and are the means of the two sets of data respectively. The correlation coefficient r ranges from -1 to 1. The larger the absolute value, the stronger the correlation between the two sets of data.

[0125] Intelligent Identification and Judgment: Image Recognition: For physical products undergoing acceptance, image recognition technology is used to photograph and identify the products, and then compared with the product images in the contract to confirm whether the product's appearance, specifications, etc. meet the requirements; Natural Language Processing: For service projects, natural language processing technology is used to parse and understand the service description and contract terms to determine whether the service is performed in accordance with the contract requirements;

[0126] Data analysis and prediction: Combining historical acceptance data with current data, neural networks are used to predict and evaluate the quality of products and services and identify potential quality issues.

[0127] Automatically generate acceptance report: Generate acceptance report based on the results of intelligent identification and judgment, including acceptance time, location, participants, acceptance results and other information;

[0128] Real-time tracking and feedback: Leveraging technologies such as the Internet of Things and sensors to track and monitor the use of products and services in real time, identify problems promptly, and provide feedback to suppliers and relevant management departments;

[0129] Problem identification: Based on the results of intelligent recognition and judgment, the system automatically identifies existing problems and non-conforming items, issues rectification notices to suppliers, and requires them to make rectifications within a specified time. The system also tracks and evaluates the suppliers’ rectifications to ensure that the problems are effectively resolved.

[0130] A management method for a comprehensive management system for university procurement performance supervision includes the following steps:

[0131] Procurement plan formulation and review: Based on actual needs, a procurement application is submitted. The procurement plan management module collects and analyzes the actual needs and determines key information such as the type, quantity, and budget of the purchased items. Based on the demand analysis results, the procurement plan management module formulates a procurement plan, including a list of purchased items, quantity, budget allocation, procurement time, etc. The procurement plan is submitted and reviewed to ensure the rationality of the plan and the feasibility of the budget. After passing the review, the procurement plan is approved by the school leader or designated person in charge;

[0132] Procurement Execution and Supplier Management: The procurement execution management module publishes procurement information, including purchased items, quantities, budgets, bid deadlines, etc., invites suppliers to bid, and conducts qualification reviews on participating suppliers, checking their business licenses, tax registration certificates, and other relevant documents. The procurement execution management module evaluates the supplier's credibility, understands their historical cooperation records, customer reviews, and other information, and ensures the supplier's reliability and compliance. The procurement execution management module conducts procurement negotiations with selected suppliers to reach consensus on key terms such as price, delivery time, and after-sales service. The procurement execution management module records and tracks the procurement negotiation process to ensure transparency and traceability, and signs electronic contracts to clarify the rights and obligations of both parties, facilitating subsequent management and execution.

[0133] Contract performance supervision and acceptance management: The contract performance acceptance management module monitors suppliers' contract performance in real time to ensure they provide products and services in accordance with contract requirements. It regularly checks suppliers' production progress and quality control to ensure that products meet the quality standards stipulated in the contract. After the supplier delivers products or services, the contract performance acceptance management module conducts acceptance work. The system records and tracks the acceptance process, including information such as the acceptance time, location, participants, and acceptance results. The contract performance acceptance management module ensures that the quality and quantity of purchased items meet contract requirements. If there are any discrepancies, the module promptly communicates with the supplier and properly handles them.

[0134] Performance evaluation and problem rectification: The performance monitoring and evaluation module regularly evaluates the efficiency, quality, and cost of procurement activities, collects and analyzes relevant data, and generates performance evaluation reports to provide reference and improvement directions for subsequent procurement activities. The module proposes corrective measures for problems identified during the evaluation, tracks the progress of rectification to ensure that problems are effectively resolved, and verifies and evaluates rectification results to ensure the effectiveness of corrective measures.

[0135] Information query and data statistics: The information query and statistics module provides relevant information query functions for procurement activities, allowing users to understand procurement progress, results, supplier information, etc. at any time. Users can enter keywords or select relevant conditions to query through the information query and statistics module to obtain the required information.

[0136] While 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 these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A comprehensive management system for university procurement performance supervision, characterized by: include: Procurement plan management module: formulate procurement plans based on the actual needs of colleges and universities, and review procurement plans; Procurement Execution Management Module: Publishes procurement information, invites suppliers to bid, conducts supplier qualification and credit assessment, records and tracks the procurement negotiation process, and electronically signs and manages contracts. The procurement plan developed by the Procurement Plan Management Module is the foundation of the Procurement Execution Management Module. Contract performance and acceptance management module: monitors the supplier's contract performance and is responsible for recording and tracking the acceptance process; Performance Monitoring and Evaluation Module: This module regularly evaluates procurement activities, generates performance evaluation reports, proposes corrective measures for issues identified during the evaluation, and tracks the progress of these corrective measures. The execution of procurement plans in the Procurement Plan Management Module will be included as part of the performance evaluation in the Performance Monitoring and Evaluation Module. Information query and statistics module: provides relevant information query function for procurement activities, and conducts statistics and analysis on procurement data.

2. A comprehensive management system for university procurement performance supervision according to claim 1, characterized in that: The procurement plan management module formulates a procurement plan based on the actual needs of the university. The specific steps are: Demand analysis: Using data analysis tools, conduct a comprehensive analysis of the university's historical procurement data, inventory data, and the needs of various departments to predict future procurement needs; Supplier screening: Through electronic procurement platforms or supplier management systems, potential suppliers are reviewed for qualifications, reputation assessments, and price comparisons; Budgeting: Use financial management software or budgeting tools to develop a procurement budget based on the market price and quantity of the items being purchased and the university's financial budget; Plan development: Use project management software or spreadsheet software to integrate purchase items, quantities, budgets, and suppliers into a purchasing plan to create a purchase list.

3. The system for comprehensive supervision of procurement performance of universities according to claim 1 is characterized in that: In demand analysis, data analysis tools are used to comprehensively analyze the university's historical procurement data, inventory data, and the needs of various departments to predict future procurement needs. Specific steps include: Data collection: Collect historical procurement data, inventory data, and demand data from the university's procurement system, inventory management system, and demand declarations from various departments; Data cleaning: pre-processing the collected data; Data visualization: Use charts to show the distribution, trends, and correlations of data, and identify patterns and outliers in the data; Statistical analysis: Use descriptive and inferential statistics to analyze data characteristics and patterns; Model training and validation: Use historical data to train time series analysis models; Demand forecasting: Use the trained time series analysis model to predict future procurement demand and obtain forecast results; Results analysis: Analyze the forecast results, including the evaluation of forecast errors, the interpretation of forecast results, and the impact of forecast results on procurement plans.

4. The system for comprehensive supervision of procurement performance of universities according to claim 1 is characterized in that: The procurement execution management module publishes procurement information, invites suppliers to bid, and conducts qualification review and credit assessment on suppliers. The specific steps are: Release of procurement information: Procurement personnel fill in procurement information according to the procurement plan, and the procurement execution management module releases the procurement information to the designated platform or channel; Invite suppliers to bid: The procurement execution management module automatically sends bidding invitations to qualified suppliers based on procurement information. After receiving the invitations, the suppliers prepare and submit bidding documents as required. Supplier qualification review: The procurement execution management module collects supplier qualification documents and conducts a preliminary review. For suppliers whose qualifications do not meet the requirements, the procurement execution management module automatically excludes them and notifies them of the reasons for non-compliance. Supplier reputation evaluation: The procurement execution management module evaluates the reputation of suppliers and assigns scores or grades to suppliers based on the evaluation results; Preliminary screening and evaluation: Based on the qualification review and reputation assessment, the procurement execution management module uses artificial intelligence technology to further conduct preliminary screening and evaluation of suppliers, analyzing the suppliers' multi-dimensional information, such as the suppliers' product quality, delivery capabilities, and after-sales service. Based on the screening and evaluation results, the procurement execution management module provides procurement personnel with a list of supplier candidates.

5. A comprehensive management system for university procurement performance supervision according to claim 4, characterized in that: The procurement execution management module uses support vector machines to further perform preliminary screening and evaluation of suppliers. The specific steps are: Collect data: extract multi-dimensional information of suppliers; Data cleaning: removing duplicate, erroneous or missing data; Feature extraction: Based on screening and evaluation requirements, extract key features that reflect the supplier's product quality, delivery capabilities, and after-sales service; Input data: The pre-processed key features and corresponding supplier labels are input into the support vector machine model; Learning algorithm: The support vector machine model uses SMO to find the best separating hyperplane, the separating hyperplane is in the form of w T x + b = 0, where w is the weight vector, x is the input feature vector, and b is the bias term, so that samples of different categories are classified as correctly as possible. The SMO algorithm is an iterative algorithm for solving the dual problem of support vector machines. In each iteration, the SMO algorithm selects two Lagrange multipliers to update to maintain the KKT condition, which is expressed as: Calculate the gradient of L(α): Calculate the Lagrangian function L(α) with respect to a i and a j The gradient of the Lagrangian function L(α) is defined as Among them, K(x i ,x j ) is the kernel function used to calculate the similarity between two samples, y i and y j Is the label of the sample, used to determine the category of the sample in the gradient calculation, about a i and a j The gradient of Here λ is the inverse of the regularization parameter C, that is, λ = 1 / C; Solve the quadratic programming problem: Simplify the problem into a quadratic programming problem to find the new a i and a j values, which will maximize L(α) under the constraints. The quadratic programming problem is expressed as Among them, the elements of the B matrix, B ii , B jj , B ij Related to the kernel function and the label, c is a constant, solve this quadratic programming problem and get the new a i and a j The value of Update a i and a j : Update a with the new value found by the solver i and a j , the updated value must satisfy the constraints of SVM, which are expressed as Calculate the new value of b: Update a i and a j After that, a support vector is selected (i.e., a i or a j samples greater than 0) to calculate the new value of b, w T x + b = 0, where w is the weight vector, expressed as Select a support vector x s , so that a s >0, then b=-w T x s +y x Substitute the expression of w into the above formula to get the new value of b; Check KKT conditions and check the updated a i 、a i Do a and b meet the KKT condition? If not, continue to iterate; if so, the algorithm converges and finds the optimal separating hyperplane. Model evaluation: After training is complete, use the test dataset to evaluate the performance of the model; Model prediction: Input the multi-dimensional information of a new supplier into the trained support vector machine model to obtain the probability or category of the supplier being a high-quality supplier; Result analysis: Based on the model's prediction results, suppliers are preliminarily screened and evaluated to generate a shortlist of suppliers.

6. The system for comprehensive supervision of procurement performance of universities according to claim 1 is characterized in that: The performance acceptance management module monitors the supplier's performance and records and tracks the acceptance process. Specific steps: Contract performance supervision preparation: After the procurement contract is signed, the contract terms are reviewed to clarify the specific products and services that the supplier should provide, the delivery time and quality standards, and a contract performance supervision plan is developed based on the contract content; Real-time contract performance monitoring: Track suppliers' contract performance progress and monitor the quality of products and services provided by suppliers during the contract performance process; Acceptance preparation: formulate acceptance criteria according to the contract content; Acceptance implementation: In accordance with the acceptance standards, accept the products and services provided by the supplier, record the acceptance process, and track and handle any problems found during the acceptance; Acceptance summary and feedback: Summarize the acceptance work, form an acceptance report, clarify the acceptance results and existing problems, and feedback the acceptance results to the supplier.

7. A comprehensive management system for university procurement performance supervision according to claim 6, characterized in that: The performance acceptance management module uses artificial intelligence technology to intelligently identify and judge the acceptance process. The specific steps are: Data collection: extract all data related to acceptance; Data cleaning: remove duplicate, erroneous or irrelevant data; Feature extraction: Based on the acceptance requirements, key features that reflect the quality of products and services are extracted, and correlation analysis is used to evaluate the features that have a significant impact on the quality of products and services. The correlation analysis calculation formula is: Among them, r is the correlation coefficient, x i and y i are the observed values of the characteristic and product and service quality variables, and are the means of the two sets of data respectively. The correlation coefficient r ranges from -1 to 1. The larger the absolute value, the stronger the correlation between the two sets of data. Intelligent Identification and Judgment: Image Recognition: For physical products undergoing acceptance, image recognition technology is used to photograph and identify the products, and then compared with the product images in the contract to confirm whether they meet the requirements; Natural Language Processing: For service projects, natural language processing technology is used to parse and understand the service descriptions and contract terms to determine whether the services are performed in accordance with the contract requirements; Data analysis and prediction: Combining historical acceptance data with current data, neural networks are used to predict and evaluate the quality of products and services and identify potential quality issues. Automatically generate acceptance report: Generate acceptance report based on the results of intelligent identification and judgment; Real-time tracking and feedback: Real-time tracking and monitoring of product and service usage, timely identification of problems and feedback to suppliers and relevant management departments; Problem identification: Based on the results of intelligent recognition and judgment, the system automatically identifies existing problems and non-conforming items, issues rectification notices to suppliers, and tracks and evaluates the rectification status of suppliers.

8. The management method of a comprehensive management system for university procurement performance supervision according to claim 1 is characterized in that: The following steps are involved: Procurement plan formulation and review: Based on actual demand, a procurement application is submitted. The procurement plan management module collects and analyzes the actual demand, determines the key information of the purchased items, and formulates a procurement plan based on the demand analysis results. The procurement plan is submitted and reviewed; Procurement Execution and Supplier Management: The procurement execution management module publishes procurement information, invites suppliers to bid, conducts qualification review of bidding suppliers, and checks their relevant certificates. The procurement execution management module evaluates the credibility of suppliers, conducts procurement negotiations with selected suppliers, and records and tracks the procurement negotiation process. Contract performance supervision and acceptance management: The contract performance acceptance management module monitors the supplier's contract performance in real time. After the supplier delivers the product or service, the contract performance acceptance management module conducts acceptance work; Performance evaluation and problem rectification: The performance monitoring and evaluation module regularly evaluates procurement activities, collects and analyzes relevant data, and generates performance evaluation reports. The module also proposes corrective measures for any problems identified during the evaluation. Information query and data statistics: The information query and statistics module provides the function of querying relevant information of procurement activities. Users can enter keywords or select relevant conditions to query through the information query and statistics module to obtain the required information.

Images