Enterprise production procurement management system and method based on ai technology

Abstract

The application relates to the technical field of production procurement management, and discloses an enterprise production procurement management system and method based on AI technology, which comprises a procurement data acquisition module, a data integration module, an intelligent analysis module, an intelligent grading module, a decision optimization module and a blockchain storage module; the system automatically generates procurement data based on a production plan and collects market dynamics in real time, greatly reduces manual intervention, and accelerates response speed; multi-source data is integrated to generate evaluation indexes, real-time business analysis is provided, strategic decision-making is assisted, and supply chain transparency is improved; indexes are constructed, optimal procurement schemes and alternative schemes are generated through grading results, cost / risk comparison analysis of multiple schemes is provided, a supplier is selected for an enterprise, and supply chain risks are dynamically avoided; a unique hash code is generated for materials, a specification model is bound, and a substitute material relationship is bound, whole-link tamper-proof tracing is realized, and data integrity and transparency are ensured.

Description

Technical Field

[0001] This invention relates to the field of production and procurement management technology, and more specifically to an enterprise production and procurement management system and method based on AI technology. Background Technology

[0002] Since the 1990s, economic globalization has accelerated, enterprises have continued to expand their production scale, and the cross-regional nature of material demand has increased.

[0003] Traditional enterprise production and procurement management involves departments submitting purchase requisitions specifying the name, specifications, quantity, and purpose of the items. These requisitions are then approved at various levels, from department managers to the general manager, with higher-value purchases requiring higher approval levels. Urgent purchases require special marking and simplified procedures. Procurement staff must compare at least three suppliers, comprehensively evaluating quality, price, and delivery time. Bulk materials are handled through bidding or competitive negotiation models such as open price inquiries or sealed bids. Purchase orders require approval before a contract is signed, clearly defining pricing, payment terms, and penalties for breach of contract. However, this system has the following drawbacks:

[0004] Procurement relies on manual price inquiries, comparisons, and order tracking. It depends on human experience and is easily affected by subjective factors. The process is cumbersome and has a high error rate, which leads to a longer procurement cycle.

[0005] Lacking accurate data support, manual price comparison is inefficient and has limited coverage, making it difficult to optimize supplier selection and negotiation, resulting in high procurement costs.

[0006] Historical systems often use decentralized databases, making it difficult to integrate supplier, inventory, and market data, thus failing to form a unified basis for decision-making and lacking risk control for risks such as supplier stability and contract performance.

[0007] Records of material procurement, logistics, and acceptance, whether kept on paper or in simple electronic form, are easily tampered with, making material traceability difficult.

[0008] Therefore, efficient, optimized decision-making, risk control, and data security methods are needed to solve the above problems. Summary of the Invention

[0009] In order to overcome the above-mentioned defects of the prior art, the present invention provides an enterprise production and procurement management system and method based on AI technology to solve the problems existing in the background art.

[0010] To achieve the above objectives, the present invention provides the following technical solution: an enterprise production and procurement management system based on AI technology, specifically comprising:

[0011] Procurement data acquisition module: Used to generate material procurement data based on production plans, and to collect relevant supplier data and market dynamic data for related materials;

[0012] Data integration module: used to clean, process and integrate the collected data to generate procurement management-related indicators and supplier management-related indicators;

[0013] Intelligent Analysis Module: Used to generate a procurement demand index based on procurement management-related indicators and a supplier index based on supplier management-related indicators;

[0014] Intelligent grading module: used to set dynamic thresholds for the procurement demand index and supplier index and perform intelligent grading;

[0015] Decision optimization module: Used to generate the optimal procurement plan based on the classification results, and provide cost / risk comparison of multiple plans;

[0016] Blockchain evidence storage module: used to generate unique codes for materials, bind specifications and models, unit substitute material relationship data, and ensure full-process traceability and immutability.

[0017] The AI-based enterprise production and procurement management method includes the following steps:

[0018] S1. Automatically generate material procurement data based on the production plan, and collect relevant historical transaction data of suppliers and market dynamic data of materials in real time;

[0019] S2. Use tools to clean and integrate the collected multi-source data to generate procurement management evaluation indicators and supplier management evaluation indicators.

[0020] S3. Using short hair, construct a procurement demand index based on relevant indicators of procurement management evaluation, and construct a supplier index based on relevant indicators of supplier management evaluation.

[0021] S4. Intelligent classification of procurement demand index and supplier index based on adaptive dynamic threshold;

[0022] S5. Generate the optimal procurement plan and alternative plans based on the intelligent classification results, and provide cost / risk comparison of multiple plans;

[0023] S6. Generate a unique hash code with a timestamp for the required materials, record the material specifications and model, substitute material relationships, and ensure traceability and immutability throughout the entire process of procurement, logistics and acceptance.

[0024] This AI-driven enterprise production and procurement management system achieves intelligent management across the entire process through six modules: the procurement data acquisition module integrates production plans and market dynamics data; the data integration module uses tools to clean multi-source data and generate management indicators; the intelligent analysis module uses algorithms to build procurement demand indices and supplier evaluation models; the intelligent grading module automatically classifies resources through dynamic thresholds; the decision optimization module provides cost and risk comparisons of multiple options; and the blockchain evidence storage module ensures traceability and tamper-proofing throughout the entire process. The system implementation steps cover a complete closed loop from data acquisition, indicator construction, intelligent grading to blockchain evidence storage, ultimately outputting the optimal procurement solution and achieving digital control of the entire supply chain.

[0025] The technical effects and advantages of this invention are as follows:

[0026] 1. The system of this invention automatically generates procurement data based on production plans and collects market dynamics in real time, greatly reducing manual intervention and speeding up response time;

[0027] 2. This invention integrates multi-source data to generate evaluation indicators, provides real-time business analysis, assists in strategic decision-making, improves supply chain transparency, and facilitates negotiation to reduce costs;

[0028] 3. This invention constructs an index and generates the optimal procurement plan and alternative plans through the hierarchical results, providing cost / risk comparison analysis of multiple plans to help enterprises select suppliers and dynamically avoid supply chain risks;

[0029] 4. This invention generates a unique hash code for each material, binding it to specifications and substitute materials, enabling tamper-proof traceability throughout the entire procurement, logistics, and acceptance process, and ensuring data integrity and transparency. Attached Figure Description

[0030] Figure 1 This is a structural block diagram of the present invention.

[0031] Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0032] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The automatic unloading device for rotary kiln with self-cooling function involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] Reference Figure 1This invention provides an enterprise production and procurement management system and method based on AI technology, including a procurement data acquisition module, a data integration module, an intelligent analysis module, an intelligent grading module, a decision optimization module, and a blockchain storage module.

[0034] Reference Figure 2 The specific implementation steps of the present invention include the following steps:

[0035] S1. Automatically generate material procurement data based on the production plan, and collect relevant historical transaction data of suppliers and market dynamic data of materials in real time;

[0036] It should be noted that the procurement data collection process is as follows:

[0037] Based on the production plan, the types and quantities of materials are identified, a purchase list is generated, and the urgency level is dynamically determined and the purchase quantity is adjusted in conjunction with the inventory level.

[0038] Connect with suppliers and material trading platforms to capture supplier and market supply capacity, historical price data, delivery data, and quality data for each type of purchased material.

[0039] S2. Use tools to clean and integrate the collected multi-source data to generate procurement management evaluation indicators and supplier management evaluation indicators.

[0040] It should be noted that the procurement management-related indicators include the procurement demand index and the supply stability index.

[0041] It should be noted that the procurement demand index reflects the urgency of a company's current procurement needs for a certain material, and is specifically calculated as a weighted average of the demand intensity coefficient and the time pressure coefficient.

[0042] It should be explained that the demand intensity coefficient = (current month's demand quantity / annual average monthly demand quantity) * urgency coefficient; where the current month's demand quantity is the quantity of the material planned for production in the current month, and the annual average monthly demand quantity is the average monthly consumption or demand quantity of the material in the past year. The ratio of the two measures the relative size of the current demand quantity to the historical level. The larger the ratio, the greater the demand quantity in the current month is compared to the normal level, and the greater the procurement pressure will be.

[0043] The urgency coefficient quantifies the non-negotiable nature of the demand time. It is set according to the actual situation and reflects the urgency of the demand. The coefficient for regular demands with buffer time is 1.0, indicating no additional pressure. The coefficient for urgent orders that need to be processed quickly is set to 1.5, doubling the pressure. The coefficient for extremely urgent orders that cannot be delayed is set to 2.0, giving them the maximum pressure weight.

[0044] The demand intensity coefficient comprehensively reflects the growth rate of material consumption and the urgency of demand. It is the core driving force of the procurement demand index and has the highest weight, with a value range of 0.55-0.6.

[0045] It needs to be explained that the time pressure coefficient = standard delivery time / remaining delivery time; where the standard delivery period is the normal time required for the supplier to complete the production and transportation of the material under normal circumstances, that is, the time from the signing of the order to the receipt of the goods; the remaining delivery time is the remaining available time from the current time until the material must be delivered to meet the production plan; the ratio of the two measures the time urgency. When the remaining time is less than the standard delivery time, that is, when the ratio is >1, it indicates that the time window has been compressed, and the procurement faces greater pressure to coordinate expedited processing, such as asking the supplier to insert orders, paying expedited fees, finding spot goods, and air freight to solve the problem. The larger the ratio, the greater the time pressure.

[0046] The time pressure coefficient quantifies the tightness of the time window. Even if the demand is not large or not particularly urgent, if the time left for procurement execution is seriously insufficient, this coefficient will significantly increase the procurement demand index, forcing procurement to take priority. The weight is between 0.4 and 0.45.

[0047] It should be noted that the supply stability index reflects the supplier's delivery timeliness, quality control, and price fluctuations during the material supply process. Specifically, it is a weighted calculation of the delivery reliability coefficient, quality stability coefficient, and price stability coefficient.

[0048] It should be explained that the delivery reliability coefficient = on-time delivery batches / total procurement batches; the on-time delivery batches are the number of times a certain material has been delivered on time in the past year, which measures the on-time delivery capability of this material. The higher the value, the more reliable the delivery of this material.

[0049] The delivery reliability coefficient is directly related to the execution of the production plan and is given the highest weight, with a weight value ranging from 0.45 to 0.5.

[0050] It should be explained that the quality stability coefficient = qualified batches / total delivered batches; qualified batches are the batches that meet the quality standards among the total batches delivered for this type of material in the past year, reflecting the stability of the material's quality compliance.

[0051] A low quality stability coefficient carries risks of returns, rework, or safety issues. A continuous decline in the pass rate of multiple batches can lead to reduced supply stability. The weight is between 0.3 and 0.35.

[0052] It should be explained that the price stability coefficient is specifically:

[0053] ;

[0054] Where W is the price stability coefficient and B is the price volatility. Price volatility = |current quote - historical average price| / historical average price. The current quote is the latest valid quote obtained from the target supplier for this demand; the historical average price is the average purchase price of the material over the past year. This ratio measures the magnitude of change in the current market price relative to the historical purchase cost. The larger the ratio, whether it is rising or falling, the more volatile the market price is, and the higher the cost uncertainty of this purchase. The smaller the price volatility, the larger the price stability coefficient, indicating that the price is more stable.

[0055] The price stability coefficient assesses the impact of market price fluctuations on the complexity and risk of the current round of procurement decisions. High volatility means that procurement requires more effort in cost analysis and risk management, such as whether to lock in prices, whether to purchase in batches, and whether to seek alternatives. Its weight on the supply stability index is between 0.25 and 0.3.

[0056] It should be noted that the supplier management-related indicators include supply capacity coefficient, price coefficient, on-time delivery rate, quality pass rate, and after-sales response coefficient.

[0057] The supply capacity coefficient is the ratio of the supplier's maximum monthly supply to the enterprise's demand, reflecting the supplier's capacity elasticity. A ratio ≥ 1.5 is a perfect score of 1 point, preventing over-reliance on a single supplier from causing supply disruptions. The score decreases as the ratio decreases, with a minimum of 0 points.

[0058] Price deviation coefficient = 1 - |quoted price - average price| / average price. It reflects the degree of deviation between the supplier's quotation and the industry average price, and reflects the reasonableness of the supplier's price. The supplier's quotation equals the market average price and gets full marks of 1 point. If the deviation is greater than 10%, deduct 0.2 points, and decrease proportionally. If the deviation is greater than 30%, get 0 points.

[0059] On-time delivery rate is the percentage of on-time delivered batches out of the total number of delivered batches. It is used to assess supply chain reliability and is expressed as a percentage.

[0060] The quality pass rate is the proportion of batches that pass the random inspection out of the total delivered batches. It monitors the quality stability of the supplier's supply. In order to ensure the timeliness of the quality pass rate, the batches in the most recent 3 months are used for calculation.

[0061] The after-sales response coefficient is calculated based on the average time to resolve after-sales issues. A full score of 1 point is awarded for a response within 1 hour, 0.8 points for a resolution within 24 hours, 0.6 points for a resolution within 48 hours, 0.4 points for a resolution within 72 hours, 0.2 points for a resolution within 120 hours, and 0 points for a resolution exceeding 120 hours.

[0062] S3. Using short hair, construct a procurement demand index based on relevant indicators of procurement management evaluation, and construct a supplier index based on relevant indicators of supplier management evaluation.

[0063] It should be noted that the procurement priority index is as follows:

[0064] ;

[0065] C represents the procurement priority index, reflecting the priority of material procurement.

[0066] X is the procurement demand index, reflecting the urgency of procurement needs. When X≤1, the function outputs 0; when X>1, the index calculation is initiated. X>1 indicates urgent demand, and the larger X is, the greater the procurement demand. k is the sensitivity coefficient, determined based on the type of material and the company's risk preference. The larger the k value, the faster the output value increases when X>1, and the more sensitive it is to changes in demand. The smaller the k value, the slower the output growth. e is the natural constant, which performs exponential decay transformation to map the infinite range of X>1 to the range of 0-1.

[0067] W is the price stability index. 1-W converts the positive indicator of W (the larger the W, the more stable it is) into a negative indicator, and the higher the 1-W, the less stable it is, so that it is consistent with the direction of the purchasing demand index.

[0068] It should be noted that the supplier index is as follows:

[0069] ;

[0070] G stands for Supplier Priority Index, which assesses the overall performance of suppliers to provide enterprises with tiered supplier management and optimize procurement strategies.

[0071] H is the supply capacity coefficient, which measures a supplier's ability to meet demand. Supply disruptions can lead to production line shutdowns or inventory crises, therefore it must be prioritized and given the highest weight. The weight ω1 ranges from 0.25 to 0.3.

[0072] J is the price deviation coefficient. Price fluctuations directly affect procurement costs, but simply having a low price can lead to poor quality or delivery risks. To ensure the objectivity of the price impact, the weight ω2 is set between 0.2 and 0.25.

[0073] Z represents the on-time delivery rate, which directly determines the efficiency of production plan execution. A delivery rate below a certain threshold triggers the risk of line stoppage. The weighting emphasizes the irreplaceable nature of time reliability, placing it alongside supply capacity as the highest weighting factor. The weight ω3 ranges from 0.25 to 0.3.

[0074] L represents the quality pass rate. Quality problems can lead to returns, rework, or customer complaints, and the costs far outweigh the price savings. It has a slightly lower weight than the on-time delivery rate. Quality problems can be mitigated through inspection. The weight ω4 is set between 0.2 and 0.25.

[0075] S is the after-sales response coefficient, which is a supportive dimension and does not directly affect core operations. It has the lowest weight, and the weight ω5 is set between 0.05 and 0.1.

[0076] S4. Intelligent classification of procurement demand index and supplier index based on adaptive dynamic threshold;

[0077] It should be specifically noted that the procurement priority index is categorized as follows:

[0078] When x1≤C≤1, it is a first-order priority;

[0079] When x2≤C<x1, it is a second-order priority;

[0080] When 0 ≤ C < x2, it is a third-level priority;

[0081] The value of x1 is between 0.8 and 0.85; the value of x2 is between 0.6 and 0.65.

[0082] It should be specifically noted that the supplier index is categorized as follows:

[0083] When G > y1, it is a Class S supplier;

[0084] When y2≤G<y1, it is a Class A supplier;

[0085] When y3≤G<y2, it is a Class B supplier;

[0086] When G < y3, it is a Class C supplier;

[0087] The values ​​of y1 range from 0.9 to 0.95; the values ​​of y2 range from 0.8 to 0.85; and the values ​​of y3 range from 0.65 to 0.7.

[0088] S5. Generate the optimal procurement plan and alternative plans based on the intelligent classification results, and provide cost / risk comparison of multiple plans;

[0089] It should be specifically noted that for Tier 1 priority materials, a high level of protection is required. A bidding-free strategy will be adopted, with priority given to directly contracting with S-level suppliers and using strategic reserve funds for priority payment.

[0090] Sign long-term agreements with price lock-in clauses and high penalty agreements for breach of contract, accounting for at least 30% of the order amount; allow a cost premium of ≤15% and prepay 50% of the payment; and require suppliers to register and purchase supply chain disruption insurance in order to avoid risks.

[0091] For Grade A suppliers, a time-limited negotiation strategy will be adopted, with a time limit of 48 to 72 hours, and at least one alternative supplier will be introduced;

[0092] A tiered pricing agreement is signed, with prices linked to purchase volume. Quality breach penalties are 20% of the goods' value, and daily penalties are imposed for delivery delays. Costs are controlled within a 10% premium, and installment payment methods are adopted. To avoid risks, bank guarantees and third-party quality inspections are required.

[0093] It should be noted that for secondary priority materials, it is necessary to balance risks and costs, implement a quarterly procurement strategy for A-level suppliers, and review prices monthly.

[0094] Sign agreements for advance payment discounts and bulk discounts to achieve cost savings of 8% to 10%, and adopt a dual-source supply strategy to ensure inventory safety.

[0095] For Class B suppliers, select more than three suppliers and adopt a dynamic bidding strategy, carry out delivery and acceptance in batches, and implement a performance bond system.

[0096] Sign quality traceability clauses, with a security deposit of 15% of the total contract amount, and a replacement response time of ≤24 hours for substandard quality; cost reduction target of 10% to 12%, with settlement based on the quantity of qualified products; and adopt on-site supervision and credit rating strategies.

[0097] It should be specifically noted that for Tier 3 priority materials, cost priority is required, reverse auction procurement is selected for Tier B suppliers, an annual centralized procurement agreement is signed, and performance points are used to reward suppliers.

[0098] Sign long-term price lock-in clauses, aim for a 15% cost reduction, and share logistics costs; adopt an on-demand procurement strategy.

[0099] For C-level suppliers, we select spot market procurement, with a 3-month trial period and mandatory rotation; we sign cash-on-delivery agreements, with returns and exchanges for quality issues, and no prepayment agreements; we aim to reach the lowest market transaction price, with freight collect; we adopt a supplier blacklist system and conduct 100% inspection of materials upon arrival.

[0100] S6. Generate a unique hash code with a timestamp for the required materials, record the material specifications and model, substitute material relationships, and ensure traceability and immutability throughout the entire process of procurement, logistics and acceptance.

[0101] A hash algorithm is used to generate a unique timestamped code for each batch of materials, which is then bound to the specifications, production batch, and alternative material relationship table, as well as the priority of the alternative materials.

[0102] During the procurement process, the procurement contract terms and the hash values ​​of the supplier qualification documents are stored on the blockchain to ensure that the contract cannot be tampered with.

[0103] In the logistics process, the shipment, transit, and arrival of goods at each logistics node are recorded into the blockchain in real time.

[0104] During the acceptance process, the quality inspection report and the warehouse receipt are linked to the blockchain code, and the handling records of non-conforming products are traceable throughout the entire process.

[0105] Using distributed ledger technology, the purchaser, supplier, and logistics provider jointly maintain the nodes, and any data modification requires consensus from more than 51% of the nodes.

[0106] Through the above description of the embodiments, those skilled in the art can clearly understand that the various embodiments of this application can be implemented by means of software or software combined with necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware functions. Based on this understanding, the technical solution of this application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions to cause a computer device, such as including but not limited to a personal computer, server, or network device, to execute all or part of the steps of the method described in any embodiment of this application.

[0107] The foregoing describes exemplary embodiments of this application. It should be understood that the above exemplary embodiments are not restrictive but illustrative, and the scope of protection of this application is not limited thereto. It should be understood that those skilled in the art can make modifications and variations to the embodiments of this application without departing from the spirit and scope of this application, and such modifications and variations should be within the scope of protection of this application.

Claims

1. An enterprise production and procurement management system based on AI technology, characterized in that, Specifically, it includes: Procurement data acquisition module: Used to generate material procurement data based on production plans, and to collect relevant supplier data and market dynamic data for related materials; Data integration module: used to clean, process and integrate the collected data to generate procurement management-related indicators and supplier management-related indicators; Intelligent Analysis Module: Used to generate a procurement priority index based on procurement management-related indicators and a supplier index based on supplier management-related indicators; Intelligent grading module: used to set dynamic thresholds for the procurement priority index and supplier index and perform intelligent grading; Decision optimization module: Used to generate the optimal procurement plan based on the hierarchical results, and provide cost / risk comparison of multiple plans; Blockchain evidence storage module: used to generate unique codes for materials, bind specifications and models, unit substitute material relationship data, and ensure full-process traceability and immutability; The procurement management-related indicators include the procurement demand index and the supply stability index; The supplier management-related indicators include supply capacity coefficient, price deviation coefficient, on-time delivery rate, quality pass rate, and after-sales response coefficient. The procurement demand index reflects the urgency of a company's current procurement needs for a certain material, and is specifically a weighted calculation of the demand intensity coefficient and the time pressure coefficient. The demand intensity coefficient = (current month's demand / average annual monthly demand) * urgency coefficient; The monthly demand is the quantity of the material planned for production in the current month, and the average monthly demand is the average monthly consumption or demand of the material over the past year. The urgency coefficient quantifies the time required for a single material. The coefficient is 1.0 for regular demand with a buffer time; 1.5 for urgent orders that need to be processed quickly; and 2.0 for extremely urgent orders that cannot be delayed. The time pressure coefficient is calculated as standard delivery time / remaining delivery time. When the remaining time is less than the standard delivery time, i.e., the ratio is greater than 1, the procurement department faces greater pressure to coordinate expedited processing. The larger the ratio, the greater the time pressure. The supply stability index reflects the supplier's delivery timeliness, quality control, and price fluctuations during the material supply process. It is a weighted calculation of the delivery reliability coefficient, quality stability coefficient, and price stability coefficient. Delivery reliability factor = On-time delivery batches / Total procurement batches; On-time delivery batches are the number of times this type of material was delivered on time in the past year; Quality stability factor = qualified batches / total delivered batches; qualified batches are the batches that meet the quality standards out of the total number of batches delivered for this type of material in the past year. The price stability coefficient is as follows: ; Where W is the price stability coefficient and B is the price volatility. Price volatility = |current inquiry - historical average price| / historical average price. The current inquiry is the latest valid quote obtained from the target supplier for this demand. The historical average price is the average purchase price of the material over the past year. The smaller the price volatility, the larger the price stability coefficient, indicating that the price is more stable. The procurement priority index is specifically as follows: ; Where C is the procurement priority index, X is the procurement demand index, X≤1 when the function outputs 0, X>1 when the index calculation is started; X>1 indicates urgent demand, the larger X is, the greater the procurement demand; k is the sensitivity coefficient, which is determined according to the type of material and the enterprise's risk preference. The larger the k value, the faster the output value grows when X>1, and the more sensitive it is to changes in demand; the smaller the k value, the slower the output growth; e is the natural constant, which realizes the exponential decay transformation to map the infinite range of X>1 to the range of 0-1; W is the price stability coefficient. 1-W converts the positive indicator W, which is more stable, into a negative indicator. The higher the 1-W, the less stable the price. The supplier index is specifically: ; G represents the supplier index, which assesses the overall performance of suppliers to provide enterprises with tiered supplier management and optimize procurement strategies. H is the supply capacity coefficient, J is the price deviation coefficient, Z is the on-time delivery rate, L is the quality pass rate, and S is the after-sales response coefficient. ω1-ω5 are the weights corresponding to the supply capacity coefficient, price deviation coefficient, on-time delivery rate, quality pass rate, and after-sales response coefficient, respectively. Among them, the value range of ω1 is 0.25-0.3, the value range of ω2 is 0.2-0.25, the value range of ω3 is 0.25-0.3, the value range of ω4 is 0.2-0.25, and the value range of ω5 is 0.05-0.

1.

2. The enterprise production and procurement management system based on AI technology according to claim 1, characterized in that: The supply capacity coefficient is the ratio of the supplier's maximum monthly supply to the enterprise's demand, reflecting the supplier's capacity elasticity. A ratio ≥ 1.5 is a full score of 1 point, and the score decreases as the ratio decreases, with a minimum of 0 points. The price deviation coefficient is calculated as 1 - |quoted price - average price| / average price. A supplier's quoted price equals the market average price, earning a full score of 1 point. A deviation greater than 10% deducts 0.2 points, decreasing proportionally. A deviation greater than 30% earns 0 points. The on-time delivery rate is the proportion of on-time delivered batches to the total number of delivered batches, expressed as a percentage. The quality pass rate is the proportion of batches that pass the random inspection to the total number of delivered batches, calculated using batches from the most recent three months. The after-sales response coefficient is calculated based on the average time to resolve after-sales issues. A full score of 1 point is awarded for a response within 1 hour, 0.8 points for a resolution within 24 hours, 0.6 points for a resolution within 48 hours, 0.4 points for a resolution within 72 hours, 0.2 points for a resolution within 120 hours, and 0 points for a resolution exceeding 120 hours.

3. An enterprise production and procurement management method based on AI technology, characterized by: The application of the AI-based enterprise production and procurement management system as described in any one of claims 1 to 2 specifically includes the following steps: S1. Automatically generate material procurement data based on the production plan, and collect relevant historical transaction data of suppliers and market dynamic data of materials in real time; S2. Use tools to clean and integrate the collected multi-source data to generate procurement management evaluation indicators and supplier management evaluation indicators. S3. Use algorithms to construct a procurement demand index based on relevant indicators of procurement management evaluation, and construct a supplier index based on relevant indicators of supplier management evaluation. S4. Intelligent classification of procurement priority index and supplier index based on adaptive dynamic threshold; S5. Generate the optimal procurement plan and alternative plans based on the intelligent classification results, and provide cost / risk comparison of multiple plans; S6. Generate a unique hash code with a timestamp for the required materials, record the material specifications and model, substitute material relationships, and ensure traceability and immutability throughout the entire process of procurement, logistics and acceptance.

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