Comprehensive supply chain control system

Abstract

The invention, which relates to the technical field of supply chain information, discloses a comprehensive supply chain control system comprising a transaction and collaborative service module, an order management and decision support module and a data interaction and integration module. The transaction and cooperation service module is used for processing transaction information of supply chain participants, ensuring information safety and accuracy, managing the full life cycle of a contract and performing real-time monitoring, establishing a real-time communication and cooperation project management channel, and improving cooperation efficiency; according to the invention, the transaction and collaborative service module has a significant effect, encryption processing ensures the security of transaction information, leakage and tampering are prevented, contract management is efficient and flexible, a multi-parameter evaluation optimization template reduces the default risk, a collaborative mechanism improves the collaborative efficiency of all parties, and the response speed of a supply chain is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of supply chain information technology, in particular to an integrated supply chain control system. Background Art

[0002] At present, the complexity of supply chain management continues to rise, and the core of corporate competition has shifted to supply chain competition. Traditional supply chain management systems lack data security and privacy protection in the processing of transaction information. When many participants transmit information, they face the risk of theft and tampering, which can easily lead to the leakage of business secrets and transaction disputes. In terms of contract management, there is a lack of standardized automation mechanisms, and drafting and revising are time-consuming and laborious. It is difficult to monitor the performance in real time, and the risk of breach of contract is high. In collaborative work, communication between various links is not smooth, tools are lacking, and information flow is blocked. For example, new product development projects often delay product launches and miss market opportunities due to insufficient collaboration;

[0003] There are many problems with order management in the existing system. The order processing process is not tracked in time and the information transmission is delayed. It is difficult for enterprises to grasp the progress in time and respond quickly to changes in customer demand, which affects customer satisfaction and generates additional costs. Inventory management lacks accurate decision-making capabilities. It is difficult to scientifically determine the replenishment quantity, safety stock and allocation strategy based on historical data, inventory levels and demand forecasts. Backlogs or out-of-stocks often occur, increasing costs or missing sales opportunities. The risk assessment and decision support system is imperfect. Enterprises find it difficult to identify various risks. There is a lack of quantitative assessment methods and response plans. They are passive in the face of risks and are prone to losses.

[0004] The information systems of the various parties involved in the supply chain are diverse, and the data formats and interface standards are not unified, which makes data interaction difficult, transmission compatibility is poor, and accuracy and timeliness cannot be guaranteed, which hinders the flow of information and makes it difficult for enterprises to obtain comprehensive and accurate data for sharing and collaboration. Data integration and cleaning lack effective means and processes, and there are a lot of duplications, errors and inconsistencies in the data, which affects the quality and availability and restricts analysis and mining work. The data analysis visualization ability is weak. Although a large amount of data has been accumulated, there is a lack of technical tools to deeply mine potential value information. The analysis results are complex and difficult to understand, which cannot help managers make decisions, resulting in a waste of data resources. There is an urgent need for innovative systems to solve problems and improve the competitiveness of the supply chain.

[0005] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0006] The purpose of the present invention is to solve the existing problems and to propose an integrated supply chain control system.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] An integrated supply chain control system, comprising:

[0009] The transaction and collaboration service module is used to process transaction information of supply chain participants, ensure information security and accuracy, manage the entire life cycle of contracts and monitor them in real time, and establish real-time communication and collaborative project management channels to improve collaboration efficiency;

[0010] Risk assessment and decision support: Identify and assess various risk factors that affect order fulfillment, including supplier supply disruption risk, logistics delay risk, and market demand fluctuation risk;

[0011] The data interaction and integration module is used to manage data interfaces to achieve efficient data interaction among all parties, integrate and clean data to improve quality, conduct in-depth analysis to mine potential valuable information and present it visually, and help managers make scientific decisions.

[0012] Furthermore, the specific process of the transaction and collaborative service module is as follows:

[0013] Transaction information processing: receiving and recording transaction information from suppliers, manufacturers, distributors, and retailers, including detailed data on the price, quantity, transaction time, and transaction location of products or services; at the same time, encrypting the transaction information to ensure the security and privacy of the information and prevent data leakage;

[0014] Contract management: used to generate, store, query and execute various supply chain contracts; automatically generate standard contract templates based on the negotiation results between different parties, covering procurement contracts, sales contracts, and logistics service contracts; when generating contract templates, generate several alternative contract templates at the same time, and select the contract template with the highest priority for use;

[0015] Collaborative work mechanism: Establish real-time communication channels between supply chain participants, including online instant messaging and video conferencing functions, so that all parties can negotiate and resolve problems in a timely manner during the transaction process, and provide collaborative project management functions so that all parties can jointly participate in the planning, execution and monitoring of supply chain projects, including joint new product development projects and promotional activities projects, to improve collaborative work efficiency.

[0016] Furthermore, the specific operation steps for encrypting the transaction information in the transaction and collaborative service module are as follows:

[0017] Collect transaction information from suppliers, manufacturers, distributors, and retailers, covering product or service prices, quantities, transaction times, and transaction locations; standardize the format of the collected information, including unified time formats and quantity units;

[0018] A symmetric encryption key is randomly generated for each transaction, and the symmetric encryption key is distributed to all parties involved in the transaction through a secure channel; the generated symmetric encryption key is used to encrypt the transaction information, converting the original plaintext information into ciphertext to ensure the confidentiality of the information during transmission and storage;

[0019] Generate a pair of asymmetric encryption keys and make the public key publicly available to supply chain participants; encrypt the symmetric encryption key using the recipient’s asymmetric encryption public key, and then transmit the encrypted symmetric encryption key along with the ciphertext transaction information to the recipient;

[0020] The receiver uses its own asymmetric encryption private key to decrypt and obtain the symmetric encryption key, and then uses the symmetric encryption key to decrypt the ciphertext transaction information to restore the original transaction information, thus achieving secure reception and use of the information;

[0021] Perform hash operation on transaction information to obtain a hash value of fixed length; store the hash value in the blockchain, and use the tamper-proof nature of the blockchain to further ensure the integrity and traceability of the transaction information.

[0022] Furthermore, the specific operation steps for selecting the highest priority contract template for use in the transaction and collaborative service module are as follows:

[0023] When generating a contract template, several alternative contract templates are generated at the same time. According to different types of supply chain contracts, multiple alternative contract templates are pre-designed, and each template contains general terms and adjustable terms;

[0024] Identify evaluation parameters for prioritizing contract templates, including:

[0025] The cost-related parameters are as follows:

[0026] Purchase cost or sales price: reflects the direct impact of the contract on the company's costs or revenues;

[0027] Logistics costs: involve transportation and warehousing costs, affecting the overall operating costs of the supply chain;

[0028] The risk related parameters are as follows:

[0029] Supplier risk: the probability of supplier interruption of supply and the financial stability of the supplier, quantified through historical data and ratings from credit assessment agencies;

[0030] Market risk: including market demand fluctuation risk and price fluctuation risk, which can be quantified using market trend analysis and historical sales data;

[0031] Legal risk: the degree of compliance of contract terms with laws and regulations, expressed as a value of 0-1;

[0032] The time-related parameters are as follows:

[0033] Lead time: the time from order placement to goods delivery;

[0034] Term of the contract;

[0035] The quality related parameters are as follows:

[0036] Product or service quality standards: quantified through quality inspection indicators and compliance with industry standards;

[0037] Logistics service quality: including cargo damage rate and on-time delivery rate;

[0038] Collect evaluation parameters from internal corporate databases, external market research agencies, and credit rating agencies; clean and organize the collected data, remove outliers and erroneous data, and ensure the accuracy and reliability of the data;

[0039] The analytic hierarchy process is used to determine the weight of each parameter in the contract template evaluation; for each candidate contract template, the score of each parameter is calculated based on the clause content and the collected data; the comprehensive evaluation value TEV of the contract template is calculated according to the following formula: In the formula, w i is the weight of the i-th parameter, s i is the score of the i-th parameter, n is the number of parameters;

[0040] According to the calculated comprehensive evaluation value, all alternative contract templates are prioritized and the contract template with the highest comprehensive evaluation value is selected as the standard contract template.

[0041] Furthermore, the execution steps of the order management and decision support module are as follows:

[0042] Order processing flow management: from the generation and receipt of orders, the order status is tracked throughout the process; when the customer places an order, the order information is automatically assigned to the corresponding processing link, including order review, inventory allocation, production scheduling, and logistics scheduling; a status update mechanism is set up in each link so that relevant personnel and participants can understand the execution progress of the order in real time;

[0043] Inventory optimization decision-making: Combining historical order data, current inventory levels and forecasted demand, using data analysis algorithms such as time series analysis and machine learning algorithms, to provide enterprises with inventory optimization decision-making suggestions; including determining the optimal replenishment quantity, safety inventory level, and inventory allocation strategy for different products in different warehouses to reduce inventory costs while avoiding out-of-stock phenomena;

[0044] Risk assessment and decision support: Identify and assess various risk factors that affect order fulfillment, including supplier supply disruption risk, logistics delay risk, and market demand fluctuation risk;

[0045] By establishing a risk assessment model, the degree of risk is quantified, and based on this, corresponding decision-making plans are provided to managers.

[0046] Furthermore, the specific operation steps for determining the optimal replenishment quantity and safety stock level in the order management and decision support module are as follows:

[0047] The optimal replenishment quantity is calculated by the following formula: The economic order quantity EOQ is obtained, where D is the total annual demand, which is the total amount of a certain product or raw material that the company expects to need in a year, and is obtained through a comprehensive analysis of historical sales data, market trends, and corporate production planning factors; S is the cost of each order, which covers all the expenses incurred each time the company places a purchase order, including the time cost of the purchaser's communication and negotiation with the supplier, the fax or electronic order transmission fee, and the administrative fee of the purchase department for processing the order; H is the annual holding cost per unit of goods, including storage costs, insurance costs, and capital occupation costs; the economic order quantity EOQ obtained by calculation is used as the standard for the optimal replenishment quantity;

[0048] Safety stock is calculated by the following formula The safety stock SS is obtained, where Z is the quantile of the standard normal distribution corresponding to the service level, and the service level is the probability of the company's expected satisfaction of customer needs. σ is the standard deviation of demand, which is a statistical indicator to measure the degree of demand fluctuation. It is calculated by analyzing historical order data. L is the lead time, that is, the time interval from the company issuing a purchase order to receiving the goods. The safety stock SS obtained by calculation helps the company determine the additional inventory required to cope with demand fluctuations and lead time uncertainties under the preset service level.

[0049] Furthermore, the assessment process of the supplier supply interruption risk, logistics delay risk and market demand fluctuation risk is as follows:

[0050] The risk of supplier interruption of supply is calculated by the formula: The probability of supplier interruption of supply P(SI) is obtained, which is a value between 0 and 1, and is used to quantify the possibility of the occurrence of supplier interruption risk events. In the formula, N(SI) is the number of times the supplier actually interrupts supply during the observation period, by continuously recording and counting the supplier's supply situation; N(T) is the total number of supply cycles during the observation period; Based on the risk of supplier interruption of supply, a comprehensive assessment of supplier risk is conducted, and the supplier risk comprehensive score SR is obtained by the formula: SR = α × P(SI) + β × C(SI) + γ × T(SI), where C(SI) represents the cost impact of supplier interruption of supply, that is, when the supplier interrupts supply, the additional cost incurred by the enterprise to find alternative supply sources and adjust production plans; T(SI) is the time impact of supplier interruption of supply, that is, the time required from the supplier interruption of supply to the enterprise resuming normal production or supply; α, β, γ are weight coefficients, which respectively represent the probability of supplier interruption of supply, the cost impact of supplier interruption of supply and the time impact of supplier interruption of supply in the comprehensive assessment, and α+β+γ=1, through the calculation of supplier risk comprehensive score SR;

[0051] The risk of logistics delay is calculated by the formula: The logistics delay risk index LRI is calculated, where D i is the actual arrival time of the i-th logistics transport, obtained through the logistics tracking system; E i is the estimated arrival time of the i-th logistics transportation, which is estimated based on the transportation mode and distance factors when the order is placed; n is the number of logistics transportations within the statistical period;

[0052] By calculating the logistics delay risk index LRI, the delay situation of logistics transportation within a period of time is reflected; when the logistics delay risk index LRI is greater than the threshold, it provides a decision to change the logistics supplier, optimize the transportation route or increase the diversity of transportation methods;

[0053] The risk of market demand fluctuation is assessed by the following formula: The market demand fluctuation risk assessment value MDVR is obtained to quantify the risk brought by the fluctuation degree of market demand, where σ MD It is the standard deviation of market demand, obtained through statistical analysis of historical market demand data, and reflects the degree of dispersion of demand; is the average value of market demand;

[0054] By calculating the market demand fluctuation risk assessment value, we can understand the stability of market demand; when the market demand fluctuation risk assessment value MDVR is greater than the threshold, different strategies need to be adopted in production planning and inventory management, including increasing the flexible production capacity of product types and improving inventory turnover rate to cope with rapid changes in demand, thereby reducing the impact of risks brought by market demand fluctuations on order fulfillment.

[0055] Furthermore, the order management and decision support module provides managers with corresponding decision solutions including:

[0056] According to the supplier risk assessment results, qualified suppliers are selected as candidates; by analyzing the supplier's risk score, product quality, price, delivery time and other factors, the candidate suppliers are ranked and analyzed, and a recommendation report is provided to managers, including the supplier's advantages, potential risks and matching information with the company's needs;

[0057] In view of the risk of logistics delay, we design emergency measures for different degrees of delay; for minor delays, we adjust the production plan and give priority to the production of unaffected orders; for moderate delays, we start alternative transportation methods or negotiate with logistics suppliers for expedited services, and notify customers in a timely manner; for severe delays, we transfer goods from local warehouses or find temporary alternative suppliers, and negotiate compensation plans with customers to reduce losses and maintain customer relationships; the delay time for minor delays, moderate delays and severe delays is 1-2 days, 3-5 days and more than 5 days respectively

[0058] Provide management with production plan adjustment suggestions based on market demand fluctuation risk assessment, including increasing inventory in advance during peak seasons and optimizing production processes to reduce costs during off-seasons;

[0059] Based on the overall risk situation, a risk warning mechanism and emergency plan are formulated, and the risk threshold is clearly defined. When the risk score exceeds the threshold, the corresponding warning signal and emergency process are automatically triggered to ensure that the company can respond to and handle risk events in a timely manner and ensure the stable operation of the supply chain. At the same time, risk assessment models and decision-making plans are regularly reviewed and optimized to adapt to the ever-changing market environment and internal corporate conditions.

[0060] Furthermore, the execution process of the data interaction and integration module is as follows:

[0061] Data interface management: Provide unified data interface standards that are compatible with the information systems of different types of supply chain participants, including suppliers' enterprise resource planning systems, logistics companies' transportation management systems, and e-commerce platforms' order management systems; through these interfaces, efficient data transmission and interaction between all parties can be achieved to ensure data accuracy and timeliness;

[0062] Data integration and cleaning: Integrate the data obtained from various interfaces to establish a unified data warehouse; clean the data to remove duplicate, erroneous and inconsistent data; and classify and label the data;

[0063] Data analysis and visualization: Use data mining technology and data analysis tools to conduct in-depth analysis of the integrated data and explore potential valuable information, including bottlenecks in the supply chain, cost structure optimization points, and customer demand trends.

[0064] Furthermore, the process of conducting in-depth analysis on the integrated data and mining potential valuable information in the data interaction and integration module is as follows:

[0065] Extract integrated data from a unified data warehouse, including supplier information, logistics data, and sales data; conduct preliminary exploration of the data, use descriptive statistical analysis methods to understand the basic characteristics of the data, and identify outliers and missing values ​​in the data;

[0066] Use process mining technology to build a business process model based on event log data to identify the key paths and frequently executed paths in the process; by analyzing the processing time, waiting time and resource utilization indicators of each link in the process, select the links that take the longest time, occupy the most resources or frequently experience delays, and identify them as supply chain bottlenecks;

[0067] Adopt cost analysis model to classify and summarize cost data according to different dimensions;

[0068] Use time series analysis methods to model and predict customer order data and sales data in time series, and analyze the changing trends of customer demand in different time periods, including demand growth or decline trends and seasonal fluctuation characteristics;

[0069] Combining market research data, customer behavior data and macroeconomic data, using cluster analysis and association rule mining technology, we can gain an in-depth understanding of the market segmentation characteristics of customer demand, product-related demand patterns, and the laws of demand being affected by external factors;

[0070] Evaluate the potential value information obtained through mining and analysis, including supply chain bottlenecks, cost structure optimization points, and customer demand trends, and judge their rationality and reliability. Specifically, cross-validation and comparative analysis with historical data are used for verification;

[0071] Visualize verified analysis results, including:

[0072] Create interactive dashboards to display dynamic trends of key performance indicators in each link of the supply chain, cost structure distribution charts, and customer demand forecast curves;

[0073] Generate reports, including bottleneck analysis reports, cost optimization solution reports, and customer demand insight reports;

[0074] Explain the analysis process and conclusions in a combination of text and diagrams;

[0075] Draw various graphics to show data relationships and trends in different dimensions, helping managers quickly understand complex data information.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] (1) The transaction and collaborative service modules of the present invention have significant effects. Encryption processing ensures the security of transaction information and prevents leakage and tampering. Contract management is efficient and flexible. Multi-parameter evaluation and optimization templates reduce the risk of default. The collaborative mechanism improves the efficiency of cooperation among all parties and enhances the response speed of the supply chain.

[0078] (2) The order management module of the present invention has outstanding advantages, process management can achieve accurate tracking, improve customer satisfaction, reduce costs, inventory optimization balances costs and out-of-stock risks, risk assessment quantifies multiple risks, provides decision-making solutions, and enhances supply chain stability;

[0079] (3) In the present invention, the data interaction and integration modules play a key role. Interface management ensures efficient and accurate data interaction, integrated cleaning improves data quality, and analysis and visualization mine valuable information, intuitively presenting results to assist managers in making scientific decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0081] Figure 1 This is the overall system block diagram of the present invention. DETAILED DESCRIPTION

[0082] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0083] It should be understood that the terms “include” and “comprising” used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0084] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations.

[0085] like Figure 1 As shown, a comprehensive supply chain control system includes a transaction and collaborative service module, an order management and decision support module, and a data interaction and integration module;

[0086] The transaction and collaboration service module is used to process transaction information of supply chain participants, ensure information security and accuracy, manage the entire life cycle of contracts and monitor them in real time, and establish real-time communication and collaborative project management channels to improve collaboration efficiency.

[0087] Transaction information processing: Receive and record transaction information from suppliers, manufacturers, distributors, and retailers, including detailed data on the price, quantity, transaction time, and transaction location of products or services; at the same time, encrypt the transaction information to ensure the security and privacy of the information and prevent data leakage. The specific process is as follows:

[0088] Collect transaction information from suppliers, manufacturers, distributors, retailers and other supply chain participants, including product or service prices, quantities, transaction times, and transaction locations; standardize the format of the collected information, including unified time formats and quantity units, to ensure information standardization; randomly generate a high-strength symmetric encryption key for each transaction, and distribute the symmetric encryption key to all parties involved in the transaction through a secure channel (such as an SSL / TLS encryption channel) to ensure the security of key transmission; use the generated symmetric encryption key to encrypt transaction information, convert the original plaintext information into ciphertext, and ensure the confidentiality of the information during transmission and storage; generate a pair of asymmetric encryption keys (such as RSA keys) The recipient uses their asymmetric encryption public key to encrypt the symmetric encryption key, and then transmits the encrypted symmetric encryption key along with the ciphertext transaction information to the recipient. The recipient uses their own asymmetric encryption private key to decrypt and obtain the symmetric encryption key, and then uses the symmetric encryption key to decrypt the ciphertext transaction information to restore the original transaction information, thereby achieving secure receipt and use of the information. The transaction information is hashed (such as SHA-256) to obtain a hash value of a fixed length. The hash value is stored in the blockchain, and the tamper-proof nature of the blockchain is used to further ensure the integrity and traceability of the transaction information and prevent the information from being tampered with.

[0089] Contract management: used to generate, store, query and execute various supply chain contracts; automatically generate standard contract templates based on the negotiation results between different parties, covering procurement contracts, sales contracts, and logistics service contracts; when generating contract templates, generate several alternative contract templates at the same time, and pre-design multiple alternative contract templates based on different types of supply chain contracts (procurement contracts, sales contracts, logistics service contracts, etc.), each template contains general terms and adjustable terms; determine quantifiable parameters for evaluating the priority of contract templates, including:

[0090] Cost-related parameters: Procurement cost (for procurement contracts) or sales price (for sales contracts): reflects the direct impact of the contract on the cost or revenue of the enterprise; Logistics costs (for logistics service contracts): involves transportation, warehousing and other costs, affecting the overall operating cost of the supply chain; Risk-related parameters: Supplier risk (for procurement contracts): such as the probability of supplier interruption of supply and the financial stability of suppliers, quantified through historical data and ratings of credit assessment agencies; Market risk (for sales contracts): including market demand fluctuation risk and price fluctuation risk, quantified using market trend analysis and historical sales data; Legal risk: the degree of compliance of contract terms with laws and regulations, expressed in 0- The value of 1 indicates that 1 is in full compliance with laws and regulations, and 0.8 indicates that there are certain legal risks; Time-related parameters: Delivery period (for purchase contracts and sales contracts): The time from the order to the delivery of goods directly affects the company's production plan and customer satisfaction; Contract period (for various contracts): Long-term contracts and short-term contracts have different impacts on the company's strategic planning and flexibility, which are quantified in months or years; Quality-related parameters: Product or service quality standards (for purchase contracts and sales contracts): quantified through quality inspection indicators, industry standard compliance, etc.; Logistics service quality (for logistics service contracts): including cargo damage rate and on-time delivery rate;

[0091] Collect data related to the above parameters from the company's internal database (such as procurement records, sales data, logistics management system), external market research institutions, credit rating agencies, etc.; clean and organize the collected data, remove outliers and erroneous data, and ensure the accuracy and reliability of the data; use methods such as the analytic hierarchy process (AHP) or expert scoring method to determine the weight of each parameter in the contract template evaluation; for each alternative contract template, calculate the score of each parameter based on its terms and collected data; calculate the comprehensive evaluation value TEV of the contract template according to the following formula: In the formula, w i is the weight of the i-th parameter, s iis the score of the i-th parameter, and n is the number of parameters; according to the calculated comprehensive evaluation value, all alternative contract templates are prioritized, and the contract template with the highest comprehensive evaluation value is selected as the standard contract template.

[0092] Collaborative work mechanism: Establish real-time communication channels between supply chain participants, including online instant messaging and video conferencing functions, so that all parties can negotiate and resolve problems in a timely manner during the transaction process, and provide collaborative project management functions so that all parties can jointly participate in the planning, execution and monitoring of supply chain projects, including joint new product development projects and promotional activities projects, to improve collaborative work efficiency.

[0093] The order management and decision support module is used to track the entire order processing process, combine multiple data application algorithms to provide inventory optimization decisions, identify and evaluate order risks and assist in decision-making, and ensure efficient and accurate fulfillment of orders;

[0094] Order processing flow management: from the generation and receipt of orders, the order status is tracked throughout the process; when the customer places an order, the order information is automatically assigned to the corresponding processing link, including order review, inventory allocation, production scheduling (for manufacturing orders), and logistics scheduling; a status update mechanism is set up in each link so that relevant personnel and participants can understand the execution progress of the order in real time;

[0095] Inventory optimization decision-making: Combining historical order data, current inventory levels and forecasted demand, using data analysis algorithms such as time series analysis and machine learning algorithms, to provide enterprises with inventory optimization decision-making suggestions; including determining the optimal replenishment quantity, safety inventory level, and inventory allocation strategy for different products in different warehouses to reduce inventory costs while avoiding out-of-stock phenomena;

[0096] The optimal replenishment quantity is calculated by the following formula: The economic order quantity EOQ is obtained, where D is the total annual demand, which is the total amount of a certain product or raw material that the company expects to need in a year. It is obtained through a comprehensive analysis of historical sales data, market trends, and corporate production plans. S is the cost of each order, which covers all the expenses incurred each time the company places a purchase order, including the time cost of the purchasing staff to communicate and negotiate with the supplier (calculated according to the salary ratio), the fax or electronic order transmission fee, and the administrative fee of the purchasing department to process the order. H is the annual holding cost per unit of goods, including storage costs (warehouse rent is allocated to each product unit, warehouse equipment depreciation costs are allocated), insurance costs (cost of purchasing insurance for inventory goods is allocated), and capital occupation costs. The economic order quantity EOQ obtained by calculation is used as the standard for the optimal replenishment quantity. By determining the economic order quantity, the company can minimize the total inventory cost while meeting production or sales needs. The safety stock is calculated by the following formula The safety stock SS is obtained, where Z is the quantile of the standard normal distribution corresponding to the service level, and the service level is the probability of the company's expected satisfaction of customer needs set in advance; σ is the standard deviation of demand, which is a statistical indicator to measure the degree of demand fluctuation; it is calculated by analyzing historical order data, and the larger the standard deviation, the greater the uncertainty of demand; L is the lead time, that is, the time interval from the company issuing a purchase order to receiving the goods; the safety stock SS obtained by calculation helps the company determine the additional inventory required to cope with demand fluctuations and lead time uncertainties at a certain service level.

[0097] Risk assessment and decision support: Identify and assess various risk factors that may affect order fulfillment, including supplier supply disruption risk, logistics delay risk, and market demand fluctuation risk;

[0098] The risk of supplier interruption of supply is calculated by the formula: The probability of supplier interruption of supply P(SI) is obtained, which is a value between 0 and 1, and is used to quantify the possibility of the risk event of supplier interruption of supply. In the formula, N(SI) is the number of times the supplier actually interrupts supply during the observation period, by continuously recording and counting the supplier's supply situation; N(T) is the total number of supply cycles during the observation period; based on the risk of supplier interruption of supply, a comprehensive supplier risk assessment is conducted, and the supplier risk comprehensive score SR is obtained through the formula: SR = α×P(SI)+β×C(SI)+γ×T(SI), where C(SI) represents the cost impact of supplier interruption of supply, that is, when the supplier interrupts supply, the additional cost incurred by the enterprise in finding alternative supply sources, adjusting production plans, etc. T(SI) is the time impact of supplier interruption of supply, that is, the time required from the supplier interruption of supply to the enterprise to resume normal production or supply, and is measured in days; α, β, and γ are weight coefficients, which respectively represent the probability of supplier interruption of supply, the cost impact of supplier interruption of supply, and the importance of the time impact of supplier interruption of supply in the comprehensive assessment, and α+β+γ=1. By calculating the supplier risk comprehensive score SR, a quantitative risk score is calculated by comprehensively considering multiple factors of supplier interruption of supply, which is used by enterprises to compare and rank the risks of different suppliers, so as to take more targeted risk management measures, including giving priority to strengthening cooperation with suppliers with lower risks and formulating response strategies for high-risk suppliers in advance;

[0099] The risk of logistics delay is calculated by the formula: The logistics delay risk index LRI is calculated, where D i is the actual arrival time of the i-th logistics transport, obtained through the logistics tracking system; E iis the estimated arrival time of the i-th logistics transportation, which is estimated based on the transportation mode and distance factors when the order is placed; n is the number of logistics transportations within the statistical period; by calculating the logistics delay risk index LRI, it reflects the delay of logistics transportation over a period of time, helping enterprises to timely understand the stability and reliability of logistics services; when the logistics delay risk index LRI is greater than the threshold, it provides decisions on changing logistics suppliers, optimizing transportation routes or increasing the diversity of transportation modes to reduce the impact of logistics delays on order fulfillment;

[0100] The risk of market demand fluctuation is assessed by the following formula: The market demand fluctuation risk assessment value MDVR is obtained to quantify the risk brought by the fluctuation degree of market demand, where σ MD It is the standard deviation of market demand, obtained through statistical analysis of historical market demand data, and reflects the degree of dispersion of demand; is the average value of market demand; by calculating the market demand fluctuation risk assessment value, we can understand the stability of market demand; if the market demand fluctuation risk assessment value MDVR is greater than the threshold, it is judged that the market demand fluctuation is large, and the market demand uncertainty faced by the enterprise is high. It is necessary to adopt more flexible strategies in production planning and inventory management, including increasing the flexible production capacity of product types and improving inventory turnover rate to cope with rapid changes in demand, so as to reduce the impact of risks brought by market demand fluctuations on order fulfillment;

[0101] By establishing a risk assessment model, we can quantify the degree of risk and provide managers with corresponding decision-making plans based on this. Specifically, we can select suppliers with lower risks and better overall performance as candidates based on the supplier risk assessment results; we can sort and analyze the candidate suppliers by considering the supplier's risk score, product quality, price, and delivery time, and provide managers with a recommendation report, including information such as the supplier's advantages, potential risks, and the degree of matching with the company's needs;

[0102] Design emergency measures for different degrees of delays in response to logistics delay risks; for mild delays (such as delays within 1-2 days), adjust production plans and give priority to the production of other unaffected orders; for moderate delays (delays of 3-5 days), activate alternative transportation methods or negotiate expedited services with logistics suppliers, and notify customers in a timely manner; for severe delays (delays of more than 5 days), urgently transfer goods from local warehouses or find temporary alternative suppliers, and negotiate compensation plans with customers to reduce losses and maintain customer relationships; provide management personnel with production plan adjustment suggestions based on market demand fluctuation risk assessment, including increasing inventory in advance during peak seasons and optimizing production processes to reduce costs during off-seasons; formulate risk warning mechanisms and emergency plans for the overall risk situation, clarify risk thresholds, and automatically trigger corresponding warning signals and emergency processes when risk scores exceed the thresholds to ensure that companies can respond to and handle risk events in a timely manner and ensure the stable operation of the supply chain; at the same time, regularly review and optimize risk assessment models and decision-making plans to adapt to the ever-changing market environment and internal corporate conditions.

[0103] The data interaction and integration module is used to manage data interfaces to achieve efficient data interaction between all parties, integrate and clean data to improve quality, conduct in-depth analysis to mine potential valuable information and present it visually, and help managers make scientific decisions;

[0104] Data interface management: Provide unified data interface standards that are compatible with information systems of different types of supply chain participants, including suppliers' enterprise resource planning (ERP) systems, logistics companies' transportation management systems (TMS), and e-commerce platforms' order management systems; through these interfaces, efficient data transmission and interaction between all parties can be achieved to ensure data accuracy and timeliness; Data integration and cleaning: Integrate data obtained from various interfaces to establish a unified data warehouse; in this process, clean the data to remove duplicate, erroneous, and inconsistent data to improve data quality; at the same time, classify and label the data for subsequent data analysis and mining;

[0105] Data analysis and visualization: Use data mining technology and data analysis tools to conduct in-depth analysis of the integrated data and mine potential valuable information, including bottlenecks in the supply chain, cost structure optimization points, and customer demand trends. The specific process is as follows:

[0106] Extract integrated data from a unified data warehouse, including supplier information (supply capacity, delivery time, raw material prices), logistics data (transportation time, transportation cost, inventory turnover), sales data (order quantity, sales amount, customer geographical distribution) and other relevant data; conduct preliminary exploration of the data, use descriptive statistical analysis methods (calculate mean, median, standard deviation, frequency distribution, etc.) to understand the basic characteristics of the data, and identify outliers and missing values ​​in the data;

[0107] Use process mining technology to build business process models based on event log data (order processing process, production process, logistics and distribution process records) to identify key paths and frequently executed paths in the process; by analyzing the processing time, waiting time and resource utilization indicators of each link in the process, find out the links that take the longest time, occupy the most resources or frequently experience delays, and determine them as supply chain bottlenecks; use cost analysis models to classify and summarize cost data according to different dimensions (purchase cost, production cost, logistics cost, inventory holding cost); use time series analysis methods (moving average method, exponential smoothing method, ARI MA model) to model and predict customer order data and sales data according to time series, and analyze the changing trends of customer demand in different time periods (monthly, quarterly, and annual), including demand growth or decline trends and seasonal fluctuation characteristics;

[0108] Combine market research data, customer behavior data (purchase frequency, purchase preference, customer evaluation) and macroeconomic data (industry growth rate, consumer confidence index), use cluster analysis and association rule mining technology to gain an in-depth understanding of the market segment characteristics of customer demand, product-related demand patterns, and the laws of demand being affected by external factors; evaluate the potential value information (supply chain bottlenecks, cost structure optimization points, customer demand trends, etc.) obtained through mining and analysis to determine its rationality and reliability. Verification can be carried out using methods such as cross-validation, comparative analysis with historical data, and expert review;

[0109] Present verified analysis results in an intuitive visual form, such as creating interactive dashboards to display dynamic trends in key performance indicators of each link in the supply chain, cost structure distribution charts, customer demand forecast curves, etc.; generate detailed reports, including bottleneck link analysis reports, cost optimization plan reports, customer demand insight reports, etc., using a combination of text and charts to explain the analysis process and conclusions; draw various types of graphics (bar charts, line charts, pie charts, flow charts) to display data relationships and trends in different dimensions, helping managers quickly understand complex data information and provide strong support for decision-making.

[0110] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An integrated supply chain control system, characterized in that: include: The transaction and collaboration service module is used to process transaction information of supply chain participants, ensure information security and accuracy, manage the entire life cycle of contracts and monitor them in real time, and establish real-time communication and collaborative project management channels to improve collaboration efficiency; Order management and decision support module: used to track the entire order processing process, combine multiple data application algorithms to provide inventory optimization decisions, identify and evaluate order risks and assist in decision-making, and ensure efficient and accurate fulfillment of orders; The data interaction and integration module is used to manage data interfaces to achieve efficient data interaction among all parties, integrate and clean data to improve quality, conduct in-depth analysis to mine potential valuable information and present it visually, and help managers make scientific decisions.

2. The integrated supply chain control system according to claim 1, characterized in that: The specific process of the transaction and collaborative service module is as follows: Transaction information processing: receiving and recording transaction information from suppliers, manufacturers, distributors, and retailers, including detailed data on the price, quantity, transaction time, and transaction location of products or services; at the same time, encrypting the transaction information to ensure the security and privacy of the information and prevent data leakage; Contract management: used to generate, store, query and execute various supply chain contracts; automatically generate standard contract templates based on the negotiation results between different parties, covering procurement contracts, sales contracts, and logistics service contracts; when generating contract templates, generate several alternative contract templates at the same time, and select the contract template with the highest priority for use; Collaborative work mechanism: Establish real-time communication channels between supply chain participants, including online instant messaging and video conferencing functions, so that all parties can negotiate and resolve problems in a timely manner during the transaction process, and provide collaborative project management functions so that all parties can jointly participate in the planning, execution and monitoring of supply chain projects, including joint new product development projects and promotional activities projects, to improve collaborative work efficiency.

3. The integrated supply chain control system according to claim 2, characterized in that: The specific steps for encrypting transaction information in the transaction and collaborative service module are as follows: Collect transaction information from suppliers, manufacturers, distributors, and retailers, covering product or service prices, quantities, transaction times, and transaction locations; standardize the format of the collected information, including unified time formats and quantity units; A symmetric encryption key is randomly generated for each transaction, and the symmetric encryption key is distributed to all parties involved in the transaction through a secure channel; the generated symmetric encryption key is used to encrypt the transaction information, converting the original plaintext information into ciphertext to ensure the confidentiality of the information during transmission and storage; Generate a pair of asymmetric encryption keys and make the public key publicly available to supply chain participants; The symmetric encryption key is encrypted using the recipient's asymmetric encryption public key, and then the encrypted symmetric encryption key is transmitted to the recipient along with the ciphertext transaction information; The receiver uses its own asymmetric encryption private key to decrypt and obtain the symmetric encryption key, and then uses the symmetric encryption key to decrypt the ciphertext transaction information to restore the original transaction information, thus achieving secure reception and use of the information; Perform hash operation on transaction information to obtain a hash value of fixed length; store the hash value in the blockchain, and use the tamper-proof nature of the blockchain to further ensure the integrity and traceability of the transaction information.

4. The integrated supply chain control system according to claim 2, characterized in that: The specific steps for selecting the highest priority contract template for use in the transaction and collaboration service module are as follows: When generating a contract template, several alternative contract templates are generated at the same time. According to different types of supply chain contracts, multiple alternative contract templates are pre-designed, and each template contains general terms and adjustable terms; Identify evaluation parameters for prioritizing contract templates, including: The cost-related parameters are as follows: Purchase cost or sales price: reflects the direct impact of the contract on the company's costs or revenues; Logistics costs: involve transportation and warehousing costs, affecting the overall operating costs of the supply chain; The risk related parameters are as follows: Supplier risk: the probability of supplier interruption of supply and the financial stability of the supplier, quantified through historical data and ratings from credit assessment agencies; Market risk: including market demand fluctuation risk and price fluctuation risk, which can be quantified using market trend analysis and historical sales data; Legal risk: the degree of compliance of contract terms with laws and regulations, expressed as a value of 0-1; The time-related parameters are as follows: Lead time: the time from order placement to goods delivery; Term of the contract; The quality related parameters are as follows: Product or service quality standards: quantified through quality inspection indicators and compliance with industry standards; Logistics service quality: including cargo damage rate and on-time delivery rate; Collect evaluation parameters from internal corporate databases, external market research agencies, and credit rating agencies; clean and organize the collected data, remove outliers and erroneous data, and ensure the accuracy and reliability of the data; The analytic hierarchy process is used to determine the weight of each parameter in the contract template evaluation; for each candidate contract template, the score of each parameter is calculated based on the clause content and the collected data; the comprehensive evaluation value TEV of the contract template is calculated according to the following formula: In the formula, w i is the weight of the i-th parameter, s i is the score of the i-th parameter, n is the number of parameters; According to the calculated comprehensive evaluation value, all alternative contract templates are prioritized and the contract template with the highest comprehensive evaluation value is selected as the standard contract template.

5. The integrated supply chain control system according to claim 1, characterized in that: The execution steps of the order management and decision support module are as follows: Order processing flow management: from the generation and receipt of orders, the order status is tracked throughout the process; when the customer places an order, the order information is automatically assigned to the corresponding processing link, including order review, inventory allocation, production scheduling, and logistics scheduling; a status update mechanism is set up in each link so that relevant personnel and participants can understand the execution progress of the order in real time; Inventory optimization decision-making: Combining historical order data, current inventory levels and forecasted demand, using data analysis algorithms such as time series analysis and machine learning algorithms, to provide enterprises with inventory optimization decision-making suggestions; including determining the optimal replenishment quantity, safety inventory level, and inventory allocation strategy for different products in different warehouses to reduce inventory costs while avoiding out-of-stock phenomena; Risk assessment and decision support: Identify and assess various risk factors that affect order fulfillment, including supplier supply disruption risk, logistics delay risk, and market demand fluctuation risk; By establishing a risk assessment model, the degree of risk is quantified, and based on this, corresponding decision-making plans are provided to managers.

6. The integrated supply chain control system according to claim 5, characterized in that: The specific steps for determining the optimal replenishment quantity and safety stock level in the order management and decision support module are as follows: The optimal replenishment quantity is calculated by the following formula: The economic order quantity EOQ is obtained, where D is the total annual demand, which is the total amount of a certain product or raw material that the company expects to need in a year, and is obtained through a comprehensive analysis of historical sales data, market trends, and corporate production planning factors; S is the cost of each order, which covers all the expenses incurred each time the company places a purchase order, including the time cost of the purchaser's communication and negotiation with the supplier, the fax or electronic order transmission fee, and the administrative fee of the purchase department for processing the order; H is the annual holding cost per unit of goods, including storage costs, insurance costs, and capital occupation costs; the economic order quantity EOQ obtained by calculation is used as the standard for the optimal replenishment quantity; Safety stock is calculated by the following formula The safety stock SS is obtained, where Z is the quantile of the standard normal distribution corresponding to the service level, and the service level is the probability of the company's expected satisfaction of customer needs. σ is the standard deviation of demand, which is a statistical indicator to measure the degree of demand fluctuation. It is calculated by analyzing historical order data. L is the lead time, that is, the time interval from the company issuing a purchase order to receiving the goods. The safety stock SS obtained by calculation helps the company determine the additional inventory required to cope with demand fluctuations and lead time uncertainties under the preset service level.

7. The integrated supply chain control system according to claim 5, characterized in that: The assessment process of the supplier supply interruption risk, logistics delay risk and market demand fluctuation risk is as follows: The risk of supplier interruption of supply is calculated by the formula: The probability of supplier interruption of supply P(SI) is obtained, which is a value between 0 and 1, which is used to quantify the possibility of the occurrence of supplier interruption of supply risk events. In the formula, N(SI) is the number of actual supplier interruptions during the observation period, which is achieved by continuously recording and counting the supplier's supply situation; N(T) is the total number of supply cycles during the observation period; Based on the risk of supplier interruption of supply, a comprehensive supplier risk assessment is conducted, and the supplier risk comprehensive score SR is obtained through the formula: SR = α × P (SI) + β × C (SI) + γ × T (SI), where C (SI) represents the cost impact of supplier interruption of supply, that is, when the supplier interrupts supply, the additional cost incurred by the enterprise to find alternative supply sources and adjust production plans; T(SI) is the time impact of supplier interruption of supply, that is, the time required from the supplier interruption of supply to the enterprise resuming normal production or supply; α, β, γ are weight coefficients, which respectively represent the probability of supplier interruption of supply, the cost impact of supplier interruption of supply and the importance of the time impact of supplier interruption of supply in the comprehensive evaluation, and α+β+γ=1, which is calculated through the supplier risk comprehensive score SR; The risk of logistics delay is calculated by the formula: The logistics delay risk index LRI is calculated, where D i is the actual arrival time of the i-th logistics transport, obtained through the logistics tracking system; E i is the estimated arrival time of the i-th logistics transportation, which is estimated based on the transportation mode and distance factors when the order is placed; n is the number of logistics transportations within the statistical period; By calculating the logistics delay risk index LRI, the delay situation of logistics transportation within a period of time is reflected; when the logistics delay risk index LRI is greater than the threshold, it provides a decision to change the logistics supplier, optimize the transportation route or increase the diversity of transportation methods; The risk of market demand fluctuation is assessed by the following formula: The market demand fluctuation risk assessment value MDVR is obtained to quantify the risk brought by the fluctuation degree of market demand, where σ MD It is the standard deviation of market demand, obtained through statistical analysis of historical market demand data, and reflects the degree of dispersion of demand; is the average value of market demand; By calculating the market demand fluctuation risk assessment value, we can understand the stability of market demand; when the market demand fluctuation risk assessment value MDVR is greater than the threshold, different strategies need to be adopted in production planning and inventory management, including increasing the flexible production capacity of product types and improving inventory turnover rate to cope with rapid changes in demand, thereby reducing the impact of risks brought by market demand fluctuations on order fulfillment.

8. The integrated supply chain control system according to claim 5, characterized in that: The order management and decision support module provides managers with corresponding decision solutions including: According to the supplier risk assessment results, qualified suppliers are selected as candidates; by analyzing the supplier's risk score, product quality, price, delivery time and other factors, the candidate suppliers are ranked and analyzed, and a recommendation report is provided to managers, including the supplier's advantages, potential risks and matching information with the company's needs; In view of the risk of logistics delay, we design emergency measures for different degrees of delay; for minor delays, we adjust the production plan and give priority to the production of unaffected orders; for moderate delays, we start alternative transportation methods or negotiate with logistics suppliers for expedited services, and notify customers in a timely manner; for severe delays, we transfer goods from local warehouses or find temporary alternative suppliers, and negotiate compensation plans with customers to reduce losses and maintain customer relationships; the delay time for minor delays, moderate delays and severe delays is 1-2 days, 3-5 days and more than 5 days respectively Provide management with production plan adjustment suggestions based on market demand fluctuation risk assessment, including increasing inventory in advance during peak seasons and optimizing production processes to reduce costs during off-seasons; Based on the overall risk situation, a risk warning mechanism and emergency plan are formulated, and the risk threshold is clearly defined. When the risk score exceeds the threshold, the corresponding warning signal and emergency process are automatically triggered to ensure that the company can respond to and handle risk events in a timely manner and ensure the stable operation of the supply chain. At the same time, risk assessment models and decision-making plans are regularly reviewed and optimized to adapt to the ever-changing market environment and internal corporate conditions.

9. The integrated supply chain control system according to claim 1, characterized in that: The execution process of the data interaction and integration module is as follows: Data interface management: Provide unified data interface standards that are compatible with the information systems of different types of supply chain participants, including suppliers’ enterprise resource planning systems, logistics companies’ transportation management systems, and e-commerce platforms’ order management systems; Through these interfaces, efficient data transmission and interaction between all parties can be achieved, ensuring the accuracy and timeliness of data; Data integration and cleaning: Integrate the data obtained from various interfaces to establish a unified data warehouse; clean the data to remove duplicate, erroneous and inconsistent data; and classify and label the data; Data analysis and visualization: Use data mining technology and data analysis tools to conduct in-depth analysis of the integrated data and explore potential valuable information, including bottlenecks in the supply chain, cost structure optimization points, and customer demand trends.

10. The integrated supply chain control system according to claim 9, characterized in that: The process of conducting in-depth analysis of the integrated data and mining potential valuable information in the data interaction and integration module is as follows: Extract integrated data from a unified data warehouse, including supplier information, logistics data, and sales data; conduct preliminary exploration of the data, use descriptive statistical analysis methods to understand the basic characteristics of the data, and identify outliers and missing values ​​in the data; Use process mining technology to build a business process model based on event log data to identify the key paths and frequently executed paths in the process; by analyzing the processing time, waiting time and resource utilization indicators of each link in the process, select the links that take the longest time, occupy the most resources or frequently experience delays, and identify them as supply chain bottlenecks; Adopt cost analysis model to classify and summarize cost data according to different dimensions; Use time series analysis methods to model and predict customer order data and sales data in time series, and analyze the changing trends of customer demand in different time periods, including demand growth or decline trends and seasonal fluctuation characteristics; Combining market research data, customer behavior data and macroeconomic data, using cluster analysis and association rule mining technology, we can gain an in-depth understanding of the market segmentation characteristics of customer demand, product-related demand patterns, and the laws of demand being affected by external factors; Evaluate the potential value information obtained through mining and analysis, including supply chain bottlenecks, cost structure optimization points, and customer demand trends, and judge their rationality and reliability. Specifically, cross-validation and comparative analysis with historical data are used for verification; Visualize verified analysis results, including: Create interactive dashboards to display dynamic trends of key performance indicators in each link of the supply chain, cost structure distribution charts, and customer demand forecast curves; Generate reports, including bottleneck analysis reports, cost optimization solution reports, and customer demand insight reports; Explain the analysis process and conclusions in a combination of text and diagrams; Draw various graphics to show data relationships and trends in different dimensions, helping managers quickly understand complex data information.

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