Supply chain optimization method and system, intelligent terminal and storage medium

Abstract

The invention relates to a supply chain optimization method and system, an intelligent terminal and a storage medium, and relates to the technical field of large models, and the method comprises the steps: collecting multi-dimensional data of each link of a supply chain of a current factory; performing preprocessing and feature extraction operation on the multi-dimensional data to obtain a multi-dimensional feature matrix; extracting a management rule of the supply chain; performing feature extraction operation on the management rules to obtain a management rule feature matrix; calling a supply chain optimization model, and performing data processing on the multi-dimensional feature matrix and the management rule feature matrix to obtain a target supply chain scheme corresponding to the supply chain; collecting an actual supply chain scheme of the supply chain; and updating the inventory management strategy of the supply chain according to the difference between the target supply chain scheme and the actual supply chain scheme. The method has the effect of improving the intelligence and real-time performance of supply chain optimization.

Description

Technical Field

[0001] The present application relates to the field of large model technology, and in particular to a supply chain optimization method, system, intelligent terminal and storage medium. Background Art

[0002] Supply chain optimization refers to improving each link in the supply chain through a series of strategies, tools and methods to improve overall efficiency, reduce costs, increase flexibility, and ensure timely and accurate product delivery. Therefore, supply chain optimization is an indispensable task in modern factories.

[0003] When designing a supply chain, relevant technologies need to collect data from each link of the supply chain in advance, and then use the Internet of Things technology to monitor the status of each link in real time, and use big data analysis methods to promptly process the data of each link in order to discover potential problems and issue early warnings, and dynamically adjust the supply chain based on real-time data and forecast results.

[0004] With regard to the above-mentioned related technologies, when dealing with the supply chain, it is difficult to ensure that the supply chain can make timely adjustments to changes in actual conditions, resulting in the supply chain being out of touch with actual conditions and affecting factory production. Summary of the invention

[0005] In order to improve the intelligence and real-time performance of supply chain optimization, the present application provides a supply chain optimization method, system, intelligent terminal and storage medium.

[0006] In the first aspect, the present application provides a supply chain optimization method, which adopts the following technical solution: A supply chain optimization method, comprising: Collect multi-dimensional data on each link of the current factory's supply chain; Performing preprocessing and feature extraction operations on the multi-dimensional data to obtain a multi-dimensional feature matrix; extracting management rules for the supply chain; Performing feature extraction operation on the management rules to obtain a management rule feature matrix; Calling the supply chain optimization model, performing data processing on the multi-dimensional feature matrix and the management rule feature matrix, and obtaining a target supply chain solution corresponding to the supply chain; Collecting actual supply chain solutions for said supply chain; The inventory management strategy of the supply chain is updated according to the difference between the target supply chain solution and the actual supply chain solution.

[0007] By adopting the above technical solution, we can collect multi-dimensional data and management rules of the supply chain, and obtain the target supply chain solution through the supply chain optimization model. Then, we can compare the target supply chain solution with the actual supply chain solution and update the supply chain inventory management solution strategy. This technical solution can introduce the supply chain optimization model, significantly improving the intelligence and real-time level of supply chain optimization, and providing important support for resource management and operational efficiency improvement of industrial manufacturing enterprises.

[0008] Optionally, a difference between the target supply chain solution and the actual supply chain solution is calculated to obtain a shortage of materials in the supply chain; When the shortage of the material is less than the remaining available inventory of the current factory, count the available materials in each inventory warehouse of the current factory; According to the shortage amount of the materials and the available materials, a target inventory warehouse is selected so that the sum of the available materials in the target inventory warehouse is greater than the shortage amount of the materials; The inventory management strategy is updated using the available materials of the target inventory warehouse.

[0009] By adopting the above technical solution, the available materials in different inventory warehouses can be adjusted according to actual conditions to realize the transfer of materials in the inventory warehouses and ensure that the normal operation of the factory will not be affected, thereby improving the intelligence and real-time level of supply chain optimization.

[0010] Optionally, when the shortage of the material is greater than the remaining movable inventory, a candidate factory is determined from the other factories according to the shortage of the material and the surplus of the material inventory of other factories, and the surplus of the material inventory corresponding to the candidate factory is greater than the shortage of the material; Counting the traffic parameters from the current factory to the candidate factory; Calling a path planning model to perform path planning according to the traffic parameters to obtain the shortest path from the candidate factory to the current factory; Obtaining the material transportation efficiency corresponding to the candidate factory according to the unit transportation volume, the material inventory balance and the shortest path corresponding to the candidate factory; The candidate factory corresponding to the minimum value of the material transportation efficiency is selected as the target factory; The inventory management policy is updated using the target plant.

[0011] By adopting the above technical solution, materials are distributed among multiple factories, so that the current factory and other factories can produce products normally. In addition, the quantity of materials owned by different factories can be regulated so that the quantity of materials in different factories tends to be balanced.

[0012] Optionally, when the target factory is not determined among the other factories, inventory information of the current factory is counted, where the inventory information includes material types and material quantities; Obtaining the production task of the current factory; Comparing the inventory information with the production tasks to obtain candidate production tasks that match the inventory information; Scoring the candidate production tasks using the inventory information to obtain scoring scores for the candidate production tasks; Determine the target production task corresponding to the maximum value of the scoring scores; The actual production task of the current factory is updated from the current production task to the target production task, and the inventory management strategy is updated according to the target production task.

[0013] By adopting the above technical solution, when the inventory is insufficient to produce the current product, the current factory's production task can be modified to the target production task to ensure the normal production of the factory, which significantly improves the intelligence and real-time level of supply chain optimization and provides important support for resource management and operational efficiency improvement of industrial manufacturing enterprises.

[0014] Optionally, a supply chain difference is obtained according to a difference between the current production task and the target production task; Obtaining a material update difference of the current factory according to the inventory information and the supply chain difference; Calculate the material transfer method according to the material update difference and the material quantity of each inventory warehouse of the current factory; The inventory management strategy is updated according to the material transfer method.

[0015] By adopting the above technical solution, the inventory management strategy can be updated according to the material transfer method, so that the factory's inventory level is kept within a reasonable range, the inventory, production and logistics strategies are optimized, and inventory backlogs and logistics costs are reduced.

[0016] Optionally, statistics are collected on historical product demands of the supply chain during similar periods in the historical period; Counting the current product demand of the supply chain in a current period, where the current period corresponds to the similar period; Integrate the historical product demand and the current product demand to obtain the theoretical product demand of the supply chain; The multi-dimensional data is updated using the theoretical product demand.

[0017] By adopting the above technical solutions, inventory strategies can be dynamically adjusted based on historical product demand and current product demand to reduce inventory costs.

[0018] Optionally, in response to receiving an input operation of a natural language, calling a semantic recognition model to perform semantic recognition processing on the natural language to obtain natural language semantics corresponding to the natural language; Performing feature extraction operation on the natural language semantics to obtain a language semantic feature matrix; Calling the supply chain optimization model, performing data processing on the language semantic feature matrix, and obtaining a semantic inventory management strategy; The inventory management policy is updated according to the semantic inventory management policy approach.

[0019] By adopting the above technical solutions, the supply chain optimization method can support natural language interaction, simplifying the difficulty of supply chain optimization and significantly improving the intelligence and real-time level of supply chain optimization.

[0020] In a second aspect, the present application provides a supply chain optimization system, which adopts the following technical solutions: A supply chain optimization system, comprising: The acquisition module is used to obtain multi-dimensional data, management rules, supply chain optimization models, actual supply chain solutions, remaining available inventory, material inventory margins, path planning models, inventory information, production tasks, historical product demand, current product demand, and natural language; A memory for storing a program of any one of the above supply chain optimization methods; The program in the memory can be loaded and executed by the processor to implement any of the supply chain optimization methods described above.

[0021] By adopting the above technical solution, we can collect multi-dimensional data and management rules of the supply chain, and obtain the target supply chain solution through the supply chain optimization model. Then, we can compare the target supply chain solution with the actual supply chain solution and update the supply chain inventory management solution strategy. This technical solution can introduce the supply chain optimization model, significantly improving the intelligence and real-time level of supply chain optimization, and providing important support for resource management and operational efficiency improvement of industrial manufacturing enterprises.

[0022] In a third aspect, the present application provides a smart terminal, which adopts the following technical solution: An intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute any one of the above-mentioned methods.

[0023] In a fourth aspect, the present application provides a computer storage medium capable of storing corresponding programs, which has the characteristics of being easy to realize the intelligent and real-time improvement of supply chain optimization, and adopts the following technical solutions: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above supply chain optimization methods.

[0024] In summary, the present application includes at least one of the following beneficial technical effects: Collect multi-dimensional data and management rules of the supply chain, and obtain the target supply chain solution through the supply chain optimization model. Then compare the target supply chain solution with the actual supply chain solution, and update the supply chain inventory management solution strategy. This technical solution can introduce the supply chain optimization model, significantly improving the intelligence and real-time level of supply chain optimization, and providing important support for resource management and operational efficiency improvement of industrial manufacturing enterprises; The available materials in different inventory warehouses can be adjusted according to actual conditions to realize the transfer of materials in the inventory warehouses and ensure that the normal operation of the factory will not be affected, thereby improving the intelligence and real-time level of supply chain optimization; Allocate materials between multiple factories so that the current factory and other factories can produce products normally. In addition, you can also control the amount of materials owned by different factories so that the amount of materials in different factories tends to be balanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of a supply chain optimization method provided in an embodiment of the present application.

[0026] Figure 2 It is a flowchart of a first method for updating an inventory management strategy provided in an embodiment of the present application.

[0027] Figure 3 It is a flowchart of a second method for updating an inventory management strategy provided in an embodiment of the present application.

[0028] Figure 4 It is a flow chart of a third method for updating an inventory management strategy provided in an embodiment of the present application.

[0029] Figure 5 It is a flow chart of a material transfer method based on supply chain optimization provided in an embodiment of the present application.

[0030] Figure 6 It is a flow chart of a method for predicting supply chain demand provided in an embodiment of the present application.

[0031] Figure 7 It is a flow chart of a natural language-based supply chain optimization method provided in an embodiment of the present application.

[0032] Figure 8 It is a structural diagram of a supply chain optimization system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figures 1 to 8 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0034] The present application embodiment discloses a supply chain optimization method. Figure 1 , the method comprising: Step S101: Collect multi-dimensional data on each link of the current factory's supply chain.

[0035] Multi-dimensional data includes order demand, inventory status, production plan, logistics timeliness and other data.

[0036] Among them, order demand refers to the demand for products corresponding to the supply. Inventory status refers to the quantity, type, location and storage status of materials in the current factory inventory. Production planning refers to the arrangement of product production volume, production sequence, production time and resource allocation based on order demand, inventory status and production capacity. Material aging refers to the time from the issuance of materials to their delivery to the current factory.

[0037] Step S102: preprocessing and feature extraction operations are performed on the multi-dimensional data to obtain a multi-dimensional feature matrix.

[0038] Preprocessing includes processing missing values, outliers, and duplicate data. Exemplarily, using a difference method to supplement missing values ​​in multidimensional data. Exemplarily, deleting outliers and duplicate data in multidimensional data.

[0039] Exemplarily, the feature extraction operation is a normalization operation.

[0040] Exemplarily, the first row of the multi-dimensional feature matrix corresponds to the vector of order requirements, and the second row of the multi-dimensional feature matrix corresponds to the vector of inventory status.

[0041] Step S103: extracting supply chain management rules.

[0042] Management rules include safety stock, transportation priority and delivery deadline. Safety stock refers to the additional materials or products in stock outside the normal inventory. Safety stock is used to deal with out-of-stock situations caused by demand fluctuations, supply chain uncertainties or other unexpected situations. Transportation priority is to prioritize different orders in material transportation according to factors such as order importance, urgency, customer needs, etc. Delivery deadline refers to the time from the product being shipped to the final delivery to the customer.

[0043] Step S104: performing feature extraction operation on the management rules to obtain a management rule feature matrix.

[0044] Exemplarily, the feature extraction operation is a normalization operation.

[0045] Exemplarily, the first row of the management rule feature matrix corresponds to the vector of safety stocks, and the second row of the management rule feature matrix corresponds to the vector of transportation priorities.

[0046] Step S105: calling the supply chain optimization model, performing data processing on the multi-dimensional feature matrix and the management rule feature matrix, and obtaining a target supply chain solution corresponding to the supply chain.

[0047] The supply chain optimization model adopts a general large model. The general large model is a model that integrates multiple functions. Exemplarily, the supply chain optimization model integrates functions such as natural language processing, reasoning and decision support, and multimodal capabilities.

[0048] The target supply chain solution includes at least one of inventory management strategy, daily production volume of products, transportation method of materials, and adjustment of inventory storage volume. It should be noted that the target supply chain solution is a supply chain solution under an ideal state obtained by the supply chain optimization model.

[0049] Step S106: Collect the actual supply chain plan of the supply chain.

[0050] The actual supply volume method is a supply chain solution in actual scenarios.

[0051] Step S107: updating the inventory management strategy of the supply chain according to the difference between the target supply chain solution and the actual supply chain solution.

[0052] Inventory management strategy refers to the way to handle raw materials or products in inventory, which includes at least one of transfer, storage, transportation, and use.

[0053] Exemplarily, the target supply chain solution is used as a reference to adjust the actual supply chain solution so that the actual supply chain is as close as possible to the target supply chain solution, thereby updating the inventory management strategy of the supply chain.

[0054] In other aspects of this embodiment, the transportation mode of the materials in the supply chain may be updated according to the difference between the target supply chain solution and the actual supply chain solution. Alternatively, the daily production volume of the products in the supply chain may be updated according to the difference between the target supply chain solution and the actual supply chain solution.

[0055] By adopting the above technical solution, we can collect multi-dimensional data and management rules of the supply chain, and obtain the target supply chain solution through the supply chain optimization model. Then, we can compare the target supply chain solution with the actual supply chain solution and update the supply chain inventory management solution strategy. This technical solution can introduce the supply chain optimization model, significantly improving the intelligence and real-time level of supply chain optimization, and providing important support for resource management and operational efficiency improvement of industrial manufacturing enterprises.

[0056] In the following embodiments, considering that in actual scenarios, the remaining available inventory of the current factory will affect inventory management, it is necessary to adjust the inventory management strategy in combination with the actual scenario. Therefore, the embodiment of the present application discloses a method for updating the inventory management strategy. Figure 2 , the method comprising: Step S201: Calculate the difference between the target supply chain solution and the actual supply chain solution to obtain the shortage of materials in the supply chain.

[0057] Exemplarily, a target material requirement in a target supply chain solution is obtained. An actual material requirement in an actual supply chain solution is obtained. A difference between the target material requirement and the actual material requirement is calculated to obtain a material shortage in the supply chain. The material shortage may represent a difference between the target material requirement and the actual material requirement when the target supply chain solution is implemented.

[0058] Step S202: When the shortage of materials is less than the remaining available inventory of the current factory, statistics are collected on the available materials in each inventory warehouse of the current factory.

[0059] The remaining available inventory refers to the quantity and type of materials in inventory. The remaining available inventory includes safety inventory and regular inventory. Among them, regular inventory refers to the inventory of products currently produced by the factory.

[0060] Available materials refer to the amount of materials corresponding to the remaining available inventory in each inventory warehouse.

[0061] Exemplarily, the inventory warehouse will record the usage of materials and the total amount of materials, and upload the aforementioned usage and total amount to the server.

[0062] Step S203: Filter out target inventory warehouses according to the shortage amount of materials and the available materials, so that the sum of the available materials in the target inventory warehouses is greater than the shortage amount of materials.

[0063] The target inventory warehouse can be one or more.

[0064] For example, after obtaining the available materials of each inventory warehouse of the current factory, the inventory warehouses are arranged and combined to obtain several inventory warehouse combinations. The sum of available materials of each inventory warehouse combination is calculated. The inventory warehouse combination whose sum of available materials is greater than the amount of missing materials is taken out to obtain the target inventory warehouse.

[0065] Step S204: Use the available materials in the target inventory warehouse to update the inventory management strategy.

[0066] Exemplarily, based on the available materials and the shortage of materials in the target inventory warehouse, the inventory management strategy is updated so that the target inventory warehouse can provide the materials with the shortage.

[0067] By adopting the above technical solution, the available materials in different inventory warehouses can be adjusted according to actual conditions to realize the transfer of materials in the inventory warehouses and ensure that the normal operation of the factory will not be affected, thereby improving the intelligence and real-time level of supply chain optimization.

[0068] In the following embodiments, when coordinating materials in the inventory warehouse, if an unexpected situation occurs, it may cause all the inventory of the current factory to be difficult to meet production needs, for example, supply chain interruption, logistics delay, shortage of raw materials, etc. To solve the above problems, the embodiment of the present application discloses a second method for updating the inventory management strategy. Figure 3 , the method comprising: Step S301: When the shortage of materials is greater than the remaining available inventory, a candidate factory is determined from other factories according to the shortage of materials and the material inventory balance of other factories, and the material inventory balance corresponding to the candidate factory is greater than the shortage of materials.

[0069] When the shortage of materials is greater than the remaining available inventory, it means that the inventory of the current factory can no longer meet the production needs of the current factory, and materials need to be transferred from other factories to maintain production.

[0070] For example, the material inventory balances of other factories are counted, and factories whose material inventory balances are greater than the material shortage of the current factory are selected as candidate factories.

[0071] Step S302: Counting the traffic parameters from the current factory to the candidate factories.

[0072] The traffic parameters include at least one of a transportation route, a route congestion level, a traffic route, an average vehicle speed, a vehicle type, and a road type.

[0073] Step S303: calling the path planning model, performing path planning according to traffic parameters, and obtaining the shortest path from the candidate factory to the current factory.

[0074] In this embodiment, the shortest path refers to a path with the shortest time, or the shortest path refers to a path with the lowest cost, or the shortest path refers to a path with the shortest distance.

[0075] Optionally, feature extraction is performed on the traffic parameters to obtain a traffic parameter feature matrix. A path planning model is called to perform path planning according to the traffic parameter feature matrix to obtain the shortest path from the candidate factory to the current factory.

[0076] Step S304: Obtain the material transportation efficiency corresponding to the candidate factory according to the unit transportation volume and the material inventory balance and the shortest path corresponding to the candidate factory.

[0077] Material transportation efficiency refers to the time required to transport materials from the candidate factory to the current factory.

[0078] Unit transport volume refers to the quantity or weight of materials transported in a single trip. For example, when transporting materials, container trucks are usually used for transportation, and the total amount of materials transported by each container truck at a time is the unit transport volume.

[0079] For example, the ratio of the material inventory balance and the unit transportation volume corresponding to the candidate factory is calculated to obtain the transportation times, and the product of the transportation times and the shortest path is used as the material transportation efficiency.

[0080] In some other embodiments, the screening can also be performed from the perspective of transportation cost instead of material transportation efficiency. The path consumption cost is calculated based on the shortest path. The ratio of the material inventory balance and the unit transportation volume corresponding to the candidate factory is calculated to obtain the number of transportations. The product of the number of transportations and the path consumption cost is used as the transportation cost corresponding to the candidate factory.

[0081] Step S305: taking the candidate factory corresponding to the minimum value of material transportation efficiency as the target factory.

[0082] In order to ensure the production efficiency of the current factory, the candidate factory corresponding to the minimum value of material transportation efficiency is taken as the target factory.

[0083] In some other embodiments, in order to reduce the operating cost of the current factory, the candidate factory corresponding to the minimum value of the transportation cost is taken as the target factory.

[0084] Step S306: Update the inventory management strategy using the target factory.

[0085] Exemplarily, the target factory is added to the inventory management strategy, so that the target factory provides materials to the current factory.

[0086] By adopting the above technical solution, materials are distributed among multiple factories, so that the current factory and other factories can produce products normally. In addition, the quantity of materials owned by different factories can be regulated so that the quantity of materials in different factories tends to be balanced.

[0087] In the following embodiment, under special circumstances, the current factory needs to switch the products it produces, which changes the supply chain of the current factory. To handle this situation, the present application embodiment discloses a third method for updating the inventory management strategy. Figure 4 , the method comprising: Step S401: When the target factory is not determined among other factories, the inventory information of the current factory is counted, and the inventory information includes material types and material quantities.

[0088] If the target factory is not determined in other factories, it means that other factories are also unable to provide the materials required by the current factory. Therefore, in this embodiment, in order to ensure that the current factory is in production, the current factory can choose to perform other production tasks.

[0089] Step S402: Obtain the production tasks of the current factory.

[0090] The production tasks include at least one of the product type, the equipment required for production, and the production process.

[0091] Step S403: Compare the inventory information and the production tasks to obtain candidate production tasks that match the inventory information.

[0092] The candidate production task is a production task that can be completed by the current factory under the premise of inventory information. For example, according to the actual demand of the production task, it is determined whether the inventory information meets the above actual demand. If so, the production task is set as a candidate production task; if not, the next production task is determined.

[0093] Step S404: Use the inventory information to score the candidate production tasks to obtain the scoring scores of the candidate production tasks.

[0094] The scoring score is used to indicate the executability of the candidate production task. The higher the scoring score, the easier it is to execute the candidate production task corresponding to the scoring score.

[0095] Exemplarily, a scoring model is called to score the candidate production tasks according to the inventory information and the candidate production tasks to obtain a scoring score for the candidate production tasks.

[0096] Step S405: Determine the target production task corresponding to the maximum value of the scoring score.

[0097] In this step, the target production task corresponding to the maximum value in the scoring score is selected, and the production task of the current factory is updated to the target production task, so that the target production task can be executed and completed by the current factory.

[0098] Step S406: Update the actual production task of the current factory from the current production task to the target production task, and update the inventory management strategy according to the target production task.

[0099] Exemplarily, the actual production task of the current factory is updated from the current production task to the target production task, and the inventory management strategy is updated according to the actual demand of the target production task.

[0100] By adopting the above technical solution, when the inventory is insufficient to produce the current product, the current factory's production task can be modified to the target production task to ensure the normal production of the factory, which significantly improves the intelligence and real-time level of supply chain optimization and provides important support for resource management and operational efficiency improvement of industrial manufacturing enterprises.

[0101] In the following embodiments, while optimizing the supply chain, materials need to be transferred to ensure smooth production. Therefore, the present application embodiment discloses a material transfer method based on supply chain optimization. Figure 5 , the method comprising: Step S501: Obtain supply chain differences based on differences between current production tasks and target production tasks.

[0102] Supply chain differences are used to indicate the difference between the supply chain used to complete the current production task and the target production task. Supply chain differences can be reflected in the difference in the types of materials used in the supply chain, the difference in the quantity of materials, the supply chain process, etc.

[0103] Step S502: Obtain the material update difference of the current factory according to the inventory information and the supply chain difference.

[0104] The actual inventory information of materials is obtained from each inventory warehouse, including the current quantity and inventory distribution of various raw materials, semi-finished products, finished products and auxiliary materials. This inventory information can reflect the current inventory level of the factory. Then, combined with the supply chain differences found in step S501, the gap between the materials required for the target production task and the current inventory is analyzed. For example, if the target production task includes more production of product A, and the raw materials required for product A are insufficient in the current inventory, the difference in material update will be identified.

[0105] Material update differences are not limited to quantity gaps, but may also involve adjustments to material types. For example, if the target task adds a new production demand for product B, but the factory is currently unable to prepare the special raw materials or parts required for product B, the shortage of these materials will be automatically calculated. Based on these differences, a material update requirement list is generated to prepare for subsequent material transfer, procurement, and scheduling.

[0106] Step S503: Calculate the material transfer method according to the material update difference and the material quantity of each inventory warehouse of the current factory.

[0107] For example, based on the material update difference and the material quantity of each inventory warehouse of the current factory, a comprehensive analysis is conducted on the material inventory of each inventory warehouse to determine which inventory warehouses have excess materials and which inventory warehouses have shortages. By analyzing the distribution of inventory, production line requirements and material flow routes, a material transfer list is generated and the optimal way of material transfer is determined.

[0108] Step S504: Update the inventory management strategy according to the material transfer method.

[0109] Exemplarily, the material transfer method replaces the content in the inventory management policy, thereby achieving an update of the inventory management policy.

[0110] Exemplarily, by adopting the above technical solution, the inventory management strategy can be updated according to the material transfer method, so that the factory's inventory level is kept within a reasonable range, the inventory, production and logistics strategies are optimized, and the inventory backlog and logistics costs are reduced.

[0111] In the following embodiments, when optimizing the supply chain, it is necessary to make a more accurate prediction of future demand to ensure that the supply chain can keep up with market changes in a timely manner. The present application embodiment discloses a method for predicting supply chain demand. Figure 6 , the method comprising: Step S601: Count historical product demands of the supply chain in similar periods of the historical period.

[0112] Historical product demand is the total market demand for the corresponding product in the supply chain.

[0113] Similar periods are located in historical periods. Similar periods are proper subsets of historical periods. For example, historical market demand refers to the total amount of the first product purchased by the market on March 1 last year.

[0114] Step S602: Count the current product demand of the supply chain in the current period, where the current period corresponds to a similar period.

[0115] Optionally, based on the current time point as the midpoint of the current period, take the preset time length as the interval length of the current period to obtain the current period. Then, the current period includes a left endpoint and a right endpoint, and the sales volume of the first product from the left endpoint to the current time point is counted. Call the product sales forecasting model, process the data of the first product sales, and obtain the sales volume of the second product from the current time point to the right endpoint. Combine the sales volume of the first product and the sales volume of the second product to obtain the current product demand change. The current product demand change describes the market demand for the product in the current period corresponding to the left endpoint to the right endpoint.

[0116] Specifically, the current period is March 1 to March 7, and the similar period was March 1 to March 7 last year.

[0117] Step S603: Integrate historical product demands and current product demands to obtain theoretical product demands of the supply chain.

[0118] Theoretical product demand refers to the quantity of product demanded by the market (or customers) in the future period.

[0119] Optionally, the average of the current product demand changes is calculated to obtain the current product demand. The historical product demand and the current product demand are weighted to obtain the theoretical product demand of the supply chain.

[0120] Optionally, based on similar periods of historical product demand, target current product data for similar periods is determined in the current product demand change situation. The mean of the historical product demand and the target current product data is calculated, and the target current product data in the current product demand change situation is replaced with the aforementioned mean to obtain the theoretical product demand.

[0121] Step S604: Use theoretical product demand to update multi-dimensional data.

[0122] Exemplarily, the order demand in the multi-dimensional data is updated using the theoretical product demand.

[0123] By adopting the above technical solutions, inventory strategies can be dynamically adjusted based on historical product demand and current product demand to reduce inventory costs.

[0124] In the following embodiments, in order to reduce the use cost of relevant personnel, the present application also provides a solution for collaborative processing in combination with natural language. Therefore, the present application embodiment discloses a supply chain optimization method based on natural language. Figure 7 , the method comprising: Step S701: In response to receiving a natural language input operation, calling a semantic recognition model to perform semantic recognition processing on the natural language to obtain natural language semantics corresponding to the natural language.

[0125] Optionally, the input operation includes a user's command, request, question or other interaction method. The natural language input content includes information about inventory, supply chain requirements, transportation, product specifications, etc.

[0126] The speech recognition model is based on natural language processing technologies, such as deep learning, neural networks, and machine learning. The core task of the semantic recognition model is to perform grammatical analysis and semantic parsing of the input natural language, and identify entities, relationships, and intentions related to the input. For example, if the natural language input by the user is "increase the inventory of product A to 1,000 pieces", the semantic recognition model recognizes that "increase" is an action, "product A" is an entity, "inventory" is a management item, and "1,000 pieces" is the target quantity. The semantic recognition model can convert natural language into structured semantic information that can be understood and processed by machines.

[0127] Step S702: Perform feature extraction operations on natural language semantics to obtain a language semantic feature matrix.

[0128] In this step, the semantics of natural language need to be converted into numerical features so that the subsequent processing model can effectively perform calculations and analysis. Feature extraction is a very important step that determines the operability and accuracy of semantic data in subsequent processing.

[0129] For example, key information extracted from natural language, such as entities, actions, time, quantity, etc., is converted into a semantic feature matrix. The semantic feature matrix is ​​a high-dimensional vector representation that captures the relevance and influence of each important factor in the input sentence. Each word or phrase can be mapped to a vector space, and then these vectors are combined into a matrix.

[0130] For example, for the natural language "increase the inventory of product A to 1,000 pieces", the feature extraction process includes: Increase: action keyword, converted into "incremental" type features. Product A: product entity, which is converted into a vector of a specific product category. Inventory: inventory-related features, representing the object of management. 1,000 pieces: target quantity feature, indicating the required inventory adjustment quantity. After the above features are extracted, a feature matrix will be formed. Each element in the matrix represents the weight, type or semantics of a part of the information in the input.

[0131] Step S703: calling the supply chain optimization model, performing data processing on the language semantic feature matrix, and obtaining a semantic inventory management strategy.

[0132] The supply chain optimization model adopts a general large model. The general large model is a model that integrates multiple functions. Exemplarily, the supply chain optimization model integrates functions such as natural language processing, reasoning and decision support, and multimodal capabilities.

[0133] Step S704: updating the inventory management policy according to the semantic inventory management policy.

[0134] Exemplarily, if there are mutually exclusive parts between the semantic inventory management strategy mode and the inventory management strategy, the semantic inventory management strategy mode is used to replace the mutually exclusive parts.

[0135] By adopting the above technical solutions, the supply chain optimization method can support natural language interaction, simplifying the difficulty of supply chain optimization and significantly improving the intelligence and real-time level of supply chain optimization.

[0136] Based on the same inventive concept, the present application embodiment provides a supply chain optimization system, please refer to Figure 8 ,include: Acquisition module 801, used to acquire multi-dimensional data, management rules, supply chain optimization models, actual supply chain solutions, remaining available inventory, material inventory margins, path planning models, inventory information, production tasks, historical product demand, current product demand, and natural language; Memory 802, used to store a program of any one of the above supply chain optimization methods; Processor 803, the program in the memory can be loaded and executed by the processor to implement any of the above supply chain optimization methods.

[0137] By adopting the above technical solution, we can collect multi-dimensional data and management rules of the supply chain, and obtain the target supply chain solution through the supply chain optimization model. Then, we can compare the target supply chain solution with the actual supply chain solution and update the supply chain inventory management solution strategy. This technical solution can introduce the supply chain optimization model, significantly improving the intelligence and real-time level of supply chain optimization, and providing important support for resource management and operational efficiency improvement of industrial manufacturing enterprises.

[0138] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0139] An embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute a supply chain optimization method.

[0140] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0141] Based on the same inventive concept, an embodiment of the present application provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute a supply chain optimization method.

[0142] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0143] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A supply chain optimization method, characterized in that: The method comprises: Collect multi-dimensional data on each link of the current factory's supply chain; Performing preprocessing and feature extraction operations on the multi-dimensional data to obtain a multi-dimensional feature matrix; extracting management rules for the supply chain; Performing feature extraction operation on the management rules to obtain a management rule feature matrix; Calling the supply chain optimization model, performing data processing on the multi-dimensional feature matrix and the management rule feature matrix, and obtaining a target supply chain solution corresponding to the supply chain; Collecting actual supply chain solutions for said supply chain; The inventory management strategy of the supply chain is updated according to the difference between the target supply chain solution and the actual supply chain solution.

2. The supply chain optimization method according to claim 1, characterized in that: The method further comprises: Calculating the difference between the target supply chain solution and the actual supply chain solution to obtain the material shortage amount of the supply chain; When the shortage of the material is less than the remaining available inventory of the current factory, count the available materials in each inventory warehouse of the current factory; According to the shortage amount of the materials and the available materials, a target inventory warehouse is selected so that the sum of the available materials in the target inventory warehouse is greater than the shortage amount of the materials; The inventory management strategy is updated using the available materials of the target inventory warehouse.

3. The supply chain optimization method according to claim 2, characterized in that: The method further comprises: In the case where the shortage of the material is greater than the remaining available inventory, a candidate factory is determined from the other factories according to the shortage of the material and the inventory balance of the material in other factories, and the inventory balance of the material corresponding to the candidate factory is greater than the shortage of the material; Counting the traffic parameters from the current factory to the candidate factory; Calling a path planning model to perform path planning according to the traffic parameters to obtain the shortest path from the candidate factory to the current factory; Obtaining the material transportation efficiency corresponding to the candidate factory according to the unit transportation volume, the material inventory balance and the shortest path corresponding to the candidate factory; The candidate factory corresponding to the minimum value of the material transportation efficiency is selected as the target factory; The inventory management policy is updated using the target plant.

4. The supply chain optimization method according to claim 3, characterized in that: The method further comprises: If the target factory is not determined in the other factories, collecting inventory information of the current factory, the inventory information including material types and material quantities; Obtaining the production task of the current factory; Comparing the inventory information with the production tasks to obtain candidate production tasks that match the inventory information; Scoring the candidate production tasks using the inventory information to obtain scoring scores for the candidate production tasks; Determine the target production task corresponding to the maximum value of the scoring scores; The actual production task of the current factory is updated from the current production task to the target production task, and the inventory management strategy is updated according to the target production task.

5. The supply chain optimization method according to claim 4, characterized in that: The method further comprises: Obtaining a supply chain difference according to a difference between the current production task and the target production task; Obtaining a material update difference of the current factory according to the inventory information and the supply chain difference; Calculate the material transfer method according to the material update difference and the material quantity of each inventory warehouse of the current factory; The inventory management strategy is updated according to the material transfer method.

6. The supply chain optimization method according to claim 2, characterized in that: The method further comprises: Counting historical product demand for the supply chain during similar periods of time in the historical period; Counting the current product demand of the supply chain in a current period, where the current period corresponds to the similar period; Integrate the historical product demand and the current product demand to obtain the theoretical product demand of the supply chain; The multi-dimensional data is updated using the theoretical product demand.

7. The supply chain optimization method according to claim 6, characterized in that: The method further comprises: In response to receiving an input operation of a natural language, calling a semantic recognition model to perform semantic recognition processing on the natural language to obtain natural language semantics corresponding to the natural language; Performing feature extraction operation on the natural language semantics to obtain a language semantic feature matrix; Calling the supply chain optimization model, performing data processing on the language semantic feature matrix, and obtaining a semantic inventory management strategy; The inventory management policy is updated according to the semantic inventory management policy approach.

8. A supply chain optimization system, characterized in that: The system comprises: The acquisition module is used to obtain multi-dimensional data, management rules, supply chain optimization models, actual supply chain solutions, remaining available inventory, material inventory margins, path planning models, inventory information, production tasks, historical product demand, current product demand, and natural language; A memory for storing a program of the supply chain optimization method according to any one of claims 1 to 7; The program in the memory can be loaded and executed by the processor to implement the supply chain optimization method as described in any one of claims 1 to 7.

9. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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