Material management system and method

Abstract

The invention relates to the technical field of computers, in particular to a material management system and method. The material management system provided by the invention comprises a material whole-course tracking module, a comprehensive recommendation module, a replacement demand prediction module and an inventory optimization module, wherein the material whole-course tracking module is used for predicting the inventory variation of materials; the comprehensive recommendation module is used for generating close placement suggestion information and warehouse-out recommendation information of each material article; the replacement demand prediction module is used for determining the replacement demand information of the vehicle for different goods and supplies based on the historical use information of any vehicle, and performing early warning when a replacement demand is triggered; and the inventory optimization module is used for formulating an inventory optimization strategy of the goods and materials based on the sales data and the inventory change data of any goods and materials. Therefore, the material management system provided by the invention can greatly improve the efficiency and accuracy of warehouse management through the functions of whole-course tracking, intelligent analysis, intelligent prediction and the like.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a material management system and method. Background Art

[0002] Chengyun Automobile Company hopes to improve the warehouse management level of its auto repair parts. The existing system simply records the in and out information of parts and lacks intelligent functions. Therefore, it is urgent to develop a new material management system to make warehouse management more efficient.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0004] In view of this, the embodiments of the present application at least provide a material management system and method, which can greatly improve the efficiency and accuracy of warehouse management.

[0005] This application mainly includes the following aspects: In a first aspect, an embodiment of the present application provides a material management system, which includes a material full-process tracking module, a comprehensive recommendation module, a replacement demand prediction module, and an inventory optimization module; wherein: The material tracking module is used to record and monitor the material from procurement, delivery, allocation, and use based on the global identification of any material. It also predicts the inventory change of the material. The comprehensive recommendation module is used to generate adjacent placement suggestion information and outbound recommendation information for each material supply based on the outbound record data of each material supply; The replacement demand prediction module is used to determine the replacement demand information of the vehicle for different supplies based on the historical usage information of any vehicle, and issue an early warning when the replacement demand is triggered; The inventory optimization module is used to formulate an inventory optimization strategy for the supplies based on the sales data and inventory change data of any of the supplies.

[0006] In a second aspect, an embodiment of the present application further provides a material management method, the method comprising: Based on the global identification of any material supply, the material supply from procurement, delivery, allocation, and use is recorded and monitored, and the inventory change of the material supply is predicted; Based on the outbound record data of each material and supply, generate the adjacent placement suggestion information and outbound recommendation information of each material and supply; Based on the historical usage information of any vehicle, determine the replacement requirements of the vehicle for different supplies and give an early warning when the replacement requirements are triggered; Based on the sales data and inventory change data of any of the supplies, an inventory optimization strategy for the supplies is formulated.

[0007] In the third aspect, an embodiment of the present application also provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the material management method described in any possible implementation manner of the second aspect above.

[0008] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the material management method described in any possible implementation manner of the second aspect above are executed.

[0009] The material management system and method provided in the embodiment of the present application include a material full-process tracking module, a comprehensive recommendation module, a replacement demand prediction module and an inventory optimization module. The material full-process tracking module is used to predict the inventory change of material supplies; the comprehensive recommendation module is used to generate adjacent placement suggestion information and outbound recommendation information for each material supply; the replacement demand prediction module is used to determine the replacement demand information of the vehicle for different material supplies based on the historical usage information of any vehicle, and to issue an early warning when the replacement demand is triggered; the inventory optimization module is used to formulate an inventory optimization strategy for materials and supplies based on the sales data and inventory change data of any material supply. Compared with the management system in the prior art that simply records the in and out warehouse information of accessories and lacks intelligent functions, the material management system provided by the present application can greatly improve the efficiency and accuracy of warehouse management through functions such as full-process tracking, intelligent analysis and intelligent prediction.

[0010] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 A schematic diagram of the structure of a material management system provided in an embodiment of the present application is shown; Figure 2 A flow chart of a material management method provided in an embodiment of the present application is shown; Figure 3 A flow chart showing another material management method provided in an embodiment of the present application is shown; Figure 4 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0013] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art, under the guidance of the content of the present application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0014] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0015] In order to enable those skilled in the art to use the contents of this application, the following implementation methods are given in combination with the specific application scenario of "material management". For those skilled in the art, the general principles defined here can be applied to other embodiments and application scenarios without departing from the spirit and scope of this application.

[0016] The following methods, devices, electronic devices or computer-readable storage media of the embodiments of the present application can be applied to any scenario requiring material management. The embodiments of the present application are not limited to specific application scenarios. Any scheme using the material management system and method provided by the embodiments of the present application is within the scope of protection of the present application.

[0017] It is worth noting that before this application was filed, Chengyun Automobile Company hoped to improve its warehouse management level for auto repair parts. The existing system simply records the in and out information of parts and lacks intelligent functions. Therefore, it is urgent to develop a new material management system to make warehouse management more efficient.

[0018] In view of the above problems, the material management system provided by the embodiment of the present application includes a material full-process tracking module, a comprehensive recommendation module, a replacement demand prediction module and an inventory optimization module. The material full-process tracking module is used to predict the inventory change of materials and supplies; the comprehensive recommendation module is used to generate adjacent placement suggestion information and outbound recommendation information for each material and supply; the replacement demand prediction module is used to determine the replacement demand information of the vehicle for different materials and supplies based on the historical use information of any vehicle, and to issue an early warning when the replacement demand is triggered; the inventory optimization module is used to formulate the inventory optimization strategy of materials and supplies based on the sales data and inventory change data of any material and supply. In this way, the material management system provided by the present application can greatly improve the efficiency and accuracy of warehouse management through functions such as full-process tracking, intelligent analysis and intelligent prediction.

[0019] To facilitate the understanding of the present application, the technical solution provided by the present application is described in detail below in conjunction with specific embodiments.

[0020] Figure 1 This is a schematic diagram of the structure of a material management system 100 provided in an embodiment of the present application. Figure 1 As shown, the material management system 100 provided in the embodiment of the present application includes a material full-process tracking module 110, a comprehensive recommendation module 120, a replacement demand prediction module 130 and an inventory optimization module 140; wherein, The material tracking module 110 is used to record and monitor the material from procurement, delivery, allocation, and use based on the global identification of any material. It also predicts the inventory change of the material. The comprehensive recommendation module 120 is used to generate adjacent placement suggestion information and outbound recommendation information for each material supply based on outbound record data of each material supply; The replacement demand prediction module 130 is used to determine the replacement demand information of the vehicle for different supplies based on the historical usage information of any vehicle, and issue an early warning when the replacement demand is triggered; The inventory optimization module 140 is used to formulate an inventory optimization strategy for the supplies based on the sales data and inventory change data of any of the supplies.

[0021] It should be noted that the material management system 100 provided in the embodiment of the present application mainly has the following functions: Function 1. Full material tracking: From the purchase of materials such as accessories to warehousing, outbound delivery, allocation, and final use, the material management system 100 will record the operations of each link in detail to ensure that all steps can be traced.

[0022] Function 2. Data-driven decision support: The material management system 100 will provide real-time data reports through intelligent analysis to help users make better decisions, such as providing nearby placement suggestions and outbound delivery recommendations.

[0023] Function 3. Intelligent prediction and recommendation: The material management system 100 can predict the demand trend of accessories and recommend materials and supplies accordingly to help optimize inventory levels.

[0024] Function 4. Automated process: The material management system 100 will automatically handle daily material management tasks, reduce human errors and improve work efficiency.

[0025] Specifically, the material tracking module 110 is mainly used for chain tracking of materials (i.e., goods, accessories, etc.): each material will generate unique batch information from the beginning of procurement, and the supplier will also use this information when shipping. After receiving the goods, the consignee will print this information into a label and stick it on the material. In this way, each material has a unique identification (global identification) to facilitate full tracking.

[0026] In one example, when the material management system 100 places an order for supplies to a supplier, batch information is generated according to the material type dimension. The supplier can also use the current system to confirm the order and ship the goods. After the supplier ships the goods in batches according to the material type, the consignee can sign for the supplies according to the batch. When signing for the goods, the system generates a unique ID (global identification) data for the supplies in the batch. The consignee can print the batch ID data into a label and affix the label to the supplies. In this way, the supplies have a unique identification. If the supplies are sold, transferred, returned or exchanged, the system will carry the unique identification of the supplies to achieve traceability of the supplies.

[0027] In the embodiment of the present application, the material management system 100 provided by the present application includes a material full-process tracking module 110, a comprehensive recommendation module 120, a replacement demand prediction module 130 and an inventory optimization module 140. The material full-process tracking module 110 is used to predict the inventory change of materials and supplies; the comprehensive recommendation module 120 is used to generate adjacent placement suggestion information and outbound recommendation information for each material and supply; the replacement demand prediction module 130 is used to determine the replacement demand information of the vehicle for different materials and supplies based on the historical use information of any vehicle, and to issue an early warning when the replacement demand is triggered; the inventory optimization module 140 is used to formulate an inventory optimization strategy for materials and supplies based on the sales data and inventory change data of any material and supply. In this way, the material management system 100 provided by the present application can greatly improve the efficiency and accuracy of warehouse management through functions such as full-process tracking, intelligent analysis and intelligent prediction.

[0028] In a possible implementation, the material tracking module 100 is specifically used to predict the inventory change of the material supplies according to the following steps: predicting the inventory change of the material supplies according to the purchase quantity, delivery quantity, and allocation quantity of the material supplies within a preset time period, and the degree of their respective impact on the inventory change.

[0029] In specific implementation, in the process of material management, a linear regression analysis algorithm can be used to predict the inventory changes of materials and supplies. Specifically, procurement in the business represents the "in" of material management, and outbound and transfer represent the "outbound". By analyzing the relationship between variables such as procurement volume, outbound volume and transfer volume within a preset time period, a model can be constructed to predict the inventory changes of materials and supplies within the preset time period in the future.

[0030] In a possible implementation, the calculation formula for predicting the inventory change of the supplies is: ; in, is the inventory change, For the purchase volume, For the outbound quantity, For the allocation amount, is the initial inventory quantity, which indicates the inventory change when the purchase quantity, outbound quantity and transfer quantity are all zero. , , are coefficients, Indicates the impact of purchase volume on inventory changes, Indicates the impact of outbound volume on inventory changes. Indicates the degree of influence of transfer quantity on inventory changes. is the error term.

[0031] here, is the inventory change, i.e. the predicted inventory increase or decrease; is the purchase volume, which indicates the quantity of materials purchased within a certain period of time; It is the outbound quantity, which indicates the quantity of materials outbound in a certain period of time; is the transfer quantity, which indicates the amount of materials transferred within a certain period of time (which may include transfers from one warehouse to another); is the intercept term, which represents the inventory change when the purchase, outbound and transfer quantities are all zero; , , are coefficients, which respectively represent the influence of purchase quantity, outbound quantity and transfer quantity on inventory change; is the error term, which represents the random variation that cannot be explained by the model.

[0032] In a possible implementation, the material tracking module 100 is further used to minimize the prediction error value according to the least squares method, and determine the numerical values ​​corresponding to the influence of the purchase quantity on the inventory change, the influence of the outbound quantity on the inventory change, and the influence of the transfer quantity on the inventory change; the calculation formula of the prediction error value is: ; in, is the prediction error value, represents a set of data points, , is a positive integer, is the number of data sets.

[0033] In the specific implementation, , , The coefficient estimation is based on the least squares method, assuming that a set of data points ,in , For specific data values, the goal of using the least squares method is to find the coefficients , , Make the prediction error Minimum, that is, the sum of squares of values ​​is minimum.

[0034] Here, the coefficient , , The estimate of can be calculated using the following matrix formula: ; in, is the design matrix, each row represents an observation, and the columns contain 1, ; is a vector containing the inventory changes of all observations ; is the estimated value of the coefficient. It should be noted that the goal of the least squares method is to find a set of coefficients , so that and The difference between them is the smallest, and this difference can be expressed by the sum of squared errors, which can be defined as , by solving the normal equation , determine the coefficients that minimize the sum of squared errors , calculate the coefficient It is calculated by the above matrix formula, that is, first calculate the design matrix The transpose of The product of itself, and then calculate the design matrix The transpose and vector The product of The inverse matrix of The transpose and vector The product of Multiply the inverse matrix of to get the estimated values ​​of the coefficients.

[0035] In a possible implementation, the comprehensive recommendation module 120 is specifically configured to generate adjacent placement recommendation information and outbound recommendation information of any of the supplies according to the following steps: Obtain the outbound record data of each material and supplies; the outbound record data includes outbound time, outbound quantity, and outbound combination data; the outbound combination data is the record data of any at least two materials and supplies being outbound together; Based on the outbound record data of each of the materials and supplies, determining the outbound mode characteristics of each of the materials and supplies and the association rules between any at least two materials and supplies; the outbound mode characteristics include the outbound frequency of materials and the combination frequency of materials; Based on the outbound mode characteristics of each of the materials and supplies, the materials and supplies are clustered to obtain multiple material clusters, and the same adjacent placement suggestion information is formulated for the materials and supplies in each material cluster; each material cluster includes at least two materials and supplies with similar outbound mode characteristics; For any of the material clusters, determining at least one similar material combination from the material cluster; Based on the generated material combination and the association rules, the recommended outbound information of each material supply is determined.

[0036] In a specific implementation, the following steps are used to generate the adjacent placement recommendation information and outbound recommendation information of any material supplies, wherein the adjacent placement recommendation information may refer to which items are recommended to be placed adjacent to when the items are put into the warehouse, for example, placing items with the same outbound frequency adjacent to each other. Outbound recommendation information refers to information that makes the recommended outbound materials have obvious correlations. For example, when outbound materials are needed, when outbound of a material, other materials that are often associated with the material can be recommended for outbound. Specifically, the following steps are included: Step 1: Data preparation, collect the outbound record data of materials and supplies, which includes outbound time, outbound quantity, and outbound combination data. The outbound combination data records the combination of materials and supplies, so as to analyze the outbound mode of materials and supplies. The above data can be collected from the material management system 100 or the outbound log to ensure that the data is complete and updated to the latest state. In addition, identify which materials and supplies are often outbound together in order to understand the correlation between materials and supplies. By analyzing the outbound time series of materials and supplies, it is possible to record which materials and supplies are outbound together at a similar time and construct a combination table of materials and supplies.

[0037] Step 2: Extract features and convert the original data (outbound record data) into a form that the algorithm can understand, including the outbound frequency of materials and supplies, the material combination frequency, etc. The material outbound frequency is the average outbound frequency of each material and supply, and the material combination frequency is the frequency of occurrence of the material and supply combination, that is, the frequency of occurrence of a specific combination within a certain period of time.

[0038] Step 3: Clustering statistics. You can use the K-means clustering algorithm to cluster supplies, that is, group them. The supplies in each group have similar delivery patterns. Specifically, first determine the number of clusters K, which usually requires determining the optimal K value based on business needs or through the elbow rule. Apply the K-means clustering algorithm to group supplies. The algorithm will assign supplies to different clusters based on characteristics (such as the frequency of material delivery).

[0039] In one example, various supplies are clustered to obtain multiple material clusters. The K-means clustering algorithm can be used, and the cluster center update formula is: ; Representative The center point of each cluster; Represents a single data point in a data set; supplies To cluster center Distance ; n represents the base That is, each material item is described as a vector with n features. is an index used to traverse data points All features of , which usually range from 1 to n; Representative data points In the The value of the dimension; represent In the The value of the dimension. similar, It is also a component of the cluster center eigenvector.

[0040] Step 4: Determine the material combination. You can use the K-Nearest Neighbors (KNN) algorithm to find similar material combinations and identify similar combinations of materials in each cluster to provide a basis for recommendation. Specifically, for each cluster, use the KNN algorithm to find the most similar material combination. The K value can be adjusted according to business needs and data volume. The KNN algorithm will determine the most similar materials based on the frequency and similarity scores of material combinations.

[0041] In one example, for any material cluster, a KNN algorithm can be used to determine at least one similar material combination from the material cluster. For any two materials in the material cluster, based on the cosine similarity between the outbound mode features of the two materials, it is determined whether they belong to a similar material combination: ;in, Represents the characteristics of a material outbound mode. In the material management system 100, this vector may include characteristics such as the outbound frequency of the material, the outbound combination of the material and the commodity (such as the material combination frequency), and the outbound time distribution. Represents the outbound mode characteristics of another material supply. resemblance, It also includes outbound mode features.

[0042] Step 5: Determine association rules, mine frequent item sets and strong association rules, discover strong associations between supplies from the data, and enhance the accuracy and relevance of recommendations. Here, you can use the Apriori algorithm or other association rule algorithms to discover frequent item sets (a group of supplies are often shipped together) and strong association rules (the appearance of a specific supply predicts the appearance of another supply) from the supply delivery data.

[0043] Step 6: Comprehensive recommendation, combining clustering, KNN algorithm and association rule learning, comprehensively using clustering results, similar material supply combinations and association rules to generate specific material supply placement suggestions and outbound recommendations.

[0044] Here, the embodiment of the present application can recommend that each material in the same material cluster be placed close to each other based on the K-means clustering algorithm, and optimize the placement layout by combining the similar material combinations determined by the KNN algorithm and considering the frequency and combination of material outbound. The results of association rule learning are applied to ensure that there is a clear correlation between the recommended materials to improve inventory management efficiency.

[0045] Step 7: Storage and output. The processed material and supplies attribute data is used in the subsequent decision support system. Specifically, the calculation results are attached to the material and supplies attribute data, including the material cluster to which the material and supplies belong, the recommended placement location, and the recommended outbound delivery information. This information can be stored in a database or report form to facilitate subsequent query and analysis. The recommended results are output for reference by warehouse managers to guide the optimization of the storage and outbound delivery process of materials and supplies.

[0046] In a possible implementation, the association rules include frequent item set support, rule confidence and rule gain; the frequent item set support of any of the supplies is the ratio of the transaction quantity of the supplies to the total transaction quantity of all supplies; the rule confidence of the supplies is the ratio of the transaction quantity of any two supplies including the supplies appearing at the same time to the transaction quantity of the supplies appearing; the rule gain of the supplies is the ratio of the rule confidence of the supplies to the frequent item set support.

[0047] In the specific implementation, the calculation formula of the frequent item set support is ; The calculation formula for rule confidence is ; The calculation formula of rule gain is .

[0048] In a possible implementation, the replacement demand prediction module 130 is specifically used to determine the replacement demand information of the vehicle for different supplies according to the following steps: obtaining the historical usage information of the vehicle; the historical usage information includes the age of the vehicle, mileage and vehicle model; for any of the supplies, determining whether the vehicle needs to replace the supplies based on the historical usage information of the vehicle and the replacement rules of the supplies; if it is determined that replacement is required, issuing a demand warning for the supplies to the vehicle.

[0049] In a possible implementation, the replacement rule includes a replacement function of years and a replacement function of mileage; the replacement demand prediction module 130 is specifically used to determine whether the vehicle needs to replace the supplies according to the following steps: Determine the warning value of the supplies according to the age replacement function, the mileage replacement function, the age weight and the mileage weight of the supplies; If the warning value of the supplies is greater than a preset threshold, or the age of the vehicle is greater than an age threshold, or the mileage is greater than a mileage threshold, it is determined that the vehicle needs to replace the supplies; The calculation formula of the warning value is: , is the warning value, Replace the function for the said period, is the mileage replacement function, is the age weight, is the mileage weight, is the age of the vehicle, For mileage.

[0050] Specifically, and It is a function designed according to the replacement rules of accessories. It can be linear, polynomial or exponential. For example, if the replacement of accessories is mainly affected by age, Can be A linear function of: ; If the replacement of parts is mainly affected by mileage, Can be The exponential function of : ; Weight and It can be adjusted according to actual conditions to reflect the relative importance of age and mileage to the need for replacement parts. Exceeds a preset threshold A warning is triggered if the age of the vehicle exceeds the age threshold for parts replacement, or if the mileage exceeds the mileage threshold for parts replacement.

[0051] In the specific implementation, according to the existing vehicle data (vehicle age, mileage and vehicle model) and the vehicle parts replacement process, the parts demand is planned and early warning is provided. Specifically, the following steps are included: Step 1. Data collection: Collect historical vehicle usage information, including vehicle age (number of years in use), mileage (mileage), and vehicle model. Replacement rule definition for accessories (supplies): Define the replacement cycle for different accessories, which can be a fixed time period or mileage, or a combination of the two. For example, some accessories may be replaced every 5 years or every 100,000 kilometers.

[0052] Step 2: Weight assignment: Assign different weights to vehicle age and mileage to determine their impact on the demand for parts replacement. For example, if the replacement of a part is mainly affected by mileage, the weight of mileage may be higher.

[0053] Step 3: Threshold setting: Set one or more thresholds. When the calculation results exceed these thresholds, an early warning is triggered.

[0054] In a possible implementation, the inventory optimization module 140 is specifically configured to formulate the inventory optimization strategy for the supplies according to the following steps: Obtaining the initial inventory and historical sales data of the supplies; Based on the historical sales data of the supplies, determine the predicted sales volume of the supplies in the tth time period; t is a positive integer; Determine the safety stock of the supplies in the tth time period according to the sales volume forecast standard deviation of the supplies, the sales volume confidence value of the normal distribution and the average delivery time of the supplier; Determine the order quantity of the supplies in the tth time period according to the demand arrival rate of the supplies, the predicted sales volume corresponding to the tth time period, and the safety stock volume; Determine whether the sum of the inventory quantity of the supplies at the end of the tth time period and the inventory replenishment quantity in the t-1th time period is less than the order quantity in the tth time period; If so, determine the inventory replenishment quantity of the supplies in time period t; Determine the total inventory replenishment cost of the supplies in the tth time period based on the inventory replenishment quantity of the supplies in the tth time period; With the goal of minimizing the total cost of replenishing inventory, the sales volume confidence value of the supplies and / or the predicted sales volume in the tth time period are adjusted to formulate an inventory optimization strategy for the supplies.

[0055] In specific implementation, optimize inventory levels based on sales data and forecasts to improve inventory turnover and reduce out-of-stocks. Specifically, initialize inventory levels (initial inventory quantity) and historical sales data ; For each time period t from 1 to T3, use the historical sales data to predict the predicted sales volume for the 𝑡th time period ; Calculate the predicted standard deviation , and determine the confidence value Z of the normal distribution sales volume based on the service level; predict the standard deviation of the sales volume of supplies , the sales confidence value Z of the normal distribution and the average supplier delivery time D, calculate the safety stock corresponding to the tth time period , ; Determine the demand arrival rate , calculate the reorder point (order quantity in time period t), ,if If the inventory needs to be replenished, calculate the inventory replenishment quantity of the supplies in the tth time period. , ; Update stock levels ; Record inventory replenishment Used for cost calculation, calculate the total cost of replenishing inventory Specifically, this can be done by optimizing the sales confidence value Z or adjusting the predicted sales volume for the tth time period. To minimize , , T3 is the total time period, is the actual sales volume in the tth time period, is the predicted sales volume for the tth time period, is the holding cost per unit of goods (annualized), is the out-of-stock cost per unit of commodity, is the inventory level at the end of the tth time period, is the inventory replenishment quantity in the tth time period, D is the average delivery time of the supplier (in time period), is the purchase cost per unit of goods. The economic order quantity (EOQ) calculation formula is: .

[0056] Based on the same application concept, the embodiments of the present application also provide a material management method corresponding to the material management system provided in the above embodiments. Since the principle of solving the problem by the method in the embodiments of the present application is similar to that of the material management system in the above embodiments of the present application, the implementation of the method can refer to the implementation of the system, and the repeated parts will not be repeated.

[0057] Figure 2 A flow chart of a material management method provided in an embodiment of the present application is shown; Figure 2 As shown, the material management method includes the following steps: S201: Based on the global identification of any material supply, the material supply from procurement, delivery, allocation, and use is recorded and monitored, and the inventory change of the material supply is predicted; S202: Based on the outbound record data of each material and supply, generate adjacent placement suggestion information and outbound recommendation information for each material and supply; S203: Based on the historical usage information of any vehicle, determine the replacement demand information of the vehicle for different supplies and supplies, and issue an early warning when the replacement demand is triggered; S204: Formulate an inventory optimization strategy for the supplies based on the sales data and inventory change data of any of the supplies.

[0058] In one possible implementation, Figure 3 FIG. 1 is a flow chart showing another material management method provided in an embodiment of the present application; Figure 3 As shown, the material management method includes the following steps: S301: Based on the global identification of any material supplies, the material supplies are recorded and monitored from procurement, delivery, allocation, and use, and the inventory change of the material supplies is predicted according to the procurement quantity, delivery quantity, and allocation quantity of the material supplies within a preset time period, and the degree of influence of each on the inventory change; S302: Based on the outbound record data of each material and supplies, generate adjacent placement suggestion information and outbound recommendation information for each material and supplies; S303: Based on the historical usage information of any vehicle, determine the replacement demand information of the vehicle for different supplies and supplies, and issue an early warning when the replacement demand is triggered; S304: Formulate an inventory optimization strategy for the supplies based on the sales data and inventory change data of any of the supplies.

[0059] In a possible implementation, the calculation formula for predicting the inventory change of the supplies is: ; in, is the inventory change, For the purchase volume, For the outbound quantity, For the allocation amount, is the initial inventory quantity, which indicates the inventory change when the purchase quantity, outbound quantity and transfer quantity are all zero. , , are coefficients, Indicates the impact of purchase volume on inventory changes, Indicates the impact of outbound volume on inventory changes. Indicates the degree of influence of transfer quantity on inventory changes. is the error term.

[0060] In a possible implementation, the adjacent placement suggestion information and the outbound recommendation information of any of the supplies are generated according to the following steps: Obtain the outbound record data of each material and supplies; the outbound record data includes outbound time, outbound quantity, and outbound combination data; the outbound combination data is the record data of any at least two materials and supplies being outbound together; Based on the outbound record data of each of the materials and supplies, determining the outbound mode characteristics of each of the materials and supplies and the association rules between any at least two materials and supplies; the outbound mode characteristics include the outbound frequency of materials and the combination frequency of materials; Based on the outbound mode characteristics of each of the materials and supplies, the materials and supplies are clustered to obtain multiple material clusters, and the same adjacent placement suggestion information is formulated for the materials and supplies in each material cluster; each material cluster includes at least two materials and supplies with similar outbound mode characteristics; For any of the material clusters, determining at least one similar material combination from the material cluster; Based on the generated material combination and the association rules, the recommended outbound information of each material supply is determined.

[0061] In a possible implementation, the replacement requirement information of the vehicle for different supplies is determined according to the following steps: Acquiring historical usage information of the vehicle; the historical usage information includes vehicle age, mileage, and vehicle model; For any of the supplies, determining whether the vehicle needs to replace the supplies based on the historical usage information of the vehicle and the replacement rules of the supplies; If it is determined that replacement is required, an early warning of the need for the materials and supplies will be issued to the vehicle.

[0062] In a possible implementation, the replacement rule includes an age replacement function and a mileage replacement function; determining whether the vehicle needs to replace the supplies is performed according to the following steps: Determine the warning value of the supplies according to the age replacement function, the mileage replacement function, the age weight and the mileage weight of the supplies; If the warning value of the supplies is greater than a preset threshold, or the age of the vehicle is greater than an age threshold, or the mileage is greater than a mileage threshold, it is determined that the vehicle needs to replace the supplies; The calculation formula of the warning value is: , is the warning value, Replace the function for the said period, is the mileage replacement function, is the age weight, is the mileage weight, is the age of the vehicle, For mileage.

[0063] In a possible implementation, the inventory optimization strategy for the supplies is formulated according to the following steps: Obtaining the initial inventory and historical sales data of the supplies; Based on the historical sales data of the supplies, determine the predicted sales volume of the supplies in the tth time period; t is a positive integer; Determine the safety stock quantity of the supplies in the tth time period according to the sales volume forecast standard deviation of the supplies, the sales volume confidence value of the normal distribution and the average delivery time of the supplier; Determine the order quantity of the supplies in the tth time period according to the demand arrival rate of the supplies, the predicted sales volume and the safety stock volume corresponding to the tth time period; Determine whether the sum of the inventory quantity of the supplies at the end of the tth time period and the inventory replenishment quantity in the t-1th time period is less than the order quantity in the tth time period; If so, determine the inventory replenishment quantity of the supplies in time period t; Determine the total inventory replenishment cost of the supplies in the tth time period based on the inventory replenishment quantity of the supplies in the tth time period; With the goal of minimizing the total cost of replenishing inventory, the sales volume confidence value of the supplies and / or the predicted sales volume in the tth time period are adjusted to formulate an inventory optimization strategy for the supplies.

[0064] Based on the same application concept, see Figure 4 As shown, it is a structural diagram of an electronic device 400 provided in an embodiment of the present application, including: a processor 410, a memory 420 and a bus 430, the memory 420 stores machine-readable instructions executable by the processor 410, when the electronic device 400 is running, the processor 410 and the memory 420 communicate through the bus 430, and the machine-readable instructions are executed by the processor 410 when running, such as the steps of the material management method described in any of the above embodiments.

[0065] In the embodiments of the present application, based on the global identification of any material supply, the materials and supplies from procurement, delivery, allocation, and use are recorded and monitored, and the inventory changes of materials and supplies are predicted; based on the delivery record data of each material supply, the adjacent placement suggestion information and delivery recommendation information of each material supply are generated; based on the historical usage information of any vehicle, the vehicle's replacement demand information for different materials and supplies is determined, and an early warning is issued when the replacement demand is triggered; based on the sales data and inventory change data of any material supply, an inventory optimization strategy for materials and supplies is formulated. Through functions such as full-process tracking, intelligent analysis, and intelligent prediction, the efficiency and accuracy of warehouse management can be greatly improved.

[0066] Based on the same application concept, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the material management method provided in the above embodiment are executed.

[0067] Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, etc. When the computer program on the storage medium is run, the above-mentioned material management method can be executed. Through functions such as full-process tracking, intelligent analysis and intelligent prediction, the efficiency and accuracy of warehouse management can be greatly improved.

[0068] In the embodiment of the present application, the computer program can also execute other machine-readable instructions when run by the processor to execute other methods described in the embodiment. For the specific execution method steps and principles, please refer to the description of the embodiment, which will not be repeated here.

[0069] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0070] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0071] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0072] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0073] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance.

[0074] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A material management system, characterized in that: The material management system includes a material full-process tracking module, a comprehensive recommendation module, a replacement demand prediction module and an inventory optimization module; wherein, The material tracking module is used to record and monitor the material from procurement, delivery, allocation, and use based on the global identification of any material. It also predicts the inventory change of the material. The comprehensive recommendation module is used to generate adjacent placement suggestion information and outbound recommendation information for each material supply based on the outbound record data of each material supply; The replacement demand prediction module is used to determine the replacement demand information of the vehicle for different supplies based on the historical usage information of any vehicle, and issue an early warning when the replacement demand is triggered; The inventory optimization module is used to formulate an inventory optimization strategy for the supplies based on the sales data and inventory change data of any of the supplies.

2. The material management system according to claim 1, characterized in that: The material tracking module is specifically used to predict the inventory change of the material supplies according to the following steps: The inventory change of the materials and supplies is predicted based on the purchase volume, delivery volume, and transfer volume of the materials and supplies within a preset time period, as well as the degree of their respective impact on the inventory change.

3. The material management system according to claim 2, characterized in that: The calculation formula for predicting the inventory change of the supplies is: ； in, is the inventory change, For the purchase volume, For the outbound quantity, For the allocation amount, is the initial inventory quantity, which indicates the inventory change when the purchase quantity, outbound quantity and transfer quantity are all zero. , , are coefficients, Indicates the impact of purchase volume on inventory changes, Indicates the impact of outbound volume on inventory changes. Indicates the degree of influence of transfer quantity on inventory changes. is the error term.

4. The material management system according to claim 1, characterized in that: The comprehensive recommendation module is specifically used to generate the adjacent placement recommendation information and the outbound recommendation information of any of the materials and supplies according to the following steps: Obtain the outbound record data of each material and supplies; the outbound record data includes outbound time, outbound quantity, and outbound combination data; the outbound combination data is the record data of any at least two materials and supplies being outbound together; Based on the outbound record data of each of the materials and supplies, determining the outbound mode characteristics of each of the materials and supplies and the association rules between any at least two materials and supplies; the outbound mode characteristics include the outbound frequency of materials and the combination frequency of materials; Based on the outbound mode characteristics of each of the materials and supplies, the materials and supplies are clustered to obtain multiple material clusters, and the same adjacent placement suggestion information is formulated for the materials and supplies in each material cluster; each material cluster includes at least two materials and supplies with similar outbound mode characteristics; For any of the material clusters, determining at least one similar material combination from the material cluster; Based on the generated material combination and the association rules, the recommended outbound information of each material supply is determined.

5. The material management system according to claim 1, characterized in that: The replacement demand prediction module is specifically used to determine the replacement demand information of the vehicle for different supplies according to the following steps: Acquiring historical usage information of the vehicle; the historical usage information includes vehicle age, mileage, and vehicle model; For any of the supplies, determining whether the vehicle needs to replace the supplies based on the historical usage information of the vehicle and the replacement rules of the supplies; If it is determined that replacement is required, an early warning of the need for the materials and supplies will be issued to the vehicle.

6. The material management system according to claim 5, characterized in that: The replacement rule includes a replacement function of years and a replacement function of mileage; the replacement demand prediction module is specifically used to determine whether the vehicle needs to replace the supplies according to the following steps: Determine the warning value of the supplies according to the age replacement function, the mileage replacement function, the age weight and the mileage weight of the supplies; If the warning value of the supplies is greater than a preset threshold, or the age of the vehicle is greater than an age threshold, or the mileage is greater than a mileage threshold, it is determined that the vehicle needs to replace the supplies; The calculation formula of the warning value is: , is the warning value, Replace the function for the said period, is the mileage replacement function, is the age weight, is the mileage weight, is the age of the vehicle, For mileage.

7. The material management system according to claim 1, characterized in that: The inventory optimization module is specifically used to formulate the inventory optimization strategy of the supplies according to the following steps: Obtaining the initial inventory and historical sales data of the supplies; Based on the historical sales data of the supplies, determine the predicted sales volume of the supplies in the tth time period; t is a positive integer; Determine the safety inventory of the supplies in the tth time period according to the sales volume forecast standard deviation of the supplies, the sales volume confidence value of the normal distribution and the average delivery time of the supplier; Determine the order quantity of the supplies in the tth time period according to the demand arrival rate of the supplies, the predicted sales volume corresponding to the tth time period, and the safety stock volume; Determine whether the sum of the inventory quantity of the supplies at the end of the tth time period and the inventory replenishment quantity in the t-1th time period is less than the order quantity in the tth time period; If so, determine the inventory replenishment quantity of the supplies in time period t; Determine the total inventory replenishment cost of the supplies in the tth time period based on the inventory replenishment quantity of the supplies in the tth time period; With the goal of minimizing the total cost of replenishing inventory, the sales volume confidence value of the supplies and / or the predicted sales volume in the tth time period are adjusted to formulate an inventory optimization strategy for the supplies.

8. A material management method, characterized in that: Applied to any one of claims 1 to 7, the material management system, the method comprising: Based on the global identification of any material supply, the material supply from procurement, delivery, allocation, and use is recorded and monitored, and the inventory change of the material supply is predicted; Based on the outbound record data of each material and supply, generate the adjacent placement suggestion information and outbound recommendation information of each material and supply; Based on the historical usage information of any vehicle, determine the replacement requirements of the vehicle for different supplies and give an early warning when the replacement requirements are triggered; Based on the sales data and inventory change data of any of the supplies, an inventory optimization strategy for the supplies is formulated.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the material management method as described in claim 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the material management method according to claim 8 are executed.

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