Method and device for consuming stiff materials

Abstract

The invention discloses a dull material consumption method and device, and the method comprises the steps: determining at least one first configuration of at least one type of first products based on dull material information; wherein the first configuration represents the material configuration of the stiff material in the first product of the corresponding class; determining at least one second configuration of at least one type of second products from the at least one first configuration of the at least one type of first products based on the business data corresponding to the stiff material in each first configuration, and stiff material consumption information corresponding to each second configuration; and determining at least one target configuration of at least one type of target products from at least one second configuration corresponding to the at least one type of second products based on the stiff material consumption information.

Description

Technical Field

[0001] The present application relates to, but is not limited to, the field of computer technology, and in particular to a method and device for consuming obsolete materials. Background Art

[0002] Manufacturing companies usually need to prepare inventory in advance to cope with complex and changing consumer trends. However, due to possible order cancellations, poor product sales, and other reasons, a large amount of materials will be piled up and become stagnant materials.

[0003] In modern manufacturing, if the risk of obsolete materials is not well controlled, it will not only increase the confusion of inventory data, but also directly affect the company's profits. Therefore, it has become an urgent problem to display the inventory information of obsolete materials in real time and recommend obsolete material consumption plans based on the obsolete material information. Summary of the invention

[0004] In view of this, the present application at least provides a method and device for consuming slow-moving materials.

[0005] The technical solution of this application is implemented as follows:

[0006] On the one hand, the present application provides a method for consuming sluggish materials, comprising:

[0007] Based on the information about obsolete materials, determining at least one first configuration of at least one category of first products; wherein the first configuration represents a material configuration containing obsolete materials in the first products of the corresponding category;

[0008] Based on the business data corresponding to the slow-moving materials in each first configuration, determine at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the slow-moving materials consumption information corresponding to each second configuration;

[0009] Based on the slow-moving material consumption information, at least one target configuration of at least one type of target product is determined from at least one second configuration corresponding to the at least one type of second product.

[0010] In some embodiments, the method further comprises:

[0011] Based on at least one material information and at least one type of third product information, a material tree corresponding to each type of the third product is constructed; wherein,

[0012] At least one material information includes slow-moving material information;

[0013] at least one category of third products includes at least one category of first products;

[0014] The material tree represents the tree structure of the third product of the corresponding class composed of at least one material.

[0015] In some embodiments, each material information includes a material score; the material score represents the importance of the corresponding material;

[0016] Determining at least one first configuration of at least one type of first product based on the slow-moving material information includes:

[0017] Based on the information of slow-moving materials and the material tree corresponding to each type of third product, determine at least one type of first product from at least one type of third product;

[0018] For each type of first product, at least one first configuration is determined from at least one configuration of the first product by using a difference algorithm based on the material score of each material in the first product.

[0019] In some embodiments, based on the material fraction of each material in the first product, using a difference algorithm, determining at least one first configuration from at least one configuration of the first product includes:

[0020] Determine at least one target node from the root node and at least one intermediate node of the material tree corresponding to the first product; wherein the target node represents a node for determining a material configuration method based on at least one material substitution group; and the material substitution group represents a combination of multiple materials having a substitution relationship;

[0021] For each target node, based on the material scores of the materials in each material substitution group corresponding to the target node, using a differential algorithm, determine at least one target node configuration of the target node;

[0022] At least one first configuration of the first product is determined based on the target node configuration and the material tree corresponding to the first product.

[0023] In some embodiments, the at least one target node includes a first target node; the first target node includes at least one first material substitution group; each first material substitution group includes at least one first material;

[0024] Based on the material scores of the materials in each material substitution group corresponding to the target node, at least one target node configuration of the target node is determined by using a differential algorithm, including:

[0025] Based on the material score of each first material, determining a difference matrix corresponding to each first material substitution group;

[0026] Determine at least one target material in each first material substitution group based on the difference matrix and the configuration quantity of the target node configuration preset for the first target node;

[0027] Based on the target material, at least one target node configuration corresponding to the first target node is determined.

[0028] In some embodiments, based on the business data corresponding to the obsolete materials in each first configuration, determining at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the obsolete material consumption information corresponding to each second configuration, includes:

[0029] Based on the business data of each material in each first configuration, determine the minimum consumption of each first configuration; the minimum consumption represents the total quantity or total value of materials corresponding to the minimum complete set quantity of the corresponding first configuration;

[0030] determining at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product based on the minimum consumption;

[0031] Based on the business data of each slow-moving material in each second configuration, the slow-moving material consumption information corresponding to each second configuration is determined.

[0032] In some embodiments, the method further comprises:

[0033] Determine a repetition factor corresponding to at least one material; the repetition factor is used to control the number of configurations containing the corresponding material;

[0034] Determining at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product based on the minimum consumption includes:

[0035] For each type of first product, determining at least one third configuration with the largest minimum consumption from the at least one first configuration;

[0036] For each material in each third configuration, determining a first quantity of third configurations that include the material;

[0037] At least one second configuration of at least one type of second product is determined from at least one third configuration of at least one type of first product based on the first number and the repetition factor.

[0038] In some embodiments, the business data of the obsolete material includes the usage information and price information of the obsolete material in the corresponding second configuration; the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information;

[0039] Based on the business data of each slow-moving material in each second configuration, the slow-moving material consumption information corresponding to each second configuration is determined, including at least one of the following:

[0040] Based on the usage information and price information of the obsolete materials in the corresponding second configurations, determine the obsolete material consumption amount information corresponding to each second configuration;

[0041] Based on the usage information of the obsolete material in the corresponding second configuration, the obsolete material consumption quantity information corresponding to each second configuration is determined.

[0042] In some embodiments, the method further comprises at least one of the following:

[0043] Displaying and outputting at least one second configuration of at least one category of second products; updating at least one second configuration of each category of second products in response to the user's configuration information of the quantity of the second configuration corresponding to each category of second products;

[0044] Display and output at least one target configuration of at least one type of target product; in response to the user's type configuration information for obsolete material consumption information, update at least one target configuration of at least one type of target product; wherein the type configuration information of the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information.

[0045] On the other hand, the present application provides a sluggish material consumption device, comprising:

[0046] A first determination module is used to determine at least one first configuration of at least one type of first product based on the information of slow-moving materials; wherein the first configuration represents a material configuration containing slow-moving materials in the first product of the corresponding type;

[0047] A second determination module is used to determine at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the slow-moving material consumption information corresponding to each second configuration, based on the business data corresponding to the slow-moving material in each first configuration;

[0048] The third determination module is used to determine at least one target configuration of at least one type of target product from at least one second configuration corresponding to at least one type of second product based on the material consumption information.

[0049] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and are not intended to limit the technical solutions of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and are used together with the specification to illustrate the technical solution of the present application.

[0051] Figure 1 A schematic diagram of the implementation process of a method for consuming slow-moving materials provided in this application;

[0052] Figure 2 A schematic diagram of an inventory optimization interface in a slow-moving material consumption method provided by the present application;

[0053] Figure 3 A schematic diagram of some nodes of a material tree in a slow-moving material consumption method provided in the present application;

[0054] Figure 4A A schematic diagram of a material score sequence of four material substitution groups of a target node in a slow-moving material consumption method provided by the present application;

[0055] Figure 4B A schematic diagram of a difference matrix of material score sequences of four material substitution groups of a target node in the slow-moving material consumption method provided in the present application;

[0056] Figure 4C A schematic diagram of boundary detection results corresponding to the difference matrix of four material substitution groups of the target node in the slow-moving material consumption method provided by the present application;

[0057] Figure 5 A schematic diagram of determining at least one second configuration of at least one second product from at least one first configuration of at least one type of first product according to the slow-moving material consumption method provided by the present application;

[0058] Figure 6 A schematic diagram of an inventory optimization interface in a slow-moving material consumption method provided by the present application;

[0059] Figure 7 A schematic diagram of an inventory optimization interface in a slow-moving material consumption method provided by the present application;

[0060] Figure 8 A schematic diagram of an implementation flow of an embodiment of a method for consuming stagnant materials provided in the present application;

[0061] Fig. 9 A comparison chart of test results of using the sluggish material consumption method provided by the present application to determine the sluggish material consumption plan and using an exhaustive algorithm to determine the sluggish material consumption plan;

[0062] Fig. 10A A comparison chart of the slow-moving material consumption effect of the slow-moving material consumption method provided in this application and the slow-moving material consumption method in the related art in different scenarios;

[0063] Fig. 10B A comparison chart of the slow-moving material consumption effect of the slow-moving material consumption method provided in this application and the slow-moving material consumption method in the related art in different scenarios;

[0064] Fig.11 A schematic diagram of the composition structure of a sluggish material consumption device provided in this application. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application are further elaborated in detail below in conjunction with the drawings and embodiments. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0066] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0067] The terms "first / second / third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understandable that "first / second / third" can be interchanged with a specific order or sequence where permitted so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0068] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing this application and are not intended to limit this application.

[0069] In the related art, a relational database is used to store the bill of material (BOM). In order to determine the consumption plan of slow-moving materials, it is first necessary to associate the slow-moving materials with the BOM to find products related to the slow-moving materials. However, when the data scale is large, for example, in a conventional relational database containing one billion data items, it takes about ten hours to find products related to slow-moving materials, which is completely unable to meet business needs.

[0070] In addition, each type of product may have different configurations. For example, the same type of laptops may have different central processing unit (CPU) configurations, graphics card configurations, memory configurations, or display configurations, etc. Therefore, in order to maximize the consumption of slow-moving materials, it is necessary to determine the final recommended configuration from the different configurations of each type of product.

[0071] To this end, there are two solutions in the related art:

[0072] The first is to rely on manual experience. This solution relies heavily on the work experience of relevant personnel and is time-consuming and labor-intensive, resulting in high labor costs and difficulty in achieving good optimization results. At the same time, this solution is only applicable to manufacturing companies with relatively simple product compositions; for manufacturing companies with complex product compositions and more material substitution relationships, this solution is unlikely to meet the needs of companies due to the large number of possible product configuration solutions and more factors that need to be considered.

[0073] The second is the exhaustive method. This solution traverses the BOM structure of each type of product, calculates all the combined configurations, and calculates the preferred configuration scheme based on the preset priority rules. It can be seen that this solution is also suitable for manufacturing companies with simpler product compositions. If a complex BOM structure appears, the search space may reach billions. Relying on a simple exhaustive method is very time-consuming and seriously affects the efficiency of algorithm decision-making.

[0074] Based on this, the present application provides a method for consuming slow-moving materials, which can be executed by a processor of a computer device. The computer device may refer to a server, a laptop, a tablet computer, a desktop computer, a smart TV, a set-top box, a mobile device (such as a mobile phone, a portable video player, a personal digital assistant, a dedicated messaging device, a portable gaming device) and other devices with data processing capabilities.

[0075] Figure 1 A schematic diagram of the implementation process of a slow-moving material consumption method provided in this application, such as Figure 1 As shown, the method includes the following steps S101 to S103:

[0076] Step S101, based on the information of obsolete materials, determine at least one first configuration of at least one category of first products; wherein the first configuration represents the material configuration of the first products of the corresponding category that contain the obsolete materials.

[0077] Here, slow-moving materials are materials that have been stored in the warehouse for longer than a preset time threshold.

[0078] The slow-moving material information may be identification information of the slow-moving material, which is used to find the corresponding material in the database.

[0079] As the storage time changes, the status of the material in the database changes accordingly. For example, materials that have been in storage for less than 180 days are non-slow-moving materials; materials that have been in storage for more than 180 days are slow-moving materials. In this way, in response to the increase in the storage time of each material in the warehouse, the status information of the material is dynamically adjusted. For example, when the storage time of a material exceeds 180 days, identification information is added to the material to indicate that the material is a slow-moving material.

[0080] Each category of first products may be products of the same series or products of the same model (Machine Type Model, MTM). For example, Lenovo ThinkPad series notebook computers are products of the same category.

[0081] Each category of first products may include multiple configurations, and different configurations have at least one different material configuration. For example, the ThinkPad E14 and ThinkPad X13 in Lenovo's ThinkPad series of laptops are different configurations of the same category of products, where the ThinkPad E14 is equipped with an Intel Core i5-13th generation processor, while the ThinkPad X13 is equipped with an AMD Ryzen 5 6650U processor.

[0082] In this way, based on the slow-moving material information, at least one first configuration of at least one type of first product that consumes the slow-moving material can be determined.

[0083] Step S102, based on the business data corresponding to the obsolete materials in each of the first configurations, determine at least one second configuration of at least one type of second product from at least one first configuration of the at least one type of first product, and the obsolete material consumption information corresponding to each of the second configurations.

[0084] Here, the business data of obsolete materials refers to data related to the sales and / or inventory of obsolete materials.

[0085] In some embodiments, the business data of slow-moving materials may include the price, inventory quantity, inventory duration, and other data related to sales and / or inventory of the slow-moving materials.

[0086] Thus, in some embodiments, based on the price and quantity information corresponding to the obsolete materials in each first configuration, the total price of the obsolete materials in each first configuration is determined; the total prices of the obsolete materials in at least one first configuration are sorted, and the first P first configurations with the highest total prices are determined as the second configurations, and the corresponding products are determined as the second products; wherein P is an integer greater than or equal to 1.

[0087] In some embodiments, the total quantity of obsolete materials in each first configuration can be determined based on the quantity information corresponding to the obsolete materials in each first configuration; the total quantity of obsolete materials in at least one first configuration is sorted, and the top Q first configurations with the highest total quantity are determined as the second configuration, and the corresponding products are determined as the second product; wherein Q is an integer greater than or equal to 1.

[0088] The obsolete material consumption information corresponding to the second configuration refers to the consumption of the obsolete materials by the second configuration based on the business data of the obsolete materials in the second configuration, for example, the total quantity information of the obsolete materials that can be consumed by the second configuration, or the total value information of the obsolete materials that can be consumed by the second configuration.

[0089] Step S103: Based on the slow-moving material consumption information, determine at least one target configuration of at least one type of target product from at least one second configuration corresponding to the at least one type of second product.

[0090] Here, based on the consumption information of the obsolete materials, at least one second configuration is sorted, and the configuration with the highest consumption of the obsolete materials and a preset number in the sorting is used as the target configuration, and the product corresponding to the target configuration is used as the target product.

[0091] As can be seen from the above, in the method for consuming obsolete materials provided by the present application, first, based on the obsolete material information, at least one first configuration containing obsolete materials of at least one type of first product is determined; then, based on the business data corresponding to the obsolete materials in each first configuration, at least one second configuration of at least one type of second product and the obsolete material consumption information corresponding to each second configuration are determined from at least one first configuration of at least one type of first product; finally, based on the obsolete material consumption information, at least one target configuration of at least one type of target product is determined. In this way, at least one configuration of at least one type of product is multi-level screened based on the obsolete material information and the business data corresponding to the obsolete material, and at least one type of target product and at least one target configuration are obtained, thereby realizing automatic determination of the consumption plan of obsolete materials and improving the efficiency of recommending the consumption plan of obsolete materials.

[0092] In some embodiments, the method for consuming slow-moving materials provided in the present application further includes the following step S104:

[0093] Step S104, based on at least one material information and at least one type of third product information, construct a material tree corresponding to each type of the third product; wherein,

[0094] The at least one material information includes the slow-moving material information;

[0095] The at least one category of third products includes the at least one category of first products;

[0096] The material tree represents a tree structure of third products of a corresponding class composed of at least one material.

[0097] Here, the material information at least includes the attribute information and identification information of the corresponding material.

[0098] In some embodiments, the material information includes unique identification information of the corresponding material in the database, type information of the material, combined materials composed of the material and / or other material attribute information.

[0099] The at least one third product category refers to any category of products stored in the database.

[0100] The at least one type of third product includes the at least one type of first product, that is, the at least one type of first product is a product containing sluggish materials in the at least one type of third product.

[0101] The third product information at least includes attribute information and identification information of the third product.

[0102] In some embodiments, the third product information includes unique identification information of the third product in the database, brand information, product family information, product type information and / or other product attribute information.

[0103] Here, based on at least one material information and at least one type of third product information, the composition relationship between at least one material and at least one third type of product is determined, so as to construct a material tree corresponding to each type of third product.

[0104] For example, the material tree corresponding to a laptop computer may include the product information corresponding to the laptop computer (for example, product model, product family, etc.) and information on various basic materials that make up the laptop computer (for example, type is CPU, brand is Intel, etc.). At the same time, the material tree of the laptop computer may also include various intermediate material combinations between the product information and various basic hardware, such as input and output devices composed of a mouse, keyboard, and touch panel, etc.

[0105] In this way, each material and the corresponding third product are used as nodes, and the association relationship between the material and the third product is used as a connecting line between the nodes to construct a material tree corresponding to each third product.

[0106] Figure 2 It is a schematic diagram of the inventory optimization interface in the slow-moving material consumption method provided in the present application, wherein the architecture design interface 240 of the inventory optimization interface 200 shows the architecture design of the material tree.

[0107] like Figure 2 As shown, the material tree includes node 210, node 220 and node 230; the node information corresponding to node 210 is shown in information box 211, the node information corresponding to node 220 is shown in information box 221, and the node information corresponding to node 230 is shown in information box 231; the association relationship between node 210, node 220 and node 230 is shown by arrows between the nodes; wherein:

[0108] In the information box 211 of the node 210, the "node" information corresponds to "material", indicating that the node 210 is a material node, that is, a leaf node in the material tree; "primary key" is used to define the unique identification information of the node 210 in the database; "attribute" is used to define the material type of the node 210, for example, the material corresponding to the node 210 is a CPU, a graphics card or a hard disk, etc.; "grouping" is used to define the material group to which the material corresponding to the node 210 belongs, and the material group includes materials of the same type as the material corresponding to the node 210;

[0109] Here, when the inventory duration of the material corresponding to the node 210 reaches the duration threshold, the slow-moving material identification information is dynamically added in the information box 211 of the node 210 .

[0110] In the information box 221 of the node 220, the "node" information corresponds to the "intermediate component", indicating that the node 220 is an intermediate node between the product and various basic materials constituting the product; the "primary key" is used to define the unique identification information of the node 220 in the database; the "group" is used to define the intermediate component group to which the intermediate node corresponding to the node 220 belongs, and the intermediate component group includes intermediate components of the same type as the intermediate node corresponding to the node 220;

[0111] In the information box 231 of the node 230, the "node" information corresponds to "product", indicating that the node 230 is a product; the "primary key" is used to define the unique identification information of the node 230 in the database; the "brand" is used to define the brand of the product corresponding to the node 230 (for example, Lenovo); the "product family" is used to define the product family to which the product corresponding to the node 230 belongs (for example, ThinkBook series); the "product type" is used to define the model of the product corresponding to the node 230 (for example, ThinkBook 14);

[0112] There are three types of arrows between node 210 and node 220; among them, the solid arrow is used to define a necessary relationship, that is, the material corresponding to node 210 is a necessary material for the intermediate component corresponding to node 220; the dashed arrow is used to define a complete substitution relationship, that is, the group where node 210 is located includes multiple materials, and each material can be used as an intermediate component corresponding to node 220 alone; the dot-dash arrow is used to define a group substitution, that is, node 220 is composed of multiple materials, and there are multiple combinations that can replace each other, and node 210 is a material in one of the multiple combinations;

[0113] For example, material A and material B are both CPUs and can replace each other, so material A and material B have a complete substitution relationship; for another example, material C and material D are material combinations with a fixed combination relationship, material E and material F are material combinations with a fixed combination relationship, and the combination of material C and material D and the combination of material E and material F can replace each other, then it is considered that the combination of material C and material D and the combination of material E and material F have a group substitution relationship.

[0114] The solid arrow between node 210 and node 230 is used to define that the material corresponding to node 210 is a necessary material for the product corresponding to node 230;

[0115] The solid arrow between the node 220 and the node 230 is used to define that the intermediate component corresponding to the node 220 is a necessary intermediate component of the product corresponding to the node 230;

[0116] The node 220 has an arrow pointing to the node 220 , which is used to define the usage relationship between different nodes 220 , that is, the product corresponding to the node 230 includes multiple nodes 220 , and one of the nodes 220 has a usage relationship (or, a necessary relationship) with another node 220 .

[0117] From the above, it can be seen that the embodiment provided by the present application uses nodes, information boxes and edges between nodes to store data of materials, products and their intermediate assemblies with complex hierarchical relationships. Compared with relational databases, more efficient BOM expansion can be achieved, thereby significantly improving the processing efficiency of BOM.

[0118] In some embodiments, each of the material information includes a material score; the material score represents the importance of the corresponding material.

[0119] Here, the importance of a material refers to the urgency of its consumption. The material score is directly proportional to its importance.

[0120] In some embodiments, the material score may be determined based on the material's inventory quantity, price, whether it is a slow-moving material, and / or other material information.

[0121] For example, the larger the inventory quantity of a material, the higher the corresponding material score; for another example, the higher the price of a material, the higher the corresponding material score; for another example, the material score of a slow-moving material is higher than the material score of a non-slow-moving material.

[0122] In this way, by determining the corresponding material score for each material, a product score or a configuration score can be determined for the product and its corresponding configuration scheme, and then product screening and / or configuration screening can be performed based on the product score and / or configuration score.

[0123] In this way, the step of determining at least one first configuration of at least one type of first product based on the slow-moving material information, that is, the above step S101 can be implemented as the following steps S1011 to S1012:

[0124] Step S1011, based on the slow-moving material information and the material tree corresponding to each type of the third product, determine the at least one type of first product from the at least one type of third products.

[0125] Here, based on the information of obsolete materials, the material tree corresponding to each type of third product is searched to determine at least one type of first product containing obsolete materials.

[0126] In some embodiments, the stagnant material information refers to the stagnant material identification information. Figure 2 The node 210 shown in FIG. 1 generates the obsolete material identification information to determine the obsolete material, and then determines the product information containing the obsolete material.

[0127] In some embodiments, after determining product information containing obsolete materials, historical sales data of products containing obsolete materials can be obtained; based on the historical sales data, at least one category of third products with the highest historical sales volume and / or historical sales volume is selected from the products containing obsolete materials as the first product.

[0128] Step S1012: for each type of first product, based on the material score of each material in the first product, using a differential algorithm, determine at least one first configuration from at least one configuration of the first product.

[0129] Here, based on the material score, a differential algorithm is used to score different configurations corresponding to each type of first product to determine at least one first configuration with a higher configuration score.

[0130] In some embodiments, based on the material tree corresponding to the first product, multiple materials or material combinations that have a complete substitution relationship or a group substitution relationship in the material tree corresponding to the first product are listed; and using a differential algorithm, the material or material combination with the highest score is screened out from the multiple materials or material combinations that have a complete substitution relationship or a group substitution relationship.

[0131] In the above embodiment, multiple configurations in each type of first product are screened based on the material score of each material to determine at least one first configuration with a higher configuration score, that is, configurations with a higher degree of importance are screened out; in addition, a differential algorithm is used to screen multiple materials or material combinations with a complete substitution relationship or a group substitution relationship, which can greatly reduce the computational complexity of the screening process, thereby improving the screening efficiency.

[0132] In some embodiments, based on the material score of each material in the first product, at least one first configuration is determined from at least one configuration of the first product using a differential algorithm, that is, the above step S1012 can be implemented as the following steps S1013 to S1015:

[0133] Step S1013, determining at least one target node from the root node and at least one intermediate node of the material tree corresponding to the first product; wherein the target node represents a node for determining a material configuration method based on at least one material substitution group; and the material substitution group represents a combination of multiple materials having a substitution relationship.

[0134] Here, the substitution relationship includes the complete substitution relationship and the group substitution relationship mentioned above.

[0135] A material substitution group represents a combination of multiple materials with a substitution relationship, that is, multiple materials in the material substitution group have a complete substitution relationship; or the material substitution group includes multiple material combinations, and multiple material combinations have a group substitution relationship.

[0136] In this way, if the target node is a node whose material configuration method is determined based on a material substitution group, the material configuration method of the target node can be determined by a material or a material combination in a material substitution group; if the target node is a node whose material configuration method is determined based on at least two material substitution groups, a material or a material combination is determined from each material substitution group, and the material configuration method of the target node is determined based on the determined at least two materials or material combinations.

[0137] Step S1014: for each target node, based on the material scores of the materials in each material substitution group corresponding to the target node, at least one target node configuration of the target node is determined using a differential algorithm.

[0138] Here, for each target node, based on the material scores of the materials in the material substitution group, a differential algorithm is used to determine the configuration score of each material configuration method corresponding to the target node, and at least one target node configuration of the target node is determined based on the sorting results of the configuration scores.

[0139] like Figure 3 As shown, node 300 is an intermediate node or a root node in the material tree, and node 300 is configured by intermediate node 310, intermediate node 320 and intermediate node 330; wherein:

[0140] Node 310 can be configured as material PN1 or material PN2, that is, material PN1 and material PN2 have a complete substitution relationship;

[0141] Node 320 can be configured as material PN3 or material PN4, that is, material PN3 and material PN4 have a complete substitution relationship;

[0142] Node 330 can be configured as node 331 or node 332. Node 331 can be configured as a combination of material PN5 and material PN6, and node 332 can be configured as a combination of material PN5 and material PN7. Therefore, node 331 and node 332 have a group substitution relationship.

[0143] It can be seen that in Figure 3 In the material tree structure shown, node 310, node 320 and node 330 may be determined as target nodes.

[0144] In this way, when determining the target node configuration corresponding to each target node, it can be:

[0145] For node 310: the material score of material PN1 is 2, and the material score of material PN2 is 1; at the same time, when material PN1 is used to configure node 310, the required quantity of material PN1 is 2, and when material PN2 is used to configure node 310, the required quantity of material PN2 is 1. Therefore, it can be determined that the total value of the material score corresponding to material PN1 is 4, and the total value of the material score corresponding to material PN2 is 1. In this way, materials PN1 and PN2 are sorted according to the total value of the material score. If the preset number of target node configurations is 1, material PN1 is determined as the target node configuration for node 310;

[0146] For node 320: the material scores of material PN1 and material PN2 in node 310 are calculated in the same way, and the total material score corresponding to material PN3 is 4, and the total material score corresponding to material PN4 is 1. In this way, material PN3 and material PN4 are sorted according to the total material score. If the number of preset target node configurations is 1, material PN3 is determined as the target node configuration of node 320;

[0147] For node 330: the material score calculation method is the same as that of material PN1 and material PN2 in node 310. It can be seen that the total material score of material PN5 in node 331 is 1, and the total material score of material PN6 is 2, so the total material score of node 331 is 3; similarly, the total material score of node 332 is 5. In this way, nodes 331 and 332 are sorted according to the total material score. If the number of preset target node configurations is 1, the configuration method of node 332 is used as the target node configuration of node 330.

[0148] The above combination Figure 3In the embodiment, the number of materials in the alternative group corresponding to each target node is small, and the target node configuration corresponding to the target node can be determined by simple enumeration and sorting. Figure 4A , Figure 4B and Figure 4C , more generally describing a method for determining at least one target node configuration corresponding to a target node using a differential algorithm.

[0149] In some embodiments, the at least one target node includes a first target node; the first target node includes at least one first material substitution group; each of the first material substitution groups includes at least one first material. Thus, the method for determining at least one target node configuration of the first target node may include the following steps S1016 to S1018:

[0150] Step S1016: determining a difference matrix corresponding to each first material substitution group based on the material score of each first material.

[0151] Here, firstly, the multiple first materials in each first material substitution group are sorted according to the size of the material scores to obtain the material score sequences corresponding to the multiple first material substitution groups;

[0152] like Figure 4A As shown, in one embodiment, the target node has 4 alternative groups, each alternative group includes material scores of 5 materials; wherein, the material scores in the first alternative group 410 are 5, 6, 9, 12, and 15 from low to high; the material scores in the second alternative group 420 are 3, 4, 6, 7, and 7 from low to high; the material scores in the third alternative group 430 are 12, 15, 20, 23, and 25 from low to high; the material scores in the fourth alternative group 440 are 2, 2, 3, 3, and 3 from low to high.

[0153] Then, calculate the difference matrix corresponding to each material substitution group, that is, for each material score sequence, calculate the absolute value of the difference between the value in the sequence and the maximum value. Continuing with the above example, Figure 4A The difference matrix corresponding to the material score sequence shown is as follows Figure 4B shown.

[0154] Step S1017: determining at least one target material in each of the first material substitution groups based on the difference matrix and the configuration quantity of the target node configuration preset for the first target node.

[0155] Here, for the difference matrix corresponding to at least one first material substitution group, boundary detection is performed in ascending order, and the number of configuration methods within the boundary line is calculated; when the number of configuration methods within the boundary line is not less than the preset configuration number for the target node configuration, the material corresponding to the value within the boundary line is used as the target material.

[0156] For example, Figure 4B The difference matrix shown first uses the rightmost column of the matrix as the data within the boundary line. It can be seen that the number of configuration methods within the boundary line (i.e., on the right side of the boundary line) is 1; then, the boundary line is moved to the right (i.e., to the side with larger numbers), for example, the 4th number in the 4th alternative group is moved to the right side of the boundary line. In this way, the number of configuration methods within the boundary line is 2; and so on.

[0157] After each movement of the boundary line, the number of configuration modes within the boundary line is calculated until the number of configuration modes within the boundary line is not less than the number of configuration modes of the preset target node configuration.

[0158] Thus, following the above example, when the preset number of configurations for the target node is 30, Figure 4B The difference matrix shown in is used for boundary detection, and we can get Figure 4C The boundary line is shown by the thinner black solid arrow 450, and the configuration mode composed of the materials on the right side of the arrow 450 is the target node configuration corresponding to the target node.

[0159] At the same time, by Figure 4C It can be seen that, for the configuration on the right side of the boundary line indicated by the thicker black solid arrow 460, although some materials (for example, the fourth material in the first alternative group) are not within the boundary line defined by arrow 450, the sum of their differences is still smaller than the sum of the differences of the configuration within the boundary line defined by arrow 450.

[0160] Therefore, the total difference of the boundary line defined by arrow 450 is further calculated (eg Figure 4C As shown, the total difference of the boundary line corresponding to arrow 450 is 4); using the total difference Figure 4B The difference matrix shown in the figure is used for boundary detection, and the Figure 4C The boundary line defined by the dotted arrow 470 is selected, and the material corresponding to the value on the right side of the boundary line defined by the dotted arrow 470 is used as the target material.

[0161] Step S1018: Based on the target material, determine at least one target node configuration corresponding to the first target node.

[0162] Here, after determining the target material in each first alternative group, the configuration scores corresponding to the multiple configurations composed of the target material are calculated based on the material score of the target material, and the calculated configuration scores are sorted to obtain the highest-ranked and preset number of target node configurations.

[0163] For example, continuing with the above example, Figure 4C For the materials within the boundary line defined by the middle dotted arrow 470, the Cartesian product is calculated based on their corresponding material scores to obtain multiple material configuration methods and their corresponding configuration scores; the calculated configuration scores are sorted to obtain the top 30 target node configurations with the highest configuration scores corresponding to the target nodes.

[0164] Step S1015: determine at least one first configuration of the first product based on the target node configuration and the material tree corresponding to the first product.

[0165] Here, according to the structure of the material tree corresponding to the first product, the target node configurations corresponding to each target node are calculated in sequence from the leaf node upward, and finally the target node configuration corresponding to the first product (ie, the root node) is determined and used as at least one first configuration of the first product.

[0166] For example, when the preset configuration quantity of at least one first configuration of the first product is 30, 30 target node configurations corresponding to each target node are calculated upward from the leaf node of the material tree of the first product, and finally the 30 first configurations corresponding to the first product are determined.

[0167] In the above embodiment, the target node configuration of the target node in each type of first product is determined by using a differential algorithm, and then at least one first configuration of the first product is determined based on the target node configuration and the material tree corresponding to the first product. In this way, since the differential algorithm has the advantage of low time calculation complexity, the differential algorithm can be used to quickly screen out the optimal configuration (i.e., at least one first configuration) corresponding to each first product, thereby improving the recommendation efficiency of the slow-moving material consumption plan.

[0168] In some embodiments, based on the business data corresponding to the obsolete materials in each of the first configurations, at least one second configuration of at least one type of second product is determined from at least one first configuration of at least one type of first product, and the obsolete material consumption information corresponding to each of the second configurations, that is, the above step S102 can be implemented as the following steps S1021 to S1023:

[0169] Step S1021, based on the business data of each material in each of the first configurations, determine the minimum consumption of each of the first configurations; the minimum consumption represents the total quantity or total value of materials corresponding to the minimum complete quantity of the corresponding first configuration.

[0170] Here, the business data of each material may include the inventory quantity and / or price corresponding to each material.

[0171] In this way, for each first configuration, the inventory quantity corresponding to each material in the first configuration is determined, and the minimum complete set quantity corresponding to the first configuration is determined based on the inventory quantity. For example, the inventory quantity corresponding to the material with the lowest inventory quantity in the first configuration is used as the minimum complete set quantity corresponding to the first configuration.

[0172] Afterwards, for each first configuration, based on the minimum complete set quantity and the quantity and / or price of each material in the first configuration, the total quantity of materials consumed by the first configuration or the total value of the materials, that is, the minimum consumption corresponding to the first configuration, is calculated.

[0173] In some embodiments, the minimum consumption y of the i-th configuration of the m-th category product can be calculated using formula (1): m,i :

[0174] y m,i =min(m i,j *inv j )*∑p j (1);

[0175] Among them, y m,i represents the minimum consumption of the ith configuration of the mth category product; m i,j represents the jth material in the i-th configuration of the m-th product; inv j represents the inventory quantity of the jth material; p j Represents the price of the j-th material.

[0176] In this way, based on the above formula (1), the total value of materials corresponding to the minimum complete set quantity of each first configuration can be calculated.

[0177] It can be understood that when the price of the j-th material in the above formula (1) is set to 1, the total quantity of materials corresponding to the minimum complete set quantity of each first configuration can be calculated.

[0178] Step S1022: Based on the minimum consumption, determine at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product.

[0179] Here, the minimum consumption corresponding to each first configuration is sorted, so that the first configuration with the highest minimum consumption and a preset number is determined as the second configuration, and accordingly, the corresponding first product is used as the second product.

[0180] In some embodiments, the method provided by the present application also includes: determining a repetition coefficient corresponding to at least one material; the repetition coefficient is used to control the number of configurations containing the corresponding material.

[0181] Here, the repetition coefficient is used to control the number of configurations containing the corresponding material. For example, when the repetition coefficient is high, the number of second configurations containing the corresponding material in at least one second configuration of at least one type of second product is smaller; correspondingly, when the repetition coefficient is low, the number of second configurations containing the corresponding material in at least one second configuration of at least one type of second product is smaller.

[0182] In some embodiments, a corresponding repetition coefficient may be set for each material in at least one second configuration, or a unified repetition system may be set for the materials in at least one second configuration.

[0183] In this way, the above step S1022 can be implemented as the following steps S1024 to S1026:

[0184] Step S1024: for each type of the first product, determine at least one third configuration with the largest minimum consumption from at least one first configuration.

[0185] Here, for each category of first products, based on the minimum consumption corresponding to each first configuration included in the first products, at least one third configuration with the largest minimum consumption corresponding to each category of first products is determined. In this way, the configuration space corresponding to each category of first products is reduced.

[0186] Step S1025: for each material in each of the third configurations, determine the first quantity of the third configurations containing the material.

[0187] Here, for each material, within the range of all determined third configurations, the first quantity of the third configurations containing the material is calculated. For example, if material A is contained in three third configurations, the first quantity corresponding to material A is 3.

[0188] Step S1026: determining at least one second configuration of at least one type of second product from at least one third configuration of at least one type of first product based on the first number and the repetition coefficient.

[0189] Here, at least one third configuration of at least one first category product is further screened based on the repetition coefficient.

[0190] For example, when the repetition coefficient is large, the third configuration with a larger number is deleted from the third configurations containing the first number of the specified material, that is, in the determined at least one second configuration, the number of the second configuration containing the specified material is smaller, so that the at least one second configuration covers a wider range of materials;

[0191] For another example, when the repetition coefficient is small, a smaller number of third configurations is deleted from the third configurations containing the first quantity of the specified material. That is, in the determined at least one second configuration, the larger the number of second configurations containing the specified material, the more likely the final screening result is to be more biased towards the screening result based on the minimum consumption, that is, the higher the minimum consumption corresponding to at least one second configuration.

[0192] In the above embodiment, the frequency with which the material is hit is adjusted by presetting the repetition coefficient corresponding to the material, thereby achieving the effect of optimizing the configuration of the product.

[0193] In some embodiments, at least one second configuration of at least one second product may be determined from at least one third configuration of at least one first product by the following formula (2):

[0194]

[0195] Among them, y m,i represents the minimum consumption corresponding to the i-th configuration of the m-th category product calculated based on the above formula (1);

[0196] x m,i , indicating whether the i-th configuration of the m-th product is selected as the third configuration corresponding to the first product. If so, then x m,i The value of x is 1, otherwise m,i The value of is 0;

[0197] M, represents the set of types corresponding to the first product;

[0198] k, represents the set of configurations corresponding to the mth product;

[0199] α, represents the repetition coefficient;

[0200] z j , represents the first quantity corresponding to the j-th material;

[0201] PN, represents the set of all materials corresponding to at least one type of first product.

[0202] It should be noted that the above formula (2) is subject to the following restrictions of formulas (3) and (4):

[0203]

[0204] z j ≥1 (4).

[0205] Thus, when determining at least one second configuration, based on the above formula (2), the minimum consumption y can be adjusted using the repetition coefficient α. m,i That is, when the repetition coefficient α is small, the higher the number of repetitions of the material in at least one second configuration, the more likely the final screening result is to be based on the minimum consumption y. m,i screening results; when the repetition coefficient α is larger, the number of repetitions of the material in at least one second configuration is smaller, so that the final screening result is more inclined to cover more materials.

[0206] In order to more clearly describe the process of determining at least one second configuration of at least one second product from at least one first configuration of at least one type of first product, Figure 5 Provide further explanation.

[0207] like Figure 5 As shown, at least one type of first product includes MTM1 510 and MTM2 520; wherein:

[0208] MTM1 510 includes two first configurations, namely, configuration 511 and configuration 512, configuration 511 includes materials PN1, PN6 and PN7, and configuration 512 includes materials PN1, PN2 and PN3;

[0209] MTM1 520 includes two first configurations, namely, configuration 521 and configuration 522 , configuration 521 includes materials PN1 , PN2 , PN3 , and PN6 , and configuration 522 includes materials PN1 , PN3 , and PN8 .

[0210] When at least one second configuration of at least one type of second product is selected from MTM1 510 and MTM2 520 using the above formulas (1) and (2):

[0211] First, the minimum consumption corresponding to configuration 511, configuration 512, configuration 521 and configuration 522 is calculated respectively;

[0212] Then, according to the minimum consumption calculation result, for MTM1 510, a configuration 512 with a larger minimum consumption is selected; for MTM2 520, a configuration 522 with a larger minimum consumption is selected;

[0213] Afterwards, when the preset repetition coefficient is small, for example, the repetition coefficient is 1, the one with the larger minimum consumption between configuration 512 and configuration 522 will be selected as the second configuration; when the preset repetition coefficient is large, for example, the repetition coefficient is 2, the one with a wider material coverage between configuration 512 and configuration 522, that is, configuration 522, will be selected as the second configuration.

[0214] As can be seen from the above, in the process of determining at least one second configuration of at least one category of second products from at least one first configuration of at least one category of first products, the present application firstly uses the business data of the materials in at least one first configuration and the minimum consumption of each first configuration to implement the configuration mode screening for each category of first products, i.e., the first-level screening; then, the first products of different categories are screened using the repetition coefficient, i.e., the second-level screening. It can be seen that the present application continuously narrows the decision space through the hierarchical selection strategy, and finally determines the sluggish material consumption plan that meets the user's expectations.

[0215] Step S1023: Determine the slow-moving material consumption information corresponding to each of the second configurations based on the business data of each slow-moving material in each of the second configurations.

[0216] Here, based on the business data of each obsolete material in each second configuration, the consumption of the obsolete material by each second configuration is determined, for example, the total quantity and / or total value of the obsolete material consumed by each second configuration.

[0217] In some embodiments, the business data of the obsolete materials includes usage information and price information of the obsolete materials in the corresponding second configuration; the obsolete material consumption information includes obsolete material consumption amount information.

[0218] In this way, the above step S1023 can be implemented as follows: based on the usage information and price information of the obsolete material in the corresponding second configuration, determine the obsolete material consumption amount information corresponding to each second configuration.

[0219] Here, for each second configuration, the minimum complete set quantity information of the second configuration, the usage information of each slow-moving material in the second configuration, and the price information of each slow-moving material are determined, so as to calculate the slow-moving material consumption amount information corresponding to the second configuration.

[0220] In some embodiments, the business data of the obsolete materials includes the usage information of the obsolete materials in the corresponding second configuration; and the obsolete material consumption information includes the obsolete material consumption quantity information.

[0221] In this way, the above step S1023 can be implemented as follows: based on the usage information of the obsolete material in the corresponding second configuration, determine the obsolete material consumption quantity information corresponding to each of the second configurations.

[0222] Here, for each second configuration, the minimum complete set quantity information of the second configuration and the usage information of each slow-moving material in the second configuration are determined, so as to calculate the slow-moving material consumption quantity information corresponding to the second configuration.

[0223] In some embodiments, the maximum dead material consumption information G corresponding to each second configuration may be determined using the following formula (5):

[0224]

[0225] in:

[0226] j represents the jth material;

[0227] e j Indicates that material j is a slow-moving material;

[0228] P j represents the price of material j;

[0229] Y m,i It indicates the minimum set quantity or recommended quantity of the ith configuration of the mth category product;

[0230] D m,i,j represents the quantity of material j required for the i-th configuration of the m-th product;

[0231] It should be noted that the above formula (5) is subject to the following restrictions as shown in formulas (6) to (8):

[0232]

[0233] in:

[0234] X j Indicates the purchase quantity of material j;

[0235] D j Indicates the inventory quantity of material j;

[0236] MP stands for Maximum Purchase Amount.

[0237] In some embodiments, the method for consuming slow-moving materials provided in the present application further includes at least one of the following steps S105 to S106:

[0238] Step S105, displaying and outputting at least one second configuration of the at least one category of second products; and updating at least one second configuration of each category of second products in response to the user's quantity configuration information of the second configuration corresponding to each category of the second products.

[0239] Here, after determining at least one second configuration corresponding to at least one category of second products based on the differential algorithm and the hierarchical selection strategy, the at least one second configuration corresponding to the determined at least one category of second products is displayed and output; thereafter, in response to the user's configuration operation on the number of second configurations corresponding to each category of second products, the differential algorithm and the hierarchical selection strategy (for example, the above formulas (1) and (2)) are used to re-screen and update at least one second configuration of each category of second products.

[0240] like Figure 6 As shown, in the configuration management interface 610 of the inventory optimization interface 600, 8 types of configuration information corresponding to each second product selected are displayed and output in a table form; wherein,

[0241] The shaded box indicates that the configuration scheme on the corresponding column contains the material on the corresponding row. For example, configuration 1 of product 20X2SA9V00 contains material SS51E21312; configuration 4 of product 20X2SA9V00 contains material SS51E21313 and material SS51E21318; and so on.

[0242] With respect to the configuration management interface 610 , the user may reconfigure the number in the configuration box 620 corresponding to the target configuration quantity K to update the number of configurations selected for each type of product.

[0243] In some embodiments, for the configuration management interface 610, the user can configure the number in the configuration box 630 corresponding to the repetition coefficient α to update the repetition coefficient in the above formula (2), thereby updating the selected products and corresponding configurations.

[0244] In this way, after the user updates the configuration information of the target configuration quantity K and the repetition coefficient, the user submits the update by clicking the submit button 640 .

[0245] Step S106, display and output at least one target configuration of the at least one type of target product; in response to the user's type configuration information for the obsolete material consumption information, update at least one target configuration of the at least one type of target product; wherein the type configuration information of the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information.

[0246] Here, the obsolete material consumption amount information refers to the total value information of the obsolete materials included in at least one target configuration.

[0247] The consumption quantity information of obsolete materials refers to the total quantity information of obsolete materials included in at least one target configuration.

[0248] In this way, after displaying and outputting at least one target configuration of at least one type of target product, the user can configure the type of obsolete material consumption information to update at least one target configuration of the screened at least one type of target product according to different types of obsolete material consumption information.

[0249] For example, in response to the user configuring the obsolete material consumption information as the obsolete material consumption quantity information, the obsolete material price parameter in the above formula (5) is set to 1, thereby recalculating the obsolete material consumption information corresponding to each second configuration; for another example, in response to the user configuring the obsolete material consumption information as the obsolete material consumption amount information, the obsolete material price parameter in the above formula (5) is set to the price corresponding to the obsolete material, thereby recalculating the obsolete material consumption information corresponding to each second configuration.

[0250] like Figure 7 As shown, in the visualization interface 710 of the inventory optimization interface 700, the material consumption of the slow-moving materials in at least one selected target configuration is displayed.

[0251] In the area 720 shown in the dotted box, the consumption of multiple obsolete materials in at least one target configuration currently screened is shown; wherein, the length of the progress bar corresponding to each obsolete material represents the total amount of the corresponding obsolete material, and the length of the shaded part of the progress bar represents the amount of the obsolete material that can be consumed by the current plan (i.e., Plan 1).

[0252] In the configuration box 721 in area 720, the user can update the currently recommended slow-moving material consumption plan through the drop-down menu;

[0253] In the configuration box 722 in the area 720, the user can update the current slow-moving material consumption information through the drop-down menu, for example, to update the slow-moving material consumption information from "amount" to "quantity".

[0254] In response to the user clicking on the obsolete material “SM30N76745” 723 in the area 720 , the area 730 indicated by the dotted box is displayed, and the material consumption plan related to the obsolete material “SM30N76745” 723 is displayed in the area 730 .

[0255] In area 730 , it is displayed that the type of the obsolete material “SM30N76745” is hard disk drive (HDD), and the total amount in current inventory is RMB 6,400; at the same time, the target configuration information including the current obsolete material is displayed in the form of a bar chart 731 .

[0256] The horizontal axis of the bar graph 731 represents the best-selling score of the corresponding product in the form of a flame. For example, a white flame represents a best-selling score of (0, 0.1], and a completely black flame represents a best-selling score of (0.9, 1]; the vertical axis of the bar graph 731 represents the number of products; each rectangle in each column in the bar graph 731 corresponds to a product that can consume the current stagnant materials. For example, the column with a best-selling score of (0.9, 1] includes 2 products, and the column with a best-selling score of (0.7, 0.9] includes 3 products.

[0257] In response to the user clicking on a rectangular portion of a bar in the bar graph 731 , a window 732 is displayed to display product information corresponding to the rectangle in the window 732 .

[0258] It can be seen from window 732 that: the product name corresponding to the current rectangle is "20X2SA9V00"; the current product set quantity is 54; the amount of obsolete materials that can be consumed is 80 yuan; the predicted quantity, that is, the predicted possible future shipments is 4; the order quantity, that is, the current order quantity is 320; the shipment quantity, that is, the number of shipments is 13.

[0259] It can be seen from the above embodiments that the present application allows users to independently configure their consumption requirements for obsolete materials by providing a configuration management interface and a visualization interface, so that the recommended obsolete material consumption plan is more in line with user expectations, thereby improving the user experience.

[0260] Next, combine Figure 8 , an embodiment of the method for consuming sluggish materials provided by the present application is described. Figure 8 As shown, this embodiment includes the following steps S810 to S860:

[0261] Step S810, in response to the slow-moving material consumption task initiated by the user, determining the slow-moving material information; thereafter, executing step S820;

[0262] Here, users can use the visual interactive interface provided by this application to initiate a slow-moving material consumption task.

[0263] In response to a slow-moving material consumption task initiated by a user, the database for storing BOM data provided by the present application retrieves the slow-moving material information.

[0264] Step S820, based on the slow-moving material information, using a differential algorithm to determine at least one first configuration of at least one first product from multiple types of products stored in the graph database; then, executing step S830;

[0265] Step S830, based on the business data of the slow-moving materials, determining at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the slow-moving materials consumption information corresponding to each second configuration; then, executing step S840;

[0266] Step S840, based on the consumption of the slow-moving materials, determining at least one target configuration of at least one target product from at least one second configuration of at least one type of second product; thereafter, executing step S850;

[0267] Step S850, based on at least one target configuration of at least one target product, display and output a consumption plan for slow-moving materials; thereafter, executing step S860;

[0268] Here, based on at least one target configuration of at least one target product, a corresponding display component is selected, and a sluggish material consumption plan is displayed and output in the visualization interface provided in the present application.

[0269] Step S860, in response to the user's configuration information on the consumption plan for obsolete materials, updating the obsolete material consumption plan.

[0270] Here, in response to the user's configuration information on the target material configuration K, the configuration information on the type of slow-moving material consumption information, etc., at least one type of target product and the corresponding target configuration are re-determined, and the slow-moving material consumption plan displayed and output is updated.

[0271] Fig. 9 The following is a comparison chart showing the test results of using the sluggish material consumption method provided by the present application to determine the sluggish material consumption plan and using the exhaustive algorithm to determine the sluggish material consumption plan.

[0272] The horizontal axis represents the number of configurations, that is, the total number of configurations corresponding to the multiple categories of products stored in the current database;

[0273] The vertical axis represents time, that is, the length of time required to determine the consumption plan for slow-moving materials; here, the coordinate system formed by the time axis and the configuration quantity axis is a logarithmic coordinate system.

[0274] The broken line 910 represents the corresponding relationship between the time and the configuration quantity used to determine the consumption plan of the slow-moving material using the exhaustive algorithm;

[0275] Broken line 920, broken line 930, broken line 940 and broken line 950 all represent the corresponding relationship between the time used to determine the slow-moving material consumption plan and the configuration quantity using the method provided in this application; among them, the target configuration quantity corresponding to broken line 920 is 10000, the target configuration quantity corresponding to broken line 930 is 1000, the target configuration quantity corresponding to broken line 940 is 100, and the target configuration quantity corresponding to broken line 950 is 10.

[0276] Depend on Fig. 9 It can be seen that when the number of configurations is small, the time consumption of the method provided by this application is similar to that of the exhaustive algorithm; however, when the number of configurations is greater than 10 5 Afterwards, the time consumption of the method provided by the present application is significantly reduced compared to the exhaustive algorithm.

[0277] Combine the following Fig. 10A and 10B , explaining the recommended effects of the obsolete material consumption method provided in this application and the obsolete material consumption method provided in the related art in different scenarios.

[0278] Fig. 10A The relationship between the configuration quantity and consumption amount screened out by different slow-moving material consumption schemes in different scenarios is shown.

[0279] Scenario 1 represents the corresponding relationship between the configuration quantity and the consumption amount screened out by the slow-moving material consumption method provided in the relevant technology in the scenario where material procurement is allowed;

[0280] Scenario 2 shows the correspondence between the configuration quantity and the consumption amount screened out by using the slow-moving material consumption method provided in the relevant technology in a scenario where material procurement is not allowed;

[0281] Scenario 3 shows the correspondence between the configuration quantity and the consumption amount screened out by the slow-moving material consumption method provided in the relevant technology in a scenario where material purchase and loss are allowed;

[0282] Scenario 4 shows the corresponding relationship between the configuration quantity and the consumption amount screened out by the slow-moving material consumption method provided in this application in a scenario where material procurement is allowed;

[0283] Scenario 5, indicating the correspondence between the configuration quantity and the consumption amount screened out by the slow-moving material consumption method provided in this application in a scenario where material procurement is not allowed;

[0284] Scenario 6 shows the correspondence between the configuration quantity and the consumption amount screened out by the slow-moving material consumption method provided in the relevant technology in the scenario where material purchase and loss are allowed;

[0285] The broken line 1010 , the broken line 1020 , the broken line 1030 , the broken line 1040 , the broken line 1050 and the broken line 1060 correspond to the test results of the above-mentioned scenarios 1 to 6 respectively.

[0286] Depend on Fig. 10AIt can be seen from the test results that in the obsolete material consumption method provided in the related art, a higher obsolete material consumption amount can only be achieved when the number of screened configurations reaches 300 to 400; while using the obsolete material consumption method provided by the present application, a higher obsolete material consumption amount can be achieved when the number of screened configurations is between 20 and 30.

[0287] Fig. 10B The relationship between the configuration quantity and the time consumed by different slow-moving material consumption schemes in different scenarios is shown.

[0288] Scenario 7, indicating the correspondence between the configuration quantity and the consumption time screened out by the slow-moving material consumption method provided in the relevant technology in the scenario where material procurement is allowed;

[0289] Scenario 8, indicating the correspondence between the configuration quantity and the consumed time screened out by the slow-moving material consumption method provided in the relevant technology in a scenario where material procurement is not allowed;

[0290] Scenario nine, indicating the correspondence between the configuration quantity and the consumed time screened by the slow-moving material consumption method provided in this application in a scenario where material procurement is allowed;

[0291] Scenario 10, indicating the correspondence between the configuration quantity and the consumed time screened out by the slow-moving material consumption method provided in this application in a scenario where material procurement is not allowed;

[0292] The broken lines 1070 , 1080 , 1090 , and 10100 correspond to the test results of the above-mentioned scenarios seven to ten, respectively.

[0293] Depend on Fig. 10B The test results show that, by using the slow-moving material consumption method provided by the present application, a smaller number of configurations can be screened out in a shorter time. Fig. 10A It can be seen from the test results that, compared with the slow-moving material consumption method in the related art, the slow-moving material consumption method provided by the present application can screen out a smaller number of configurations in a shorter time, while achieving a better slow-moving material consumption effect.

[0294] Based on the aforementioned embodiments, the present application provides a device for consuming idle materials, which includes the units included therein and the modules included in the units, and can be implemented by a processor in a computer device; of course, it can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP) or a field programmable gate array (FPGA), etc.

[0295] Fig.11 A schematic diagram of the composition structure of a sluggish material consumption device provided in this application, such as Fig.11 As shown, the slow-moving material consumption device 1100 includes: a first determination module 1110, a second determination module 1120 and a third determination module 1130, wherein:

[0296] A first determination module 1110 is used to determine at least one first configuration of at least one type of first product based on the slow-moving material information; wherein the first configuration represents a material configuration in which the slow-moving material is included in the first product of the corresponding type;

[0297] A second determining module 1120 is configured to determine at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the slow-moving material consumption information corresponding to each of the second configurations, based on the business data corresponding to the slow-moving materials in each of the first configurations;

[0298] The third determination module 1130 is used to determine at least one target configuration of at least one type of target product from at least one second configuration corresponding to the at least one type of second product based on the material consumption information.

[0299] In some embodiments, the apparatus 1100 further includes a material tree construction module 1140;

[0300] The material tree construction module 1140 is used to construct a material tree corresponding to each type of the third product based on at least one material information and at least one type of third product information; wherein:

[0301] The at least one material information includes the slow-moving material information;

[0302] The at least one category of third products includes the at least one category of first products;

[0303] The material tree represents a tree structure of third products of a corresponding class composed of at least one material.

[0304] In some embodiments, each of the material information includes a material score; the material score represents the importance of the corresponding material;

[0305] The first determining module 1110 includes:

[0306] A first determination submodule 1111 determines the at least one type of first product from the at least one type of third product based on the slow-moving material information and a material tree corresponding to each type of the third product;

[0307] The second determination submodule 1112 determines, for each type of first product, at least one first configuration from at least one configuration of the first product by using a differential algorithm based on the material score of each material in the first product.

[0308] In some embodiments, the second determining submodule 1112 is used to:

[0309] Determine at least one target node from the root node and at least one intermediate node of the material tree corresponding to the first product; wherein the target node represents a node for determining a material configuration method based on at least one material substitution group; the material substitution group represents a combination of multiple materials having a substitution relationship;

[0310] For each target node, based on the material scores of the materials in each material substitution group corresponding to the target node, using a differential algorithm, determine at least one target node configuration of the target node;

[0311] At least one first configuration of the first product is determined based on the target node configuration and a material tree corresponding to the first product.

[0312] In some embodiments, the at least one target node includes a first target node; the first target node includes at least one first material substitution group; each of the first material substitution groups includes at least one first material;

[0313] The second determining submodule 1112 is used to:

[0314] Based on the material score of each of the first materials, determining a difference matrix corresponding to each of the first material substitution groups;

[0315] Determine at least one target material in each of the first material substitution groups based on the difference matrix and the configuration quantity of the target node configuration preset for the first target node;

[0316] Based on the target material, at least one target node configuration corresponding to the first target node is determined.

[0317] In some embodiments, the second determining module 1120 is configured to:

[0318] Based on the business data of each material in each of the first configurations, determining the minimum consumption of each of the first configurations; the minimum consumption represents the total quantity or total value of the materials corresponding to the minimum complete set quantity of the corresponding first configuration;

[0319] determining at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product based on the minimum consumption;

[0320] Based on the business data of each slow-moving material in each second configuration, the slow-moving material consumption information corresponding to each second configuration is determined.

[0321] In some embodiments, the apparatus 1100 further includes a fourth determination module 1140;

[0322] The fourth determination module 1140 determines a repetition coefficient corresponding to at least one material; the repetition coefficient represents the number of configurations containing the corresponding material;

[0323] The second determining module 1120 is configured to:

[0324] For each type of the first product, determining at least one third configuration with the largest minimum consumption from at least one first configuration;

[0325] For each material in each of the third configurations, determining a first quantity of the third configurations containing the material;

[0326] At least one second configuration of at least one type of second product is determined from at least one third configuration of at least one type of first product based on the first number and the repetition factor.

[0327] In some embodiments, the business data of the obsolete material includes the usage information and price information of the obsolete material in the corresponding second configuration; the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information;

[0328] The second determining module 1120 is configured to perform at least one of the following:

[0329] Based on the usage information and price information of the obsolete materials in the corresponding second configurations, determine the obsolete material consumption amount information corresponding to each of the second configurations;

[0330] Based on the usage information of the obsolete material in the corresponding second configuration, the obsolete material consumption quantity information corresponding to each of the second configurations is determined.

[0331] In some embodiments, the device 1100 further includes a display module 1150 and an update module 1160; wherein,

[0332] The display module 1150 displays and outputs at least one second configuration of the at least one category of second products; the update module 1160 updates at least one second configuration of each category of second products in response to the user's configuration information of the quantity of the second configuration corresponding to each category of the second products; or

[0333] The display module 1150 displays and outputs at least one target configuration of the at least one type of target product; the update module 1160 updates at least one target configuration of the at least one type of target product in response to the user's type configuration information for the obsolete material consumption information; wherein the type configuration information of the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information.

[0334] The description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0335] It should be noted that in the embodiment of the present application, if the above-mentioned sluggish material consumption method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific hardware, software or firmware, or any combination of hardware, software, and firmware.

[0336] An embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, some or all of the steps in the above method are implemented.

[0337] The embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, some or all of the steps in the above method are implemented. The computer-readable storage medium can be transient or non-transient.

[0338] An embodiment of the present application provides a computer program, including a computer-readable code. When the computer-readable code is run in a computer device, a processor in the computer device executes some or all of the steps for implementing the above method.

[0339] The embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and when the computer program is read and executed by a computer, some or all of the steps in the above method are implemented. The computer program product can be implemented specifically by hardware, software or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium, and in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK) and the like.

[0340] It should be noted here that the description of the various embodiments above tends to emphasize the differences between the various embodiments, and the same or similar aspects can be referenced to each other. The description of the above device, storage medium, computer program and computer program product embodiments is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the embodiments of the device, storage medium, computer program and computer program product of this application, please refer to the description of the method embodiment of this application for understanding.

[0341] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the serial number of each step / process mentioned above does not mean the order of execution, and the execution order of each step / process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application. The serial numbers of the embodiments of the present application mentioned above are for description only and do not represent the advantages and disadvantages of the embodiments.

[0342] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0343] In the several 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0344] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; 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 present embodiment.

[0345] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0346] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, etc., various media that can store program codes.

[0347] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0348] The above is only an implementation method of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for consuming slow-moving materials, comprising: Based on the information of slow-moving materials, at least one first configuration of at least one type of first product is determined; wherein the first configuration represents a material configuration of the first product of the corresponding type that contains the slow-moving material; Based on the business data corresponding to the obsolete materials in each of the first configurations, determining at least one second configuration of at least one type of second product from at least one first configuration of the at least one type of first product, and obsolete material consumption information corresponding to each of the second configurations; Based on the slow-moving material consumption information, at least one target configuration of at least one type of target product is determined from at least one second configuration corresponding to the at least one type of second product.

2. The method according to claim 1, wherein: The method further comprises: Based on at least one material information and at least one type of third product information, a material tree corresponding to each type of the third product is constructed; wherein, The at least one material information includes the slow-moving material information; The at least one category of third products includes the at least one category of first products; The material tree represents a tree structure of third products of a corresponding class composed of at least one material.

3. The method according to claim 2, wherein: Each of the material information includes a material score; the material score represents the importance of the corresponding material; The step of determining at least one first configuration of at least one type of first product based on the slow-moving material information includes: Determine the at least one category of first products from the at least one category of third products based on the slow-moving material information and the material tree corresponding to each category of the third products; For each type of first product, at least one first configuration is determined from at least one configuration of the first product by using a difference algorithm based on the material score of each material in the first product.

4. The method according to claim 3, wherein: The determining at least one first configuration from at least one configuration of the first product by using a difference algorithm based on the material fraction of each material in the first product comprises: Determine at least one target node from the root node and at least one intermediate node of the material tree corresponding to the first product; wherein the target node represents a node for determining a material configuration method based on at least one material substitution group; the material substitution group represents a combination of multiple materials having a substitution relationship; For each target node, based on the material scores of the materials in each material substitution group corresponding to the target node, using a differential algorithm, determine at least one target node configuration of the target node; At least one first configuration of the first product is determined based on the target node configuration and a material tree corresponding to the first product.

5. The method according to claim 4, wherein: The at least one target node includes a first target node; the first target node includes at least one first material substitution group; each of the first material substitution groups includes at least one first material; The determining at least one target node configuration of the target node by using a differential algorithm based on the material scores of the materials in each material substitution group corresponding to the target node includes: Based on the material score of each of the first materials, determining a difference matrix corresponding to each of the first material substitution groups; Determine at least one target material in each of the first material substitution groups based on the difference matrix and the configuration quantity of the target node configuration preset for the first target node; Based on the target material, at least one target node configuration corresponding to the first target node is determined.

6. The method according to claim 1, wherein: The determining, based on the business data corresponding to the obsolete materials in each of the first configurations, at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the obsolete material consumption information corresponding to each of the second configurations, includes: Based on the business data of each material in each of the first configurations, determining the minimum consumption of each of the first configurations; the minimum consumption represents the total quantity or total value of the materials corresponding to the minimum complete set quantity of the corresponding first configuration; determining at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product based on the minimum consumption; Based on the business data of each slow-moving material in each second configuration, the slow-moving material consumption information corresponding to each second configuration is determined.

7. The method according to claim 6, wherein: The method further comprises: Determining a repetition coefficient corresponding to at least one material; the repetition coefficient is used to control the number of configurations containing the corresponding material; The determining, based on the minimum consumption, at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product comprises: For each type of the first product, determining at least one third configuration with the largest minimum consumption from at least one first configuration; For each material in each of the third configurations, determining a first quantity of the third configurations containing the material; At least one second configuration of at least one type of second product is determined from at least one third configuration of at least one type of first product based on the first number and the repetition factor.

8. The method according to claim 6, wherein: The business data of the obsolete material includes the usage information and price information of the obsolete material in the corresponding second configuration; the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information; The determining, based on the business data of each slow-moving material in each second configuration, the slow-moving material consumption information corresponding to each second configuration includes at least one of the following: Based on the usage information and price information of the obsolete materials in the corresponding second configurations, determine the obsolete material consumption amount information corresponding to each of the second configurations; Based on the usage information of the obsolete material in the corresponding second configuration, the obsolete material consumption quantity information corresponding to each of the second configurations is determined.

9. The method according to claim 1, further comprising at least one of the following: Displaying and outputting at least one second configuration of the at least one category of second products; updating at least one second configuration of each category of second products in response to the user's configuration information of the quantity of the second configuration corresponding to each category of the second products; Display and output at least one target configuration of at least one type of target product; update at least one target configuration of at least one type of target product in response to the user's type configuration information for the slow-moving material consumption information; wherein, The type configuration information of the obsolete material consumption information includes at least one of the following: obsolete material consumption amount information, obsolete material consumption quantity information.

10. A sluggish material consumption device, comprising: A first determination module is used to determine at least one first configuration of at least one type of first product based on the information of slow-moving materials; wherein the first configuration represents a material configuration in which the slow-moving materials are contained in the first product of the corresponding type; A second determination module is used to determine at least one second configuration of at least one type of second product from at least one first configuration of at least one type of first product, and the slow-moving material consumption information corresponding to each of the second configurations, based on the business data corresponding to the slow-moving materials in each of the first configurations; The third determination module is used to determine at least one target configuration of at least one type of target product from at least one second configuration corresponding to the at least one type of second product based on the material consumption information.

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