Multi-level material surplus prediction method, system, electronic device and storage medium

Abstract

The present invention provides a multi-level material surplus forecasting method, system, electronic device and storage medium, the method comprising: obtaining the first forecast demand corresponding to the enterprise order in the first stage, determining the second demand information of the second layer material corresponding to the target material; the second layer material is used to prepare the first layer material, and the first layer material is used to prepare the target material; obtaining the second layer material corresponding to the second demand information; obtaining the second forecast demand corresponding to the enterprise order in the second stage, determining the first demand information of the first layer material; based on the obtained second layer material, preparing the first layer material corresponding to the first demand information, and determining the material surplus forecast result. The method ensures the dynamic balance of material demand by forecasting and preparing materials in stages and levels, reduces the problems of material stagnation and resource waste caused by forecast fluctuations, and improves the flexibility and rapid response capability of the supply chain.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a multi-level material surplus prediction method, system, electronic equipment and storage medium. Background Art

[0002] In the rapidly developing electronics industry, especially in the highly competitive electronics manufacturing industry, the stability and efficiency of material supply are directly related to the production capacity and market competitiveness of enterprises. When enterprises bring complex products to the market, they not only need "primary materials" that can be directly used to assemble the final products, but also need to pay in-depth attention to the secondary material supply chain behind these primary materials to ensure the smooth operation of the entire production system.

[0003] Take the production of mobile phones as an example. Mobile phone chargers are an important part of the primary materials of mobile phone manufacturers. Their production depends on secondary materials such as printed circuit boards (PCBs), casings, batteries, etc. These secondary materials are easily affected by a variety of external factors, resulting in uncertainty in the supply chain. Therefore, for mobile phone manufacturers, only focusing on the supply and demand balance of primary materials is not enough to cope with the rapid changes in the market. It is necessary to further extend to the management and control of secondary materials to prevent and resolve potential supply risks in advance.

[0004] At present, there are three traditional modes for the control of secondary materials. The first is the designated supplier procurement (Assign) mode, which provides demand forecasts to suppliers and allows them to purchase and produce secondary materials on their own; the second is the customer supply and buy and sell (BuySell) mode, in which mobile phone manufacturers purchase secondary materials in a unified manner and resell them to suppliers; the third is the customer supply and no buy and sell mode, which is similar to the BuySell mode, but does not perform a separate calculation for secondary materials in the financial department, but deducts them from the price of the final product (such as a charger). These traditional modes are unable to cope with the complex and changing supply chain environment, especially in terms of the accuracy of demand forecasts, transparency of the supply chain, and response speed. Summary of the invention

[0005] One of the purposes of the present invention is to provide a multi-level material surplus prediction method to solve the technical problem that the prior art can only control the procurement situation of materials by suppliers but fails to further control the production situation of materials, resulting in excessive material stagnation and waste of resources.

[0006] One of the purposes of the present invention is to provide a multi-level material surplus prediction system.

[0007] One of the objectives of the present invention is to provide an electronic device.

[0008] One of the objects of the present invention is to provide a computer storage medium.

[0009] In order to achieve one of the above-mentioned invention purposes, the present invention provides a multi-level material surplus forecasting method, including: obtaining a first predicted demand corresponding to an enterprise order in the first stage, and determining a second demand information of a second-layer material corresponding to a target material; the second-layer material is used to prepare a first-layer material, and the first-layer material is used to prepare the target material; obtaining the second-layer material corresponding to the second demand information; obtaining the second predicted demand corresponding to the enterprise order in the second stage, and determining the first demand information of the first-layer material; based on the obtained second-layer material, preparing the first-layer material corresponding to the first demand information, and determining the material surplus forecasting result.

[0010] As a further improvement of an embodiment of the present invention, the method of preparing the first layer material corresponding to the first demand information based on the obtained second layer material and determining the material remaining forecast result includes: updating the second forecast result of the second layer material used to prepare the first layer material in the second demand information according to the first forecast result of the first layer material in the first demand information to obtain the updated second demand information; and determining the material remaining forecast result according to the updated second demand information and the first demand information.

[0011] As a further improvement of an embodiment of the present invention, the updating of the second prediction result of the second layer material used to prepare the first layer material in the second demand information includes: determining whether the first prediction result is greater than or equal to the second prediction result; if so, updating the second prediction result to 0; if not, updating the second prediction result to the difference between the second prediction result and the first prediction result.

[0012] As a further improvement of an embodiment of the present invention, determining the material remaining forecast result based on the updated second demand information and the first demand information includes: combining the first demand information and the updated second demand information to obtain the material remaining forecast result.

[0013] As a further improvement of an embodiment of the present invention, after determining the material surplus forecast result, it includes: determining the remaining material net demand information according to the actual demand of the enterprise order and the material surplus forecast result; and updating the determined material surplus forecast result based on the remaining material net demand information.

[0014] As a further improvement of an embodiment of the present invention, the updating and determining of the material remaining forecast result based on the remaining material net demand information includes: based on the defined material supply ratio, splitting the remaining material net demand information, and determining a number of remaining material net demand information provided by a number of material suppliers; the material supply ratio includes at least one of a supplier ratio and an alternative material ratio; and determining an updated material remaining forecast result based on each remaining material net demand information.

[0015] As a further improvement of an embodiment of the present invention, the material surplus forecast result is offset based on the actual demand information of the target material to determine the net demand information of the remaining material, including: determining the actual demand quantity of the first-layer material corresponding to the target material according to the actual demand information of the target material; determining the net demand quantity of the remaining material according to the difference between the actual demand quantity and the forecast demand quantity of the second-layer material used to prepare the first-layer material in the material surplus forecast result.

[0016] As a further improvement of an implementation manner of the present invention, the cumulative release volume of the first predicted demand is less than or equal to the cumulative release volume of the second predicted demand.

[0017] As a further improvement of an embodiment of the present invention, the method also includes: determining the acquisition cycle of each material in the first layer of materials, and publishing the demand information of the materials with longer acquisition cycles until the first layer of materials are released; determining the acquisition cycle of each material in the second layer of materials, and publishing the demand information of the materials with longer acquisition cycles until the second layer of materials are released.

[0018] To achieve one of the above-mentioned purposes of the invention, the present invention also provides a multi-level material surplus forecasting system, comprising: a first module, used to obtain the first predicted demand corresponding to the enterprise order in the first stage, and determine the second demand information of the second-layer material corresponding to the target material, the second-layer material is used to prepare the first-layer material, and the first-layer material is used to prepare the target material; used to obtain the second-layer material corresponding to the second demand information; a second module, used to obtain the second predicted demand corresponding to the enterprise order in the second stage, and determine the first demand information of the first-layer material; a third module, used to prepare the first-layer material corresponding to the first demand information based on the obtained second-layer material, and determine the material surplus forecasting result.

[0019] In order to achieve one of the above-mentioned purposes of the invention, the present invention also provides an electronic device, comprising: at least one processor; a memory, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, it executes the steps of the multi-level material surplus prediction method described in any of the above-mentioned technical solutions.

[0020] In order to achieve one of the above-mentioned purposes of the invention, the present invention also provides a computer storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the multi-level material surplus prediction method described in any of the above-mentioned technical solutions are performed.

[0021] Compared with the prior art, the embodiments of the present invention have at least one of the following beneficial effects:

[0022] The present invention adopts a multi-level material surplus forecasting method. By determining the second demand information of the second-level materials corresponding to the first stage, and the first demand information of the first-level materials corresponding to the second stage, it can realize staged and hierarchical forecasting and material preparation, and can more comprehensively reflect the material demand situation in the production process; first determine the second demand information of the second-level materials, allowing suppliers to have enough time to prepare the second-level materials, and when the first demand information of the first-level materials is determined, make necessary adjustments to the previously released second-level material demand information, and jointly realize the management of material procurement and production processes, ensure the dynamic balance of material demand, reduce material stagnation and resource waste caused by forecast fluctuations, and improve the flexibility and rapid response capability of the supply chain.

[0023] In addition, when there is still material left after the second demand information meets the first-level material preparation needs, the company only needs to bear the purchase cost of this part of the remaining materials without paying additional production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the structure of a multi-level material surplus prediction system in one embodiment of the present invention.

[0025] Figure 2 It is a schematic diagram of the structure of the bill of materials of a mobile phone product in one embodiment of the present invention.

[0026] Figure 3 It is a schematic diagram of the steps of a multi-level material surplus prediction method in one embodiment of the present invention.

[0027] Figure 4 2 is a schematic diagram of step S4 in one embodiment of the present invention.

[0028] Figure 5 It is a schematic diagram of step S41 of a specific embodiment of an embodiment of the present invention.

[0029] Figure 6 It is a structural diagram of a bill of materials for a mobile phone product with alternative suppliers in one embodiment of the present invention.

[0030] Figure 7 It is a schematic diagram of steps after step S4 in a specific embodiment of an embodiment of the present invention.

[0031] Figure 8 It is a schematic diagram of step S5 of a specific embodiment of an embodiment of the present invention.

[0032] Fig. 9 It is a schematic diagram of step S512 of a specific embodiment of an embodiment of the present invention.

[0033] Fig.10 It is a schematic diagram of step S5 of another specific embodiment of one embodiment of the present invention.

[0034] Fig.11 It is a flow chart of a multi-level material surplus prediction method in a preferred embodiment of the present invention.

[0035] Fig.12 It is a schematic structural diagram of a refrigeration device in one embodiment of the present invention. DETAILED DESCRIPTION

[0036] The present invention will be described in detail below in conjunction with the specific embodiments shown in the accompanying drawings. However, these embodiments do not limit the present invention, and any structural, methodological, or functional changes made by a person skilled in the art based on these embodiments are all within the scope of protection of the present invention.

[0037] It should be noted that the term "comprises" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In addition, the terms "first", "second", etc. are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0038] like Figure 1 As shown, an embodiment of the present invention provides a multi-level material surplus prediction system 100.

[0039] The multi-level material surplus forecasting system 100 is a supply chain management system that comprehensively considers the forecasted demand of enterprises at different stages, decomposes the material demand into multiple levels according to the product structure and production process, and forecasts and manages the material demand at each level respectively. It ensures the dynamic balance between material supply and production demand, and reduces the problems of material stagnation and resource waste caused by forecast fluctuations.

[0040] For example, Figure 2As shown in the figure, the product structure and generation process are described by taking the bill of materials of a mobile phone manufacturer as an example. For a mobile phone manufacturer, the "mobile phone" is the final product, which is directly purchased and used by users. The "mobile phone" as a whole includes all necessary components and accessories to meet the basic communication and entertainment needs of users. Among them, the components and accessories include at least one of the primary materials and the secondary materials.

[0041] Among them, primary materials, also known as purchased parts, refer to components or parts purchased directly by mobile phone manufacturers from upstream suppliers for the production or assembly of final products. When these materials reach mobile phone manufacturers, they are already finished or semi-finished products and can be used in production directly or after simple processing.

[0042] Secondary materials refer to materials that are not directly purchased by mobile phone manufacturers from suppliers. They are components of primary materials and are further processed or produced by suppliers of primary materials. These materials are at a deeper level in the supply chain and may not be known or managed by mobile phone manufacturers, but their quality and cost directly affect the performance and cost of primary materials and even the final product.

[0043] Primary materials and secondary materials are at different levels in the supply chain. Primary materials are directly provided to mobile phone manufacturers, while secondary materials indirectly serve mobile phone manufacturers through suppliers of primary materials. Therefore, mobile phone manufacturers are directly dependent on primary materials, while their dependence on secondary materials is indirect, realized through suppliers of primary materials.

[0044] For example, a mobile phone manufacturer will prepare the "bare phone" + "shell components" into a "bare phone"; prepare the "battery cell" + "others" into a "PCB", and then prepare the "PCB" + "shell" into a "charger"; and finally prepare the "bare phone" + "packaging materials" + "charger" into a "mobile phone".

[0045] "Shell components", "packaging materials", "chargers", etc. can all be purchased directly from upstream suppliers. Current mobile phone suppliers only need to continue processing, and these materials are purchased parts or first-level materials. For some materials, such as "chargers", they are purchased from first-level material suppliers. When first-level material suppliers generate "chargers", they will use "PCB" and "shells". The preparation of "PCBs" will use "battery cells" and other materials. Therefore, "PCB", "shells", "battery cells" and "others" are collectively referred to as the second-level materials of current mobile phone manufacturers.

[0046] Among them, materials such as "PCB" that need further preparation are also called the first layer of materials that need to be produced in the secondary materials (or, the first layer of materials in the secondary materials), and "battery cells" are called the second layer of materials that need to be prepared in the secondary materials (or, the second layer of materials in the secondary materials).

[0047] In one embodiment, the multi-level material surplus forecasting system 100 predicts demand information of materials at different levels according to a multi-level material surplus forecasting method, so as to guide material suppliers to prepare materials in advance.

[0048] In a specific embodiment, the multi-level material surplus prediction method can be implemented by referring to any technical solution provided below.

[0049] The multi-level material surplus forecasting system 100 comprises a first module 11. The first module 11 is used to process the forecasting demand of the first stage.

[0050] In one embodiment, the first module 11 is used to obtain the first forecast demand corresponding to the enterprise order in the first stage, and determine the second demand information of the second layer material corresponding to the target material. The second layer material is used to prepare the first layer material, and the first layer material is used to prepare the target material.

[0051] In a specific embodiment, the second layer material can be a raw material. Figure 2 As shown, for example, the second layer material is "battery cell", which is used to prepare the first layer material "PCB", and the first layer material "PCB" is used to prepare the target material "charger".

[0052] In one embodiment, the first module 11 is used to obtain the second layer material corresponding to the second demand information.

[0053] In a specific embodiment, if the supplier does not have the production capacity or the production cost is higher than the purchase cost, the second layer material corresponding to the second demand information is obtained through procurement.

[0054] In a specific embodiment, if the supplier has production capacity, the second-layer material corresponding to the second demand information can be obtained through production.

[0055] The multi-level material surplus forecasting system 100 comprises a second module 12. The second module 12 is used to process the forecasting demand of the second stage.

[0056] In one embodiment, the second module 12 is used to obtain the second forecast demand corresponding to the enterprise order in the second stage, and determine the first demand information of the first layer material.

[0057] In a specific embodiment, the first layer of material can be a semi-finished product or an intermediate product. Figure 2 As shown, for example, the first-layer materials "PCB" and "casing" corresponding to the target raw material "charger" are used to directly assemble the first-level material "charger" of the mobile phone.

[0058] In one embodiment, the acquisition period of the first layer of materials is shorter than the acquisition period of the second layer of materials, wherein the acquisition period includes at least one of a procurement period and a production period.

[0059] In this way, the forecast demand for the second-level materials is released first, and then the forecast demand for the first-level materials is released. This can reduce or even avoid material stagnation caused by excessive previous forecasts due to a reduction in subsequent forecast demand.

[0060] The multi-level material surplus forecasting system 100 includes a third module 13. The third module 13 is used to comprehensively consider the forecasting demand of the first stage and the forecasting demand of the second stage.

[0061] In one embodiment, the third module 13 is used to prepare the first-layer material corresponding to the first demand information based on the obtained second-layer material, and determine the material surplus prediction result.

[0062] Reference Figure 1 The content shown summarizes the working process of the multi-level material surplus forecasting system.

[0063] Based on historical data, market demand and other factors, the initial forecast of the demand for corporate orders in the future is determined to determine the first forecast demand for the corresponding corporate orders in the first phase, and the second demand information for the second-layer materials is determined based on the first forecast demand. Specifically, based on the production demand of the target material, the demand for the second-layer materials required to prepare the first-layer materials is reversely calculated; based on the second demand information, purchase or deployment is carried out to ensure that there are enough second-layer materials for subsequent production. It can be seen that the first module determines the demand for the final product by predicting demand, and then gradually calculates the demand for the first-layer materials and the second-layer materials, and finally obtains the materials.

[0064] After the first stage, the forecasted order demand may be updated or revised based on new market information or changes in forecasted orders; the demand for the first-tier materials (e.g., intermediate or semi-finished products) is re-determined based on the updated forecast demand. It can be seen that the second module can flexibly and dynamically adjust the demand for intermediate products based on changes in forecast demand. The first-tier materials are prepared using the acquired second-tier materials. During the preparation process, the future material surplus is predicted based on consumption and inventory conditions, so that the procurement or production plan can be adjusted in a timely manner.

[0065] The entire process reflects a complete supply chain from demand forecasting to material preparation to production execution. Each module is closely connected and interdependent, forming an efficient and flexible material management and production planning system. Through continuous optimization and adjustment, the system can ensure that while meeting market demand, inventory costs and material stagnation are minimized.

[0066] like Figure 3As shown, one embodiment of the present invention provides a multi-level material surplus prediction method.

[0067] The multi-level material surplus prediction method is applied to a multi-level material surplus prediction system.

[0068] In one embodiment, the multi-level material surplus prediction system can be as follows: Figure 1 The configuration is performed as described above, and the corresponding technical solution is set and referenced in the generation method provided by the present invention. Of course, the multi-level material surplus prediction system used in the multi-level material surplus prediction method provided by the present invention is not limited to this configuration structure.

[0069] like Figure 3 As shown, a multi-level material surplus prediction method provided in one embodiment of the present invention includes the following steps.

[0070] Step S1, obtaining the first forecast demand corresponding to the enterprise order in the first stage, and determining the second demand information of the second-layer material corresponding to the target material;

[0071] Step S2, obtaining a second-layer material corresponding to the second demand information;

[0072] Step S3, obtaining the second forecast demand corresponding to the enterprise order in the second stage, and determining the first demand information of the first layer material;

[0073] Step S4: based on the obtained second-layer materials, prepare the first-layer materials corresponding to the first demand information and determine the material surplus prediction result.

[0074] In this way, by determining the second demand information corresponding to the second-layer materials in the first stage, and the first demand information corresponding to the first-layer materials in the second stage, it is possible to achieve phased and hierarchical forecasting and material preparation, which can more comprehensively reflect the material demand situation in the production process; first determine the second demand information of the second-layer materials, allowing suppliers to have enough time to prepare the second-layer materials, and when the first demand information of the first-layer materials is determined, make necessary adjustments to the previously released second-layer material demand information, and jointly realize the management of material procurement and material production processes, ensure the dynamic balance of material demand, reduce material stagnation and resource waste caused by forecast fluctuations, and improve the flexibility and rapid response capabilities of the supply chain.

[0075] In one embodiment, the second layer material is used to prepare the first layer material, and the first layer material is used to prepare the target material. Preparation refers to all means of obtaining the first layer material and / or the second layer material, including at least one of procurement and production.

[0076] In this embodiment, the first layer of material and the second layer of material are both relative to the target material. Figure 2As shown, if the target material is a "charger", the corresponding first-layer material includes "PCB" and the second-layer material includes "battery cell".

[0077] Understandably, different materials have different acquisition cycles (e.g., procurement cycles and / or production cycles). In order to minimize the double losses of procurement costs and production costs, the order of releasing material forecast information is determined based on the difference in the length of material acquisition cycles. That is, the demand information of the second-tier materials with longer acquisition cycles is released first, and the demand information of materials with shorter acquisition cycles and / or higher values ​​is released later. In this way, the material demand information released in advance can be dynamically adjusted according to the material demand information released later.

[0078] The "enterprise order" in step S1 does not directly refer to an actual order that has been placed and confirmed, but rather an estimate of the order volume that may be generated in the future based on environmental factors, wherein the environmental factors include at least one of market forecasts, historical sales data, and production plans.

[0079] The first stage can be understood as the early stage in the supply chain, when the company has just obtained or predicted the initial market demand and has specified the initial material procurement and production plan accordingly. In the first stage, since some materials have a long acquisition cycle, the company needs to predict and purchase them in the early stage to ensure the smooth progress of subsequent production.

[0080] It can be seen that the first predicted demand is a preliminary forecast of the demand for the final product based on some method (such as market forecast, sales forecast, etc.); based on the first predicted demand, the demand information of the second-layer material required to prepare the target material is determined through the bill of materials or production process analysis, that is, the second demand information of the second-layer material is determined, which is based on the preliminary market forecast and production plan.

[0081] The second stage can be understood as being based on the first stage. As market demand becomes clearer and production progress advances, the company enters the second stage. At this stage, the company's forecasted demand may change, and the second forecasted demand is obtained. The second forecasted demand is the forecasted demand for the first-level materials.

[0082] It can be seen that the second predicted demand is also a further forecast of the demand for the final product based on some method (such as market forecast, sales forecast, etc.); according to the second predicted demand and the second demand information, the demand information of the first-layer material required to prepare the target material is determined through the bill of materials or production process analysis, that is, the first demand information of the first-layer material is determined, which is based on further market forecasts and production plans.

[0083] Therefore, whether it is the first forecast demand or the second forecast demand, whether it is the first demand information or the second demand information, they are all the forecast results of the enterprise for the target material at different stages, which can be used to release to suppliers in advance to guide suppliers to prepare different materials at different stages.

[0084] In addition, taking into account the cyclical changes in demand, such as seasonal changes (the impact of holidays on sales), market trends (the release of new products), consumer behavior patterns, etc., the first predicted demand and / or the second predicted demand can be divided into different forecast periods, for example, divided into the first week, second week, third week, etc. after the current time point, and can be dynamically adjusted according to actual conditions without specific restrictions.

[0085] It should be noted that the first forecast demand and the second forecast demand are contractually agreed upon, and the enterprise supplier can use this to request subsequent compensation for material obsoleteness from the supplier.

[0086] In one embodiment, if the first layer of materials includes multiple materials, and / or the second layer of materials includes multiple materials, the materials are released in sequence according to the length of the acquisition cycle of each group of materials.

[0087] In a specific embodiment, the acquisition cycle of each material in the first layer of materials is determined, and the demand information of the materials with the longest acquisition cycle is released until the first layer of materials is completely released.

[0088] Specifically, the acquisition cycle of each material in the first layer of materials can be sorted first, and then released in descending order; or, based on the acquisition cycle of each material, the corresponding average value is determined first, and then the materials with an acquisition cycle higher than the average value are released, and finally the materials with an acquisition cycle lower than the average value are released; or, based on the acquisition cycle of each material, the corresponding median is determined first, and then the materials with an acquisition cycle higher than the median are released, and finally the materials with an acquisition cycle lower than the median are released. In this regard, the present invention does not make specific restrictions, and can be freely selected according to actual conditions.

[0089] In a specific embodiment, the acquisition cycle of each material in the second-layer materials is determined, and the demand information of the materials with the longest acquisition cycle is released until the second-layer materials are completely released.

[0090] Similarly, the method for publishing the second-layer materials can also refer to the method for publishing the first-layer materials mentioned above, and will not be repeated here.

[0091] In one embodiment, the cumulative release volume of the first forecast demand is less than or equal to the cumulative release volume of the second forecast demand. In this way, the enterprise will not prepare too much material in advance, thus avoiding unnecessary inventory backlog.

[0092] like Figure 4As shown, in one embodiment, step S4 may specifically include but is not limited to the following steps.

[0093] Step S41, updating the second prediction result of the second layer material used for preparing the first layer material in the second demand information according to the first prediction result of the first layer material in the first demand information, to obtain updated second demand information;

[0094] Step S42: determining the material remaining forecast result according to the updated second demand information and the first demand information.

[0095] In this way, based on the first forecast results of the first-layer materials that have been determined, the quantity of second-layer materials required to generate these first-layer materials is reversely calculated and adjusted to ensure that the supply of second-layer materials can be synchronized and matched with the demand for first-layer materials, avoiding material shortages or surpluses.

[0096] like Figure 5 As shown, in a specific embodiment, the part of "updating the second prediction result of the second layer material used for preparing the first layer material in the second demand information" in step S41 can specifically include the following steps.

[0097] Step S411, determining whether the first prediction result is greater than or equal to the second prediction result;

[0098] If yes, jump to step S412A and update the second prediction result to 0;

[0099] If not, jump to step S412B to update the second prediction result to the difference between the second prediction result and the first prediction result.

[0100] In this way, by comparing the sizes of the first prediction result and the second prediction result, the second prediction result is updated to achieve accurate matching and reduce redundant inventory.

[0101] In one embodiment, step S42 may specifically include the following steps.

[0102] Step S42', combining the first demand information and the updated second demand information to obtain the material remaining prediction result.

[0103] In this way, by combining the first demand information and the second demand information, the company can clearly understand the demand situation of each layer of materials, and adjust the procurement and production plans according to the actual situation, avoiding material shortages or surpluses caused by opaque information or inaccurate forecasts.

[0104] To facilitate understanding of the above technical solution, we can take a mobile phone manufacturer as an example. In this example, considering that different mobile phone models or systems may have different product positioning, such as flagship models may focus more on fast charging technology and user experience, while entry-level models may focus more on cost control. Therefore, as part of the first-level materials of mobile phones, chargers can be replaced by setting the ratio of chargers with different specifications and performances to effectively control costs and improve product competitiveness.

[0105] like Figure 6 As shown in the figure, based on market supply relationships and price factors, mobile phone manufacturers will have multiple material suppliers, such as multiple charger suppliers, and material supply ratios. At the beginning of the project, mobile phone manufacturers can publish not only the demand information for mobile phone products, but also the demand information for at least one of the primary and secondary materials based on factors such as mobile phone demand, comprehensive price and production capacity. They can publish forecasted demand within the forecast period, such as demand information for the next week (WK1), two weeks (WK2), three weeks (WK3) or even four weeks (WK4).

[0106] Assume that in the initial stage, the demand information of mobile phones is WK1 2000, WK2 2000, WK3 2000 and WK4 2000, and set the supply ratio of charger 1 and charger 2 to 7:3. Different materials have different acquisition cycles. According to the difference in the length of the acquisition cycle, the predicted demand of materials at each level is determined, and the initial demand information is shown in Table 1:

[0107]

[0108] Table 1

[0109] As shown in Table 1, the first forecast demand for the corresponding enterprise orders in the first phase is obtained. As part of the accessories (or primary materials) of mobile phones, the demand information of chargers (including charger 1 and charger 2) is the same as that of mobile phones, both of which are 2000. Similarly, the demand information of the first-layer materials of chargers, PCB (including PCB1 and PCB2) and shell (including shell 1 and shell 2), should also be the same as that of chargers, both of which are 2000.

[0110] Based on the long procurement cycle of battery cells and the short production cycle of PCBs, the initial forecast information of secondary materials for mobile phones is determined as shown in Table 2. The content shown in Table 2 is the initial forecast information of the mobile phone manufacturer, but it is not necessarily the final forecast information released to suppliers.

[0111]

[0112] Table 2

[0113] Since the published forecasts are contractually agreed, if there is a decrease in demand later, resulting in multiple forecasts, the mobile phone manufacturer needs to bear the corresponding responsibility. Therefore, when the actual forecast is released, based on the longer procurement cycle of battery cells and the shorter PCB production cycle, the second-layer materials with shorter acquisition cycles are released first, while the first-layer demand information of the first-layer materials with shorter growth cycles and / or higher prices is delayed (because the closer the forecast results are to the actual situation, the closer they are to the actual situation). That is, according to the first predicted demand, the second demand information of the second-layer materials corresponding to the charger (target material) is determined, as shown in Table 3, and the second demand information shown in Table 3 is released first.

[0114]

[0115] Table 3

[0116] Among them, the mobile phone manufacturer's supplier 1 and supplier 2 can prepare the secondary materials in advance according to the forecast in Table 3. In other words, Table 3 can be understood as the inventory of supplier 1 and supplier 2 after procurement.

[0117] According to the actual acquisition cycle or actual production rhythm, the second forecast demand of the corresponding enterprise order in the second stage is obtained, and the first demand information of the first-level material is determined. The first demand information may be slightly different from the initial forecast information of the secondary material shown in Table 2. It is assumed to be as shown in Table 4, that is, the first demand information shown in Table 4 is released later.

[0118]

[0119] Table 4

[0120] It can be seen from Table 4 that the demand for PCB1 and PCB2 in the first demand information released later is 1200 and 800 respectively, which is lower than the demand for battery cells (supplier 1) and battery cells (supplier 2) in the second demand information shown in Table 3. This may indicate that mobile phone manufacturers adjusted the material forecast demand when they found that the market demand decreased in the later period.

[0121] In this way, even if an order is placed according to the first demand information, when the second demand information is stagnant, the mobile phone manufacturer will only compensate for the purchase cost of the stagnant second demand information, and will not compensate for the production cost of using battery cells to prepare PCBs.

[0122] At this time, as shown in Table 5, the second demand information is adjusted based on the first demand information released later to obtain the adjusted second demand information.

[0123]

[0124] Table 5

[0125] According to the first demand information described in Table 4, the demand for PCB1 is 1200, and PCB1 is produced by battery cells (supplier 1), so the battery cells (supplier 1) that need to be consumed are also 1200. According to Table 3, the purchase quantity of battery cells (supplier 1) is 1400, which means that within the WK1 time, the remaining forecast result of battery cells (supplier 1) is 1400-1200=200.

[0126] Similarly, the first demand information shows that the demand for PCB2 is 800, and PCB2 is produced by the battery cell (supplier 2), so the battery cells (supplier 2) that need to be consumed are also 800. According to Table 3, the purchase quantity of battery cells (supplier 2) is 600, which means that within the WK1 time, the purchase quantity of battery cells (supplier 2) needs to be used for preparation, and the corresponding remaining forecast result is 0, and there is still a shortfall of 200, which can be deducted in the subsequent WK2 time. That is, the battery cell (supplier 2) corresponding to WK2 in the first demand information is 600, and after deducting the 200 required in WK1, the corresponding remaining forecast result is 400.

[0127] The first demand information and the adjusted second demand information are combined to obtain the material remaining prediction result, as shown in Table 6.

[0128]

[0129] Table 6

[0130] In addition, market demand is dynamic, and releasing actual orders too early may lead to overproduction or underproduction due to changes in subsequent demand. Some excess materials may have high value, and once excess demand or demand changes occur, it may lead to greater economic losses. In order to minimize this risk, choose to release the actual production plan (or place a purchase order) when the actual demand is clearer.

[0131] In one embodiment, the actual production plan is published separately and the publishing time is later than the publishing time of the first demand information and the second demand information.

[0132] In one embodiment, the material surplus forecast result is offset based on the actual production plan, which helps the enterprise to timely discover and adjust the material demand plan and reduce the risk of stagnation.

[0133] like Figure 7 As shown, in a specific embodiment, after step S4, the method may further include the following steps.

[0134] Step S5, determining the remaining material net demand information according to the actual demand of the enterprise order and the material remaining forecast result;

[0135] Step S6: based on the remaining material net demand information, update and determine the material remaining forecast result.

[0136] In this way, by comparing the actual order demand and the material remaining forecast results, the net demand for each material (that is, the actual quantity that needs to be purchased or adjusted) can be accurately calculated, thereby guiding the company to formulate a more accurate procurement plan and reduce cost waste or production delays caused by over- or under-purchasing.

[0137] Among them, the "corporate order" in step S5 is also called a purchase order (PO), which is a formal document issued by the purchaser (such as a mobile phone manufacturer) to the supplier (such as supplier 1 and / or supplier 2). It is an actual, issued and confirmed order used to clarify the transaction details and terms between the two parties.

[0138] In one embodiment, the corresponding actual demand information is determined according to the suppliers of the target material, specifically, the first actual demand information provided by the first supplier (charger 1) is determined, and / or the second actual demand information provided by the second supplier (charger 2) is determined.

[0139] After clarifying the actual demand of the enterprise order and determining the actual demand information of the target material accordingly, it is necessary to have an in-depth understanding of the hierarchical structure of material supply, including the dependency relationship between materials at different levels, supply cycle and other factors. By comprehensively considering these factors, the overall demand can be converted into detailed net demand information for materials at each level.

[0140] In a specific embodiment, the remaining net material requirement is calculated based on a material requirement planning (MRP) method. Figure 8 As shown, in a specific embodiment, step S5 may specifically include but not be limited to the following steps.

[0141] Step S511, determining the corresponding actual demand information of the target material according to the actual demand of the enterprise order;

[0142] Step S512: based on the actual demand information of the target material, the material remaining forecast result is reduced to determine the remaining material net demand information.

[0143] The actual demand refers to the demand for a specific product in the order that the enterprise actually receives and needs to fulfill. The actual demand information for the target material refers to the specific demand for the target material required for the specific product, including the material type (such as the first-tier material and / or the second-tier material), material quantity, supplier, etc. of the target material.

[0144] For example, if the actual demand for an enterprise order is for mobile phones, then the actual demand information for the corresponding target materials will be determined based on the bill of materials, including the demand for chargers, casings, PCBs, battery cells and other materials.

[0145] Offsetting refers to the process of offsetting income or consumption. Specifically, offsetting can be partial offsetting or full offsetting. In the present invention, offsetting refers to the act of offsetting the actual demand for target materials with the remaining forecast of the materials.

[0146] like Fig. 9 As shown, in a specific embodiment, the method described in step S512 of the present invention may also include the following steps.

[0147] Step S5121, determining the actual demand quantity of the first-layer material corresponding to the target material according to the actual demand information of the target material;

[0148] Step S5122: determine the remaining material net requirement based on the difference between the actual requirement and the predicted requirement of the second layer material used to prepare the first layer material in the material remaining prediction result.

[0149] In this way, the remaining net material demand is determined based on the actual material demand and the remaining forecast demand, which helps to reduce material waste and excess inventory and improve material utilization efficiency.

[0150] In this embodiment, the remaining net material requirement is the amount of first-layer material that still needs to be prepared after considering the remaining forecast results of the existing materials. If the first-layer material is composed of multiple components that can be prepared separately, it can be further divided down to a finer level, that is, the net requirement of the second-layer material.

[0151] like Fig.10 As shown, in a specific embodiment, step S5 may specifically include but not be limited to the following steps.

[0152] Step S521, based on the defined material supply ratio, split the remaining material net demand information to determine a number of remaining material net demand information provided by a number of material suppliers;

[0153] Step S522: determining and updating the material remaining forecast result according to the net demand information of each remaining material.

[0154] In this way, the remaining net material demand is split according to the material supply ratio, and the corresponding supplier's net material demand information is generated. This enables enterprises to adjust supplier allocation according to actual demand, improve the refinement of material demand management, and enhance the flexibility and response speed of the supply chain.

[0155] In one embodiment, the material supply ratio includes at least one of a supplier ratio and an alternative material ratio.

[0156] Supplier ratio refers to the ratio of the number of orders placed by the enterprise to a certain supplier in a certain period of time to the total number of purchase orders of the same type; alternative material ratio refers to the proportion of alternative materials that the enterprise chooses to use to replace the original materials in the actual production process. The net demand for remaining materials refers to the number of materials that still need to be replenished after taking into account the existing inventory in order to meet production or sales needs in a specific period of time.

[0157] In one embodiment, the net requirement for remaining materials is determined based on the actual requirement information of the target materials and the reduction of the material remaining forecast result, and is used to supplement the material quantity to meet the actual demand.

[0158] In order to facilitate understanding of the above technical solution, a mobile phone manufacturer can be used as an example for further explanation. After obtaining the material surplus prediction result (ie, Table 6), the material surplus prediction result is updated according to the actual purchase order placed by the mobile phone manufacturer.

[0159] Assuming that the actual order information of the mobile phone manufacturer is 1000 for charger 1 and 500 for charger 2, the material remaining forecast result shown in Table 6 is updated according to the actual order information to obtain the updated material remaining forecast result (including the first-layer materials and the second-layer materials), as shown in Table 7.

[0160]

[0161] Table 7

[0162] In Table 7, since the actual order information is that Charger 1 is 1000, the PCB1, Shell 1 and Battery (Supplier 1) that need to be consumed are all 1000. In the original material remaining forecast results shown in Table 6, PCB1 is 1200 and Shell is 1400, so the remaining is 1200-1000=200, 1400-1000=400. Similarly, the remaining PCB2 is 800-500=300, and the remaining Shell 2 is 600-500=100. The remaining forecast results in the subsequent forecast cycle (WK2-WK4) remain unchanged.

[0163] It should be noted that during the material requirement planning calculation process, the material demand is determined based on certain forecast data, and these demands are allocated to different suppliers or production lines according to the supply ratio. However, in actual operation, due to various factors (such as delayed delivery, production line failure, changes in market demand, etc.), the actual material supply may deviate from the forecast. If the demand is split only according to the preset procurement or production ratio, and these actual deviations are not taken into account, there may be a large gap between the forecast demand and the actual demand of some suppliers or production lines. This gap may further affect the actual supply ratio, thereby destroying the original supply and demand balance.

[0164] Therefore, the remaining material forecast results obtained here will be used as material supply again and participate in the next material requirement planning calculation as "special inventory". Assuming that in the next material requirement planning calculation, the demand for mobile phones has changed, WK2 2400, WK3 1800, WK4 1500, WK5 2000, when the charger 1 and charger 2 are replaced, the "special inventory" of the published forecast will be considered, and the complete set will be calculated to make branch selection. For example, the charger 1 branch selection is 3200, and the charger 2 branch selection is 1300; the remaining material net demand is split according to the set material supply ratio to obtain the net demand information of materials at each level, as shown in Table 8.

[0165]

[0166] Table 8

[0167] Specifically, according to the material remaining prediction results shown in Table 6, the total remaining quantity of battery cells (supplier 1) in WK1-WK4 is 200+1400+1400=3000. 3000 battery cells can produce 3000 PCB1s, and 3000 PCB1s can be produced into 3000 chargers 1. In addition, the remaining quantity of PCB1 in WK1 is 200. It can be seen that the material remaining prediction results shown in Table 6 can produce a maximum of 3200 chargers 1, that is, the above-mentioned "charger 1 branch selects 3200".

[0168] Similarly, the total remaining quantity of battery cells in WK1-WK4 (supplier 2) is 400+600=1000, and the remaining quantity of PCB2 in WK1 is 300. It can be seen that the remaining material prediction results shown in Table 6 can produce a maximum of 1300 chargers 2, that is, the above-mentioned "charger 2 branch selection 1300" is obtained.

[0169] According to the new actual demand information, the actual demand for the first layer of materials is determined to be 2400+1800+1500+2000=7700. The current material remaining forecast result shows that the predicted demand for the second layer of materials used to prepare the first layer of materials is 3200+1300=4500. The difference between the two gives a net demand for the remaining materials of 7700-4500=3200.

[0170] According to the material remaining prediction results shown in Table 6, the remaining PCB1 and battery cells (supplier 1) in WK1 to WK2 can produce 200+200+1400=1800 chargers 1. The demand for WK2 is 2400, and the corresponding charger 2 requires 600 (first use the PCB2 in WK1 and then use 300 of the 400 battery cells (supplier 2) in WK2).

[0171] The demand for WK3 is 1800, while the remaining cells in WK3 (supplier 1) are 1400, indicating that the remaining quantity will be completely consumed, that is, the charger 1 in WK3 in Table 8 is 1400, and the corresponding charger 2 requires 1800-1400=400, and the material remaining forecast result is 1300-600-400=300. It can be seen that after the WK3 forecast cycle, the material remaining forecast result of charger 1 is 0, and the material remaining forecast result of charger 2 is 300.

[0172] In the new actual demand information, WK4 is 1500. Excluding the remaining 300, the net demand for the remaining materials split into WK4 is 1200. According to the defined material supply ratio of 7:3, the net demand information of charger 1 in WK4 is the remaining prediction result + split result = 0 + 1200*0.7 = 840, and the net demand information of charger 2 is the remaining prediction result + split result = 300 + 1200*0.3 = 660, as shown in Table 8 above.

[0173] Similarly, according to the actual demand of WK5 of 2000 and the defined material supply ratio of 7:3, the net demand information of charger 1 in WK5 is 2000*0.7=1400, and the net demand information of charger 2 is 2000*0.3=600, as shown in Table 8 above. The net demand information of the first-layer materials and the second-layer materials corresponding to charger 1 and charger 2 can be referred to as described above, and the calculation results can also be shown in Table 8, which will not be repeated here.

[0174] According to the net demand information of materials at each level shown in Table 8, the incremental material forecast information is determined, as shown in Table 9.

[0175]

[0176] Table 9

[0177] The second demand information of the second-level materials and the first demand information of the first-level materials can be released again in a rolling manner. Through rolling release and automatic reduction, the proportion of multi-level materials can be continuously corrected according to the material remaining forecast results. In addition, by releasing demand information in batches, it is possible to accurately control materials with different acquisition cycles and reduce liability compensation caused by material stagnation.

[0178] Fig.11 A schematic flow chart of a multi-level material surplus prediction method in a preferred embodiment is shown.

[0179] In this embodiment, the mobile phone manufacturer regularly updates the market demand for mobile phone products in the future based on market trends. This forecast is not only for the final product, but also goes deep into the various levels of materials that make up the mobile phone.

[0180] Based on the forecast of mobile phone demand, material demand forecast (MRP calculation) is carried out to determine the specific material types and quantities required for the production of mobile phones, and to determine the secondary material forecast information. The secondary material forecast information is released in batches according to the length of the material acquisition cycle. The second demand information of the second-level materials with a longer acquisition cycle is released in advance, and the first demand information of the first-level materials with a shorter acquisition cycle is released later.

[0181] In order to obtain a more accurate total forecast for secondary materials, the secondary material forecast information is reduced by using a reduction mechanism according to the first demand information released later. Specifically, the second demand information in the secondary material forecast information is reduced to obtain the reduced second demand information. The first demand information released later and the reduced second demand information are combined to obtain the total forecast information for secondary materials.

[0182] In addition, the secondary material total forecast information also incorporates the feedback of actual order information, so it is closer to actual production needs. At the same time, the secondary material total forecast information is used as a special inventory to participate in the next MRP calculation, so as to avoid the deviation between the forecast release or the actual order and the set ratio affecting the actual material supply ratio.

[0183] The advantages of the above scheme over the existing scheme are as follows: First, compared with the traditional method that does not support multi-level material calculation or only supports one-layer material calculation, the present invention can not only control the supplier's material procurement situation, but also control its material production situation, with a wider level and depth of control. Secondly, the present invention controls the production rhythm of the first-layer materials (or manufactured parts) by releasing materials in batches, which can avoid material stagnation caused by forecast fluctuations and avoid stagnation compensation liability caused by excessive early generation by suppliers due to opaque generation progress. Finally, the material remaining forecast results are used as special inventory in the calculation to avoid deviations in the actual material supply ratio.

[0184] like Fig.12 As shown, an embodiment of the present invention provides an electronic device 200.

[0185] The electronic device 200 may specifically be a computer device, and the computer device may be a terminal device or a server.

[0186] The electronic device 200 includes at least one processor. The multi-level material surplus prediction method provided by the present invention can be applied to the processor or implemented by the processor. The processor can be a central processing unit (CPU) 21.

[0187] The electronic device 200 includes a memory. The memory is used to store various types of data to support the operation of the electronic device 200. Examples of such data include: any computer program for operating on a computer device. The memory may be a read-only memory (ROM) 22, a random access memory (RAM) 23, or other storage part 28. The storage part 28 may be located inside the electronic device 200 or outside the electronic device 200.

[0188] In one embodiment, when the processor executes the computer program stored in the memory, the steps of the multi-level material surplus prediction method in any technical solution of the present invention are executed.

[0189] In one embodiment, the electronic device 200 includes a central processor 21, which can perform various appropriate actions and processes according to the program stored in the read-only memory 22 or the program loaded from the storage part 28 to the random access memory 23. Various programs and data required for system operation are also stored in the random access memory 23. The central processor 21, the read-only memory 22 and the random access memory 23 are connected to each other through a bus 24. An input / output interface (Input / Output interface, i.e., I / O interface) 25 is also connected to the bus 24.

[0190] The following components are connected to the input / output interface 25: an input section 26 including a keyboard, a mouse, etc.; an output section 27 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 28 including a hard disk, etc.; and a communication section 29 including a network interface card such as a LAN card, a modem, etc. The communication section 29 performs communication processing via a network such as the Internet. A drive 210 is also connected to the input / output interface 25 as needed. A removable medium 211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 210 as needed, so that a computer program read therefrom is installed into the storage section 28 as needed.

[0191] One embodiment of the present invention provides a computer-readable storage medium.

[0192] In one embodiment, a computer readable storage medium stores a computer program executed by the processor mentioned above, or a multi-level material surplus prediction method in any of the technical solutions mentioned above.

[0193] When the processor executes the computer program, it can execute the description of the multi-level material surplus prediction method in any of the above technical solutions, so it will not be repeated here. In addition, the description of the beneficial effects of using the same method will not be repeated.

[0194] The computer-readable storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0195] In summary, the present invention provides a multi-level material surplus prediction method, system, electronic device and storage medium. The method can achieve phased and hierarchical prediction and material preparation by determining the second demand information corresponding to the second-layer material in the first stage, and the first demand information corresponding to the first-layer material in the second stage, and can more comprehensively reflect the material demand situation in the production process; first determine the second demand information of the second-layer material, allowing suppliers to have enough time to prepare the second-layer material, and when the first demand information of the first-layer material is determined, make necessary adjustments to the previously released second-layer material demand information, jointly realize the management of material procurement and production processes, ensure the dynamic balance of material demand, reduce material stagnation and resource waste caused by forecast fluctuations, and improve the flexibility and rapid response capability of the supply chain.

[0196] In addition, when the second-level material demand forecast results meet the first-level material production demand and there is still material left, the company only needs to bear the purchase cost of this part of the remaining material without paying additional production costs.

[0197] It should be understood that although this specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each implementation mode may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0198] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent implementation methods or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-level material surplus prediction method, characterized in that: include: Obtain the first forecast demand corresponding to the enterprise order in the first stage, and determine the second demand information of the second-level material corresponding to the target material; The second layer of material is used to prepare the first layer of material, and the first layer of material is used to prepare the target material; Obtaining a second-layer material corresponding to the second demand information; Obtain the second forecast demand corresponding to the enterprise order in the second stage, and determine the first demand information of the first-layer material; Based on the obtained second-layer materials, prepare the first-layer materials corresponding to the first demand information, and determine the material remaining prediction result; Among them, the acquisition cycle of the first-level materials is shorter than that of the second-level materials; the second demand information with a longer acquisition cycle is released first, and the first demand information with a shorter acquisition cycle is released later; the second demand information is adjusted based on the first demand information released later to obtain the adjusted second demand information.

2. The multi-level material surplus prediction method according to claim 1, characterized in that: The step of preparing the first-layer material corresponding to the first demand information based on the obtained second-layer material and determining the material remaining prediction result includes: According to the first prediction result of the first layer material in the first demand information, the second prediction result of the second layer material used for preparing the first layer material in the second demand information is updated to obtain the updated second demand information; The material remaining forecast result is determined according to the updated second demand information and the first demand information.

3. The multi-level material surplus prediction method according to claim 2, characterized in that: The updating of the second prediction result of the second layer material used for preparing the first layer material in the second demand information includes: Determining whether the first prediction result is greater than or equal to the second prediction result; If yes, update the second prediction result to 0; If not, the second prediction result is updated to the difference between the second prediction result and the first prediction result.

4. The multi-level material surplus prediction method according to claim 1, characterized in that: The determining the material remaining prediction result according to the updated second demand information and the first demand information includes: The first demand information and the updated second demand information are combined to obtain the material remaining prediction result.

5. The multi-level material surplus prediction method according to claim 1, characterized in that: After determining the material remaining prediction result, the following steps are included: Determine the remaining material net demand information based on the actual demand of the enterprise order and the remaining material forecast results; Based on the remaining material net demand information, the material remaining forecast result is updated and determined.

6. The multi-level material surplus prediction method according to claim 5, characterized in that: The updating and determining of the material remaining forecast result based on the remaining material net demand information includes: Based on the defined material supply ratio, the remaining material net demand information is split to determine a number of remaining material net demand information provided by a number of material suppliers; the material supply ratio includes at least one of a supplier ratio and an alternative material ratio; Based on the net demand information of each remaining material, determine and update the material remaining forecast results.

7. The multi-level material surplus prediction method according to claim 5, characterized in that: Determining the remaining material net demand information according to the actual demand of the enterprise order and the remaining material forecast result includes: Determine the actual demand information of the corresponding target materials according to the actual demand of the enterprise order; Based on the actual demand information of the target material, the material remaining forecast result is reduced to determine the remaining material net demand information.

8. The multi-level material surplus prediction method according to claim 7, characterized in that: The method of performing a reduction operation on the material remaining forecast result based on the actual demand information of the target material to determine the remaining material net demand information includes: Determine the actual demand quantity of the first-layer material corresponding to the target material according to the actual demand information of the target material; The net requirement of the remaining materials is determined according to the difference between the actual requirement and the predicted requirement of the second layer material for preparing the first layer material in the material remaining prediction result.

9. The multi-level material surplus prediction method according to claim 1, characterized in that: The cumulative release volume of the first predicted demand is less than or equal to the cumulative release volume of the second predicted demand.

10. The multi-level material surplus prediction method according to claim 1, characterized in that: The method further comprises: Determine the acquisition cycle of each material in the first layer, and publish the demand information of materials with long acquisition cycles until the first layer of materials are released; Determine the acquisition cycle of each material in the second-tier materials, and publish the demand information of materials with long acquisition cycles until the second-tier materials are released.

11. A multi-level material surplus prediction system, characterized in that: include: The first module is used to obtain the first forecast demand corresponding to the enterprise order in the first stage, and determine the second demand information of the second layer material corresponding to the target material, the second layer material is used to prepare the first layer material, and the first layer material is used to prepare the target material; Used to obtain a second layer of materials corresponding to the second demand information; The second module is used to obtain the second forecast demand corresponding to the enterprise order in the second stage and determine the first demand information of the first layer material; The third module is used to prepare the first-layer materials corresponding to the first demand information based on the obtained second-layer materials, and determine the material surplus prediction results.

12. An electronic device comprising: at least one processor; A memory storing a computer program executable on the processor, wherein the processor executes the steps of the multi-level material surplus prediction method as described in any one of claims 1 to 10 when executing the program.

13. A computer storage medium, wherein the computer readable storage medium stores a computer program, characterized in that: When the computer program is executed by a processor, the steps of the multi-level material surplus prediction method according to any one of claims 1 to 10 are performed.

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