Warehouse recommendation method and device for steel coil warehousing, electronic equipment and storage medium

Abstract

The invention relates to the technical field of logistics management, and discloses a warehouse recommendation method and device for steel coil warehousing, electronic equipment and a storage medium, and the method comprises the steps: obtaining the steel coil information of a target steel coil, carrying out the first matching of a technological parameter and a technological production condition of a production line, and if the first matching succeeds, carrying out the second matching; if the first matching is successful, determining a target cold rolling library of the target steel coil based on the cold rolling library corresponding to the successfully matched process production condition, if the first matching is failed, performing second matching with the historical order according to the order data, and if the second matching is successful, determining the target cold rolling library based on the cold rolling library corresponding to the successfully matched historical order, if the second matching fails, determining a target cold rolling warehouse according to the inventory of each cold rolling warehouse and the production line capacity of each production line; according to the method, the steel coils meeting the process production conditions are placed in the corresponding warehouses, the steel coil stack transferring workload is reduced, the proportion of the steel coils distributed in the same warehouse in the same order is increased, and the operation efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of logistics management, and in particular to a warehouse recommendation method, device, electronic equipment and storage medium for warehousing steel coils. Background Art

[0002] In steelmaking, the ESP (Endless Strip Production) process is an endless continuous casting and rolling process that uses thin slab casting and rolling equipment to produce thin and ultra-thin hot-rolled strip directly from molten steel. This process enables fully continuous production from molten steel to hot-rolled strip, eliminating the frequent coil changes required in traditional processes and significantly improving production efficiency and product quality.

[0003] ESP steel coils are transported from the hot-rolled finished product warehouse to the cold-rolled raw material warehouse according to the transport plan that specifies the specific flow direction of the steel coils. The current transport plan is prepared by the planner on a daily basis. First, the steel coils in the hot-rolled warehouse that meet the transport conditions are selected, and then the transport direction of each steel coil is given based on manual experience. The manual preparation of the transport plan is very time-consuming and labor-intensive, and the factors considered are not perfect. Since the transport plan is prepared only after the steel coils meet the transport conditions, there will inevitably be a large number of steel coil stacking operations when performing the transport loading task. The stacking of steel coils greatly reduces the transport efficiency, increases the risk of damage to the steel coils, and increases the energy consumption and life of the vehicle. Obviously, there is an urgent need for a new warehouse recommendation method for steel coil storage to solve at least one of the above problems.

[0004] It should be noted that the above content only provides background technical information related to this application and does not necessarily constitute prior art. Summary of the Invention

[0005] In view of the shortcomings of the existing technology mentioned above, the present application provides a warehouse recommendation method, device, electronic equipment and storage medium for the storage of steel coils, which places steel coils that meet the process production conditions in the corresponding warehouse, reduces the workload of steel coil stacking, and increases the proportion of steel coils of the same order distributed in the same warehouse, thereby improving operational efficiency.

[0006] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the present application.

[0007] According to one aspect of an embodiment of the present application, a warehouse recommendation method for warehousing steel coils is provided, comprising: obtaining steel coil information of a target steel coil, the steel coil information comprising process parameters and order data; performing a first matching between the process parameters and the process production conditions of the production line, and if the first matching is successful, determining a target cold rolling warehouse for the target steel coil based on the cold rolling warehouse corresponding to the successfully matched process production conditions; if the first matching fails, performing a second matching between the order data and historical orders, and if the second matching is successful, determining the target cold rolling warehouse based on the cold rolling warehouse corresponding to the successfully matched historical orders; if the second matching fails, determining the target cold rolling warehouse based on the inventory of each cold rolling warehouse and the production capacity of each production line, wherein there is a corresponding relationship between the cold rolling warehouse and the production line.

[0008] In one embodiment of the present application, based on the aforementioned scheme, the target cold rolling warehouse of the target steel coil is determined based on the cold rolling warehouse corresponding to the successfully matched process production conditions, including: determining the cold rolling warehouse to be selected based on the successfully matched process production conditions, and counting the number of optional cold rolling warehouses in the to-be-selected cold rolling warehouses, wherein the optional cold rolling warehouse represents a cold rolling warehouse whose inventory is less than a preset inventory threshold; if the number of cold rolling warehouses is greater than the preset quantity threshold, obtaining the condition priority corresponding to the successfully matched process production conditions and the flow priority corresponding to each of the optional cold rolling warehouses, and determining the target cold rolling warehouse based on the condition priority and the flow priority; if the number of cold rolling warehouses is less than or equal to the preset quantity threshold, determining the optional cold rolling warehouse as the target cold rolling warehouse.

[0009] In one embodiment of the present application, based on the aforementioned scheme, the target cold rolling warehouse is determined based on the condition priority and the flow priority, including at least one of the following: sorting the successfully matched process production conditions in descending order based on the condition priority, determining the process production condition ranked first as the target production condition, sorting the optional cold rolling warehouses in descending order according to the flow priority corresponding to the target production condition, and determining the optional cold rolling warehouse ranked first as the target cold rolling warehouse; calculating the overall priority score of each optional cold rolling warehouse based on the condition priority and the flow priority, sorting each optional cold rolling warehouse in descending order according to the overall priority score, and determining the optional cold rolling warehouse ranked first as the target cold rolling warehouse.

[0010] In one embodiment of the present application, based on the aforementioned scheme, a second match is performed based on the order data and the historical orders. If the second match is successful, the target cold rolling warehouse is determined based on the cold rolling warehouse corresponding to the successfully matched historical order, including: a second match is performed based on the order data and the historical orders. If the second match is successful, the successfully matched historical order is determined as the order to be selected; the predecessor order of the previous steel coil of the target steel coil is determined from the orders to be selected; the predecessor cold rolling warehouse corresponding to the predecessor order is obtained, and the predecessor cold rolling warehouse is determined as the target cold rolling warehouse.

[0011] In one embodiment of the present application, based on the aforementioned scheme, the target cold rolling warehouse is determined according to the inventory of each cold rolling warehouse and the production capacity of each production line, including: obtaining the inventory of each cold rolling warehouse and the production capacity of each production line, and calculating the demand of each production line based on the production line capacity; calculating the initial weight of each cold rolling warehouse based on the demand and the inventory, normalizing the initial weight to obtain the target weight of each cold rolling warehouse; calculating the cumulative probability distribution of each cold rolling warehouse based on the target weight, and obtaining the probability distribution interval corresponding to each cold rolling warehouse; randomly generating a random number within a preset range, determining the target distribution interval where the random number is located from the probability distribution interval, and determining the cold rolling warehouse corresponding to the target distribution interval as the target cold rolling warehouse.

[0012] In one embodiment of the present application, based on the aforementioned scheme, after determining the target cold rolling warehouse, the method further includes: obtaining the logistics distance between the optional storage area in the target cold rolling warehouse and the starting position of the production line, wherein the optional storage area is a storage area representing an area where the inventory is less than the preset inventory; sorting the optional storage areas in ascending order according to the logistics distance, and determining the first-ranked optional storage area as the target area; obtaining the storage position of the previous steel coil in the target area, and obtaining the storage status of the steel coils at the adjacent positions of the storage position; and determining the target storage position of the target steel coil based on the storage position and the storage status of the steel coils.

[0013] In one embodiment of the present application, based on the aforementioned scheme, after obtaining the steel coil information of the target steel coil, the method further includes: checking whether the process parameters are complete; if the process parameters are complete, performing a first matching of the process parameters and the process production conditions; if the process parameters are incomplete, re-acquiring the process parameters of the target steel coil.

[0014] According to one aspect of an embodiment of the present application, a warehouse recommendation device for warehousing steel coils is provided, comprising: a data acquisition module for acquiring steel coil information of a target steel coil, wherein the steel coil information comprises process parameters and order data; a first matching module for performing a first matching between the process parameters and the process production conditions of the production line, and if the first matching is successful, determining a target cold rolling warehouse for the target steel coil based on the cold rolling warehouse corresponding to the successfully matched process production conditions; a second matching module for performing a second matching between the order data and historical orders if the first matching fails, and if the second matching is successful, determining the target cold rolling warehouse based on the cold rolling warehouse corresponding to the successfully matched historical orders; a determination module for determining the target cold rolling warehouse based on the inventory of each cold rolling warehouse and the production capacity of each production line if the second matching fails, wherein there is a corresponding relationship between the cold rolling warehouse and the production line.

[0015] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the warehouse recommendation method for steel coil storage as described in any one of the above embodiments.

[0016] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer processor, the computer is caused to execute the warehouse recommendation method for steel coil storage as described in any one of the above embodiments.

[0017] The beneficial effects of the present application are as follows: the present application obtains the steel coil information of the target steel coil, the steel coil information includes process parameters and order data, and performs a first match between the process parameters and the process production conditions of the production line. If the first match is successful, the target cold rolling warehouse of the target steel coil is determined based on the cold rolling warehouse corresponding to the successfully matched process production conditions. If the first match fails, a second match is performed based on the order data and the historical orders. If the second match is successful, the target cold rolling warehouse is determined based on the cold rolling warehouse corresponding to the successfully matched historical orders. If the second match fails, the target cold rolling warehouse is determined based on the inventory of each cold rolling warehouse and the production capacity of each production line, wherein there is a corresponding relationship between the cold rolling warehouse and the production line. The above method is used to complete the warehouse recommendation for the target steel coil to be put into storage, and the steel coils that meet the process production conditions of the production line can be stored in the corresponding cold rolling warehouse, which can greatly reduce the workload of steel coil stacking and improve work efficiency.

[0018] In addition, the process production conditions can be flexibly configured to adapt to various changes in the production line, and the dual priority of the process production conditions can effectively avoid rule conflicts; this application also takes into account the constraints of order data, which can increase the proportion of steel coils with the same order distributed in the same finished product warehouse, which is beneficial to the later sales and shipment, and can greatly reduce the proportion of sales vehicles going to multiple finished product warehouses to select steel coils for loading; finally, determining the target cold rolling warehouse based on the inventory volume of the cold rolling warehouse and the production line capacity can effectively avoid the problem of overly concentrated distribution of steel coils into the warehouse.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, serving to explain the principles of the present application. It is obvious that the drawings described below are merely some embodiments of the present application, and a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0021] Figure 1 is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application;

[0022] Figure 2 1 is a flow chart of a warehouse recommendation method for storing steel coils according to an exemplary embodiment of the present application;

[0023] Figure 3 1 is a schematic diagram of a scenario of a warehouse recommendation method for storing steel coils, shown in an exemplary embodiment of the present application;

[0024] Figure 4 is a flow chart of a warehouse recommendation method for storing steel coils according to another exemplary embodiment of the present application;

[0025] Figure 5 This is a schematic diagram of a scenario in which steel coils in the same hot rolling warehouse are centrally stored according to the flow direction of each station, as shown in an exemplary embodiment of the present application;

[0026] Figure 6 is a block diagram of a warehouse recommendation device for steel coil storage shown in an exemplary embodiment of the present application;

[0027] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] The following will describe the embodiments of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand the other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for the purpose of illustrating the present application and are not intended to limit the scope of protection of the present application.

[0029] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. Therefore, the illustrations only show components related to the present application and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0030] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0031] First, it's important to note that in steelmaking, the ESP (Endless Strip Production) process is an endless continuous casting and rolling process that uses thin slab casting and rolling equipment to produce thin and ultra-thin hot-rolled strip directly from molten steel. This process enables fully continuous production from molten steel to hot-rolled strip, eliminating the frequent coil changes required in traditional processes and significantly improving production efficiency and product quality.

[0032] The production of ESP steel coils involves two stages: hot rolling and cold rolling. Due to differences in process conditions, the hot rolling and cold rolling lines are located in different factory areas. Therefore, semi-finished ESP steel coils must be transported from the hot rolling finished product warehouse to the cold rolling raw material warehouse. Typically, after ESP steel coils leave the hot rolling line, they undergo quality inspection and slow cooling in the hot rolling finished product warehouse. Once they meet the requirements for transfer, they are transported by train to the cold rolling raw material warehouse for further cooling. Once they meet the requirements for cold rolling process production, they are then transferred to the cold rolling line for processing.

[0033] The ESP process has the following advantages: 1. High efficiency and performance: The ESP process can complete the entire process from molten steel to the down-coiler in a short time, significantly reducing the time required by traditional processes. Its high rolling speed and high output ensure efficient production. 2. High-quality products: The strip produced by the ESP process has a uniform microstructure and excellent mechanical properties, allowing it to replace some cold-rolled products and proceed directly to pickling and galvanizing. 3. Low energy consumption and environmental friendliness: The ESP process rolls at high temperatures, reducing energy consumption and greenhouse gas emissions, saving approximately 40% compared to traditional hot strip mills. 4. Compact process flow: The entire production line is very compact, reducing equipment and plant investment and significantly improving yield. 5. High yield rate: The ESP process boasts a yield rate of up to 98.5%, exceeding that of traditional processes. Due to its high efficiency, high quality, and low energy consumption, the ESP process is primarily used to produce thin-gauge hot-rolled strip. The process has broad application prospects in the construction, automotive, home appliance, and electronics industries. With increasing global demand for efficient and environmentally friendly production technologies, the ESP process holds a promising market prospect.

[0034] ESP coils are transferred from the hot-rolled finished product warehouse to the cold-rolled raw material warehouse according to a transfer plan. When specifying the coil flow, multiple factors need to be considered. Some coils can only go to a specific flow due to their specific process conditions. For other coils that can go to multiple flows, more factors need to be considered, including the production capacity of the cold-rolled production line, the inventory level of the cold-rolled raw material warehouse, and the constraints of vehicle loading and shipping.

[0035] Figure 1 It is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application.

[0036] Reference Figure 1As shown, the system architecture may include a data acquisition device 101 and a computer device 102. Computer device 102 may be at least one of a desktop graphics processing unit (GPU) computer, a GPU computing cluster, a neural network computer, and the like. Data acquisition device 101 is used to collect coil information of target coils, inventory levels of each cold rolling depot, and production capacity of each production line. The coil information includes process parameters and order data. In this embodiment, data acquisition device 101 acquires this data and provides it to computer device 102 for processing. Relevant technical personnel can use the computer device 102 to perform a first match between the process parameters and the process production conditions of the production line. If the first match is successful, the target cold rolling warehouse of the target steel coil is determined based on the cold rolling warehouse corresponding to the successfully matched process production conditions. If the first match fails, a second match is performed based on the order data and historical orders. If the second match is successful, the target cold rolling warehouse is determined based on the cold rolling warehouse corresponding to the successfully matched historical orders. If the second match fails, the target cold rolling warehouse is determined based on the inventory of each cold rolling warehouse and the production capacity of each production line to complete the warehouse recommendation for the steel coil to be put into storage, wherein there is a corresponding relationship between the cold rolling warehouse and the production line. It should be noted that the data acquisition device 101 and computer device 102 provided in this embodiment are only an example and should not bring any limitations to the functions and scope of use of the embodiments of this application.

[0037] It should be noted that the warehouse recommendation method for steel coil storage provided in the embodiment of the present application is generally executed by the computer device 102 , and accordingly, the warehouse recommendation device for steel coil storage is generally set in the computer device 102 .

[0038] Figure 2 The flowchart of the warehouse recommendation method for steel coil storage shown in an exemplary embodiment of the present application can be executed by a computing and processing device. The computing and processing device can be Figure 1 The computer device 102 shown in FIG. Figure 2 As shown, the warehouse recommendation method for steel coil storage includes at least steps S210 to S240, which are described in detail as follows:

[0039] In step S210, the steel coil information of the target steel coil is acquired.

[0040] In one embodiment of the present application, steel coil information includes process parameters and order data. Process parameters include, but are not limited to, chemical composition such as carbon content, alloying elements, and impurity elements; physical properties such as thickness, width, and coil weight; rolling parameters such as rolling temperature and rolling force; and production control parameters such as product specifications and usage classification. Order data includes, but is not limited to, order number, customer name, basic specifications such as material, thickness, and inner diameter; and delivery requirements such as delivery date, delivery status (e.g., hot-rolled, cold-rolled, annealed, or tempered), and transportation method.

[0041] In this embodiment, the target steel coil is an ESP steel coil obtained through the ESP process. Each ESP steel coil has corresponding process parameters, such as process type, brand, product name, thickness, width, steel grade, rolling force, etc. The process production conditions can be composed of a single or multiple process parameters as required. In other words, the correspondence between process production conditions and process parameters can be one-to-one or one-to-many.

[0042] In step S220, a first matching is performed between the process parameters and the process production conditions of the production line. If the first matching is successful, a target cold rolling warehouse for the target steel coil is determined based on the cold rolling warehouse corresponding to the successfully matched process production conditions.

[0043] In one embodiment of the present application, a cold rolling warehouse to be selected is determined based on the successfully matched process production conditions, and the number of optional cold rolling warehouses in the selected cold rolling warehouses is counted, wherein the optional cold rolling warehouse represents a cold rolling warehouse whose inventory is less than a preset inventory threshold; if the number of cold rolling warehouses is greater than the preset quantity threshold, the condition priority corresponding to the successfully matched process production conditions and the flow priority corresponding to each optional cold rolling warehouse are obtained, and the target cold rolling warehouse is determined based on the condition priority and the flow priority; if the number of cold rolling warehouses is less than or equal to the preset quantity threshold, the optional cold rolling warehouse is determined as the target cold rolling warehouse.

[0044] In this embodiment, the preset inventory threshold can be the maximum inventory of the cold rolling warehouse. The preset inventory threshold can also be determined based on the inventory of the cold rolling warehouse and the production capacity of the production line corresponding to the cold rolling warehouse, or can be determined based on demand. This application does not impose any restrictions on this. Taking the preset quantity threshold as 1 as an example, if the number of cold rolling warehouses is greater than 1, the condition priority corresponding to the successfully matched process production conditions and the flow priority corresponding to each optional cold rolling warehouse are obtained, and the target cold rolling warehouse is determined based on the condition priority and the flow priority; if the number of cold rolling warehouses is less than or equal to 1, the optional cold rolling warehouse is determined as the target cold rolling warehouse.

[0045] In one embodiment of the present application, the method of determining the target cold rolling warehouse based on the condition priority and the flow priority includes at least one of the following: sorting the successfully matched process production conditions in descending order based on the condition priority, determining the process production condition ranked first as the target production condition, sorting the optional cold rolling warehouses in descending order according to the flow priority corresponding to the target production condition, and determining the optional cold rolling warehouse ranked first as the target cold rolling warehouse; calculating the overall priority score of each optional cold rolling warehouse based on the condition priority and the flow priority, sorting each optional cold rolling warehouse in descending order according to the overall priority score, and determining the optional cold rolling warehouse ranked first as the target cold rolling warehouse.

[0046] In this embodiment, the condition priority is the priority of each process production condition. The same process production condition can have multiple flow directions corresponding to multiple cold rolling warehouses, where the flow direction refers to the flow to a certain cold rolling warehouse. Each flow direction corresponds to a flow direction priority, that is, one cold rolling warehouse corresponds to one flow direction priority.

[0047] In some embodiments, the downstream cold rolling production line can only receive steel coils within the corresponding specific process parameter range for cold rolling production. For example, the No. 1 cold rolling production line can only produce thin-gauge steel coils, the No. 3 cold rolling production line can only produce galvanized process steel coils, and 1260 cross-section steel coils cannot enter the No. 6 and No. 7 cold rolling production lines, etc. By sorting out the process production conditions of the cold rolling production line and the mapping relationship between the production line and the cold rolling warehouse, a series of warehousing rules can be sorted out. Referring to Table 1, Table 1 is a schematic table of warehousing rules. Table 1 illustrates some rules. It can be understood that the content in Table 1 is only for illustration. The warehousing rules and the specific content of the rules can be increased, reduced or changed according to actual needs, and this application does not limit this. Preferably, a complete warehousing rule includes a rule name, a rule priority (also called a condition priority), a process type, a rule condition, a rule flow direction, and a flow priority.

[0048] Table 1

[0049]

[0050] The rule name identifies a group of rules that share the same rule conditions, but may have multiple rule flows. Different flow directions have corresponding priorities, identified by numbers 1-3, with 1 being the default priority. A higher priority indicates a higher probability of reaching the corresponding flow direction. For example, in Table 1, rules 10, 11, and 12 share the same rule name and form a group of rules. When a hot-rolled steel coil (i.e., the target coil) meets the corresponding rule conditions, its downstream flow direction can be assigned to one of P1, P9, or P10, with the probability of assignment decreasing in descending order. The rule priority, used to indicate the priority of a group of rules with the same rule name, is identified by the letters A to Z, with A being the default priority. In particular, rule groups with priorities Y and Z represent negative rules, meaning that coils that meet the corresponding rule conditions cannot flow to the corresponding rule direction. The process type and rule conditions together constitute the conditional portion of the rule, which defines the process parameter conditions that must be met for the hot-rolled steel coil to flow to the corresponding direction. The rule flow is the result part of this rule, that is, if the hot-rolled steel coil meets the corresponding process parameter conditions, it can be allocated to the corresponding flow direction, that is, the corresponding cold rolling warehouse.

[0051] The above details the detailed structure of production line entry rules. When switching production line processes or adding new production lines, simply modify and edit the corresponding rule conditions on the system front-end, allowing for flexible configuration of production line entry rules. At the system implementation level, a rule engine has been built to decouple business rules from applications. This eliminates the need to rebuild system code when rules are changed. Furthermore, rule conflicts often arise within the rule engine. Specifically, this involves assigning flow directions when a single steel coil meets the requirements of multiple rules. This issue is mitigated by setting dual priorities: rule priority and flow priority. As shown in Table 1, a rule's priority is composed of two components: the rule priority (primary) and the flow priority (secondary). Table 2 provides a reference table for setting production line entry rule priorities and calculating the overall priority score. Refer to Table 2 to calculate a rule's overall priority score. Table 2 shows that the overall priority score = rule priority score + 3 * (5 - flow priority) + a random integer, where the random integer is an integer between 0 and 10. Preferably, the rule priority score is set with a gradient of 20, which can ensure that the calculated overall priority score of the lower priority is lower than the overall priority score of the higher priority rule; the flow priority is set with a gradient of 3, plus a random number between 0-10, to ensure that the lower priority flow in a set of rules will not overtake the higher priority flow.

[0052] Table 2

[0053] Rule priority Rule priority score Flow priority Overall priority score A 100 X(1、2、3) 100+3*(5-x)+rand(10) B 80 X(1、2、3) 80+3*(5-x)+rand(10) C 60 X(1、2、3) 60+3*(5-x)+rand(10) D, E, F… 40 X(1、2、3) 40+3*(5-x)+rand(10) ... ... ... ... Z 0 X(1、2、3) 3*(5-x)+rand(10)

[0054] As can be seen from Table 2, the overall priority score is determined based on the rule priority and the flow priority. It should be noted that this embodiment is only for illustration, and the rule priority, rule priority score and flow priority can be increased, decreased or changed according to actual needs, and their corresponding content including the numerical value can also be modified according to actual needs, and this application does not limit this.

[0055] In step S230, if the first matching fails, a second matching is performed based on the order data and the historical orders. If the second matching is successful, the target cold rolling warehouse is determined based on the cold rolling warehouse corresponding to the successfully matched historical orders.

[0056] In one embodiment of the present application, a second match is performed based on the order data and the historical orders. If the second match is successful, the successfully matched historical order is determined as the order to be selected; the predecessor order of the previous steel coil of the target steel coil is determined from the orders to be selected; the predecessor cold rolling warehouse corresponding to the predecessor order is obtained, and the predecessor cold rolling warehouse is determined as the target cold rolling warehouse.

[0057] In this embodiment, if the target steel coil does not match the flow direction in step S220, it is expected that the steel coils of the same order will be assigned to the same downstream flow direction. In this way, the cold-rolled finished products of the same order will be distributed in the same finished product warehouse, which will greatly facilitate the subsequent sales and shipment organization and effectively improve the shipping efficiency. The specific steps are as follows: query whether the order number of the hot-rolled steel coil off the line, that is, the target steel coil, appears in the inventory of the cold-rolled raw material warehouse, that is, the cold-rolling warehouse. If so, directly mark the corresponding flow direction, that is, determine the cold-rolling warehouse as the target cold-rolling warehouse; if not, query whether the order number of the hot-rolled steel coil off the line appears in the inventory of the cold-rolled finished product warehouse. If so, mark the corresponding flow direction according to the mapping relationship between the finished product warehouse and the raw material warehouse; if not, query whether the order number of the hot-rolled steel coil off the line appears in the inventory of the hot-rolled finished product warehouse. If so, according to the order sequence of the steel coils off the line, the previous steel coil must have been assigned a flow direction, thereby matching the downstream flow direction of the previous steel coil as the flow direction of this coil. It should be noted that the above steps only consider the previous steel coil with the same order number as this coil to reduce unnecessary steps.

[0058] In step S240 , if the second matching fails, the target cold rolling warehouse is determined based on the inventory of each cold rolling warehouse and the production capacity of each production line.

[0059] Among them, there is a corresponding relationship between the cold rolling warehouse and the production line.

[0060] In one embodiment of the present application, the inventory of each cold rolling warehouse and the production capacity of each production line are obtained, and the demand of each production line is calculated based on the production line capacity; the initial weight of each cold rolling warehouse is calculated based on the demand and inventory, and the initial weight is normalized to obtain the target weight of each cold rolling warehouse; the cumulative probability distribution of each cold rolling warehouse is calculated based on the target weight, and the probability distribution interval corresponding to each cold rolling warehouse is obtained; a random number within a preset range is randomly generated, and the target distribution interval where the random number is located is determined from the probability distribution interval, and the cold rolling warehouse corresponding to the target distribution interval is determined as the target cold rolling warehouse.

[0061] In this embodiment, for coils that do not match a flow direction in both steps S220 and S230, that is, if the target coil fails to match in both steps S220 and S230, it indicates that the coil can be assigned to any production line in terms of process production and is not constrained to have the same flow direction for the same order. For such coils, the flow direction can be randomly assigned using the inventory level and production line capacity constraints as weights to balance the inventory level of cold-rolled raw materials. The specific steps are as follows:

[0062] First, calculate the initial flow weights. The current inventory levels of each cold-rolled raw material warehouse are tallied, aggregated to the warehouse based on the estimated production capacity of each cold-rolled production line, and demand is calculated. The initial weights assigned to each warehouse are calculated based on the difference between demand and inventory. For example, if the inventory levels of cold-rolled raw material warehouses P1, P2, P3, P9, and P10 are 8,000, 3,000, 3,500, 6,000, and 4,000, respectively, and the demand levels are 6,000, 6,000, 6,000, 6,000, and 6,000, respectively, the initial weights for each cold-rolled raw material warehouse are -2,000, 3,000, 2,500, 0, and 2,000, respectively.

[0063] Secondly, weight adjustment. For the initial weight of the cold-rolled raw material warehouse, normalization processing is performed to normalize the initial weight to between 0 and 1. The calculation formula is as follows (1):

[0064] weight_new = (weight_old - min + L_index) / (max - min + L_index) Formula (1)

[0065] Where weight_new is the normalized weight of each cold-rolled raw material warehouse, weight_old is the initial weight of each cold-rolled raw material warehouse, min is the minimum weight among the initial weights of each cold-rolled raw material warehouse, max is the maximum weight among the initial weights of each cold-rolled raw material warehouse, and L_index is the Laplace smoothing factor. For example, if the Laplace smoothing factor is 20 tons, the normalized weights of each cold-rolled raw material warehouse are 0.004, 1.0, 0.9, 0.402, and 0.801, respectively.

[0066] Then, the cumulative probability distribution is calculated. Based on the adjusted weights, the cumulative probability distribution of each cold-rolled raw material warehouse is calculated. The calculation formula is as follows (2):

[0067]

[0068] Among them, P i Refers to the cumulative probability distribution of the i-th cold-rolled raw material warehouse, weight j The weight of the jth cold-rolled raw material warehouse is N, and the total number of cold-rolled raw material warehouses is N. The cumulative probability distributions for each cold-rolled raw material warehouse are 0.001, 0.323, 0.613, 0.741, and 1.0, respectively. Correspondingly, the probability distribution intervals for cold-rolled raw material warehouses P1, P2, P3, P9, and P10 are [0, 0.001], [0.001, 0.323], [0.323, 0.613], [0.613, 0.741], and [0.741, 1.0], respectively. It can be understood that the numerical value distribution at the edge of the probability distribution interval can be set according to needs. For example, 0.001 can be set to belong to the interval [0, 0.001] or 0.001 can be set to belong to the interval [0.001, 0.323]. That is, the interval can be set as an open interval, a closed interval or a half-open and half-closed interval according to needs. That is, [0.001, 0.323] can be understood as (0.001, 0.323], it can be understood as [0.001, 0.323), it can also be understood as (0.001, 0.323), it can also be understood as [0.001, 0.323]. This application does not limit this.

[0069] Finally, the flow direction is randomly assigned. A random decimal r between 0 and 1 is generated. Based on the probability distribution interval of r, the corresponding flow direction is assigned to the steel coil. For example, if the random decimal r generated is 0.666, which falls in the interval [0.613, 0.741], the flow direction P9 is assigned.

[0070] Through the above steps, the random flow distribution of the target steel coil can be completed.

[0071] In one embodiment of the present application, the process after determining the target cold rolling warehouse also includes the following steps: obtaining the logistics distance between the optional storage area in the target cold rolling warehouse and the starting position of the production line, wherein the optional storage area is a storage area representing an area where the inventory is less than the preset inventory; sorting the optional storage areas in ascending order according to the logistics distance, and determining the first-ranked optional storage area as the target area; obtaining the storage position of the previous steel coil in the target area, and obtaining the storage status of the steel coils at the adjacent positions of the storage position; determining the target storage position of the target steel coil based on the storage position and the storage status of the steel coil.

[0072] In this embodiment, the target storage location for the target coil is determined based on the storage location, the coil storage status, and a preset recommendation rule. The first recommendation rule consists of two storage locations in a first-tier structure. If the preset recommendation rule is the first recommendation rule and the coil storage status of the second storage location in the first-tier structure is no coils stored, the target storage location is determined to be the second storage location in the first-tier structure. The second recommendation rule consists of three consecutive storage locations in a first-tier structure and a second-tier structure, with the first-tier structure placed on the second-tier structure, the first-tier structure including one storage location, and the second-tier structure including two storage locations. If the preset recommendation rule is the second recommendation rule and the coil storage status of the second storage location in the second-tier structure is no coils stored, the target storage location is determined to be the second storage location in the second-tier structure. If the preset recommendation rule is the second recommendation rule and the coil storage status of the first storage location in the first-tier structure is no coils stored, the target storage location is determined to be the first storage location in the first-tier structure. Alternatively, if the preset recommendation rule is the second recommendation rule, the second-tier structure of the three storage locations is prioritized to be filled before the first-tier structure. It can be understood that the preset recommendation rules can be set according to needs, and can be at least one of the first recommendation rules and the second recommendation rules listed above, or other set recommendation rules. This application does not limit this, nor should it bring any limitations to the functions and scope of use of the embodiments of this application.

[0073] In one embodiment of the present application, the process after obtaining the steel coil information of the target steel coil also includes the following steps: checking whether the process parameters are complete; if the process parameters are complete, first matching the process parameters and process production conditions; if the process parameters are incomplete, re-obtaining the process parameters of the target steel coil.

[0074] In this embodiment, the order data can also be checked for completeness. If the order data is complete, a second match is performed between the order data and historical orders. If the order data is incomplete, the order data of the target steel coil is reacquired. The target steel coil's process parameters and order data can be reacquired by manually supplementing the missing process parameters and order data, or by using an image acquisition device to acquire images and then performing image recognition on the acquired images.

[0075] refer to Figure 3 , Figure 3 : is a schematic diagram of a scenario of a warehouse recommendation method for storing steel coils, shown in an exemplary embodiment of the present application. Figure 3 An example of a transfer scenario of steel coils between a hot-rolled finished product warehouse and a cold-rolled raw material warehouse is shown. This application mainly transfers the target steel coils in the hot-rolled finished product warehouse to the cold-rolled raw material warehouse.

[0076] Figure 4This is a flow chart illustrating a warehouse recommendation method for steel coil storage, according to another exemplary embodiment of the present application. In this exemplary embodiment, a rule engine is constructed based on a rule model to pre-schedule and recommend the flow direction of hot-rolled steel coils, i.e., to recommend a target cold-rolled warehouse for the target steel coil. Specifically, when the steel coil is rolled off the hot-rolled line, the system synchronously obtains the process parameter information of the target steel coil itself, and then inputs it into the rule engine to mark the steel coil flow direction. See the description of steps S1-S3 below:

[0077] In step S1, the process parameters of the target steel coil are matched with the process production conditions of the cold rolling production line, that is, the warehousing rules of the cold rolling warehouse. If they match, the flow direction is directly marked;

[0078] In step S2, if S1 fails to match the flow direction, in order to facilitate the subsequent shipment of finished steel coils, the flow direction of the steel coil with the same order is matched. If a match is found, the flow direction is directly marked.

[0079] In step S3, if both step S1 and step S2 fail to calibrate the flow direction of the steel coils, the flow direction of the steel coils can be randomly assigned according to the weights set according to the cold-rolled inventory and the production line capacity.

[0080] The above describes the ESP coil flow pre-arrangement recommendation process based on the rule engine, wherein the specific operation of each step has been described in detail in the above embodiments and will not be repeated here.

[0081] In this embodiment, the flow direction of the target steel coil is given when it comes out of the hot rolling line, so that the hot rolling warehouse can plan the storage area in advance. For example, area A stores the steel coils that will flow to the cold rolling warehouse P1, and the steel coils with the same flow direction are sorted according to the production time and stored and cooled in a centralized manner. Figure 5 , Figure 5 This is a schematic diagram of an exemplary embodiment of the present application showing how steel coils in a hot rolling mill are centrally stored according to their station flow. This method of storing steel coils and then loading them by crane can greatly improve efficiency.

[0082] This application builds a large-scale rule-based model engine that includes production line entry rules, same-order same-flow rules, and random allocation flow rules. It recommends flow pre-routing for steel coils as they come off the hot rolling line. This guides warehouse management personnel to assign storage saddles to steel coils based on the recommended pre-routing flow, thereby reducing the amount of stacking work required for subsequent loading and unloading, lowering the risk of coil damage and improving transfer efficiency.

[0083] This application uses a rule model to pre-schedule and recommend the flow direction of ESP steel coils off the hot rolling line to the next station, which can guide warehouse management personnel to uniformly arrange the storage of steel coils with the same flow direction in the saddle area according to the flow direction of the next station, which brings great convenience to subsequent loading and unloading, can greatly reduce the workload of steel coil unloading, improve train loading efficiency, and improve driving operation efficiency; in addition, the flexible configuration of production line warehousing rules can adapt to various changes in the production line; the dual priority design of the rules can effectively avoid rule conflicts; the rule engine also considers the constraints of the same order and the same flow direction, which can increase the proportion of steel coils of the same order distributed in the same finished product warehouse, which brings obvious advantages to the subsequent sales and shipment, and can greatly reduce the proportion of sales vehicles going to multiple finished product warehouses to select coils for loading; finally, the allocation of random flow directions fully considers inventory and production capacity as allocation weights, and the adjustment of weight normalization can effectively avoid over-concentrated distribution of flow directions.

[0084] Figure 6 This is a block diagram of a warehouse recommendation device for steel coil storage shown in an exemplary embodiment of the present application. The device can be applied to Figure 1 The implementation environment shown is specifically configured in the computer device 102. The apparatus may also be applicable to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the apparatus is applicable.

[0085] like Figure 6 As shown, the exemplary warehouse recommendation device for steel coil storage includes: a data acquisition module 610 , a first matching module 620 , a second matching module 630 and a determination module 640 .

[0086] Among them, the data acquisition module 610 is used to obtain the steel coil information of the target steel coil, and the steel coil information includes process parameters and order data; the first matching module 620 is used to perform a first matching of the process parameters and the process production conditions of the production line. If the first matching is successful, the target cold rolling warehouse of the target steel coil is determined based on the cold rolling warehouse corresponding to the successfully matched process production conditions; the second matching module 630 is used to perform a second matching based on the order data and the historical orders if the first matching fails. If the second matching is successful, the target cold rolling warehouse is determined based on the cold rolling warehouse corresponding to the successfully matched historical orders; the determination module 640 is used to determine the target cold rolling warehouse based on the inventory of each cold rolling warehouse and the production capacity of each production line if the second matching fails, wherein there is a corresponding relationship between the cold rolling warehouse and the production line.

[0087] It should be noted that the warehouse recommendation device for steel coil storage provided in the above embodiment and the warehouse recommendation method for steel coil storage provided in the above embodiment are based on the same concept. The specific manner in which each module and unit performs operations has been described in detail in the method embodiment and will not be repeated here. In actual applications, the warehouse recommendation device for steel coil storage provided in the above embodiment can, as needed, allocate the above functions to different functional modules, i.e., divide the internal structure of the device into different functional modules to perform all or part of the functions described above, and this is not limited here.

[0088] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, which, when executed by one or more processors, enables the electronic device to implement the warehouse recommendation method for steel coil storage provided in the above-mentioned embodiments.

[0089] Figure 7 The following is a schematic diagram showing the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application. Figure 7 The computer system 700 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0090] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 702 or the program loaded from the storage part 708 into the random access memory (RAM) 703, such as executing the methods provided in the above-mentioned various embodiments. Various programs and data required for system operation are also stored in the RAM 703. The CPU 701, ROM 702 and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0091] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, and the like; an output section 707 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. Removable media 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like, is installed in the drive 710 as needed, so that computer programs read therefrom can be installed into the storage section 708 as needed.

[0092] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from a removable medium 711. When the computer program is executed by the central processing unit (CPU) 701, the various functions defined in the system of the present application are executed.

[0093] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0095] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0096] Another aspect of the present application provides a computer-readable storage medium storing a computer program. When executed by a computer processor, the computer program causes the computer to perform the warehouse recommendation method for steel coil storage provided in the aforementioned embodiments. The computer-readable storage medium may be included in the electronic device described in the aforementioned embodiments, or may exist independently and not be incorporated into the electronic device.

[0097] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0098] Another aspect of the present application provides a computer program product or computer program, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the warehouse recommendation method for steel coil storage provided in each of the above-described embodiments.

[0099] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0100] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of this application and include common knowledge or customary techniques in the art that are not disclosed herein.

[0101] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, any equivalent modifications or alterations accomplished by a person of ordinary skill in the art without departing from the spirit and technical concepts disclosed in this application shall be covered by the claims of this application.

Claims

1. A warehouse recommendation method for steel coil storage, characterized in that: include: Acquire steel coil information of a target steel coil, wherein the steel coil information includes process parameters and order data; Performing a first match between the process parameters and the process production conditions of the production line, and if the first match is successful, determining a target cold rolling warehouse for the target steel coil based on the cold rolling warehouse corresponding to the successfully matched process production conditions; If the first matching fails, a second matching is performed based on the order data and historical orders; if the second matching is successful, the target cold rolling warehouse is determined based on the cold rolling warehouse corresponding to the successfully matched historical orders; If the second matching fails, the target cold rolling warehouse is determined according to the inventory of each cold rolling warehouse and the production capacity of each production line, wherein there is a corresponding relationship between the cold rolling warehouse and the production line.

2. The warehouse recommendation method for steel coil storage according to claim 1, characterized in that: Determining a target cold rolling warehouse for the target steel coil based on the cold rolling warehouse corresponding to the successfully matched process production conditions includes: Determine the cold rolling warehouse to be selected based on the successfully matched process production conditions, and count the number of cold rolling warehouses that are optional among the cold rolling warehouses to be selected, wherein the optional cold rolling warehouse represents a cold rolling warehouse whose inventory is less than a preset inventory threshold; If the number of cold rolling warehouses is greater than a preset number threshold, the condition priority corresponding to the successfully matched process production condition and the flow priority corresponding to each optional cold rolling warehouse are obtained, and the target cold rolling warehouse is determined based on the condition priority and the flow priority; If the number of cold rolling warehouses is less than or equal to the preset number threshold, the optional cold rolling warehouse is determined as the target cold rolling warehouse.

3. The warehouse recommendation method for steel coil storage according to claim 2, characterized in that: Determining the target cold rolling warehouse based on the condition priority and the flow direction priority includes at least one of the following: Sorting the successfully matched process production conditions in descending order based on the condition priorities, determining the process production condition ranked first as the target production condition, and sorting the optional cold rolling warehouses in descending order according to the flow direction priorities corresponding to the target production conditions, and determining the optional cold rolling warehouse ranked first as the target cold rolling warehouse; The overall priority score of each optional cold rolling warehouse is calculated based on the condition priority and the flow priority, and the optional cold rolling warehouse is sorted in descending order according to the overall priority score, and the optional cold rolling warehouse ranked first is determined as the target cold rolling warehouse.

4. The warehouse recommendation method for steel coil storage according to any one of claims 1 to 3, characterized in that: Performing a second match between the order data and the historical orders, and if the second match is successful, determining the target cold rolling warehouse based on the cold rolling warehouse corresponding to the successfully matched historical orders, including: Performing a second match between the order data and historical orders, and if the second match succeeds, determining the successfully matched historical order as the order to be selected; Determining a preceding order for a steel coil preceding the target steel coil from the orders to be selected; Obtain the preceding cold rolling warehouse corresponding to the preceding order, and determine the preceding cold rolling warehouse as the target cold rolling warehouse.

5. The warehouse recommendation method for steel coil storage according to any one of claims 1 to 3, characterized in that: The target cold rolling warehouse is determined according to the inventory of each cold rolling warehouse and the production capacity of each production line, including: Obtaining the inventory of each cold rolling warehouse and the production capacity of each production line, and calculating the demand of each production line based on the production line capacity; Calculating an initial weight of each cold rolling warehouse based on the demand and the inventory, and normalizing the initial weight to obtain a target weight of each cold rolling warehouse; Based on the target weight, the cumulative probability distribution of each cold rolling warehouse is calculated and the probability distribution interval corresponding to each cold rolling warehouse is obtained; A random number within a preset range is randomly generated, a target distribution interval in which the random number is located is determined from the probability distribution interval, and a cold rolling warehouse corresponding to the target distribution interval is determined as the target cold rolling warehouse.

6. The warehouse recommendation method for steel coil storage according to any one of claims 1 to 3, characterized in that: After determining the target cold rolling warehouse, the method further includes: Obtaining a logistics distance between an optional storage area in the target cold rolling warehouse and a starting position of the production line, wherein the optional storage area is a storage area where the inventory in the area is less than the preset inventory; sorting the optional storage areas in ascending order according to the logistics distance, and determining the optional storage area ranked first as the target area; Obtaining the storage location of the previous steel coil in the target area, and obtaining the storage status of the steel coils at locations adjacent to the storage location; A target storage location of the target steel coil is determined based on the storage position and the storage status of the steel coil.

7. The warehouse recommendation method for steel coil storage according to any one of claims 1 to 3, characterized in that: After obtaining the steel coil information of the target steel coil, the method further includes: Check whether the process parameters are complete; If the process parameters are complete, first matching the process parameters with the process production conditions; If the process parameters are incomplete, the process parameters of the target steel coil are re-acquired.

8. A warehouse recommendation device for steel coil storage, characterized in that: include: A data acquisition module, configured to obtain steel coil information of a target steel coil, wherein the steel coil information includes process parameters and order data; a first matching module, configured to perform a first matching between the process parameters and the process production conditions of the production line; and if the first matching is successful, determining a target cold rolling warehouse for the target steel coil based on a cold rolling warehouse corresponding to the successfully matched process production conditions; A second matching module is configured to perform a second matching between the order data and historical orders if the first matching fails, and to determine the target cold rolling warehouse based on the cold rolling warehouse corresponding to the successfully matched historical orders if the second matching succeeds; A determination module is used to determine the target cold rolling warehouse according to the inventory of each cold rolling warehouse and the production capacity of each production line if the second matching fails, wherein there is a corresponding relationship between the cold rolling warehouse and the production line.

9. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the warehouse recommendation method for steel coil storage as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor of a computer, the computer is caused to execute the warehouse recommendation method for steel coil storage according to any one of claims 1 to 7.

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