Warehouse credit line rating method, device and system
By building a warehouse basic situation database and combining deep learning and ARIMA model to predict goods prices, the objectivity problem of chemical companies in rating hazardous chemical warehouses is solved, and the accurate credit line assessment of chemical companies' warehouses is achieved, reducing the risk of product loss.
Patent Information
- Application Number
- CN202510326955.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-19
- Publication Date
- 2025-07-25
AI Technical Summary
The existing technology cannot meet the storage management requirements of chemical companies for hazardous chemical warehouses. The traditional warehouse rating method lacks objectivity and changes in goods prices lead to inaccurate credit limits, which poses economic risks.
Build a database of basic warehouse situations, calculate the total warehouse score based on business ratings and financial ratings, use deep learning and ARIMA models to predict the price of goods, determine early warning prompts based on the actual value of goods and credit limit, use automatic detection devices to obtain the quantity of goods, and establish an objective warehouse rating system.
It improves the accuracy of chemical companies' evaluation of hazardous chemical warehouses, reduces the risk of product loss, and provides a more objective credit line evaluation.
Smart Images
Figure CN120373928A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of warehouse management methods and systems, and particularly relates to a method, device and system for rating the credit limit of a warehouse. Background Art
[0002] The raw materials and products of chemical enterprises generally belong to bulk commodities and require a large amount of storage space. Therefore, chemical enterprises need to build, manage and rent a large number of warehouses. Especially when renting third-party warehouses, due to different enterprise mechanisms, management levels and hardware facilities, the storage conditions of warehouses vary greatly. Moreover, since some chemical products are of high value, once the goods are not properly stored, chemical enterprises will suffer great economic losses. Therefore, chemical enterprises need to carry out rating work on warehouses and set credit limits. However, the current warehouse rating work generally has the following disadvantages:
[0003] First, the warehouse rating is set only based on the enterprise mechanism, management level, hardware facilities, historical credit level and guarantee situation of the warehouse. However, in the chemical industry, many of the goods in the warehouse are hazardous chemicals, which have special requirements for the incoming, storage, outgoing and handling capabilities. Therefore, the traditional warehouse rating method cannot reflect the storage and management requirements of the chemical industry for hazardous chemicals.
[0004] Second, after setting the warehouse credit limit, the warehouse administrator needs to manually set the types and prices of the actual goods in the warehouse. However, the prices of goods in the market change in real time, and the value of the current goods may decline in the future, resulting in the warehouse value being less than the credit limit. The traditional time series ARIMA model is good at capturing the linear trend and periodicity of time series, but has limited modeling ability for non-linear relationships (such as price mutations and multi-variable coupling effects).
[0005] Third, the traditional warehouse rating mainly relies on the work experience of managers to set the warehouse level and credit limit, with many subjective factors and a lack of objectivity, resulting in the credit limit not conforming to the actual situation of the warehouse. Therefore, it is easy to bring economic risks and losses to chemical enterprises. Summary of the Invention
[0006] The technical problem to be solved by the present invention is to provide a method for rating the credit limit of a warehouse, which solves the problem that the traditional warehouse rating method in the prior art cannot meet the storage and management requirements of hazardous chemicals.
[0007] The present invention adopts the following technical solutions to solve the above technical problems:
[0008] Warehouse credit limit rating method. First, construct a database of the basic situation of the warehouse, calculate the business score and financial score of different warehouses according to the pre-set business rating reference list and financial rating reference list, and calculate the total score of the warehouse; and refer to the pre-set credit rating table to determine the credit rating of the warehouse. Second, calculate the warehouse credit limit according to the credit rating of the warehouse, the basic situation of the warehouse management unit and the pre-set credit limit table. Then, obtain the actual situation of the goods and calculate the actual value of the goods. Finally, determine whether to issue a warning prompt according to the actual value of the goods and the warehouse credit limit.
[0009] The content of the business rating reference list includes rating categories, rating items within the rating categories, the scoring reference values corresponding to each item, and the weights of the rating categories; the content of the financial rating reference list includes rating categories and several items at different levels within the rating categories.
[0010] The calculation rule of the business score is: multiply the score of each item in the business rating list by the corresponding score ratio, and sum up the ratios of each item to summarize the business score value; the calculation rule of the financial score is: multiply the score of each item in the financial rating reference list by the corresponding score ratio, and sum up the ratios of each item to summarize the financial score value.
[0011] The total score of the warehouse = business score value + financial score value.
[0012] The actual value of the goods is calculated based on the quantity and unit price of the goods. Among them, the unit price of the goods is obtained by comprehensively calculating the ex-factory price of the goods, the terminal price, the prices of upstream and downstream products, the historical trend, and the future price trend.
[0013] The basis for whether to issue a warning prompt is:
[0014] Compare the price of the goods on the same day * the inventory quantity on the same day with the warehouse credit limit. If the value of the goods in the warehouse exceeds the credit limit, a warning message will be issued;
[0015] If the price of the goods on the same day cannot be obtained, then judge according to the fixed price * the inventory quantity. If the value of the goods is greater than the credit limit of the warehouse rating, a warning message will be issued.
[0016] In order to further solve the problem that the warehouse administrator needs to manually set the types and prices of the actual goods in the warehouse, the present invention also provides a warehouse credit limit rating device. The specific technical solution is as follows:
[0017] Warehouse credit limit rating device, including a calculation module, a database interface, a human-machine interface, and a storage module. The calculation module includes a business score calculation module, a financial score calculation module, a total score calculation module, and a calculation module for the actual value of goods. The database interface is used to obtain information from the warehouse database, enterprise database, and goods database. The human-machine interface is used for an operator to input basic information of the warehouse, enterprise, and goods, and display the credit limit, credit rating, and goods value information of the warehouse. The storage module is used to store the credit rating table, credit limit table, and intermediate processing data. Use the method described in any one of claims 1 to 6 to rate the warehouse and issue corresponding alarm signals.
[0018] In order to further solve the problem that there are many subjective factors and lack of objectivity in the warehouse rating system, resulting in the credit limit not conforming to the actual situation of the warehouse, the present invention also provides a warehouse credit limit rating system. The specific technical solution is as follows:
[0019] Warehouse credit limit rating system, including a warehouse credit limit rating device, a goods quantity sensor, a database server, and a data transmission module. Among them, the goods quantity sensor includes at least one of a handheld three-dimensional scanning device, a liquid level sensor, and a counter. The database server is used to store data of the warehouse, enterprise, and goods. The warehouse credit limit rating device is used to calculate the credit rating, credit limit, and actual value of goods of the warehouse, as well as process human-computer interaction function data. The data transmission module is used to connect field sensors, the database server, and the warehouse credit limit rating device to realize data and information interaction.
[0020] A goods quantity automatic detection function device is deployed inside the warehouse.
[0021] For bulk stacking warehouses, directly collect the data interface of the stacking three-dimensional scanning equipment. The on-site operator uses a handheld three-dimensional scanning device to walk around the stacking for one circle, automatically scan and calculate the volume of the stacking, and upload the volume data to the warehouse database, and then multiply it by the stacking unit price to calculate the actual value of the goods.
[0022] For liquid warehouse storage tanks, a liquid level sensor is installed inside the storage tank. The liquid level sensor automatically collects the liquid level height of the liquid, and then multiplies it by the liquid unit price to calculate the actual value of the goods.
[0023] For packaged goods, a counter is installed on the conveyor belt to automatically calculate the number of goods entering or leaving the warehouse, and then multiply it by the unit price of the goods to calculate the actual value of the goods.
[0024] Compared with the prior art, the present invention has the following beneficial effects:
[0025] 1. Incorporate the storage capacity of hazardous chemicals into the warehouse rating system to further meet the evaluation needs of chemical enterprises for hazardous chemical warehouses.
[0026] 2. Combine the ARIMA model with deep learning methods to predict the prices of chemical products in the warehouse, improving the accuracy and real-time nature of the value of goods.
[0027] 3. Comprehensively consider multiple influencing factors of the warehouse rating, obtain the warehouse rating through weighting, and finally give the credit limit of the warehouse, which helps the management personnel of chemical enterprises to select the optimal warehouse for storing chemical goods and reduce the risk of product loss. Description of the Drawings
[0028] Figure 1 It is a flowchart of the method for rating the credit limit of the warehouse of the present invention.
[0029] Figure 2 It is a module diagram of the device for rating the credit limit of the warehouse of the present invention.
[0030] Figure 3 It is a module composition diagram of the system for rating the credit limit of the warehouse of the present invention. Detailed Embodiments
[0031] In order to enable those skilled in the art of this technology to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.
[0032] For the method of rating the credit limit of the warehouse, first, construct a database of the basic situation of the warehouse, calculate the business scores and financial scores of different warehouses according to the pre-set business rating reference list and financial rating reference list, and calculate the total score of the warehouse with reference to the pre-set credit rating table; secondly, calculate the credit limit of the warehouse according to the total score of the warehouse, the basic situation of the warehouse management unit and the pre-set credit limit table; then, obtain the actual situation of the goods and calculate the actual value of the goods; finally, determine whether to issue a warning prompt according to the actual value of the goods and the credit limit of the warehouse.
[0033] Specific embodiments are as Figure 1 shown
[0034] This embodiment comprehensively considers the business rating and financial rating of the warehouse, gives a quantitative warehouse level, and further obtains the credit limit of the warehouse, accurately judges the maximum amount of goods that can be stored in the warehouse, automatically judges the actual value of the goods, and helps chemical enterprises to more accurately evaluate the risk exposure of the goods in the warehouse and avoid causing losses to the enterprises.
[0035] The overall business logic of the warehouse rating: Based on the business rating score, financial rating score, and the set guarantee score, the total score is aggregated to determine the warehouse level and display the limit of the warehoused goods value.
[0036] The method for rating the credit limit of a warehouse includes the following steps:
[0037] First step, construct a database of the basic situation of the warehouse. The database stores a pre-established business rating reference list and a financial rating reference list. According to the business rating reference list and the financial rating reference list, calculate the business score and financial score of different warehouses respectively, and calculate the total score of the warehouse; and refer to the pre-set credit rating table to determine the credit rating of the warehouse; the total score of the warehouse = business score value + financial score value.
[0038] The calculation rule of the business score is: Multiply the score of each item in the business rating list by the corresponding score proportion, and aggregate the proportion of each item to summarize the business score value; the calculation rule of the financial score is: Multiply the score of each item in the financial rating reference list by the corresponding score proportion, and aggregate the proportion of each item to summarize the financial score value.
[0039] The content of the business rating reference list includes the rating category, the rating items within the rating category, the scoring reference value corresponding to each item, and the weight of the rating category; the content of the financial rating reference list includes the rating category and several items at different levels within the rating category. The business rating reference list used in this embodiment is shown in Table 1,
[0040] Table 1
[0041]
[0042] The financial rating reference list used is shown in Table 2,
[0043] Table 2
[0044]
[0045] The pre-set credit rating table is shown in Table 3,
[0046] Table 3
[0047]
[0048] Second step, calculate the credit limit of the warehouse according to the credit rating of the warehouse, the basic situation of the enterprise, and the pre-set credit limit table;
[0049] The said credit limit table is shown in Table 4,
[0050] Table 4 Corresponding Table of Basic Warehoused Goods Value (Unit: 10,000 yuan)
[0051]
[0052] The third step is to obtain the actual situation of the goods and calculate the actual value of the goods; the actual value of the goods is calculated based on the quantity of goods and the unit price, where the unit price of the goods is calculated based on a method combining deep learning and the ARIMA model.
[0053] First, use ARIMA to predict the original time series data of the unit price of the goods to obtain the baseline prediction value .
[0054] Calculate the residual sequence .
[0055] Construct an LSTM / TCN network to model and predict the residual correction amount .
[0056] Loss function expression:
[0057]
[0058] where is the weight coefficient of the prediction error term (the recommended value is 0.6 - 0.8), is the weight coefficient of the distribution alignment term (the recommended value is 0.2 - 0.4), is the Kullback-Leibler divergence operator, which calculates the difference between two probability distributions.
[0059] The final predicted value .
[0060] The fourth step is to determine whether to issue a warning prompt based on the actual value of the goods and the warehouse credit limit.
[0061] The basis for whether to issue a warning prompt is:
[0062] Compare the price of the goods on the same day * the inventory on the same day with the warehouse credit limit. If the value of the goods in the warehouse exceeds the credit limit, a warning message will be issued;
[0063] If the price of the goods on the same day cannot be obtained, then judge according to the fixed price * the inventory. If the value of the goods is greater than the credit limit of the warehouse rating, a warning message will be issued.
[0064] Next, take a specific chemical enterprise as an example to illustrate this method in detail.
[0065] The first step is to give the total score of the warehouse according to the basic situation of the warehouse. First, collect the business status of the enterprise and give a business score item by item. As shown in Table 5 below, the business score is 92 points:
[0066] Table 5
[0067]
[0068] Then collect the financial status of the enterprise and give a financial score item by item. As shown in Table 6 below, the financial score is 75 points:
[0069] Table 6
[0070]
[0071] Then, based on the business score of 92 and the financial score of 75, calculate the total score through weighted calculation:
[0072] Total score = business score × 0.7 + financial score × 0.3 = 92 × 0.7 + 75 × 0.3 = 86.9
[0073] According to the total score, find the corresponding range in Table 3 and confirm that the corresponding credit rating is AA level.
[0074] In the second step, according to the business operation status of the enterprise, it is determined that the enterprise is G2: controlled by a provincial state-owned enterprise. Then, find the basic storage value of the corresponding AA-class risk rating in Table 4, which is 150 million yuan, that is, the credit limit is 150 million yuan.
[0075] In the third step, according to the actual situation of the unit price, total quantity, quality, etc. of the goods in the warehouse, calculate the value of the goods. Assume the actual value of the goods is 170 million yuan.
[0076] In the fourth step, the system automatically compares the basic storage value and the actual value of the goods. 170 million > 150 million. Therefore, the system sends a warning message to the administrator that the current value of the goods has exceeded the credit limit, and measures need to be taken to avoid losses.
[0077] The warehouse credit limit rating device includes a calculation module, a database interface, a human-machine interface, and a storage module. The calculation module includes a business score calculation module, a financial score calculation module, a total score calculation module, and an actual value calculation module of the goods; the database interface is used to obtain information from the warehouse database, enterprise database, and goods database; the human-machine interface is used for the operator to input the basic information of the warehouse, enterprise, and goods, and display the credit limit, credit rating, and goods value information of the warehouse; the storage module is used to store the credit rating table, credit limit table, and intermediate processing data; using the above method, rate the warehouse and send out corresponding alarm signals.
[0078] Warehouse credit limit rating system, including a warehouse credit limit rating device, a goods quantity sensor, a database server, and a data transmission module; among them, the goods quantity sensor includes at least one of a handheld three-dimensional scanning device, a liquid level sensor, and a counter; the database server is used to store data of warehouses, enterprises, and goods; the warehouse credit limit rating device is used to calculate the credit rating, credit limit, and actual value of goods of the warehouse, as well as process human-computer interaction function data; the data transmission module is used to connect on-site sensors, the database server, and the warehouse credit limit rating device to achieve data and information interaction.
[0079] A goods quantity automatic detection function device is deployed inside the warehouse.
[0080] For bulk stacking warehouses, directly collect the data interface of the stacking three-dimensional scanning equipment. The on-site operator uses a handheld three-dimensional scanning device to walk around the stacking for one circle, automatically scan and calculate the volume of the stacking, and upload the volume data to the warehouse database, and then multiply it by the stacking unit price to calculate the actual value of the goods;
[0081] For liquid storage tanks in liquid warehouses, a liquid level sensor is installed inside the storage tank. The liquid level sensor automatically collects the liquid level height of the liquid, and then multiplies it by the liquid unit price to calculate the actual value of the goods;
[0082] For packaged goods, a counter is installed on the conveyor belt to automatically calculate the number of goods entering or leaving the warehouse, and then multiply it by the unit price of the goods to calculate the actual value of the goods.
[0083] It should be noted that the terms "including" and "having" and any variations thereof in the description, claims, and above-mentioned drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products, or devices.
[0084] In this application, the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", etc. is based on the orientation or positional relationship shown in the drawings. These terms are mainly used to better describe this application and its embodiments, and are not used to limit that the indicated device, element, or component must have a specific orientation, or be constructed and operated in a specific orientation.
[0085] Moreover, in addition to being used to indicate orientation or positional relationship, some of the above terms may also be used to indicate other meanings. For example, the term "upper" may also be used to indicate a certain attachment relationship or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to specific circumstances.
[0086] In addition, the terms "install", "set", "provided with", "connect", "connected", "socketed" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or there can be internal communication between two devices, components or parts. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.
Claims
1. Warehouse credit limit rating method, characterized in that: First, construct a database of the basic situation of the warehouse, calculate the business score and financial score of different warehouses according to the pre-set business rating reference list and financial rating reference list, and calculate the total score of the warehouse; And determine the credit rating of the warehouse with reference to the pre-set credit rating table; Secondly, calculate the credit line of the warehouse according to the credit rating of the warehouse, the basic situation of the warehouse management unit and the pre-set credit line table; then, obtain the actual situation of the goods and calculate the actual value of the goods; finally, determine whether to issue a warning prompt according to the actual value of the goods and the credit line of the warehouse.
2. The warehouse credit limit rating method according to claim 1, wherein: The content of the business rating reference list includes rating categories, rating items within the rating categories, the scoring reference values corresponding to each item, and the weights of the rating categories; the content of the financial rating reference list includes rating categories and several items at different levels within the rating categories.
3. The warehouse credit limit rating method according to claim 2, wherein: The calculation rule of the business score is: multiply the score of each item in the business rating list by the corresponding score proportion, and sum up the proportion of each item to summarize the business score value; the calculation rule of the financial score is: multiply the score of each item in the financial rating reference list by the corresponding score proportion, and sum up the proportion of each item to summarize the financial score value.
4. The warehouse credit limit rating method according to claim 1, characterized in that: The total score of the warehouse = business score value + financial score value.
5. The warehouse credit limit rating method according to claim 1, characterized in that: The actual value of the goods is calculated based on the quantity and unit price of the goods. Among them, the unit price of the goods is calculated based on the method combining deep learning and the ARIMA model.
6. The warehouse credit limit rating method according to claim 1, characterized in that: The basis for whether to issue a warning prompt is: Compare the price of the goods on the same day * the inventory quantity on the same day with the credit line of the warehouse. If the value of the goods in the warehouse exceeds the credit line, a warning message will be issued; If the price of the goods on the same day cannot be obtained, it will be judged according to the fixed price * the inventory quantity. If the value of the goods is greater than the credit line of the warehouse rating, a warning message will be issued.
7. Warehouse credit limit rating device, characterized in that: It includes a calculation module, a database interface, a human-machine interface, and a storage module. Among them, the calculation module includes a business score calculation module, a financial score calculation module, a total score calculation module, and an actual value calculation module of the goods; The database interface is used to obtain information from the warehouse database, enterprise database, and goods database; the human-machine interface is used for the operator to input the basic information of the warehouse, enterprise, and goods, and display the credit line, credit rating, and goods value information of the warehouse; the storage module is used to store the credit rating table, credit line table, and intermediate processing data; apply the method described in any one of claims 1 to 6 to rate the warehouse and issue corresponding alarm signals.
8. Warehouse credit limit rating system, characterized in that: It includes a warehouse credit line rating device, a goods quantity sensor, a database server, and a data transmission module; among them, the goods quantity sensor includes at least one of a handheld three-dimensional scanning device, a liquid level sensor, and a counter; the database server is used to store data of the warehouse, enterprise, and goods; the warehouse credit line rating device is used to calculate the credit rating, credit line, and actual value of the goods of the warehouse, and process human-computer interaction function data; the data transmission module is used to connect field sensors, the database server, and the warehouse credit line rating device to realize data and information interaction.
9. The warehouse credit limit rating system according to claim 8, characterized in that: A goods quantity automatic detection function device is deployed inside the warehouse.
10. The warehouse credit limit rating system according to claim 9, characterized in that: For bulk storage warehouses, directly collect the data interface of the three-dimensional scanning equipment for the piled materials. The on-site operators use a handheld three-dimensional scanning device to walk around the piled materials for one circle, automatically scan and calculate the volume of the piled materials, and upload the volume data to the warehouse database, and then multiply it by the unit price of the piled materials to calculate the actual value of the goods; For liquid storage tanks in liquid warehouses, a liquid level sensor is installed inside the tank. The liquid level sensor automatically collects the liquid level height of the liquid, and then multiplies it by the unit price of the liquid to calculate the actual value of the goods; For packaged goods, a counter is installed on the conveyor belt to automatically calculate the number of goods entering or leaving the warehouse, and then multiply it by the unit price of the goods to calculate the actual value of the goods.