Intelligent warehouse management system and method based on big data

Abstract

The invention provides an intelligent warehouse management system and method based on big data, and relates to the technical field of warehouse logistics, and the system comprises a data collection module which is used for collecting the electronic tag information, goods location coordinates and environment data of materials in a warehouse in real time through a radio frequency identification reader-writer and a wireless sensor network node, and uploading the information to a central server; the inventory early warning module is used for dynamically classifying the materials in the warehouse in the central server, calculating safety inventory intervals of various materials through historical turnover rate data, and correcting an inventory threshold value in combination with a real-time correction factor; and the positioning navigation module is used for acquiring the real-time positions of the materials according to the new safe inventory interval, and generating a goods allocation electronic map and final path navigation. According to the invention, the warehouse management efficiency and accuracy are effectively improved, the warehouse space utilization is optimized, the warehouse-in and warehouse-out operation level is improved, and visual and intelligent management is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of warehousing logistics, and particularly to an intelligent warehouse management system and method based on big data. Background Art

[0002] Traditional warehouse management mostly uses the simple moving average method for market demand forecasting. Although this method is simple to calculate, it is difficult to capture the complexity and dynamics of market demand. For example, a modern high-tech enterprise specializing in cold chain logistics, the market demand for goods is affected by seasonal and holiday factors. Under the traditional management mode, the company uses the simple moving average method to predict market demand. However, this method fails to accurately capture the sharp increase in market demand during the Spring Festival, resulting in insufficient inventory of the company, unable to meet customer needs, and thus affecting customer satisfaction and market share.

[0003] In addition, some traditional warehouse management lacks the ability to analyze the correlation between different goods and cannot achieve refined inventory management. For example, in traditional warehouse management, the formulation of inventory strategies mainly relies on the experience judgment of warehouse managers. Due to the lack of analysis of historical sales data and the turnover times of goods in and out of the warehouse, the company often adopts fixed safety inventory levels and reorder points. However, with the increasing diversification and complexity of customer order patterns, this fixed inventory strategy gradually reveals its limitations. For example, when popular products are out of stock, the company cannot adjust the inventory strategy in time to meet market demand; while when slow-moving products are overstocked, the company cannot reduce inventory in time to lower storage costs. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an intelligent warehouse management system and method based on big data, improve the intelligent level of warehouse management, and achieve accurate prediction of goods in and out of the warehouse and optimization of inventory strategies.

[0005] To solve the above technical problems, the technical solution of the present invention is as follows:

[0006] In the first aspect, an intelligent warehouse management system based on big data includes:

[0007] A data acquisition module, configured to collect the electronic tag information, location coordinates, and environmental data of the materials in the warehouse in real time through a radio frequency identification reader and a wireless sensor network node, and upload them to the central server;

[0008] An inventory warning module, configured to dynamically classify the materials in the warehouse in the central server, calculate the safety inventory range of various materials through historical turnover rate data, and correct the inventory threshold in combination with real-time correction factors;

[0009] A positioning and navigation module, which is used to obtain the real-time location of materials according to the new safety inventory range, and generate an electronic map of storage locations and a final path navigation;

[0010] A storage location optimization module, which is used to optimize the shelf layout using the latest inventory status and generate a three-dimensional storage location allocation plan;

[0011] An intelligent terminal module, which is used to execute inbound and outbound instructions according to the three-dimensional storage location allocation plan, display the real-time location information of materials and warning prompts, and synchronize and update the inventory data with the central server.

[0012] Furthermore, dynamically classify the materials in the central server, calculate the safety inventory range of various materials through historical turnover rate data, and correct the inventory threshold in combination with real-time correction factors, including:

[0013] Determine the historical turnover rate data of materials and conduct preliminary classification, including high-turnover materials, medium-turnover materials and low-turnover materials;

[0014] According to the historical turnover rate data, analyze the demand fluctuation of various materials, and determine the replenishment lead time of various materials to calculate the safety inventory range of various materials;

[0015] Combine the safety inventory range with the real-time correction factor to correct the inventory threshold of various materials.

[0016] Furthermore, the real-time correction factor includes:

[0017] Environmental factor: When the storage environment parameter > the preset threshold, the upward adjustment range of the high-risk material threshold is ≥ 0.1 to 0.3 times of the basic threshold;

[0018] Supply chain factor: When the supplier delivery delay rate > 15%, the upward adjustment range of all material thresholds is ≥ 0.2 to 0.5 times of the basic threshold;

[0019] Event factor: During the promotion period, the temporary upward adjustment range of the high-turnover material threshold is ≥ 0.1 to 0.2 times of the basic threshold.

[0020] Furthermore, according to the historical turnover rate data, analyze the demand fluctuation of various materials, and determine the replenishment lead time of various materials to calculate the safety inventory range of various materials, including:

[0021] According to the material category, analyze the demand fluctuation in different scenarios to obtain the demand fluctuation range;

[0022] According to the historical delivery data, calculate the fluctuation range of the delivery time, and combine it with the demand fluctuation range to obtain the supply risk value;

[0023] Monitor the emergency event data in real time according to the supply risk value, and obtain the impact volume of the emergency event based on the probability of the risk occurrence and the potential impact degree.

[0024] Obtain the seasonal inventory increment according to the impact volume of the emergency event and the historical seasonal sales data.

[0025] Integrate the demand fluctuation range, supply risk value, impact volume of the emergency event and seasonal inventory increment to obtain the safety inventory range.

[0026] Furthermore, according to the new safety inventory range, obtain the real-time location of the materials and generate the electronic map of the storage location and the final path navigation, including:

[0027] Automatically screen the replenishment demand and storage relocation demand operations according to the new safety inventory range to obtain the replenishment and storage relocation task list.

[0028] Divide the warehouse space into grid-shaped storage locations according to the replenishment and storage relocation task list and the layout data of the warehouse, and each storage location corresponds to a unique coordinate.

[0029] Distinguish the status of the storage location by color marking to generate the electronic map of the storage location. When searching for and handling materials, input the relevant information of the materials, including the material name, specification, model and batch number, to obtain the final path navigation from the current location to the target material location.

[0030] Furthermore, use the new inventory status to optimize the shelf layout and generate a three-dimensional storage location allocation plan, including:

[0031] Obtain the new inventory data from the central server, including the material type, quantity, turnover rate, storage location occupancy status and physical properties of the materials, and identify the association relationship between the materials and the matching degree between the materials and the warehouse area.

[0032] Divide the storage priorities according to the material turnover rate and divide the warehouse into functional areas, including the high-frequency picking area, heavy storage area and constant temperature area. Set storage rules for each area to generate an interactive shelf layout diagram, that is, a three-dimensional storage location allocation plan.

[0033] Furthermore, according to the three-dimensional storage location allocation plan, execute the inbound and outbound instructions, display the material positioning information and warning prompts in real time, and synchronize and update the inventory data with the central server, including:

[0034] Determine the inbound and outbound paths of the materials according to the three-dimensional storage location allocation plan and the actual layout of the warehouse.

[0035] When performing the inbound operation, carry the materials to the designated storage location and automatically complete the handling and storage through the RFID reader / writer. When outbound, take out the materials from the designated storage location and confirm the removal again through the equipment.

[0036] During the execution of inbound and outbound operations, the sensor nodes are used to locate the equipment, obtain the position information of the materials, and display the moving trajectory and current position in the warehouse in real time;

[0037] When the current position of the materials and the planned path do not match the target storage location, a position anomaly warning is issued. At the same time, when a fault occurs in the equipment in the warehouse or a collision anomaly occurs during the handling process, corresponding warning information is issued;

[0038] After each inbound and outbound operation is completed, the status of the storage location in the three-dimensional storage plan is adjusted, and the inventory data is synchronized and updated with the central server.

[0039] In a second aspect, a warehouse intelligent management method based on big data includes:

[0040] Through the radio frequency identification reader and wireless sensor network nodes, the electronic tag information, storage location coordinates and environmental data of the materials in the warehouse are collected in real time, and the data is uploaded to the central server;

[0041] According to the data of the central server, the materials are dynamically classified, the safety inventory range of each type of material is determined, and corresponding warning prompts are triggered according to the real-time inventory;

[0042] According to the safety inventory range and real-time position information, a storage location electronic map is generated, and a final path navigation is planned for the inbound and outbound of materials;

[0043] According to the latest material position and status information, combined with the material attributes and the shelf bearing capacity, and using three-dimensional space modeling to optimize the storage location layout, a storage location allocation plan is generated;

[0044] According to the storage location allocation plan, the inbound and outbound instructions are executed, and the position and status of the materials are confirmed in real time through the radio frequency identification reader, so that the operation data is synchronized back to the central server.

[0045] In a third aspect, a computing device includes:

[0046] One or more processors;

[0047] A storage device for storing one or more programs, which when executed by the one or more processors cause the one or more processors to implement the system.

[0048] In a fourth aspect, a computer-readable storage medium stores a program, and when the program is executed by a processor, the system is implemented.

[0049] The above solution of the present invention has at least the following beneficial effects:

[0050] By dynamically classifying the materials in the warehouse, calculating the safety inventory range based on historical turnover rate data, and correcting the inventory threshold in combination with real-time correction factors, the inventory levels of various materials can be accurately grasped. This helps avoid the waste of funds caused by inventory backlogs and the business delays caused by out-of-stock situations, ensuring that while meeting business needs, the warehouse can optimize inventory costs. Using the latest inventory status to optimize the shelf layout and generate a three-dimensional storage location allocation plan can make full use of the warehouse space and improve space utilization rate. At the same time, reasonably allocate storage locations according to the inbound and outbound frequencies and characteristics of materials, reduce the handling distance and time of materials, and lower labor and equipment costs.

[0051] Execute inbound and outbound instructions according to the three-dimensional storage location allocation plan and plan the optimal path. Staff and automated equipment operate according to the path, reducing the time for finding materials and planning routes. Real-time display of material positioning information and warning prompts enables staff to promptly discover and handle abnormal situations, ensuring the accuracy and efficiency of inbound and outbound operations. Synchronize and update inventory data with the central server to ensure the consistency and timeliness of data in all links. By analyzing the demand fluctuations of materials, it provides a basis for enterprises to formulate more reasonable procurement plans and marketing strategies, helping enterprises better respond to market changes and enhance overall competitiveness. Brief Description of the Drawings

[0052] Figure 1 is a schematic diagram of an intelligent warehouse management system based on big data provided by an embodiment of the present invention.

[0053] Figure 2 is a schematic flowchart of an intelligent warehouse management method based on big data provided by an embodiment of the present invention. Detailed Embodiments

[0054] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0055] As Figure 1 shown, an embodiment of the present invention proposes an intelligent warehouse management system based on big data, including:

[0056] A data acquisition module 1, configured to collect the electronic tag information, location coordinates, and environmental data of the materials in the warehouse in real time through a radio frequency identification reader and a wireless sensor network node, and upload them to the central server;

[0057] The inventory warning module 2 is used to dynamically classify the materials in the warehouse of the central server, calculate the safety inventory range of various materials through historical turnover rate data, and correct the inventory threshold in combination with real-time correction factors;

[0058] The positioning and navigation module 3 is used to obtain the real-time location of materials according to the new safety inventory range, and generate a location electronic map and the final path navigation;

[0059] The storage location optimization module 4 is used to optimize the shelf layout using the latest inventory status and generate a three-dimensional storage location allocation plan;

[0060] The intelligent terminal module 5 is used to execute the inbound and outbound instructions according to the three-dimensional storage location allocation plan, display the material positioning information and warning prompts in real time, and synchronize and update the inventory data with the central server.

[0061] In the embodiment of the present invention, the data acquisition module 1 uses radio frequency identification readers and wireless sensor network nodes to collect the electronic tag information, location coordinates and environmental data of the materials in the warehouse in real time, ensuring the immediate acquisition of data. The warehouse management system always grasps the latest material dynamics, including the inbound and outbound time of materials, changes in storage locations, and temperature and humidity information of the warehouse environment, avoiding management mistakes caused by data lag, and providing a solid data basis for precise management. Automatically collect data and upload it to the central server without manual recording and entry, reducing labor costs and human errors.

[0062] The inventory warning module 2 can accurately grasp the reasonable inventory range of various materials by dynamically classifying the materials in the warehouse, calculating the safety inventory range according to historical turnover rate data, and correcting the inventory threshold in combination with real-time correction factors. It effectively avoids inventory backlog occupying funds and production interruptions or sales losses caused by out-of-stock, ensuring the stable operation of the enterprise's supply chain. The real-time correction factor takes into account dynamic factors such as market demand and supply situation, enabling the inventory threshold to adapt to market changes in a timely manner. When the market demand fluctuates greatly and is unstable, the inventory warning can be adjusted in a timely manner, and the enterprise can flexibly adjust the procurement plan and production arrangement, enhancing the enterprise's response ability to market changes.

[0063] The positioning and navigation module 3 obtains the real-time location of materials according to the new safety inventory range, enabling warehouse staff to quickly find the required materials, shortening the search time, improving work efficiency, and reducing the time wasted due to searching for materials. It generates an electronic map of storage locations and a final path navigation, providing clear guidance for staff and avoiding operation errors caused by human memory errors and judgment mistakes. Whether it is inbound, outbound, or inventory-taking operations, they can be carried out along the accurate path, reducing the probability of misplacing and mis-taking materials and improving the accuracy of warehouse operations. The unified positioning and navigation standard and the visual electronic map of storage locations help standardize the warehouse management process, enabling faster familiarity with the warehouse layout and material storage rules, reducing training costs and the time to get started, and making warehouse management more standardized and standardized.

[0064] The storage location optimization module 4 optimizes the shelf layout using the latest inventory status, generating a three-dimensional storage location allocation plan. It fully considers factors such as the size, weight, and inbound and outbound frequency of materials, and can reasonably utilize the warehouse space. By reasonably planning storage locations, it avoids space waste, improves the storage capacity of the warehouse, and can store more materials without increasing the warehouse area. Optimize storage locations according to materials, place materials with frequent inbound and outbound in convenient positions for handling, reducing the distance and time of material handling, lowering labor costs. At the same time, it also reduces the wear and tear of handling equipment and energy consumption, reducing the overall material handling cost. The optimized storage location layout makes the warehouse operation process smoother, reducing operation conflicts and waiting time caused by unreasonable storage locations.

[0065] The intelligent terminal module 5 executes inbound and outbound instructions according to the three-dimensional storage location allocation plan and operates according to the guidance, reducing operation errors and improving the accuracy and efficiency of inbound and outbound. It displays the real-time location information of materials, facilitating the confirmation of material locations at any time, avoiding misoperations, and ensuring the smooth progress of the inbound and outbound process. It displays the real-time location information of materials and warning prompts, enabling managers to monitor the dynamics of materials in the warehouse in real time. Once an abnormal situation occurs, including abnormal material locations and inventory exceeding the threshold, it issues a warning in a timely manner, and managers can quickly take measures to handle it, ensuring the safety and stability of warehouse operations. It synchronizes and updates inventory data with the central server, ensuring data consistency in all links. Each department of the enterprise can obtain the latest inventory information, providing an accurate basis for procurement, sales, and production decisions, avoiding decision-making mistakes caused by inconsistent data, enabling the enterprise to make reasonable decisions in a timely manner, and improving the enterprise's operation and management level.

[0066] In a preferred embodiment of the present invention, dynamically classifying the materials in the warehouse in the central server, calculating the safety inventory range of various materials through historical turnover rate data, and correcting the inventory threshold in combination with real-time correction factors may include:

[0067] Determine the historical turnover rate data of materials and conduct preliminary classification, including high-turnover materials, medium-turnover materials, and low-turnover materials;

[0068] Based on the historical turnover rate data, analyze the demand fluctuation of various materials, and determine the replenishment lead time for various materials to calculate the safety stock range for various materials;

[0069] Combine the safety stock range with the real-time correction factor to correct the inventory threshold for various materials.

[0070] In the embodiment of the present invention, extract the inbound and outbound records of all materials in the warehouse from the database of the central server within a certain time period, and for each material, calculate the historical turnover rate. According to the calculated historical turnover rate, classify the materials into high-turnover materials, medium-turnover materials, and low-turnover materials. Materials with a relatively large turnover rate (10 times per year) are high-turnover materials; materials with a turnover rate in the middle range (2 - 10 times per year) are medium-turnover materials; materials with a relatively low turnover rate (2 times per year) are low-turnover materials. For each type of material, analyze the demand fluctuation within the statistical time period. The demand quantity for each time period can be calculated, and the maximum value, minimum value, average value, and standard deviation statistics of these demand quantities can be counted. The larger the standard deviation, the greater the demand fluctuation. Communicate with the supplier or based on historical purchase records, determine the time required for each type of material from issuing a replenishment order to the actual receipt of the material, that is, the replenishment lead time. The replenishment lead time may vary due to factors such as the type of material, the geographical location and supply capacity of the supplier, etc.

[0071] Comprehensively consider the demand fluctuation and the replenishment lead time, and calculate the safety stock range for various materials. Generally speaking, the greater the demand fluctuation and the longer the replenishment lead time, the higher the required safety stock. The lower limit of the safety stock range should be able to meet the minimum demand during the replenishment lead time, while the upper limit should avoid excessive inventory backlog and cause waste of funds. The real-time correction factor is dynamically adjusted according to current market demand, supply situation, and seasonal change factors. During the peak sales season, when the market demand increases, the real-time correction factor can be appropriately increased; in the case of supply tension, the correction factor also needs to be adjusted accordingly. Multiply the calculated safety stock range by the real-time correction factor to correct the inventory threshold for various materials. The corrected inventory threshold can better adapt to market changes and actual demands, and ensure the supply stability and rationality of materials in the warehouse.

[0072] Suppose there is an electronics warehouse with three materials: mobile phones, tablets, and smart watches.

[0073] Determine the historical turnover rate data of the materials and conduct preliminary classification. Collect the inbound and outbound records of these three materials in the past year. It is found that the total annual outbound quantity of mobile phones is 10,000 units, and the average inventory quantity is 1,000 units; the total annual outbound quantity of tablets is 3,000 units, and the average inventory quantity is 1,000 units; the total annual outbound quantity of smart watches is 500 units, and the average inventory quantity is 500 units. Calculate the historical turnover rate: The historical turnover rate of mobile phones is 10,000÷1,000 = 10 times / year; the historical turnover rate of tablets is 3,000÷1,000 = 3 times / year; the historical turnover rate of smart watches is 500÷500 = 1 time / year. Preliminary classification: Set the turnover rate greater than 8 times / year as high-turnover materials, 2 - 8 times / year as medium-turnover materials, and less than 2 times / year as low-turnover materials. Then mobile phones are high-turnover materials, tablets are medium-turnover materials, and smart watches are low-turnover materials.

[0074] Analyze the monthly demand quantity of mobile phones and find that the standard deviation is relatively large, indicating large demand fluctuations; the demand for tablets is relatively stable with a small standard deviation; the demand for smart watches also fluctuates less. Communicate with the suppliers and learn that the replenishment lead time for mobile phones is 1 week, the replenishment lead time for tablets is 2 weeks, and the replenishment lead time for smart watches is 3 weeks. Considering the large demand fluctuations and short replenishment lead time for mobile phones, the safety inventory range is set at 500 - 1,500 units; the demand for tablets is stable but the replenishment lead time is relatively long, and the safety inventory range is set at 300 - 800 units; the demand for smart watches fluctuates little but the replenishment lead time is the longest, and the safety inventory range is set at 100 - 300 units. Near the shopping festival, the market demand is expected to increase significantly. The real-time correction factor for mobile phones is set at 1.5, the real-time correction factor for tablets is set at 1.3, and the real-time correction factor for smart watches is set at 1.2. Through market research and sales data analysis, the demand growth trend during the shopping festival is confirmed.

[0075] By initially classifying materials and calculating the safety inventory range, the inventory requirements of different materials can be grasped more accurately. High-turnover materials can maintain a relatively low safety inventory to avoid inventory backlogs; while low-turnover materials can appropriately increase the safety inventory to ensure that there will be no out-of-stock situations when demand suddenly increases. Combining real-time correction factors to modify the inventory threshold enables inventory management to adapt to market changes in a timely manner, improving the flexibility and accuracy of inventory management. It avoids the capital occupation and increased warehousing costs caused by excessive inventory. By reasonably setting the safety inventory range and modifying the inventory threshold, an enterprise can reduce unnecessary inventory backlogs and lower capital and warehousing costs on the premise of meeting market demand. Adjust the inventory threshold in a timely manner to ensure timely replenishment when market demand changes, avoiding sales losses and decreased customer satisfaction caused by out-of-stock situations. Accurate inventory management helps improve the stability of the supply chain. An enterprise can communicate the replenishment plan with the supplier in a timely manner according to the modified inventory threshold to ensure the timely supply of materials and avoid affecting production and sales due to supply interruptions.

[0076] In a preferred embodiment of the present invention, the real-time correction factor may include:

[0077] Environmental factor: When the storage environment parameter > the preset threshold, the upward adjustment range of the high-risk material threshold is ≥ 0.1 to 0.3 times the basic threshold;

[0078] Supply chain factor: When the supplier delivery delay rate > 15%, the upward adjustment range of the threshold of all materials is ≥ 0.2 to 0.5 times the basic threshold;

[0079] Event factor: During the promotion period, the temporary upward adjustment range of the high-turnover material threshold is ≥ 0.1 to 0.2 times the basic threshold.

[0080] In the embodiments of the present invention, environmental parameters such as temperature, humidity, and light intensity in the warehouse are monitored in real time by sensors. The basic thresholds of the environmental parameters are set as temperature ≤ 30°C and humidity ≤ 70%. When the monitored value > the threshold, correction is triggered, and the upward adjustment range of the inventory threshold is 0.1 - 0.3 times the basic threshold. The supplier delivery delay rate is obtained in real time. When the delay rate > 15%, a supply chain risk warning is triggered, and the inventory thresholds of all materials are uniformly increased by 0.2 - 0.5 times the basic threshold. The basic threshold of Material H is 200 pieces, and the basic threshold of Material G is 150 pieces. According to the rules, the upward adjustment range of the thresholds of all materials is ≥ 0.2 to 0.5 times the basic threshold, and the upward adjustment multiple is determined according to the severity of the delay. If the delay situation is relatively serious, a 0.5 - fold increase is selected. The time arrangement and participating commodity information of the promotional activities are obtained. When it is identified that it is during the promotional activities, the event factor adjustment mechanism is started. Based on the historical turnover data of the materials, the high - turnover materials are determined. The basic inventory threshold of Electronic Product T is 300 pieces, and the basic inventory threshold of Garment E is 400 pieces. During the promotional activities, according to the rules, the temporary upward adjustment range of the thresholds of high - turnover materials is ≥ 0.1 to 0.2 times the basic threshold, and a 0.15 - fold increase is selected according to the scale of the promotional activities and the expected sales volume.

[0081] Suppose an e - commerce warehouse stores a variety of commodities, and there is a batch of perishable food which belongs to high - risk materials with a basic inventory threshold of 500 pieces; the warehouse mainly purchases commodities from three suppliers, and the procurement data in the past month shows that the supplier delivery delay rate is 20%; and the e - commerce is conducting a large - scale promotional activity for one week. The humidity sensor in the warehouse monitors that the humidity in the warehouse reaches 70%, while the preset humidity threshold for this batch of perishable food is 60%. Since the humidity is greater than the preset threshold, the inventory threshold of the high - risk materials (perishable food) is increased according to the rules. The upward adjustment range is determined to be 0.2 times the basic threshold, that is, the adjusted threshold is 500×(1 + 0.2)=600 pieces. Because the supplier delivery delay rate is 20%, which is greater than the standard of 15%. The inventory thresholds of all materials in the warehouse are increased, and the upward adjustment range is determined to be 0.3 times the basic threshold. Suppose the basic inventory threshold of a daily necessity is 800 pieces, and the adjusted threshold becomes 800×(1 + 0.3)=1040 pieces. During the promotional activities, a popular toy in the warehouse is determined to be a high - turnover material with a basic inventory threshold of 1500 pieces. According to the rules, the threshold of the high - turnover material is increased, and the upward adjustment range is 0.15 times the basic threshold. The adjusted threshold is 1500×(1 + 0.15)=1725 pieces.

[0082] The settings of environmental factors enable the inventory threshold of high-risk materials to be adjusted in a timely manner when abnormalities occur in the storage environment. This ensures that there is sufficient material reserve under adverse storage conditions, reduces the risk of material damage caused by environmental problems, and guarantees the quality and safety of materials. The supply chain factor adjusts the thresholds of all materials according to the supplier delivery delay rate, effectively coping with the uncertainties in the supply chain. When the supplier delivery delay rate is relatively high, increasing the inventory threshold can ensure that there is sufficient material supply in the warehouse, avoid production stagnation caused by supplier delivery delays, and maintain the normal operation of the enterprise. The event factor increases the threshold of high-turnover materials during promotional activities, which can accurately match the fluctuations in market demand. During promotional activities, the demand for goods usually increases significantly. By increasing the threshold of high-turnover materials, sufficient goods can be stocked in advance to meet the purchase needs of consumers, increase sales volume and customer satisfaction. Considering these real-time correction factors comprehensively, the inventory threshold can be dynamically adjusted according to the actual situation, achieving more scientific and accurate inventory management. It avoids the capital backlog and increased warehousing costs caused by excessive inventory, and at the same time prevents various losses caused by insufficient inventory, improving the operation efficiency and economic benefits of the enterprise.

[0083] In a preferred embodiment of the present invention, based on historical turnover data, the demand fluctuation situations of various types of materials are analyzed, and the replenishment lead times of various types of materials are determined to calculate the safety inventory intervals, which may include:

[0084] According to the material categories, analyze the demand fluctuations in different scenarios to obtain the demand fluctuation range;

[0085] According to historical delivery data, calculate the fluctuation range of delivery time, and combine it with the demand fluctuation range to obtain the supply risk value;

[0086] According to the supply risk value, monitor the emergency event data in real time, and obtain the emergency event impact volume according to the probability of risk occurrence and the potential impact degree;

[0087] According to the emergency event impact volume and historical seasonal sales data, obtain the seasonal inventory increment;

[0088] Integrate the demand fluctuation range, supply risk value, emergency event impact volume and seasonal inventory increment to obtain the safety inventory interval.

[0089] In the embodiment of the present invention, for each type of material, different demand scenarios are clearly defined. For the demand data in each scenario, calculate the average value . represents different scenarios, is the total number of scenarios. For the demand data in each scenario ( represents the time point), calculate , that is, the square of the difference between the demand data at each time point and the average value of the scenario. Multiply these squared values by the corresponding weights and then sum them up, that is = 0.3, to obtain . Then divide this sum by the time period (total number of days counted), and take the square root of the result, that is . This part of the result reflects the demand fluctuation range of materials under different scenarios, corresponding to in the formula part, and are adjustment coefficients set according to material characteristics and enterprise management strategies, = 1.2, = 0.8.

[0090] Obtain the historical delivery data of various materials from the procurement record database, including the order placement time and the actual delivery time. Calculate the time difference for each delivery of each type of material to obtain the delivery time series. Assume that there are 5 delivery records for the material, and the time differences are [10, 12, 8, 11, 9] days. Calculate the average value of the series, and the average delivery time L = = 10 days. Calculate the square of the difference between each delivery time in the delivery time series and the average delivery time, sum these squared values and divide by the number of deliveries ( = 5), and then take the square root of the result. Taking the delivery time of 12 days as an example, = 4, sum up all the squared differences: + + + + = 0 + 4 + 4 + 1 + 1 = 10, and the delivery time fluctuation range is . Calculate the supply risk value: Multiply the demand fluctuation range by a coefficient related to demand fluctuation, and then add the delivery time fluctuation range multiplied by a coefficient related to supply. Assume = 1.5, = 0.6, including the calculated value of the average delivery time information (here assume = 10, that is, the average delivery time), to obtain the supply risk value. Corresponding to in the formula.

[0091] According to the supply risk value, monitor the emergency event data in real time, and based on the probability and potential impact degree of the risk occurrence, obtain the emergency event impact amount, and multiply the supply risk value by the probability of the emergency event occurrence and the potential impact degree , namely 0.2, = 0.5, to obtain the impact volume of the emergency. In the formula, it corresponds to the part. Assume that it is set according to the enterprise's tolerance for emergency risks and response strategies = 1.1, = 0.9, indicating at the moment the impact degree of the emergency on the material supply, = = 0.2×0.5 = 0.1. Combining the impact volume of the emergency, considering the enterprise's inventory strategy and market demand forecast, adjust the seasonal sales fluctuation data. Integrate the demand fluctuation range, supply risk value, impact volume of the emergency and seasonal inventory increment to obtain the safety inventory range , where is the impact volume of the emergency.

[0092] By analyzing the demand fluctuations in different scenarios, combining historical delivery data, emergencies and seasonal sales data to calculate the safety inventory range, it is possible to accurately determine the reasonable inventory levels of various materials. Avoid problems of excessive or insufficient inventory caused by simple estimation, reduce inventory backlogs and out-of-stock phenomena, reduce inventory costs while ensuring the timeliness of material supply. Considering the supply risk value and the impact volume of the emergency, the enterprise can make preparations in advance for possible supply interruptions or demand mutations. In the face of natural disasters, supplier problems and other emergencies, there is enough inventory buffer to reduce production stagnation or sales losses. Combining historical seasonal sales data to obtain the seasonal inventory increment enables the enterprise's inventory to better adapt to the seasonal fluctuations of the market. Before the peak sales season arrives, increase inventory in advance to meet market demand, increase sales volume and customer satisfaction; in the off-season, reasonably control inventory to avoid capital occupation and increased warehousing costs. For example, for the clothing industry, increase the inventory of thick coats before winter and reduce its inventory in summer, optimize the inventory structure, and improve the enterprise's market competitiveness. The entire calculation process provides a scientific basis for the enterprise's inventory management decision-making. Managers can formulate more reasonable procurement plans, production plans and sales strategies according to the safety inventory ranges of different materials.

[0093] In a preferred embodiment of the present invention, according to the new safety inventory range, obtaining the real-time position of the materials and generating a location electronic map and a final path navigation may include:

[0094] Automatically screen the replenishment demand and stock transfer demand operations according to the new safety inventory range to obtain a replenishment and stock transfer task list;

[0095] According to the replenishment and stock transfer task list and the layout data of the warehouse, divide the warehouse space into grid-shaped storage locations, and each storage location corresponds to a unique coordinate;

[0096] Distinguish the status of storage locations through color marking to generate an electronic map of storage locations. When searching for and transporting materials, input the relevant information of the materials, including the material name, specification, model, and batch number, to obtain the final path navigation from the current location to the target material location.

[0097] In the embodiment of the present invention, obtain the current inventory quantity and new safety inventory range data of various materials from inventory management. At the same time, collect the basic information of the materials, including the material name, specification, model, and batch number. For each material, compare the current inventory quantity with the new safety inventory range. If the current inventory quantity is lower than the lower limit of the safety inventory range, it is determined that the material has a replenishment requirement; if the inventory quantity is greater than the upper limit of the safety inventory range, it is determined that the material has a stock transfer requirement. Organize the material information with replenishment and stock transfer requirements into a replenishment and stock transfer task list, and the list should include the detailed information of the materials, the type of requirement, and the estimated required quantity.

[0098] Obtain the detailed layout information of the warehouse, including the length, width, and height of the warehouse, the location, quantity, and size of the shelves. According to the layout of the warehouse and the storage characteristics of the materials, divide the warehouse space into evenly sized grid-shaped storage locations. When dividing, consider the location of the shelves and the setting of the aisles to ensure that each storage location can facilitate the storage and retrieval of materials. Assign a unique coordinate to each storage location. A three-dimensional coordinate ( , , ) can be used to represent the location of the storage location, where , represent the horizontal position, and represents the vertical position (the number of layers of the shelf). Assign a specific color to each storage location status. Integrate the grid-shaped storage locations and color marking information into the electronic map. The electronic map intuitively displays the overall layout of the warehouse and the status of each storage location. When it is necessary to search for and transport materials, the operator inputs the relevant information of the materials, including the material name, specification, model, and batch number, into the electronic map. Search for the coordinate of the storage location where the material is located in the database according to the input information, and combine it with the current location of the operator to obtain the final path navigation from the current location to the target material location and display the path on the electronic map.

[0099] Assume that the enterprise's warehouse mainly stores electronic products and a new safety stock range has been determined. The current inventory quantity of mobile phone A obtained from the inventory management system is 50 units, and the new safety stock range is [80, 120] units. Since 50 is lower than 80, it is determined that there is a replenishment requirement for mobile phone A, and the estimated replenishment quantity is 30 units. The current inventory quantity of tablet computer B is 150 units, and the safety stock range is [50, 100] units. Since 150 exceeds 100, it is determined that there is a need to relocate tablet computer B, and 50 units of tablet computer B need to be moved to a more appropriate storage location. The replenishment requirement of mobile phone A and the relocation requirement of tablet computer B are sorted into a replenishment and relocation task list. The length of the warehouse is 50 meters, the width is 30 meters, and the height is 10 meters. The height of the shelves is 5 meters, with a total of 5 layers. The warehouse is divided into grid-shaped storage locations of 1 meter × 1 meter × 1 meter. Taking a corner of the warehouse as the origin (0, 0, 0), the length direction is axis, the width direction is axis, and the height direction is axis. For example, the storage location coordinates of the 3rd row, 5th column, and 2nd layer are (3, 5, 2). A digital map of the storage locations is generated, and the status of each storage location is marked with colors on the map. When an operator needs to search for mobile phone A, the name, specifications, model, and batch information of mobile phone A are entered in the digital map. It is found that mobile phone A is stored in the storage location with coordinates (10, 15, 3). Assuming the operator's current location is (2, 5, 1), the final path navigation from (2, 5, 1) to (10, 15, 3) is obtained and displayed on the digital map.

[0100] By automatically screening replenishment and relocation requirements, inventory anomalies can be detected in a timely manner, ensuring that the inventory quantity of materials always remains within a reasonable range, avoiding production stagnation caused by insufficient inventory or capital backlog caused by excessive inventory. The generation of the replenishment and relocation task list enables warehouse managers to arrange work in a targeted manner, improving work efficiency. Dividing the warehouse space into grid-shaped storage locations and assigning unique coordinates helps to achieve refined management of the warehouse. The storage locations can be reasonably arranged according to the characteristics and requirements of the materials, improving the utilization rate of the warehouse space. Through relocation operations, materials can be adjusted to more appropriate positions, reducing the handling distance and time of the materials and improving the operational efficiency of the warehouse. The digital map of the storage locations intuitively displays the status of the storage locations through color markings, enabling warehouse managers to quickly understand the overall situation of the warehouse and facilitating the search and positioning of materials. The final path navigation function provides the operator with the best path from the current location to the location of the target material, reducing the time and error rate of searching for and handling materials and improving work efficiency.

[0101] In a preferred embodiment of the present invention, a new inventory status is used to optimize the shelf layout and generate a three-dimensional storage location allocation plan, which may include:

[0102] Obtain new inventory data from the central server, including the types of materials, quantities, turnover rates, storage location occupancy status, and physical properties of the materials, and identify the association relationships between the materials and the matching degree between the materials and the warehouse areas;

[0103] Divide the storage priorities according to the material turnover rate, and divide the warehouse into functional areas, including high-frequency picking areas, heavy storage areas, and constant temperature areas. Set storage rules for each area to generate an interactive shelf layout diagram, that is, a three-dimensional storage location allocation plan.

[0104] In the embodiment of the present invention, establish a stable connection with the central server, and extract the latest inventory data from the database, including mobile phones, computers, and accessories in the electronic product warehouse. Quantity, that is, the specific inventory quantity of each material; Turnover rate, calculated by analyzing historical inbound and outbound records, reflecting the flow rate of materials; Storage location occupancy status, clarifying whether the current storage location of the material is occupied and the physical properties of the material.

[0105] Mine the sales records and usage scenarios of various materials. In the office supplies warehouse, it is found that printers and ink cartridges are often issued together, indicating a strong association relationship between them; in the food warehouse, some snacks and beverages are purchased in large quantities together during promotional activities, which is also an association relationship. Combine the characteristics of different areas of the warehouse, including ventilation conditions, lighting conditions, and space size, to evaluate the matching degree between the materials and the warehouse areas. For materials that require good ventilation, judge their suitability for well-ventilated areas of the warehouse; for materials with a large volume, consider their matching degree with spacious areas. According to the material turnover rate, divide the materials into three categories: high, medium, and low turnover rates.

[0106] High-turnover materials, including popular electronic products and best-selling snacks, are set as high storage priorities; medium-turnover materials come second; low-turnover materials, including some infrequently used equipment accessories and office supplies with weak seasonality, have lower storage priorities. Divide the warehouse into functional areas according to the physical properties and storage requirements of the materials. The high-frequency picking area is used to store small high-turnover materials for convenient and quick picking; the heavy storage area is specifically for storing materials with a large weight because the shelf structure is more stable; the constant temperature area is used for temperature-sensitive materials, including drugs and special foods. Formulate corresponding storage rules for each functional area. In the high-frequency picking area, it is stipulated that the materials are arranged in descending order of turnover rate to reduce the picking time; in the heavy storage area, the materials are allocated according to the load-bearing capacity of the shelves to ensure safe storage; in the constant temperature area, the temperature range is strictly controlled, and the storage positions are arranged according to the shelf life or usage frequency of the materials. Combine the inventory data, storage priorities, functional area division, and storage rules to construct a three-dimensional map of the warehouse. Allocate specific storage locations for each material to form a visual interactive shelf layout diagram, that is, a three-dimensional storage location allocation plan.

[0107] Suppose there is an e-commerce warehouse dealing in electronic products. It obtains the current inventory data from the central server. There are 500 mobile phones, 300 tablets, and 800 pairs of headphones. The turnover rate of mobile phones is relatively high, followed by tablets, and the turnover rate of headphones is relatively low. Some storage locations are already occupied. Mobile phones and tablets are relatively small in size, while headphones are relatively lighter. The chargers for mobile phones and tablets are sold in sets with the corresponding devices. By analyzing the sales records, it is found that most customers who buy mobile phones also buy phone cases and chargers, so there is an association relationship between mobile phones and phone cases, chargers. Customers who buy tablets often buy keyboards and styluses in combination, and there is also an association between them. There is an area in the warehouse with good ventilation and a relatively small space, which is suitable for storing headphones that are small in size and have low ventilation requirements. Another area has strong shelves and is suitable for storing heavier computer hosts. There is also an area where the temperature can be adjusted, which is suitable for storing certain temperature-sensitive electronic components. Mobile phones are classified as high storage priority due to their high turnover rate, tablets are medium priority, and headphones are low priority. The warehouse is divided into a high-frequency picking area, a heavy storage area, and a constant temperature area.

[0108] The high-frequency picking area is used to store materials such as mobile phones and headphones that are small and have a high turnover rate; the heavy storage area stores materials such as computer hosts that are heavier; the constant temperature area stores temperature-sensitive electronic components. In the high-frequency picking area, materials are arranged in descending order of turnover rate. Mobile phones are placed in the most accessible position, followed by headphones. In the heavy storage area, materials are allocated according to the load-bearing capacity of the shelves. Heavier computer hosts are placed on the lower shelves. In the constant temperature area, the storage positions are arranged according to the expiration date of the materials. Materials with an earlier expiration date are placed in easily accessible positions. A 3D map of the warehouse is generated, clearly showing the specific storage locations of mobile phones and headphones in the high-frequency picking area, the placement positions of computer hosts in the heavy storage area, and the storage layout of electronic components in the constant temperature area, forming a visual interactive shelf layout diagram, which is convenient for warehouse staff to quickly understand the storage locations of materials and improve work efficiency.

[0109] By dividing storage priorities and setting up high-frequency picking areas, placing high-turnover materials in positions convenient for quick picking reduces picking time, improves order processing speed, meets customers' needs for quick receipt of goods, and enhances customer satisfaction. Functional areas are divided according to the physical properties of materials, including a heavy storage area for specifically storing heavy objects to avoid safety accidents caused by improper shelf selection; a constant temperature area to ensure the quality and safety of temperature-sensitive materials and reduce material damage and losses. Storage locations are reasonably allocated based on the volume and quantity of materials, making full use of the warehouse space and increasing the warehouse's storage capacity. Identify the associated relationships of materials, place related materials in close positions for convenient simultaneous picking and shipping, improving the coherence of warehouse operations; at the same time, store materials according to their matching degree with the warehouse area, enhancing the rationality and scientific nature of inventory management. The generated three-dimensional storage location allocation plan is presented as a visual interactive shelf layout diagram, enabling warehouse managers to intuitively understand the distribution of materials in the warehouse, facilitating tasks such as inventory counting, replenishment plan formulation, and warehouse layout adjustment, and improving management efficiency and decision-making accuracy.

[0110] In a preferred embodiment of the present invention, according to the three-dimensional storage location allocation plan, executing inbound and outbound instructions, real-time displaying material positioning information and warning prompts, and synchronously updating inventory data with the central server may include:

[0111] Determine the inbound and outbound paths of materials according to the three-dimensional storage location allocation plan and the actual layout of the warehouse;

[0112] When performing an inbound operation, carry the material to the designated storage location and automatically complete the handling and storage through a radio frequency identification reader / writer. When outbound, take out the material from the designated storage location and confirm the removal again through the equipment;

[0113] During the execution of inbound and outbound operations, obtain the position information of the material through the sensor node positioning device and display the moving trajectory and current position in the warehouse in real time;

[0114] When the current position of the material and the planned path do not match the target storage location, issue a position anomaly warning. At the same time, when a malfunction occurs in the warehouse equipment or a collision anomaly occurs during the handling process, issue corresponding warning information;

[0115] After each inbound and outbound operation is completed, adjust the storage location status in the three-dimensional storage location plan and synchronously update the inventory data with the central server.

[0116] In the embodiments of the present invention, the target storage location information of the materials is obtained from the three-dimensional storage location allocation plan, and at the same time, the actual layout data of the warehouse is combined, including the shelf location, aisle distribution, and equipment placement information. Warehouse staff transports the materials to the designated storage location according to the planned inbound path. After arriving at the storage location, the electronic tag on the materials is scanned by the radio frequency identification reader / writer installed on the storage location, and the information that the materials have been successfully stored in the storage location is automatically recorded, completing the inbound operation. At the same time, the storage location information of the materials is updated. When receiving the outbound instruction, the staff arrives at the designated storage location where the materials are located according to the planned outbound path. After taking out the materials from the storage location, the material label is scanned again by the nearby radio frequency identification reader / writer to confirm that the materials have been removed from the storage location, completing the confirmation step of the outbound operation to ensure accurate recording of the outbound information. Sensor node positioning devices are reasonably deployed in the warehouse, including Bluetooth positioning beacons and ultra-wideband (UWB) positioning base stations. When the materials move in the warehouse, the positioning tags carried on the materials interact with the surrounding sensor nodes. After the sensor nodes collect the position data of the materials, the data is transmitted to the warehouse management system through the wireless transmission network. After receiving the position data, the warehouse management system displays the movement trajectory and current position of the materials in real time on the visualization interface. By marking the position points of the materials on the three-dimensional warehouse map and connecting these points according to the time sequence, the movement trajectory of the materials is formed, which is convenient for the management personnel to intuitively understand the dynamic situation of the materials in the warehouse.

[0117] Continuously compare the actual position information of the materials with the planned inbound and outbound paths and the target storage location information. When it is found that the current position of the materials deviates from the planned path by a certain distance or the target storage location has not been reached for a long time, it is determined that the position is abnormal, and the position anomaly warning mechanism is triggered. Sensors are installed on the key equipment (handling equipment, shelves) in the warehouse to monitor the operating status of the equipment in real time. When the equipment fails (motor failure, track blockage) or a collision occurs during the handling process, corresponding warning information is issued. Once a warning is triggered, relevant personnel are notified in multiple ways, including popping up a warning window on the warehouse management system interface, sending a text message to notify the warehouse management personnel, and emitting an audible alarm. After each inbound and outbound operation is completed, the storage location status in the three-dimensional storage location allocation plan is automatically adjusted. During inbound, the status of the target storage location is updated from idle to occupied, and the stored material information is associated; during outbound, the status of the original storage location is updated from occupied to idle. The quantity and type information of the materials involved in the inbound and outbound operations are synchronized and updated with the central server. After receiving the data, the central server makes corresponding adjustments to the inventory data to ensure that the inventory data in the central server is consistent with the actual inventory situation in the warehouse, providing accurate data support for the overall operation and management of the enterprise.

[0118] Suppose there is a large e-commerce warehouse storing various kinds of goods. A batch of new smart watches arrives and needs to be stored in the warehouse. According to the three-dimensional storage location allocation plan, it is known that this batch of watches should be stored on a specific layer and location of the shelf. Combining with the warehouse layout, an inbound path is planned from the warehouse entrance through a specific passage, bypassing the area where handling operations are in progress, to reach the target storage location. When a customer places an order for a mobile phone, an outbound path is planned from the storage location of the mobile phone through a suitable passage to the warehouse exit according to the storage location of the mobile phone and the warehouse layout. During inbound, the staff uses an automated guided vehicle (AGV) to transport the smart watches to the designated storage location, and the RFID reader on the storage location automatically scans the electronic tags on the watches to confirm that the watches have been correctly stored. During outbound, the AGV reaches the storage location of the mobile phone according to the planned path. After taking out the mobile phone, the nearby RFID device confirms that the mobile phone has been removed from the storage location.

[0119] Ultra-wideband (UWB) positioning base stations are installed in the warehouse, and both the smart watches and mobile phones are equipped with UWB positioning tags. During the inbound process of the smart watches and the outbound process of the mobile phones, the positioning tags interact with the base stations, and the base stations transmit the location data to the warehouse management system. The movement trajectory of the smart watches from the entrance to the target storage location and the movement of the mobile phones from the storage location to the exit are displayed in real time on the visualization interface, enabling the management personnel to understand the dynamics of the materials at any time. If the AGV deviates from the planned path due to a malfunction during the handling of the smart watches and the location anomaly is detected, a warning window will immediately pop up on the management interface, and a text message will be sent to the management personnel. If a collision occurs among the handling equipment in the warehouse, a warning will also be issued to remind the staff to handle it in a timely manner. After the smart watches are successfully stored in the warehouse, the status of the storage location where the smart watches are stored is updated from idle to occupied, and the inbound quantity is synchronized to the central server, and the central server updates the inventory data. After the mobile phone is shipped out, the system updates the original storage location status of the mobile phone to idle, and at the same time synchronizes the outbound information to the central server to ensure the accuracy of the inventory data.

[0120] By pre-planning the final inbound and outbound paths, the handling time of materials in the warehouse is reduced, chaos and congestion during handling are avoided, the overall efficiency of inbound and outbound operations is improved, enabling the warehouse to process orders faster and meet customer needs. Using radio frequency identification technology and real-time update mechanisms ensures accurate recording of material inbound and outbound information. Meanwhile, the three-dimensional storage location plan and inventory data on the central server are updated in a timely manner, keeping the inventory information always consistent with the actual situation, providing a reliable data basis for the enterprise's inventory management, and reducing the workload and errors of inventory counting. By real-time monitoring of the material location and equipment operation status, abnormal positions, equipment failures, and collisions are promptly detected and warned, allowing managers to quickly take measures to avoid material damage, the expansion of equipment failures, and the occurrence of safety accidents, ensuring the safety of personnel, materials, and equipment in the warehouse. The real-time display of the movement trajectory and current location of materials enables warehouse managers to intuitively understand the dynamic situation of materials in the warehouse, facilitating real-time scheduling and management decisions. Visual management improves the transparency and controllability of warehouse management and enhances the overall management level. Synchronizing and updating inventory data with the central server ensures that the inventory data obtained by various departments of the enterprise (procurement, sales, finance) is consistent, providing accurate data support for the overall operation decision-making of the enterprise, avoiding decision-making mistakes caused by inconsistent data, and improving the operation efficiency and competitiveness of the enterprise.

[0121] As Figure 2 shown, an embodiment of the present invention further provides a warehouse intelligent management method based on big data, including:

[0122] Real-time collecting the electronic tag information, storage location coordinates, and environmental data of materials in the warehouse through radio frequency identification readers and wireless sensor network nodes, and uploading the data to the central server;

[0123] Dynamically classifying the materials according to the data of the central server, determining the safety inventory range for various types of materials, and triggering corresponding warning prompts according to the real-time inventory quantity;

[0124] Generating a storage location electronic map based on the safety inventory range and real-time location information, and planning the final path navigation for material inbound and outbound;

[0125] Generating a storage location allocation plan according to the latest material location and status information, combining material attributes and shelf load-bearing capacity, and optimizing the storage location layout using three-dimensional spatial modeling;

[0126] Executing the inbound and outbound instructions according to the storage location allocation plan, and real-time confirming the location and status of materials through radio frequency identification readers, synchronizing the operation data back to the central server.

[0127] It should be noted that this method corresponds to the above-mentioned system, and all implementation manners in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0128] An embodiment of the present invention further provides a computing device, including: a processor and a memory storing a computer program. When the computer program is run by the processor, it executes the system as described above. All implementation manners in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0129] An embodiment of the present invention further provides a computer-readable storage medium storing instructions. When the instructions are run on a computer, the computer is caused to execute the system as described above. All implementation manners in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0130] The above is the preferred embodiment of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A warehouse intelligent management system based on big data, characterized in that: include: The data collection module is used to collect the electronic tag information, cargo location coordinates and environmental data of materials in the warehouse in real time through the radio frequency identification reader and writer and the wireless sensor network node, and upload it to the central server; The inventory warning module is used to dynamically classify materials in the warehouse in the central server, calculate the safety inventory range of various materials through historical turnover rate data, and correct the inventory threshold in combination with real-time correction factors; Positioning and navigation module, used to obtain the real-time location of materials according to the new safety inventory interval, and generate an electronic map of the cargo location and final path navigation; The storage optimization module is used to optimize the shelf layout and generate a three-dimensional storage allocation plan using the latest inventory status; The intelligent terminal module is used to execute warehousing and outbound instructions according to the three-dimensional storage allocation plan, display material location information and early warning prompts in real time, and synchronize inventory data with the central server.

2. The intelligent warehouse management system based on big data according to claim 1 is characterized in that: Dynamically classify the materials in the warehouse in the central server, calculate the safety inventory range of each type of materials through historical turnover data, and modify the inventory threshold in combination with real-time correction factors, including: Determine historical turnover rate data for materials and make preliminary classifications, including high-turnover materials, medium-turnover materials, and low-turnover materials; Analyze the demand fluctuations of various materials based on historical turnover rate data, and determine the replenishment lead time of various materials to calculate the safety inventory range of various materials; Combine the safety stock range with the real-time correction factor to correct the inventory thresholds of various types of materials.

3. The intelligent warehouse management system based on big data according to claim 2 is characterized in that: Real-time correction factors include: Environmental factors: When the storage environment parameters are greater than the preset threshold, the threshold for high-risk materials will be increased by ≥ 0.1 to 0.3 times the basic threshold; Supply chain factor: When the supplier delivery delay rate is greater than 15%, the thresholds for all materials will be increased by ≥ 0.2 to 0.5 times the basic threshold; Event factor: During promotional activities, the threshold for high-turnover materials is temporarily increased by ≥ 0.1 to 0.2 times the basic threshold.

4. The intelligent warehouse management system based on big data according to claim 3 is characterized in that: Based on historical turnover rate data, analyze the demand fluctuations of various materials and determine the replenishment lead time of various materials to calculate the safety inventory range of various materials, including: According to the material category, analyze the demand fluctuations in different scenarios and obtain the demand fluctuation range; Based on historical delivery data, calculate the fluctuation range of delivery time, and combine it with the fluctuation range of demand to obtain the supply risk value; According to the supply risk value, the emergency data is monitored in real time, and the impact of the emergency is obtained according to the probability of risk occurrence and the potential impact degree; According to the impact of unexpected events and historical seasonal sales data, seasonal inventory increment is obtained; The demand fluctuation range, supply risk value, emergency impact and seasonal inventory increase are integrated to obtain the safety stock range.

5. The intelligent warehouse management system based on big data according to claim 4 is characterized in that: According to the new safety inventory range, obtain the real-time location of materials, and generate an electronic map of the cargo location and the final path navigation, including: According to the new safety stock range, the replenishment demand and warehouse transfer demand operations are automatically screened to obtain the replenishment and warehouse transfer task list; According to the replenishment and transfer task list and warehouse layout data, the warehouse space is divided into grid-shaped cargo locations, each of which corresponds to a unique coordinate; The cargo location status is distinguished by color marking, and an electronic cargo location map is generated. When searching and moving materials, relevant information of the materials, including material name, specification, model and batch, is input to obtain the final path navigation from the current location to the target material location.

6. The intelligent warehouse management system based on big data according to claim 5 is characterized in that: Use the new inventory status to optimize shelf layout and generate a three-dimensional storage allocation plan, including: Obtain new inventory data from the central server, including material types, quantities, turnover rates, storage space occupancy status, and physical properties of materials, and identify the relationships between materials and the matching degree between materials and warehouse areas; Storage priorities are divided according to material turnover rates, and the warehouse is divided into functional areas, including high-frequency picking areas, heavy storage areas, and constant temperature areas. Storage rules are set for each area to generate an interactive shelf layout diagram, that is, a three-dimensional storage allocation plan.

7. The intelligent warehouse management system based on big data according to claim 6 is characterized in that: According to the 3D storage allocation plan, execute the in and out instructions, display the material location information and early warning prompts in real time, and update the inventory data synchronously with the central server, including: Determine the material entry and exit paths based on the three-dimensional storage allocation plan and the actual layout of the warehouse; When performing the warehousing operation, the materials are moved to the designated storage location and automatically moved and stored through the RFID reader. When leaving the warehouse, the materials are taken out from the designated storage location and the removal is confirmed again through the equipment. During the process of entering and leaving the warehouse, the sensor node positioning equipment is used to obtain the location information of the materials, and the movement trajectory and current location in the warehouse are displayed in real time; When the current location and planned path of the material do not match the target storage location, an abnormal location warning will be issued. At the same time, when equipment in the warehouse fails or an abnormal collision occurs during transportation, a corresponding warning message will be issued; After each warehousing and outbound operation is completed, the cargo location status in the three-dimensional storage plan is adjusted, and the inventory data is updated synchronously with the central server.

8. A warehouse intelligent management method based on big data, the method realizing the system as claimed in any one of claims 1 to 7, characterized in that: include: Through RFID readers and wireless sensor network nodes, the electronic tag information, cargo location coordinates and environmental data of materials in the warehouse are collected in real time, and the data is uploaded to the central server; According to the data from the central server, materials are dynamically classified to determine the safe inventory range of each type of materials, and corresponding early warning prompts are triggered based on the real-time inventory level; Generate an electronic map of cargo locations based on safety inventory intervals and real-time location information, and plan the final path navigation for materials in and out of the warehouse; Based on the latest material location and status information, combined with material attributes and shelf carrying capacity, three-dimensional space modeling is used to optimize storage layout and generate storage allocation plans; Execute in-and-out instructions according to the storage allocation plan, and confirm the location and status of materials in real time through RFID readers and writers, so that the operation data can be synchronized back to the central server.

9. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the system according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, and when the program is executed by a processor, the system according to any one of claims 1 to 7 is implemented.

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