Intelligent warehouse management optimization method and system based on RFID technology

Abstract

The invention discloses an intelligent warehouse management optimization method and system based on an RFID technology, relates to the technical field of warehouse management optimization, and solves the technical problems that in the prior art, targeted inventory management cannot be carried out according to an inventory prediction result, safe inventory calculation and replenishment point calculation are not executed, and the warehouse management optimization efficiency is reduced. The layout construction unit is used for carrying out layout construction on a warehouse, completing sensor layout and completing RFID reader hardware detection; the inventory prediction unit is used for carrying out inventory prediction on the storage area and generating an inventory emergency signal or a space idle signal according to a prediction result; the inventory management unit is used for carrying out inventory management on the storage areas and carrying out inventory management according to the corresponding inventory prediction signals; and the path optimization unit is used for carrying out path identification optimization on real-time inventory management during different modes of warehouse management.

Description

Technical Field

[0001] This invention relates to the field of warehouse management optimization technology, specifically to an intelligent warehouse management optimization method and system based on RFID technology. Background Technology

[0002] Intelligent warehouse management optimization is key to improving warehouse efficiency, reducing costs, and enhancing supply chain responsiveness, involving multiple dimensions such as technology application, process reengineering, and data-driven approaches. The core of intelligent warehousing lies in replacing manual operations with technology, improving data accuracy, and increasing the level of process automation.

[0003] However, in existing technologies, warehouse areas cannot be accurately laid out, and inventory forecasting for warehouse areas is not possible, which reduces the timeliness of warehouse area management. In addition, targeted inventory management cannot be carried out based on inventory forecast results, and safety stock calculation and replenishment point calculation are not performed, which reduces the efficiency of warehouse management optimization.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems mentioned above by proposing an intelligent warehouse management optimization method and system based on RFID technology.

[0006] The objective of this invention can be achieved through the following technical solutions: The intelligent warehouse management optimization system based on RFID technology includes a warehouse management center, and the communication connections of the warehouse management center are as follows: The layout building unit is used to build the warehouse layout, complete the sensor layout, and complete the RFID reader hardware testing. The inventory forecasting unit forecasts inventory levels in the storage area and generates an inventory shortage signal or a space idle signal based on the forecast results. The inventory management unit manages inventory in the warehouse area based on corresponding inventory forecast signals. The path optimization unit performs path identification and optimization for real-time inventory management when different warehouse management methods are used.

[0007] In a preferred embodiment of the present invention, the process of laying out the building units is as follows: Obtain the area of ​​the region where sensors are deployed in the warehouse and label it M. At the same time, obtain the effective coverage area of ​​a single sensor and label it m. Different types of sensors have different effective coverage areas, so the average value is used. Set a redundancy coefficient and assign a label k, typically between 1.2 and 1.4, to ensure full coverage and avoid monitoring blind spots; according to the formula... The number of sensors S is obtained, and the sensor layout is determined based on the required sensor types within the coverage area.

[0008] In a preferred embodiment of the present invention, after the layout is completed, the power of the RFID reader is calculated. Set the reader's transmit power to label P, and simultaneously obtain the tag's receive sensitivity and set it to label P. L Furthermore, the expected maximum recognition distance of the reader is obtained, and an environmental attenuation factor is set according to the type of reader, with the label L; substitute into the formula. ; The obtained reader transmission power is compared with a threshold: if the current reader transmission power exceeds the set power threshold, it indicates that the reader settings are qualified; otherwise, if the current reader transmission power does not exceed the set power threshold, it indicates that the reader settings are unqualified; hardware debugging is performed to determine whether the reader power is qualified or not.

[0009] In a preferred embodiment of the present invention, the process of the inventory forecasting unit is as follows: The specific formula for forecasting inventory levels for the current period in a given inventory region is as follows: ; in, This is represented as the observation value of the time series at time t; B represents the lag factor. The lag operator B shifts the time series forward by one time step. It is represented as an autoregressive polynomial, where p is the autoregressive order; It is represented as a difference operator, where d is the difference order; The moving average polynomial q is the order of the moving average. It is represented as a white noise sequence.

[0010] In a preferred embodiment of the present invention, the observation values ​​at corresponding times are obtained in the time series of the current period. The observation values ​​are sorted in chronological order and the fluctuation trend of the observation values ​​is recorded. Combined with the inventory inflow and outflow situation in the corresponding time periods of each adjacent time period, that is, whether there is inventory much greater than outflow or outflow much greater than inventory; and when there is no inventory inflow or outflow, if the fluctuation trend of the observation values ​​continues to decline, it indicates that the current inventory demand is at a trough, generating an inventory emergency signal and sending it to the warehouse management center; if the fluctuation trend of the observation values ​​continues to rise, it indicates that the current inventory demand is at a peak, generating a space idle signal and sending it to the warehouse management center.

[0011] In a preferred embodiment of the present invention, the process of the inventory management unit is as follows: Upon receiving a space vacancy signal, the current storage area will be marked as an inventory increase phase; Obtain the Z-value corresponding to the service level of the warehouse area during the inventory increase phase, specifically the standard normal distribution quantile in statistics; and assign a label Z. Simultaneously, the procurement lead time of each storage node during the inventory increase phase is obtained and labeled LT; the standard deviation of the lead time is calculated based on the cumulative floating period of the procurement lead time and labeled accordingly. ; The standard deviation of demand is calculated based on the supply and demand corresponding to the storage area, and a label is assigned. ; The average demand is obtained based on the real-time demand in the storage area, and a label is set. ; Substitute the values ​​into the formula to calculate the safety stock value AK. The formula is as follows: ; After obtaining the safety stock value, the system performs synchronous analysis based on the real-time safety stock value of the warehouse area, along with demand and supply. The system then compares the inventory value with the safety stock value and generates a warehouse shipment signal when the safety stock value is reached. This signal is sent to the warehouse management center, and an early warning is issued.

[0012] In a preferred embodiment of the present invention, upon receiving an inventory shortage signal, the current storage area is marked as an inventory reduction phase. Collect data from adjacent inventory increase phases during the current inventory decrease phase, and obtain the average supply required, procurement lead time, and safety stock value during the inventory increase phase; then substitute these values ​​into the formula to calculate the replenishment inventory point (BHD). The specific formula is as follows: Once the replenishment point is obtained, the system monitors the real-time inventory level. If the replenishment point is reached or the interval between replenishment points exceeds the available warehouse capacity, a replenishment signal is generated and sent to the warehouse management center.

[0013] In a preferred embodiment of the present invention, the path optimization unit operates as follows: The deviation values ​​of the average increase rate of the inbound volume recorded by the sensors at each inbound location within the storage area are obtained, and the fluctuation deviations of the outbound volume recorded by the readers at different times at each outbound location within the storage area are also obtained. The collected deviation values ​​of the average increase rate of the inbound volume and the fluctuation deviations of the outbound volume at different times are compared with the average deviation threshold and the fluctuation deviation threshold, respectively.

[0014] In a preferred embodiment of the present invention, if the deviation of the average rate of increase in regional inbound volume exceeds the average deviation threshold, or the fluctuation deviation of regional outbound volume at different times exceeds the fluctuation deviation threshold, a path optimization signal is generated and sent to the warehouse management center; if the deviation of the average rate of increase in regional inbound volume does not exceed the average deviation threshold, and the fluctuation deviation of regional outbound volume at different times does not exceed the fluctuation deviation threshold, a path satisfaction signal is generated and sent to the warehouse management center.

[0015] As a preferred embodiment of the present invention, the intelligent warehouse management optimization method based on RFID technology is as follows: Layout construction: Build the warehouse layout, complete the sensor layout, and complete the RFID reader hardware testing; Inventory forecasting involves predicting inventory levels in the storage area and generating signals of low inventory or vacant space based on the forecast results. Inventory management involves managing inventory in the warehouse area based on corresponding inventory forecast signals. Path optimization involves optimizing the path identification for real-time inventory management when different warehouse management methods are used.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. In this invention, the warehouse layout is constructed by building sensors in the warehouse area to ensure sensor coverage of the entire warehouse area. At the same time, the power consumption of the hardware is detected based on the power calculation of the RFID reader, so as to effectively utilize RFID technology and improve the intelligent management of the warehouse. Inventory forecasting is performed in the warehouse area, and the warehouse is intelligently controlled based on the inventory forecast results. This allows real-time warehouse control to adapt to the real-time warehouse storage status, ensure supply and inventory balance, avoid untimely supply and reduce the risk of inventory backlog, and improve the efficiency of intelligent warehouse management.

[0017] 2. In this invention, inventory management is implemented in the warehouse area. Inventory management is divided into safety stock calculation and replenishment point calculation. Targeted inventory control is carried out based on different types of signals to improve the management efficiency of the current warehouse area. At the same time, it can ensure the supply and storage balance of the warehouse, ensure that the warehouse area can effectively store and supply goods, reduce the pressure of excessive storage and excessive supply, and enhance the feasibility of optimized warehouse management. Path optimization is performed according to the inventory management required in the warehouse management process. Path identification optimization is performed on real-time inventory management in different warehouse management methods, which improves the management efficiency during warehouse optimization management, facilitates the implementation feasibility of management methods, and further promotes the high efficiency of warehouse management. Attached Figure Description

[0018] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0019] Figure 1 This is a system principle block diagram of the present invention; Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] Please see Figure 1 As shown, the intelligent warehouse management optimization system based on RFID technology includes a warehouse management center, which is connected to a layout building unit, an inventory forecasting unit, an inventory management unit, and a path optimization unit. The warehouse management center generates a layout building signal and sends it to the layout building unit; After receiving the layout construction signal, the layout construction unit constructs the layout of the warehouse. It constructs sensors in the warehouse area to enable sensor detection to cover the entire warehouse area. At the same time, it calculates the power consumption of the hardware based on the RFID reader power to effectively utilize RFID technology and improve the intelligent management of the warehouse. Obtain the area of ​​the region where sensors are deployed in the warehouse and label it M. At the same time, obtain the effective coverage area of ​​a single sensor and label it m. Different types of sensors have different effective coverage areas, so the average value is used. Set a redundancy coefficient and assign a label k, typically between 1.2 and 1.4, to ensure full coverage and avoid monitoring blind spots; according to the formula... Obtain the number of sensors S, and then deploy them according to the required sensor types within the coverage area; After the layout is completed, the power of the RFID reader is calculated. Set the reader's transmit power to label P, and simultaneously obtain the tag's receive sensitivity and set it to label P. L Furthermore, the expected maximum recognition distance of the reader is obtained, and the environmental attenuation factor is set according to the type of reader. The label L is set, which is generally 3-5 dB in warehouse environments with many metal shelves and 1-2 dB in ordinary warehouse environments. Substitute into the formula ; The obtained reader transmit power is then compared to a threshold: If the current reader's transmission power exceeds the set power threshold, it indicates that the reader settings are qualified; Conversely, if the current reader's transmission power does not exceed the set power threshold, it indicates that the reader settings are not up to standard; hardware adjustments should be made to determine whether the reader's power is up to standard. After the layout is completed, the warehouse management center generates an inventory forecast signal and sends it to the inventory forecasting unit; After receiving the inventory forecast signal, the inventory forecasting unit forecasts the inventory in the storage area and uses the inventory forecast results to intelligently control the warehouse, so that real-time warehouse control can be adapted to the real-time warehouse storage status, ensuring supply and inventory balance, avoiding untimely supply and reducing the risk of inventory backlog, and improving the efficiency of intelligent warehouse management. The specific formula for forecasting inventory levels for the current period in a given inventory region is as follows: ; in, This is represented as the observations of a time series at time t. In the scenario of inventory demand forecasting, This could be the inventory demand for the t-th time period (e.g., day t, week t, etc.). For example, if the inventory demand for a product is calculated in weeks, then X1 is the demand for the first week, X2 is the demand for the second week, and so on. B represents the lag factor. The lag operator B shifts the time series forward by one time step; for example... This means moving the observation at time t to time t-1. Using the lag operator, the lag term of a time series can be conveniently represented. Represented as an autoregressive polynomial, in the form of: , where p is the autoregressive order; It is represented as a difference operator, where d is the difference order; in many real time series, the data may have non-stationary characteristics such as trends or seasonality, while the ARIMA model requires the time series to be stationary; the role of the difference operator is to transform a non-stationary time series into a stationary time series by performing difference operations on the time series. Represented as a moving average polynomial, in the form of: q is the order of the moving average; the moving average part is mainly used to capture random fluctuations in time series. These are moving average coefficients, which reflect the degree of influence of white noise at different times in the past on the current value; Represented as a white noise sequence, a white noise sequence is a random sequence with a mean of 0, a constant variance, and independent sequences. In the ARIMA model, it represents the random fluctuations in the time series that cannot be explained by the autoregressive and moving average components, i.e., the residual term of the model; The observation values ​​at the corresponding time in the time series of the current period are obtained, and the observation values ​​are sorted in time order. The fluctuation trend of the observation values ​​is recorded. Combined with the inventory inflow and outflow of each adjacent time period, that is, whether there is inventory much greater than outflow or outflow much greater than inventory. "Much greater" means that the inventory-outflow ratio exceeds the set threshold. Generally, 1.2 times the single inflow or outflow of inventory is used as the set threshold. And if the observed value continues to decline when there is no inventory inflow or outflow, it indicates that the current inventory demand is at its lowest point, generating an inventory emergency signal and sending it to the warehouse management center. If the observed value continues to rise, it indicates that the current inventory demand is at its peak, generating a space idle signal and sending it to the warehouse management center. The warehouse management center manages and controls the warehouse based on signals of low inventory or vacant space. Generate inventory management signals and send them to the inventory management unit; After receiving the inventory management signal, the inventory management unit performs inventory management in the storage area. Inventory management is divided into safety stock calculation and replenishment point calculation. Targeted inventory control is carried out according to different types of signals to improve the management efficiency of the current storage area. At the same time, it can ensure the supply and storage balance of the storage area, ensure that the storage area can effectively store and supply goods, reduce the pressure of excessive storage and excessive supply, and enhance the feasibility of optimized management of the storage area. Upon receiving a space vacancy signal, the current storage area will be marked as an inventory increase phase; Obtain the Z-value corresponding to the service level of the warehouse area during the inventory increase phase, specifically the standard normal distribution quantile in statistics; and assign a label Z. Simultaneously, the procurement lead time of each storage node during the inventory increase phase is obtained and labeled LT; the standard deviation of the lead time is calculated based on the cumulative floating period of the procurement lead time and labeled accordingly. ; The standard deviation of demand is calculated based on the supply and demand corresponding to the storage area, and a label is assigned. ; The average demand is obtained based on the real-time demand in the storage area, and a label is set. ; Substitute the values ​​into the formula to calculate the safety stock value AK. The formula is as follows: ; After obtaining the safety stock value, the system performs synchronous analysis based on the real-time safety stock value of the warehouse area, demand, and supply. The system determines the rise and fall of the inventory value based on the synchronous analysis of real-time demand and supply, compares it with the safety stock value, and generates a warehouse shipment signal when the safety stock value is reached. This signal is then sent to the warehouse management center, and an early warning is issued. Upon receiving a low inventory signal, the current storage area will be marked as being in a low inventory phase. Collect data from adjacent inventory increase phases during the current inventory decrease phase, and obtain the average supply required, procurement lead time, and safety stock value during the inventory increase phase; then substitute these values ​​into the formula to calculate the replenishment inventory point (BHD). The specific formula is as follows: ; Once the replenishment point is obtained, based on real-time inventory monitoring, if the replenishment point is reached or the interval between replenishment points exceeds the available warehouse capacity, an inventory replenishment signal is generated and sent to the warehouse management center. After determining the replenishment inventory point and safety stock value, a path optimization signal is generated and sent to the path optimization unit. After receiving the data, the path optimization unit optimizes the path according to the inventory management required in the warehouse management process. It identifies and optimizes the path for real-time inventory management in different warehouse management methods, which improves the management efficiency during warehouse optimization management, facilitates the implementation feasibility of management methods, and further promotes the high efficiency of warehouse management. The deviation value of the average increase rate of the inbound quantity recorded by the sensor at each inbound location in the storage area is obtained, and the fluctuation deviation of the outbound quantity recorded by the reader at different times at each outbound location in the storage area is also obtained. The deviation of the average rate of increase in regional inbound volume and the fluctuation deviation of regional outbound volume at different times are compared with the mean deviation threshold and the fluctuation deviation threshold, respectively. If the deviation of the average rate of increase in regional inbound volume exceeds the average deviation threshold, or the fluctuation deviation of regional outbound volume at different times exceeds the fluctuation deviation threshold, it is inferred that the inventory management in the storage area needs to be optimized. A path optimization signal is generated and sent to the storage management center. After receiving the signal, the storage management center will adjust the path in a timely manner according to the fluctuation of the item layout in the storage area. If the deviation of the average rate of increase in regional inbound volume does not exceed the average deviation threshold, and the fluctuation deviation of regional outbound volume at different times does not exceed the fluctuation deviation threshold, it is inferred that inventory management within the storage area does not require path optimization, and a path satisfaction signal is generated and sent to the storage management center.

[0023] Please see Figure 2 As shown, the intelligent warehouse management optimization method based on RFID technology is as follows: Layout construction: Build the warehouse layout, complete the sensor layout, and complete the RFID reader hardware testing; Inventory forecasting involves predicting inventory levels in the storage area and generating signals of low inventory or vacant space based on the forecast results. Inventory management involves managing inventory in the warehouse area based on corresponding inventory forecast signals. Path optimization involves optimizing the path identification for real-time inventory management when different warehouse management methods are used.

[0024] In use, this invention comprises: a layout construction unit for constructing the warehouse layout, completing sensor placement, and performing RFID reader hardware testing; an inventory prediction unit for predicting inventory in the storage area and generating an inventory shortage signal or a space idle signal based on the prediction results; an inventory management unit for managing inventory in the storage area and managing inventory based on the corresponding inventory prediction signal; and a path optimization unit for optimizing real-time inventory management through path identification during different warehouse management methods.

[0025] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influences. Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0026] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent warehouse management optimization system based on RFID technology, characterized in that, This includes the warehouse management center, whose communication connections include: The layout building unit is used to build the warehouse layout, complete the sensor layout, and complete the RFID reader hardware testing. The inventory forecasting unit forecasts inventory levels in the storage area and generates an inventory shortage signal or a space idle signal based on the forecast results. The inventory management unit manages inventory in the warehouse area based on corresponding inventory forecast signals. The path optimization unit performs path identification and optimization for real-time inventory management when different warehouse management methods are used. 2.The RFID technology based intelligent warehouse management optimization system according to claim 1, wherein, The process of laying out building blocks is as follows: Obtain the area of ​​the region where sensors are deployed in the warehouse and label it M. At the same time, obtain the effective coverage area of ​​a single sensor and label it m. Different types of sensors have different effective coverage areas, so the average value is used. Set a redundancy coefficient and assign a label k, typically between 1.2 and 1.4, to ensure full coverage and avoid monitoring blind spots; according to the formula... The number of sensors S is obtained, and the sensor layout is determined based on the required sensor types within the coverage area.

3. The intelligent warehouse management optimization system based on RFID technology according to claim 2, characterized in that, After the layout is completed, the power of the RFID reader is calculated. Set the reader's transmit power to label P, and simultaneously obtain the tag's receive sensitivity and set it to label P. L Furthermore, the expected maximum recognition distance of the reader is obtained, and an environmental attenuation factor is set according to the type of reader, with the label L; substitute into the formula. ; The obtained reader transmission power is compared with a threshold: if the current reader transmission power exceeds the set power threshold, it indicates that the reader settings are qualified; otherwise, if the current reader transmission power does not exceed the set power threshold, it indicates that the reader settings are unqualified; hardware debugging is performed to determine whether the reader power is qualified or not. 4.The RFID technology-based intelligent warehouse management optimization system of claim 3, wherein, The process of the inventory forecasting unit is as follows: The specific formula for forecasting inventory levels for the current period in a given inventory region is as follows: ； wherein, denotes the observation at time instant t as a time series; B represents the lag factor. The lag operator B shifts the time series forward by one time step. is represented as an autoregressive polynomial, where p is the autoregressive order; is expressed as a difference operator, where d is the difference order; q is a moving average order; is represented as a white noise sequence.

5. The intelligent warehouse management optimization system based on RFID technology according to claim 4, characterized in that, Obtain the observation values ​​at the corresponding time in the time series of the current period, sort the observation values ​​in chronological order, record the fluctuation trend of the observation values, and combine the inventory inflow and outflow of each adjacent time period to determine whether there is inventory much greater than outflow or outflow much greater than inventory. And if the observed value continues to decline when there is no inventory inflow or outflow, it indicates that the current inventory demand is at its lowest point, generating an inventory emergency signal and sending it to the warehouse management center. If the observed value continues to rise, it indicates that the current inventory demand is at its peak, generating a space idle signal that is sent to the warehouse management center. 6.The RFID technology-based intelligent warehouse management optimization system according to claim 5, wherein, The process of the inventory management unit is as follows: Upon receiving a space vacancy signal, the current storage area will be marked as an inventory increase phase; Obtain the Z-value corresponding to the service level of the warehouse area during the inventory increase phase, specifically the standard normal distribution quantile in statistics; and assign a label Z. At the same time, the lead time of each storage node in the inventory increasing stage is obtained, and a label LT is set; the standard deviation of the lead time is calculated according to the cumulative floating period of the lead time, and a label is set According to the warehouse area corresponding to the supply demand quantity calculation demand standard deviation, and set the label ; According to the required supply amount of the real-time storage area, a required supply amount average is obtained, and a label is set ; The safety stock value AK is calculated by substituting the formula: ; After obtaining the safety stock value, the system performs synchronous analysis based on the real-time safety stock value of the warehouse area, along with demand and supply. The system then compares the inventory value with the safety stock value and generates a warehouse shipment signal when the safety stock value is reached. This signal is sent to the warehouse management center, and an early warning is issued. 7.The RFID technology based smart warehousing management optimization system as claimed in claim 6, wherein, Upon receiving a low inventory signal, the current storage area will be marked as being in a low inventory phase. Collect data on inventory increases adjacent to the current inventory decrease phase, and obtain the average supply required, procurement lead time, and safety stock value during the inventory increase phase. And substitute the formula to calculate the replenishment inventory point BHD, the specific formula is: ; Once the replenishment point is obtained, a replenishment signal is generated and sent to the warehouse management center if the replenishment point is reached or the interval between replenishment points exceeds the warehouse's available capacity, based on real-time inventory monitoring.

8. The intelligent warehouse management optimization system based on RFID technology according to claim 7, characterized in that, The process of the path optimization unit is as follows: The deviation values ​​of the average increase rate of the inbound volume recorded by the sensors at each inbound location within the storage area are obtained, and the fluctuation deviations of the outbound volume recorded by the readers at different times at each outbound location within the storage area are also obtained. The collected deviation values ​​of the average increase rate of the inbound volume and the fluctuation deviations of the outbound volume at different times are compared with the average deviation threshold and the fluctuation deviation threshold, respectively. 9.The RFID technology-based intelligent warehouse management optimization system of claim 8, wherein, If the deviation of the average rate of increase in regional inbound volume exceeds the average deviation threshold, or the fluctuation deviation of regional outbound volume at different times exceeds the fluctuation deviation threshold, a path optimization signal is generated and sent to the warehouse management center; if the deviation of the average rate of increase in regional inbound volume does not exceed the average deviation threshold, and the fluctuation deviation of regional outbound volume at different times does not exceed the fluctuation deviation threshold, a path satisfaction signal is generated and sent to the warehouse management center.

10. A method for optimizing intelligent warehouse management based on RFID technology, characterized in that, The specific management optimization methods are as follows: Layout construction: Build the warehouse layout, complete the sensor layout, and complete the RFID reader hardware testing; Inventory forecasting involves predicting inventory levels in the storage area and generating signals of low inventory or vacant space based on the forecast results. Inventory management involves managing inventory in the warehouse area based on corresponding inventory forecast signals. Path optimization involves optimizing the path identification for real-time inventory management when different warehouse management methods are used.

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