Intelligent warehouse checking method based on RFID

Abstract

The invention discloses an RFID-based intelligent warehouse checking method, and relates to the technical field of warehouse intelligent checking, and the method comprises the steps: obtaining the basic information of commodities in a warehouse RFID tag, collecting tag data, and transmitting the tag data to a database for storage in real time; comparing the data read by the RFID with an inventory record to identify a difference value; comparing and analyzing the commodity environment data with standard environment data to obtain a storage evaluation value; identifying and classifying the marked commodities, and allocating managers to confirm and process the commodities; the warehouse is divided into a plurality of areas for separate inventory, so that the actual inventory condition of commodities in the warehouse can be quickly and accurately obtained, and the time and errors of manual inventory are reduced; through continuous monitoring of the storage environment, damage or expiration of the commodities caused by improper storage can be effectively reduced, and the safety and quality of the commodities are improved; due to real-time monitoring and early warning, the frequency of manual inspection is reduced, and meanwhile, the overall management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent warehouse inventory counting, and in particular to an intelligent warehouse inventory counting method based on RFID. Background Art

[0002] Warehouse inventory is an important part of enterprise inventory management. Regular inventory can help enterprises accurately grasp inventory status and optimize operation processes. Warehouse inventory can verify the actual quantity of goods in the warehouse with the inventory quantity recorded by the system to ensure the authenticity and accuracy of inventory data. Accurate inventory data is the basis for purchasing, production and sales decisions, which helps enterprises avoid excessive inventory backlogs and reduce capital occupation. At the same time, it can also prevent insufficient inventory, avoid supply chain disruptions and loss of sales opportunities. Inventory can timely discover problems such as loss, damage or deterioration of goods, reduce the company's property losses, and optimize the storage and maintenance of goods. Regular inventory can help managers analyze inventory turnover and goods flow, find out slow-selling, about to expire or need to be re-ordered goods, and optimize inventory management strategies. Accurate inventory data allows warehouse managers to reasonably arrange replenishment, delivery and storage space utilization, and improve overall operational efficiency. Although inventory counting is crucial to enterprises, traditional inventory counting methods have some problems and challenges; traditional manual inventory counting methods are very time-consuming, especially in large-scale warehouses, where staff need to check the goods one by one and record the quantity. The whole process usually takes a lot of time, seriously affecting work efficiency; traditional inventory counting data is usually updated in the system only after the inventory counting is completed, which makes the warehouse inventory data in a lagging state during the inventory counting cycle and cannot reflect the actual inventory situation in real time; during the inventory counting process, it is difficult to detect unsaleable, expired or about to expire goods in time, causing these goods to occupy warehouse space and even cause losses. Summary of the invention

[0003] The purpose of the present invention is to solve the problems of the above-mentioned background technology and to propose an intelligent warehouse inventory method based on RFID.

[0004] The purpose of the present invention can be achieved by the following technical solution: An intelligent warehouse inventory method based on RFID, comprising the following steps: S1: Obtain basic information of goods in warehouse RFID tags, collect tag data and send it to the database for storage in real time; S2: Compare the data read by RFID with the inventory records to identify the difference value, and send the commodity difference value to the database for storage; the specific steps are: At the beginning of the inventory, the warehouse is divided into several areas according to its size and recorded as j, where j=1, 2, 3...J, J is a positive integer, J represents the total number of warehouse areas, and j represents the serial number of any area in the warehouse; use the RFID reader to scan all areas of the entire warehouse, the reader will automatically read the RFID tag information passed by, and transmit the data to the server for storage in real time; use the RFID reader to obtain the type of goods in the RFID tag and record it as i, where i=1, 2, 3...I, I is a positive integer, I represents the total number of types of goods, i represents the type of any one of the goods, and each type of goods has a specific storage area; obtain the collected inventory quantity of goods and record it as Lij; obtain the production date and shelf life of the goods, as well as the storage time of the goods, and calculate the difference between them to obtain the remaining validity period of the goods, and record it as Qij; obtain the expected inventory quantity of the goods and record it as Yij; set the optimal remaining validity period of the expected goods and record it as Xij; Substitute the values ​​of the product inventory quantity Lij, the expected product inventory quantity Yij, the product remaining validity period Qij, and the expected product optimal remaining validity period Xij into the formula Calculate and obtain the commodity difference value Pij, where a1 and a2 are respectively the set weight factors, and e is represented as a natural constant; set a commodity difference threshold, compare and analyze the commodity difference value with the commodity difference threshold, when the commodity difference value is less than the set commodity difference threshold, it means that the commodity inventory quantity and the commodity remaining validity period are smaller than the expected commodity inventory quantity and the expected best remaining validity period, then the commodity is marked as a commodity to be confirmed as a commodity with insufficient inventory and approaching expiration; when the commodity difference value is equal to the set commodity difference threshold, it means that the commodity inventory quantity and the commodity remaining validity period are no different from the expected commodity inventory quantity and the expected best remaining validity period; when the commodity difference value is greater than the set commodity difference threshold, it means that the commodity inventory quantity and the commodity remaining validity period are larger than the expected commodity inventory quantity and the expected best remaining validity period, then the commodity is marked as a commodity to be confirmed as a surplus commodity; when the commodity difference value is greater than or less than the commodity difference threshold, issue an early warning and notify the management personnel to promptly confirm and handle the abnormal situation; and generate a detailed difference report based on the abnormal data of the marked commodity and send it to the database for storage; S3: Compare and analyze the commodity environmental data with the standard environmental data to obtain a storage evaluation value, and send it to the database for storage; S4: Identify and classify the marked goods and assign management personnel to confirm and process them.

[0005] As a preferred embodiment of the present invention, the basic information of the commodity includes: commodity type, batch number, quantity, storage time, production date and shelf life.

[0006] As a preferred embodiment of the present invention, the specific analysis steps for storing the evaluation value are: Get the best storage temperature range for the product, set the middle value of the temperature range as the standard temperature value, and record it as Bij; get the best storage humidity range for the product, set the middle value of the humidity range as the standard humidity value, and record it as Zij; get the current temperature value and current humidity value of the product and record them as Wij and Dij respectively; substitute the values ​​of the standard temperature value Bij, the standard humidity value Zij, the current temperature value Wij and the current humidity value Dij into the formula The environmental adaptation value Vij is calculated, where a3 and a4 are the set weight factors, and e is a natural constant. The collection frequency of environmental monitoring data is once every 12 hours, and the cycle of data samples is one week. The specific collection frequency and sample cycle can be set by the enterprise according to the characteristics of the product.

[0007] Set an environmental adaptation value threshold interval, compare and analyze the environmental adaptation values ​​collected within a week with the set environmental adaptation value threshold interval. When the environmental adaptation value is greater than the maximum value in the set environmental adaptation value threshold interval, it means that the product is in the best storage environment at this time, and the first-level storage environment is accumulated once; when the environmental adaptation value is within the set environmental adaptation value threshold interval, the second-level storage environment is accumulated once; when the environmental adaptation value is less than the minimum value of the set environmental adaptation value threshold interval, the third-level storage environment is accumulated once; count the cumulative times of the first-level storage environment, the second-level storage environment and the third-level storage environment respectively, and record them as C1, C2 and C3 respectively; sum up the environmental adaptation values ​​corresponding to the first-level storage environment, the second-level storage environment and the third-level storage environment to obtain the first-level environment value, the second-level environment value and the third-level environment value, and record them as C4, C5 and C6 respectively; substitute the values ​​of the total number of the first-level storage environment C1, the total number of the second-level storage environment C2, the total number of the third-level storage environment C3, the first-level environment value C4, the second-level environment value C5 and the third-level environment value C6 into the formula The storage evaluation value Gij is calculated, where a5, a6 and a7 are respectively set weight factors, and a5>a6>a7>0; A storage evaluation threshold interval is set, and the storage evaluation value is compared with the set storage evaluation threshold interval for analysis. When the storage evaluation value of a commodity is greater than the maximum value of the set storage evaluation threshold interval, it indicates that the storage environment of the commodity is relatively stable, and the commodity is marked as the best storage commodity; when the storage evaluation value of a commodity is within the set storage evaluation threshold interval, it indicates that the storage environment of the commodity has changed significantly, and the commodity is marked as a commodity with an abnormal environment to be confirmed; when the storage evaluation value of a commodity is less than the minimum value of the set storage evaluation threshold interval, it indicates that the storage environment of the commodity is relatively poor, and the commodity is marked as a commodity with an abnormal environment to be confirmed first; and based on the abnormal data of the marked commodity, a detailed difference report is generated and sent to the database for storage.

[0008] As a preferred embodiment of the present invention, the specific steps of identifying and classifying the marked goods are: Compare and analyze the data read by RFID with the inventory records in the database to identify the marked goods; obtain the marked goods that are in short supply and about to expire from the database, arrange them by value from small to large, and classify them as Q1; arrange the goods that are in excess to be confirmed by value from large to small, and classify them as Q2; arrange the goods that are in environmental abnormalities to be confirmed by value from small to large, and classify them as Q3; arrange the goods that are in environmental abnormalities that are given priority by value from small to large, classify them as Q4, and wait for the management personnel to confirm and process them.

[0009] As a preferred implementation of the present invention, the specific steps of assigning management personnel to confirm and process are: Get the current position of the manager, take the ground center point of the product area j with the product difference value as the center, and then draw a circle with a preset radius to get the matching area; mark the manager whose current position is in the matching area as the preliminary matching person; get the current position of the preliminary matching person and the position of the product area to calculate the distance difference to get the matching distance and record it as K1; get the personnel information of the preliminary matching person, where the personnel information includes the name, mobile phone number, employment time and age of the manager; calculate the time difference between the employment time of the preliminary matching person and the current time of the system to get the employment time of the preliminary matching person and record it as K2; record the age of the preliminary matching person as K3; substitute the values ​​of the matching distance K1, employment time K2, age K3 and priority value K4 of the preliminary matching person into the formula The allocation value Kij of the preliminary matching personnel is calculated, where b1, b2, b3 and b4 are the set weight factors respectively, and e is represented as a natural constant; the manager with the largest allocation value matched according to the commodity difference category is the final matching personnel, and the commodity information is sent to the mobile terminal of the assigned final matching personnel.

[0010] As a preferred embodiment of the present invention, the specific analysis steps of the priority values ​​of the preliminary matching personnel are as follows: When the final matching personnel receives the warning signal and the marked product information, they arrive at the product area for processing and mark the area as a processed product difference area. After the final matching personnel completes the processing of the product difference area, they send a processing completion signal to the database; the timing starts after the final matching personnel receives the warning signal, and ends after sending the processing completion signal. The time difference between the end time and the start time is calculated to obtain the processing time; the total number of processing times of the final matching personnel is obtained and recorded as K5, all the processing times of the final matching personnel are summed up and the average is calculated to obtain the average processing time of the final matching personnel and recorded as K6; the values ​​of the total number of processing times K5 and the average processing time K6 of the final matching personnel are substituted into the formula Calculate the priority value of the final matching person.

[0011] As a preferred embodiment of the present invention, the specific steps of the allocation rules of Q1, Q2, Q3 and Q4 after the commodities are classified are as follows: After calculating the final matching person with the largest allocation value, assign Q4 product information to the final matching person, and add this final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q3 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q2 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q1 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; when the final matching person sends a processing completion signal to the database, re-add the preliminary matching person for allocation until the products with product difference values ​​are processed.

[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. Through automatic scanning of RFID readers and dividing the warehouse into several areas, the actual inventory status of goods in the warehouse can be obtained quickly and accurately, reducing the time and error of manual inventory counting; by calculating the remaining validity period of the goods, it can effectively monitor the goods that are about to expire, reduce the risk of loss, and optimize inventory turnover; by setting the threshold of commodity difference and comparing them, early warnings can be issued in time to notify management personnel to deal with abnormal situations and improve the response speed of inventory management; through precise inventory management and effective early warnings, inventory backlogs and out-of-stock phenomena can be reduced, which not only improves the efficiency and accuracy of inventory management, but also helps enterprises achieve higher operating levels and economic benefits, thereby reducing operating costs and improving profitability.

[0013] 2. By integrating environmental monitoring sensors, the temperature and humidity of goods can be obtained in real time, and environmental changes can be detected in time, which helps to keep goods in optimal storage conditions. When an abnormality is detected, the system can immediately issue an early warning to notify management personnel and take prompt measures to reduce the risk of product loss. Through continuous monitoring of the storage environment, it can effectively reduce damage or expiration of goods caused by improper storage, and improve the safety and quality of goods. Automated monitoring and early warning reduce the frequency of manual inspections, ensure product quality and safety, and improve overall management efficiency.

[0014] 3. By classifying and sorting goods by difference category, managers can give priority to the most urgent and important goods issues, thereby improving overall processing efficiency; matching is based on information such as the manager's current position, length of service and age, ensuring that the right managers are assigned to the right tasks and optimizing the use of human resources; real-time receipt of product difference information and automatic allocation can respond quickly to potential problems and reduce product losses and impacts; by recording the number of times and time managers handle the process, quantitative performance data is provided to help companies evaluate and optimize personnel performance; each product difference processing process is clearly recorded, and managers can check the processing progress at any time to ensure transparency and traceability, improve the level and efficiency of warehouse management, ensure the quality and safety of goods, and provide strong data support for management decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0016] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0017] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0018] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0019] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so as to describe the embodiments of the present invention described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0020] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0021] According to an embodiment of the present invention, Figure 1 As shown, a smart warehouse inventory method based on RFID is provided, comprising the following steps: S1: Obtain basic information of goods in warehouse RFID tags, collect tag data and send it to the database for storage in real time; the basic information of goods includes: product type, batch number, quantity, storage time, production date and shelf life; it should be noted that in order to ensure the quality of the label and the location of the label is easy for the RFID reader to read, especially on metal goods or sealed packaging, special RFID tags should be used; S2: Compare the data read by RFID with the inventory records to identify the difference value, and send the commodity difference value to the database for storage; the specific steps are: At the beginning of the inventory, the warehouse is divided into several areas according to its size and recorded as j, where j=1, 2, 3...J, J is a positive integer, J represents the total number of warehouse areas, and j represents the serial number of any area in the warehouse; use the RFID reader to scan all areas of the entire warehouse, the reader will automatically read the RFID tag information passed by, and transmit the data to the server for storage in real time; the type of goods obtained by the RFID reader in the RFID tag is recorded as i, where i=1, 2, 3...I, I is a positive integer, I represents the total number of goods, i represents the type of any one of them, and each type of goods has a specific storage area; obtain the collected inventory quantity of goods and record it as Lij; obtain the production date and shelf life of the goods, as well as the storage time of the goods, and calculate the difference between them to obtain the remaining validity period of the goods, and record it as Qij; obtain the expected inventory quantity of the goods and record it as Yij; set the optimal remaining validity period of the expected goods and record it as Xij; Substitute the values ​​of product inventory quantity Lij, expected product inventory quantity Yij, product remaining validity period Qij, and expected product optimal remaining validity period Xij into the set formula The product difference value Pij is calculated, where a1 and a2 are respectively the set weight factors, and e is represented as a natural constant. It can be obtained from the formula that when the inventory quantity of the product is less than the expected inventory quantity of the product, the inventory difference value of the product is smaller; when the inventory quantity of the product is greater than the expected inventory quantity of the product, the inventory difference value of the product is larger; when the remaining validity period of the product is less than the expected optimal remaining validity period of the product, the inventory difference value of the product is smaller; when the remaining validity period of the product is greater than the expected optimal remaining validity period of the product, the inventory difference value of the product is larger; A commodity difference threshold is set, and the commodity difference value is compared and analyzed with the commodity difference threshold. When the commodity difference value is less than the set commodity difference threshold, it means that the commodity inventory quantity and the remaining validity period of the commodity are smaller than the expected commodity inventory quantity and the expected best remaining validity period of the commodity, and the commodity is marked as a commodity to be confirmed as a commodity with insufficient inventory and expiring; when the commodity difference value is equal to the set commodity difference threshold, it means that the commodity inventory quantity and the remaining validity period of the commodity are no different from the expected commodity inventory quantity and the expected best remaining validity period of the commodity; when the commodity difference value is greater than the set commodity difference threshold, it means that the commodity inventory quantity and the remaining validity period of the commodity are larger than the expected commodity inventory quantity and the expected best remaining validity period of the commodity, and the commodity is marked as a commodity to be confirmed as a surplus commodity; when the commodity difference value is greater than or less than the commodity difference threshold, an early warning is issued and the management personnel are notified to confirm and handle the abnormal situation in time; and based on the abnormal data of the marked commodity, a detailed difference report is generated and sent to the database for storage, wherein the difference report includes the difference quantity, commodity information, status description and the remaining validity period of the commodity; Through automatic scanning of RFID readers and dividing the warehouse into several areas, the actual inventory status of goods in the warehouse can be obtained quickly and accurately, reducing the time and error of manual inventory counting; by calculating the remaining validity period of goods, it can effectively monitor goods that are about to expire, reduce the risk of loss, and optimize inventory turnover; by setting and comparing commodity difference thresholds, early warnings can be issued in time to notify management personnel to deal with abnormal situations and improve the response speed of inventory management; through precise inventory management and effective early warnings, inventory backlogs and out-of-stock phenomena can be reduced, which not only improves the efficiency and accuracy of inventory management, but also helps enterprises achieve higher operating levels and economic benefits, thereby reducing operating costs and improving profitability; S3: Compare and analyze the commodity environmental data with the standard environmental data to obtain a storage evaluation value, and send it to the database for storage; the specific steps are as follows: RFID tags can be integrated with environmental monitoring sensors, such as vibration sensors, temperature sensors or humidity sensors. When the vibration sensor detects that the product is vibrating, it directly issues an early warning and notifies the management personnel to deal with the abnormal situation in time; obtain the best storage temperature range for product i, set the middle value of the temperature range as the standard temperature value, and record it as Bij; obtain the best storage humidity range for product i, set the middle value of the humidity range as the standard humidity value, and record it as Zij; obtain the current temperature value of product i and record it as Wij; obtain the current humidity value of product i and record it as Dij; substitute the values ​​of the standard temperature value Bij, the standard humidity value Zij, the current temperature value Wij and the current humidity value Dij into the set formula The environmental adaptability value Vij is calculated, where a3 and a4 are the set weight factors, and e is a natural constant. It can be seen from the formula that the closer the temperature of the product is to the standard temperature, the greater the environmental adaptability value; the closer the humidity of the product is to the standard humidity, the greater the environmental adaptability value. It should be noted that the greater the environmental adaptability value, the closer the current temperature and humidity values ​​of the product are to the optimal storage conditions of the product. It should be noted that the collection frequency of the above environmental monitoring data is once every 12 hours, and the cycle of the data sample is one week. The specific collection frequency and sample cycle can be set by the enterprise according to the characteristics of the product. Set an environmental adaptation value threshold interval, compare and analyze the environmental adaptation values ​​collected within a week with the set environmental adaptation value threshold interval, when the environmental adaptation value is greater than the maximum value in the set environmental adaptation value threshold interval, it means that the product is in the best storage environment at this time, and the first-level storage environment is accumulated once; when the environmental adaptation value is within the set environmental adaptation value threshold interval, the second-level storage environment is accumulated once; when the environmental adaptation value is less than the minimum value of the set environmental adaptation value threshold interval, the third-level storage environment is accumulated once; count the cumulative times of the first-level storage environment, the second-level storage environment and the third-level storage environment respectively, and record them as C1, C2 and C3 respectively; sum up the environmental adaptation values ​​corresponding to the first-level storage environment, the second-level storage environment and the third-level storage environment to obtain the first-level environment value, the second-level environment value and the third-level environment value, and record them as C4, C5 and C6 respectively; substitute the values ​​of the total number of the first-level storage environment C1, the total number of the second-level storage environment C2, the total number of the third-level storage environment C3, the first-level environment value C4, the second-level environment value C5 and the third-level environment value C6 into the set formula Calculate and obtain the stored evaluation value Gij, where a5, a6 and a7 are respectively set weight factors, and a5>a6>a7>0; A storage evaluation threshold interval is set, and the storage evaluation value is compared and analyzed with the set storage evaluation threshold interval. When the storage evaluation value of the commodity is greater than the maximum value of the set storage evaluation threshold interval, it means that the storage environment of the commodity is relatively stable, and the commodity is marked as the best storage commodity; when the storage evaluation value of the commodity is within the set storage evaluation threshold interval, it means that the storage environment of the commodity has changed greatly, and the commodity is marked as a commodity with abnormal environment to be confirmed; when the storage evaluation value of the commodity is less than the minimum value of the set storage evaluation threshold interval, it means that the storage environment of the commodity is relatively bad, and the commodity is marked as a commodity with abnormal environment to be confirmed first; and based on the abnormal data of the marked commodity, a detailed difference report is generated and sent to the database for storage, wherein the difference report includes the difference quantity, commodity information, status description and the remaining validity period of the commodity; By integrating environmental monitoring sensors, the temperature and humidity of goods can be obtained in real time, and environmental changes can be detected in time, which helps to keep goods in optimal storage conditions. When abnormalities are detected, the system can immediately issue an early warning to notify management personnel and take prompt measures to reduce the risk of product loss. Through continuous monitoring of the storage environment, it can effectively reduce damage or expiration of goods caused by improper storage, and improve the safety and quality of goods. Automated monitoring and early warning reduce the frequency of manual inspections, ensure product quality and safety, and improve overall management efficiency. S4: Identify and classify the marked goods and assign management personnel to confirm and process them; the specific steps are as follows: Compare and analyze the data read by RFID with the inventory records in the database to identify the marked goods; obtain the marked goods to be confirmed that are in short supply and about to expire from the database, arrange them by value from small to large, and classify them as Q1, waiting for the management personnel to confirm and process; arrange the goods to be confirmed that are in excess by value from large to small, and classify them as Q2, waiting for the management personnel to confirm and process; arrange the goods to be confirmed that are in abnormal environment by value from small to large, and classify them as Q3, waiting for the management personnel to confirm and process; arrange the goods to be confirmed that are in abnormal environment by value from small to large, and classify them as Q4, waiting for the management personnel to confirm and process; Get the current position of the manager, take the ground center point of the product area j where the product difference value exists as the center, and then draw a circle with a preset radius to get the matching area; mark the manager whose current position is in the matching area as the preliminary matching person; get the current position of the preliminary matching person and the position of the product area j to calculate the distance difference to get the matching distance and record it as K1; get the personnel information of the preliminary matching person, where the personnel information includes the name, mobile phone number, employment time and age of the manager; calculate the time difference between the employment time of the preliminary matching person and the current time of the system to get the employment time of the preliminary matching person and record it as K2; record the age of the preliminary matching person as K3; substitute the values ​​of the matching distance K1, employment time K2 and age K3 of the preliminary matching person into the set formula The allocation value Kij of the preliminary matching personnel is calculated, where b1, b2, b3 and b4 are respectively set weight factors, whose sizes are custom values, e is represented by a natural constant, and K4 is the priority value of the preliminary matching personnel; the manager with the largest allocation value Kij matched according to the commodity difference category is the final matching personnel, and the commodity information is sent to the mobile terminal of the assigned final matching personnel; the specific analysis steps of the priority value K4 of the preliminary matching personnel are as follows: When the final matching personnel receives the warning signal and the marked product information, they arrive at the product area for processing and mark the area as a processed product difference area. After the final matching personnel completes the processing of the product difference area, they send a processing completion signal to the database; the timing starts after the final matching personnel receives the warning signal, and ends after sending the processing completion signal. The time difference between the end time and the start time is calculated to obtain the processing time; the total number of processing times of the final matching personnel is obtained and recorded as K5, and all the processing times of the final matching personnel are summed and averaged to obtain the average processing time of the final matching personnel and recorded as K6; the values ​​of the total number of processing times K5 and the average processing time K6 of the final matching personnel are substituted into the set formula The priority value K4 of the final matching person is calculated, where b5 and b6 are the set weight factors respectively; The specific steps of the allocation rules for Q1, Q2, Q3 and Q4 after the goods are classified are as follows: After calculating the final matching person with the largest allocation value, assign Q4 product information to the final matching person, and add this final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q3 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q2 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q1 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; when the final matching person sends a processing completion signal to the database, re-add the preliminary matching person for allocation until the products with product difference values ​​are processed; By classifying and sorting goods by difference category, managers can give priority to the most urgent and important goods issues, thereby improving overall processing efficiency; matching is based on information such as the manager's current position, length of service and age, ensuring that the right manager is assigned to the right task and optimizing the use of human resources; real-time receipt of product difference information and automatic allocation can respond quickly to potential problems and reduce product losses and impacts; by recording the number of times and processing time handled by managers, quantitative performance data is provided to help companies evaluate and optimize personnel performance; the processing process of each product difference is clearly recorded, and managers can check the processing progress at any time to ensure transparency and traceability, improve the level and efficiency of warehouse management, ensure the quality and safety of goods, and provide strong data support for management decisions.

[0022] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0023] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent warehouse inventory method based on RFID, characterized in that: The following steps are involved: S1: Obtain basic information of goods in warehouse RFID tags, collect tag data and send it to the database for storage in real time; S2: Compare the data read by RFID with the inventory records to identify the difference value, and send the commodity difference value to the database for storage; the specific steps are: The values ​​of the commodity inventory quantity, the expected commodity inventory quantity, the commodity remaining validity period and the expected optimal remaining validity period of the commodity are obtained and normalized to obtain the commodity difference value; a commodity difference threshold is set, and the commodity difference value is compared and analyzed with the commodity difference threshold. When the commodity difference value is less than the set commodity difference threshold, it means that the commodity inventory quantity and the commodity remaining validity period are smaller than the expected commodity inventory quantity and the expected optimal remaining validity period of the commodity, and the commodity is marked as a commodity to be confirmed as a commodity close to expiration due to insufficient inventory; when the commodity difference value is equal to the set commodity difference threshold, it means that the commodity inventory quantity and the commodity remaining validity period are no different from the expected commodity inventory quantity and the expected optimal remaining validity period of the commodity; when the commodity difference value is greater than the set commodity difference threshold, it means that the commodity inventory quantity and the commodity remaining validity period are larger than the expected commodity inventory quantity and the expected optimal remaining validity period of the commodity, and the commodity is marked as a commodity to be confirmed as a surplus commodity; when the commodity difference value is greater than or less than the commodity difference threshold, an early warning is issued and the management personnel are notified to confirm and handle the abnormal situation in a timely manner; and a detailed difference report is generated based on the abnormal data of the marked commodities; S3: Obtain storage assessment value based on commodity environmental data and comparison analysis with standard environmental data; S4: Identify and classify the marked goods and assign management personnel to confirm and process them.

2. The RFID-based intelligent warehouse inventory method according to claim 1, characterized in that: The basic information of the goods includes: product type, batch number, quantity, warehousing time, production date and shelf life; the specific process of obtaining the numerical values ​​of the product inventory quantity, expected product inventory quantity, remaining validity period of the product and the expected optimal remaining validity period of the product is as follows: at the beginning of the inventory, the warehouse is divided into several areas according to the warehouse size; the RFID reader is used to scan all areas of the entire warehouse, and the reader will automatically read the RFID tag information passing through, and transmit the data to the server for storage in real time; the RFID reader is used to obtain the product type in the RFID tag; obtain the collected product inventory quantity; obtain the product's production date and shelf life, as well as the product's warehousing time, and calculate the difference between them to obtain the product's remaining validity period; obtain the expected inventory quantity of the product; set the expected optimal remaining validity period of the product.

3. The RFID-based intelligent warehouse inventory counting method according to claim 1 is characterized in that: The specific analysis steps for storing the evaluation value are: Obtain the optimal storage temperature range of the product, and set the middle value of the temperature range as the standard temperature value; obtain the optimal storage humidity range of the product, and set the middle value of the humidity range as the standard humidity value; obtain the current temperature value and current humidity value of the product; normalize the standard temperature value, standard humidity value, current temperature value and current humidity value to obtain the environmental adaptation value; Set an environmental adaptation value threshold interval, compare and analyze the environmental adaptation values ​​collected within a week with the set environmental adaptation value threshold interval. When the environmental adaptation value is greater than the maximum value in the set environmental adaptation value threshold interval, it means that the product is in the best storage environment at this time, and the first-level storage environment is accumulated once; when the environmental adaptation value is within the set environmental adaptation value threshold interval, the second-level storage environment is accumulated once; when the environmental adaptation value is less than the minimum value of the set environmental adaptation value threshold interval, the third-level storage environment is accumulated once; The cumulative number of the first-level storage environment, the second-level storage environment, and the third-level storage environment are counted respectively; the environmental adaptability values ​​corresponding to the first-level storage environment, the second-level storage environment, and the third-level storage environment are summed up to obtain the first-level environment value, the second-level environment value, and the third-level environment value; the total number of the first-level storage environment, the total number of the second-level storage environment, the total number of the third-level storage environment, the first-level environment value, the second-level environment value, and the third-level environment value are normalized to obtain the storage assessment value; A storage evaluation threshold interval is set, and the storage evaluation value is compared with the set storage evaluation threshold interval for analysis. When the storage evaluation value of a commodity is greater than the maximum value of the set storage evaluation threshold interval, it indicates that the storage environment of the commodity is relatively stable, and the commodity is marked as the best storage commodity; when the storage evaluation value of a commodity is within the set storage evaluation threshold interval, it indicates that the storage environment of the commodity has changed significantly, and the commodity is marked as a commodity with an abnormal environment to be confirmed; when the storage evaluation value of a commodity is less than the minimum value of the set storage evaluation threshold interval, it indicates that the storage environment of the commodity is relatively poor, and the commodity is marked as a commodity with an abnormal environment to be confirmed first; and based on the abnormal data of the marked commodity, a detailed difference report is generated and sent to the database for storage.

4. The RFID-based intelligent warehouse inventory method according to claim 1, characterized in that: The specific steps to identify and classify the marked goods are: Compare and analyze the data read by RFID with the inventory records in the database to identify the marked goods; obtain the marked goods that are in short supply and about to expire from the database, arrange them by value from small to large, and classify them as Q1; arrange the goods that are in excess to be confirmed by value from large to small, and classify them as Q2; arrange the goods that are in environmental abnormalities to be confirmed by value from small to large, and classify them as Q3; arrange the goods that are in environmental abnormalities that are given priority by value from small to large, classify them as Q4, and wait for the management personnel to confirm and process them.

5. The RFID-based intelligent warehouse inventory counting method according to claim 1, characterized in that: The specific steps for assigning management personnel to confirm and process are: Get the current position of the manager, take the ground center point of the product area j with product difference value as the center, and then draw a circle with a preset radius to get the matching area; mark the manager whose current position is in the matching area as the preliminary matching person; get the current position of the preliminary matching person and the position of the product area to calculate the distance difference to get the matching distance; get the personnel information of the preliminary matching person, where the personnel information includes the name, mobile phone number, employment time and age of the manager; calculate the time difference between the employment time of the preliminary matching person and the current time of the system to get the employment time of the preliminary matching person; Normalize the matching distance, employment time, age and priority value of the preliminary matching personnel to obtain the allocation value of the preliminary matching personnel; The manager with the largest assigned value according to the commodity difference category is matched as the final matching person, and the commodity information is sent to the assigned final matching person's mobile terminal.

6. The RFID-based intelligent warehouse inventory counting method according to claim 5, characterized in that: The specific analysis steps for the priority values ​​of preliminary matching personnel are: When the final matching personnel receives the warning signal and the marked product information, they arrive at the product area for processing and mark the area as a processed product difference area. After the final matching personnel completes the processing of the product difference area, they send a processing completion signal to the database; the timing starts after the final matching personnel receives the warning signal and ends after sending the processing completion signal. The time difference between the end time and the start time is calculated to obtain the processing time; Obtain the total number of processing times of the final matching personnel, sum up all processing times of the final matching personnel and calculate the average processing time of the final matching personnel; The total number of processing times and the average processing time of the final matching personnel are normalized to obtain the priority value of the final matching personnel.

7. The RFID-based intelligent warehouse inventory counting method according to claim 4 is characterized in that: The specific steps of the allocation rules for Q1, Q2, Q3 and Q4 after the goods are classified are as follows: After calculating the final matching person with the largest allocation value, assign Q4 product information to the final matching person, and add this final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q3 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q2 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; recalculate the final matching person with the largest allocation value and assign Q1 product information to the current final matching person, and add this current final assigned person to the sequence of product differences being processed; when the final matching person sends a processing completion signal to the database, re-add the preliminary matching person for allocation until the products with product difference values ​​are processed.

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