A daily commodities warehouse intelligent sorting and inventory dynamic management method

Abstract

The application discloses a kind of daily necessities warehouse intelligent sorting and inventory dynamic management method, including warehousing information acquisition step, commodity coding and file establishment step, dynamic allocation step of location, order receiving and batch processing step, sorting path planning step, sorting execution and inventory real-time deduction step, dynamic inventory and inventory early warning step.The application is integrated by warehousing file establishment, dynamic allocation of location, order batch, intelligent sorting path planning, sorting execution and inventory real-time deduction, and dynamic inventory and early warning, and forms closed-loop management scheme covering the whole process of warehouse operation.Overall, the application has significant beneficial effects in improving sorting efficiency, improving inventory accuracy, reducing operating costs and the like.

Description

Technical Field

[0001] This invention relates to the field of warehousing and logistics management technology, specifically to a method for intelligent sorting and dynamic inventory management of daily necessities. Background Technology

[0002] With the rapid development of e-commerce and the retail industry, the warehousing management of daily necessities faces significant challenges, including a wide variety of products, large differences in specifications and sizes, highly fragmented orders, and frequent inventory turnover. In traditional warehousing management models, sorting operations mainly rely on manual picking of orders one by one, resulting in low efficiency, high error rates, and difficulty in flexibly allocating manpower as order volumes fluctuate. Regarding inventory management, existing warehouse management systems typically update inventory data through periodic stocktaking, which is time-consuming, data-lagging, and unable to reflect real-time dynamic changes in inventory, leading to frequent stockouts or overstocking.

[0003] In recent years, some warehousing companies have introduced automated sorting equipment and warehouse management systems. However, the sorting and inventory management processes often operate independently, lacking effective data linkage and collaborative optimization mechanisms. Sorting decisions fail to fully utilize real-time inventory status information, and inventory updates lag behind the actual completion of sorting operations. Furthermore, daily necessities exhibit significant seasonal sales characteristics and shelf-life sensitivity. Existing methods lack targeted solutions for dynamic warehouse location adjustments and inventory early warnings, making it difficult to achieve efficient allocation and precise management of warehousing resources. Summary of the Invention

[0004] To address this, the present invention provides a method for intelligent sorting and dynamic inventory management in the warehousing of daily necessities, thereby solving the problem that existing technologies lack targeted processing methods for dynamic adjustment of storage locations and inventory early warning, making it difficult to achieve efficient allocation and precise management of warehousing resources.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for intelligent sorting and dynamic inventory management in the warehousing of daily necessities includes the following steps:

[0007] Inbound information collection steps: Obtain the product attribute information of the daily necessities to be inbound, including product name, product specifications, product weight, product volume, production batch number and expiration date;

[0008] Product coding and file creation steps: Assign a unique identification code to each product to be put into the warehouse, bind and store the unique identification code with the product attribute information, and create an electronic file for the product;

[0009] The dynamic allocation steps for warehouse locations are as follows: Obtain the warehouse location attribute information of each available warehouse location, including warehouse location number, warehouse location coordinates, warehouse location load limit and warehouse location volume; Calculate the matching score of each available warehouse location based on the matching degree between the product attribute information and the warehouse location attribute information, allocate the products to be put into the warehouse to the available warehouse location with the highest matching score, and update the occupancy status of the warehouse location.

[0010] Order receiving and batch processing steps: Receive multiple customer orders from the sales terminal. Each customer order contains at least one order detail item, and each order detail item includes the product name and the required quantity. Classify and merge all customer orders according to the product name in the order detail item, and group order detail items containing the same product name into the same picking batch to generate at least one picking batch.

[0011] Sorting route planning steps: For each picking batch, obtain the location coordinates of the storage locations corresponding to each product in the picking batch; calculate the shortest walking path from the sorting starting point to traverse all target storage locations in the picking batch and return to the sorting endpoint based on the location coordinates, and use this path as the sorting path for the picking batch.

[0012] Sorting execution and real-time inventory deduction steps: Arrive at each target storage location in sequence according to the sorting path, and retrieve the corresponding goods and required quantities from each target storage location; After completing the retrieval operation of each target storage location, immediately subtract the retrieved quantity from the inventory quantity of the corresponding goods in that target storage location, and record the inventory deduction timestamp.

[0013] Dynamic inventory counting and inventory warning steps: Scan and count the actual inventory of each storage location in the warehouse according to the preset inventory counting cycle, compare the actual inventory quantity with the inventory quantity recorded in the system, and calculate the inventory deviation; when the absolute value of the inventory deviation exceeds the preset deviation threshold, an inventory count anomaly report is generated; when the system-recorded inventory quantity of any product is lower than the preset safety stock threshold, a replenishment suggestion is generated.

[0014] Preferably, in the dynamic allocation step of storage locations, the formula for calculating the adaptation score is:

[0015] The matching score is calculated as follows: (volume matching coefficient × first weight) + (load-bearing matching coefficient × second weight) + (heat matching coefficient × third weight).

[0016] Among them, the volume matching coefficient is determined based on the ratio of the commodity volume to the storage space volume, the load-bearing matching coefficient is determined based on the ratio of the commodity weight to the storage space load-bearing limit, and the heat matching coefficient is determined based on the commodity's historical outbound frequency; the first weight, the second weight, and the third weight are preset weight coefficients, and the sum of the three is equal to 1.

[0017] Preferably, in the order receiving and batch processing step, before classifying and merging all customer orders according to the product names in the order details, an order priority sorting operation is also performed: obtaining the order placement timestamp and delivery time requirements of each customer order, calculating the comprehensive priority score of each customer order based on the order of the order placement timestamps and the urgency of the delivery time requirements, and sorting the customer orders in descending order of comprehensive priority scores.

[0018] Preferably, in the sorting path planning step, the shortest walking path is determined in the following way: obtaining the starting coordinates of the sorting starting point and the ending coordinates of the sorting ending point; for N target storage locations in the picking batch, calculating the walking distance from the current coordinate position to the coordinates of the next target storage location in sequence, where N is a positive integer; using a dynamic adjustment strategy to determine the access order of the target storage locations, so that the total walking distance from the sorting starting point through all target storage locations in sequence to the sorting ending point is minimized; wherein, the initial value of the current coordinate position is the starting coordinate, and after determining the access order of each target storage location, the coordinates of the target storage location are updated to the current coordinate position, until all N target storage locations have been accessed.

[0019] Preferably, in the sorting execution and real-time inventory deduction steps, after each retrieval operation of a target storage location is completed, the following operations are also performed: obtain the first inventory quantity of the target storage location before the retrieval operation, obtain the retrieval quantity taken out during the retrieval operation, subtract the retrieval quantity from the first inventory quantity to obtain the second inventory quantity; write the second inventory quantity into the system inventory record, and generate an inventory deduction log containing the storage location number, product name, retrieval quantity, and inventory deduction timestamp; and synchronously upload the inventory deduction log to the cloud server for backup storage.

[0020] Preferably, in the sorting execution and real-time inventory deduction steps, when the goods retrieved from the target storage location are expiration-sensitive goods, an expiration verification operation is performed before the retrieval operation: the expiration information of each goods stored in the target storage location is read, the goods in the target storage location are sorted according to the expiration date, and the goods with the closest expiration date are retrieved first; if the expiration date of a certain goods in the target storage location is less than the preset expiration date warning days from the current date, an expiration date warning information is generated and the outbound operation of the goods is suspended until a confirmation release instruction is received.

[0021] Preferably, in the dynamic inventory counting and inventory early warning step, the preset inventory counting cycle is dynamically adjusted according to the historical outbound frequency of the goods: the daily outbound frequency of each goods in the past preset time period is obtained, and the goods are divided into a first frequency level, a second frequency level, and a third frequency level according to the daily outbound frequency from high to low; the first frequency level goods use the first inventory counting cycle, the second frequency level goods use the second inventory counting cycle, and the third frequency level goods use the third inventory counting cycle; the first inventory counting cycle is shorter than the second inventory counting cycle, and the second inventory counting cycle is shorter than the third inventory counting cycle.

[0022] Preferably, in the dynamic inventory count and inventory warning step, the specific method for generating replenishment suggestions is as follows: obtain the product name, current inventory quantity, and preset safety stock threshold of the products whose inventory is lower than the preset safety stock threshold; calculate the replenishment suggestion quantity, which is equal to the preset safety stock threshold minus the current inventory quantity multiplied by a preset replenishment coefficient, the preset replenishment coefficient being in the range of 1.2 to 1.8; generate a replenishment task order based on the replenishment suggestion quantity, the replenishment task order including the product name, the replenishment suggestion quantity, and the suggested replenishment location.

[0023] Preferably, in the dynamic inventory counting and inventory early warning steps, after generating the inventory count anomaly report, anomaly handling operations are also performed: obtaining the abnormal storage location number and abnormal product name involved in the inventory count anomaly report; re-counting the abnormal storage location, and comparing the re-counted inventory quantity with the system-recorded inventory quantity a second time; if the absolute value of the inventory deviation after the second comparison is still greater than the preset deviation threshold, then the abnormal storage location is marked as pending verification, and a verification task sheet containing the abnormal storage location number, abnormal product name, system-recorded inventory quantity, actual inventory quantity, and inventory deviation is generated, and the verification task sheet is sent to the management terminal.

[0024] This invention offers the following advantages: By organically integrating processes such as inbound record keeping, dynamic allocation of storage locations, order batching, intelligent sorting path planning, sorting execution and real-time inventory deduction, as well as dynamic inventory counting and early warning, it forms a closed-loop management solution covering the entire warehousing operation process. During the inbound stage, dynamic allocation of storage locations based on product attributes and historical sales volume improves the storage and retrieval efficiency of high-turnover goods; order batching reduces the reciprocating stroke of sorting equipment by merging similar orders, effectively increasing sorting throughput; sorting path planning employs a dynamic optimization strategy driven by real-time inventory data, significantly shortening the average picking path length; inventory data updates are triggered immediately after sorting, eliminating the drawbacks of inventory lag in traditional models; the dynamic inventory counting and early warning mechanism can promptly detect inventory deviations and trigger replenishment or transfer suggestions, effectively reducing stockout rates and expired loss rates. Overall, this invention has significant beneficial effects in improving sorting efficiency, increasing inventory accuracy, and reducing operating costs. Attached Figure Description

[0025] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0026] Figure 1 A flowchart illustrating a method for intelligent sorting and dynamic inventory management in the warehousing of daily necessities, provided as an embodiment of this application. Detailed Implementation

[0027] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these embodiments are merely for further explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. Technical engineers in the field can make some non-essential improvements and adjustments to the present invention based on the above-described content. 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.

[0028] Please see Figure 1 A method for intelligent sorting and dynamic inventory management in the warehousing of daily necessities includes the following steps:

[0029] Inbound information collection steps: Obtain the product attribute information of the daily necessities to be inbound, including product name, product specifications, product weight, product volume, production batch number and expiration date;

[0030] Product coding and file creation steps: Assign a unique identification code to each product to be put into the warehouse, bind and store the unique identification code with the product attribute information, and create an electronic file for the product;

[0031] The dynamic allocation steps for warehouse locations are as follows: Obtain the warehouse location attribute information of each available warehouse location, including warehouse location number, warehouse location coordinates, warehouse location load limit and warehouse location volume; Calculate the matching score of each available warehouse location based on the matching degree between the product attribute information and the warehouse location attribute information, allocate the products to be put into the warehouse to the available warehouse location with the highest matching score, and update the occupancy status of the warehouse location.

[0032] Order receiving and batch processing steps: Receive multiple customer orders from the sales terminal. Each customer order contains at least one order detail item, and each order detail item includes the product name and the required quantity. Classify and merge all customer orders according to the product name in the order detail item, and group order detail items containing the same product name into the same picking batch to generate at least one picking batch.

[0033] Sorting route planning steps: For each picking batch, obtain the location coordinates of the storage locations corresponding to each product in the picking batch; calculate the shortest walking path from the sorting starting point to traverse all target storage locations in the picking batch and return to the sorting endpoint based on the location coordinates, and use this path as the sorting path for the picking batch.

[0034] Sorting execution and real-time inventory deduction steps: Arrive at each target storage location in sequence according to the sorting path, and retrieve the corresponding goods and required quantities from each target storage location; After completing the retrieval operation of each target storage location, immediately subtract the retrieved quantity from the inventory quantity of the corresponding goods in that target storage location, and record the inventory deduction timestamp.

[0035] Dynamic inventory counting and inventory warning steps: Scan and count the actual inventory of each storage location in the warehouse according to the preset inventory counting cycle, compare the actual inventory quantity with the inventory quantity recorded in the system, and calculate the inventory deviation; when the absolute value of the inventory deviation exceeds the preset deviation threshold, an inventory count anomaly report is generated; when the system-recorded inventory quantity of any product is lower than the preset safety stock threshold, a replenishment suggestion is generated.

[0036] Example:

[0037] I. Steps for collecting inbound information

[0038] In this embodiment, when a batch of daily necessities arrives at the warehouse, the first step is to collect inbound information. The warehouse manager scans the barcodes or RFID tags on the outer packaging of each product using a scanning device (such as a barcode scanner or RFID reader) to obtain the product attribute information. The product attribute information specifically includes the product name (e.g., "500ml shampoo"), product specifications (e.g., "500ml / bottle"), product weight (e.g., "0.6kg"), product volume (e.g., "0.8dm³"), production batch number (e.g., "BATCH20260501"), and expiration date (e.g., "20280501"). For products without pre-installed barcodes or RFID tags, the system automatically generates and prints tags, which are then affixed to the outer packaging.

[0039] II. Commodity Coding and File Creation Steps

[0040] After acquiring product attribute information, the system executes the product coding and file creation steps. Each product to be received is assigned a globally unique identification code, which can be in the form of a QR code or an RFID tag in EPC encoding format. The system binds this unique identification code to the aforementioned collected product attribute information and stores it in the warehouse management system's database, thus creating a complete electronic file for each product. The establishment of electronic files ensures traceability for each product from the moment it enters the warehouse, providing a data foundation for subsequent sorting, outbound, and inventory operations.

[0041] III. Steps for Dynamic Allocation of Storage Locations

[0042] The dynamic allocation of storage locations is one of the key steps in this invention. The system first acquires the storage location attribute information for all available storage locations within the warehouse, including the location number (e.g., "A0305"), location coordinates (e.g., "X=12.5m, Y=8.3m, Z=1.2m"), maximum load capacity (e.g., "200kg"), and storage location volume (e.g., "2.5dm"). 3 Subsequently, the system calculates an adaptation score for each available storage location based on the matching degree between the product attribute information and the storage location attribute information.

[0043] The formula for calculating the fit score is:

[0044] Compatibility score = (volume matching coefficient × α) + (load-bearing matching coefficient × β) + (thermal matching coefficient × γ)

[0045] α, β, and γ are the first weight, second weight, and third weight, respectively, and are preset weight coefficients. The sum of the three is equal to 1.

[0046] The volume matching coefficient is determined based on the ratio of the product volume to the storage location volume: 1.0 when the product volume does not exceed 80% of the storage location volume; 0.6 when the product volume exceeds 80% but does not exceed 100% of the storage location volume; and 0 when the product volume exceeds the storage location volume, indicating that the storage location is unavailable. The load-bearing capacity matching coefficient is determined based on the ratio of the product weight to the storage location's maximum load-bearing capacity: 1.0 when the product weight does not exceed 70% of the storage location's maximum load-bearing capacity; 0.5 when the product weight exceeds 70% but does not exceed 100% of the storage location's maximum load-bearing capacity; and 0 when the product weight exceeds the storage location's maximum load-bearing capacity. The popularity matching coefficient is determined based on the historical outbound frequency of the goods: The number of outbound shipments of goods in the past 30 days is statistically analyzed. The top 20% of goods with the highest outbound frequency are identified as high-popularity goods, with a popularity matching coefficient of 1.0; the middle 60% of goods with the lowest outbound frequency are identified as medium-popularity goods, with a popularity matching coefficient of 0.7; and the bottom 20% of goods with the lowest outbound frequency are identified as low-popularity goods, with a popularity matching coefficient of 0.4. α, β, and γ are preset weighting coefficients. In this embodiment, α is 0.3, β is 0.2, and γ is 0.5, with a sum of 1. After calculating the adaptation score for each available storage location, the system assigns the goods to be received to the available storage location with the highest adaptation score and updates the occupancy status of that location to "occupied".

[0047] IV. Order Receiving and Batch Processing Steps

[0048] The system receives multiple customer orders in real time from sales terminals such as e-commerce platforms and in-store POS systems. Each customer order contains at least one order detail item, which includes the product name (e.g., "500ml shampoo") and the quantity requested (e.g., "2 bottles"). Before processing orders in batches, the system first performs an order priority sorting operation: it obtains the order timestamp and delivery time requirement (e.g., "same-day delivery," "next-day delivery," or "standard delivery") for each customer order, and calculates a comprehensive priority score based on the order of the order timestamps and the urgency of the delivery time requirement. Specifically, orders placed earlier receive a higher timeliness score, and orders with more urgent delivery time requirements receive a higher urgency score. The comprehensive priority score is a weighted sum of the timeliness score and the urgency score. The system then sorts and processes customer orders according to their comprehensive priority scores from highest to lowest.

[0049] Subsequently, the system categorizes and merges all customer orders according to the product names in the order details: order details containing the same product name are grouped into the same picking batch. For example, if order A requires 2 bottles of "500ml shampoo" and 1 tube of "toothpaste," and order B requires 3 bottles of "500ml shampoo" and 1 bottle of "laundry detergent," the system will merge the details involving "500ml shampoo" in both orders into one picking batch, which will require picking a total of 5 bottles of "500ml shampoo." Through this categorization and merging method, the system generates at least one picking batch, and each picking batch corresponds to the total demand quantity of one product in all pending orders.

[0050] V. Sorting Path Planning Steps

[0051] For each picking batch, the system first obtains the coordinates of the storage location corresponding to the goods in that picking batch. Specifically, the system queries the electronic file of the goods based on the goods name to determine the target storage location number where the goods are currently stored, and then obtains the corresponding storage location coordinates from the storage location attribute information based on the storage location number. If the same goods in a picking batch may be stored in multiple storage locations, the system determines the target storage location in descending order of inventory quantity, prioritizing the storage location with the largest inventory quantity. If the inventory quantity in that storage location is insufficient to meet the picking batch's demand, subsequent storage locations are replenished sequentially.

[0052] After identifying all target storage locations, the system calculates the shortest path from the sorting starting point, traversing all target storage locations in the picking batch, and returning to the sorting endpoint. Assuming the coordinates of the sorting starting point are positive integers, for N target storage locations in the picking batch (N is a positive integer), the system sequentially calculates the walking distance from the current coordinate position to the coordinates of the next target storage location. The walking distance is calculated using Manhattan distance, which is equal to the sum of the absolute values ​​of the distances between two points along the X-axis and the Y-axis. The system employs a dynamic adjustment strategy to determine the access order of target storage locations: the initial value of the current coordinate position is the starting point coordinate. The system evaluates each unvisited target storage location, selects the target storage location closest to the current coordinate position as the next access target, updates the coordinates of that target storage location to the current coordinate position, and repeats this process until all N target storage locations have been accessed. Finally, the distance from the last accessed target storage location to the sorting endpoint is calculated. By using the above method, the system minimizes the total walking distance from the sorting starting point, through all target storage locations, to the sorting endpoint, and uses the access order corresponding to this total walking distance as the sorting path for that picking batch.

[0053] VI. Sorting Execution and Real-time Inventory Deduction Steps

[0054] The system sends the planned sorting path to the sorting equipment (such as automated guided vehicles or electronic tag picking systems), which then sequentially arrives at each target storage location according to the sorting path. Upon arrival at each target storage location, the system prompts the operator via light indicators or a display screen to retrieve the corresponding goods and the required quantity from that location.

[0055] After each pickup operation at a target storage location is completed, the system immediately performs a real-time inventory deduction operation. Specifically, the system obtains the initial inventory quantity of the target storage location before the pickup operation (e.g., "15 bottles"), the quantity retrieved during the pickup operation (e.g., "5 bottles"), and subtracts the retrieved quantity from the initial inventory quantity to obtain the second inventory quantity (i.e., "10 bottles"). The system writes the second inventory quantity into the system inventory record, replacing the original initial inventory quantity, and generates an inventory deduction log containing the storage location number (e.g., "A0305"), product name (e.g., "500ml shampoo"), pickup quantity (e.g., "5 bottles"), and inventory deduction timestamp (e.g., "20260616 10:23:45"). Simultaneously, the system synchronously uploads the inventory deduction log to a cloud server for backup storage, ensuring data persistence and traceability.

[0056] For products with sensitive expiration dates (such as food and cosmetics), the system performs an expiration date verification operation before retrieving the goods. The system reads the expiration date information of each product stored in the target storage location, sorts the products in the target storage location according to their expiration dates, and prioritizes retrieving the product with the closest expiration date, following the first-to-last-out principle. If the expiration date of a product in the target storage location is less than the preset expiration date warning number (e.g., 30 days), the system generates an expiration date warning message, displays the product's expiration date risk warning on the operation terminal, and suspends the retrieving operation for that product until the warehouse management personnel confirm the release instruction before continuing the retrieving operation. This mechanism effectively prevents expired products from reaching customers and reduces losses caused by expired products.

[0057] VII. Dynamic Inventory Count and Inventory Early Warning Procedures

[0058] The system scans and counts the actual inventory in each storage location within the warehouse according to a preset inventory counting cycle. In this embodiment, the preset inventory counting cycle is not fixed but dynamically adjusted based on the historical outbound frequency of the goods. The system obtains the daily outbound frequency of each product over the past 30 days and classifies the products into three levels according to their daily outbound frequency, from high to low: the top 20% of products by daily outbound frequency are classified as the first frequency level (high-frequency products), the middle 60% of products by daily outbound frequency are classified as the second frequency level (medium-frequency products), and the bottom 20% of products by daily outbound frequency are classified as the third frequency level (low-frequency products). Products in the first frequency level are counted using the first inventory counting cycle (e.g., once every 4 hours), products in the second frequency level are counted using the second inventory counting cycle (e.g., once every 24 hours), and products in the third frequency level are counted using the third inventory counting cycle (e.g., once every 7 days). The first inventory counting cycle is shorter than the second inventory counting cycle, and the second inventory counting cycle is shorter than the third inventory counting cycle. High-frequency goods have fast turnover and frequent inventory changes, requiring more frequent inventory checks to ensure inventory accuracy; low-frequency goods have slow turnover, so the frequency of inventory checks can be appropriately reduced to save system resources.

[0059] During inventory checks, operators use handheld RFID readers or fixed scanning devices to scan each storage location to obtain the actual inventory quantity of goods in each location. The system compares the actual inventory quantity with the inventory quantity recorded in the system and calculates the inventory deviation (Inventory Deviation = Actual Inventory Quantity - System Recorded Inventory Quantity). When the absolute value of the inventory deviation exceeds a preset deviation threshold (e.g., a deviation threshold of 2 items or a deviation ratio exceeding 5%), the system generates an inventory discrepancy report.

[0060] After generating an inventory discrepancy report, the system further executes discrepancy handling operations. The system obtains the discrepancy location number and discrepancy product name involved in the inventory discrepancy report, instructing operators to re-count the discrepancy location. Operators rescan all products in the discrepancy location and compare the re-counted inventory quantity with the system-recorded inventory quantity. If the absolute value of the inventory deviation after the second comparison is still greater than a preset deviation threshold, the system marks the discrepancy location as "pending verification" and generates a verification task sheet. The verification task sheet contains complete information such as the discrepancy location number, discrepancy product name, system-recorded inventory quantity, actual inventory quantity, and inventory deviation. The system sends the verification task sheet to the warehouse management terminal, where management personnel assign a dedicated person to perform the verification.

[0061] In addition, the system monitors the inventory level of each product in real time. When the system-recorded inventory of any product falls below the preset safety stock threshold, the system automatically generates a replenishment suggestion. The replenishment suggestion quantity is calculated as follows: Replenishment suggestion quantity = (Preset safety stock threshold - Current inventory quantity) × Preset replenishment coefficient. In this embodiment, the preset replenishment coefficient is set to 1.5. For example, if the preset safety stock threshold for a product is 100 units and the current inventory quantity is 30 units, then the replenishment suggestion quantity = (100-30) × 1.5 = 105 units. The system generates a replenishment task order based on the replenishment suggestion quantity. The replenishment task order includes the product name, the replenishment suggestion quantity, and the suggested replenishment location. After review by warehouse management personnel, the replenishment operation is executed.

[0062] Through the coordinated efforts of the above steps, including inbound filing, dynamic allocation of storage locations, order batching, sorting path planning, sorting execution and real-time inventory deduction, dynamic inventory counting and early warning, this invention achieves intelligent and dynamic full-process warehousing, sorting and inventory management of daily necessities, effectively improving warehousing efficiency and inventory management level.

[0063] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent sorting and dynamic inventory management in the warehousing of daily necessities, characterized in that, Includes the following steps: Inbound information collection steps: Obtain the product attribute information of the daily necessities to be inbound, including product name, product specifications, product weight, product volume, production batch number and expiration date; Product coding and file creation steps: Assign a unique identification code to each product to be put into the warehouse, bind and store the unique identification code with the product attribute information, and create an electronic file for the product; The dynamic allocation steps for warehouse locations are as follows: Obtain the warehouse location attribute information of each available warehouse location, including warehouse location number, warehouse location coordinates, warehouse location load limit and warehouse location volume; Calculate the matching score of each available warehouse location based on the matching degree between the product attribute information and the warehouse location attribute information, allocate the products to be put into the warehouse to the available warehouse location with the highest matching score, and update the occupancy status of the warehouse location. Order receiving and batch processing steps: Receive multiple customer orders from the sales terminal. Each customer order contains at least one order detail item, and each order detail item includes the product name and the required quantity. Classify and merge all customer orders according to the product name in the order detail item, and group order detail items containing the same product name into the same picking batch to generate at least one picking batch. Sorting route planning steps: For each picking batch, obtain the location coordinates of the storage locations corresponding to each product in the picking batch; calculate the shortest walking path from the sorting starting point to traverse all target storage locations in the picking batch and return to the sorting endpoint based on the location coordinates, and use this path as the sorting path for the picking batch. Sorting execution and real-time inventory deduction steps: Arrive at each target storage location in sequence according to the sorting path, and retrieve the corresponding goods and required quantities from each target storage location; After completing the retrieval operation of each target storage location, immediately subtract the retrieved quantity from the inventory quantity of the corresponding goods in that target storage location, and record the inventory deduction timestamp. Dynamic inventory count and inventory early warning steps: Scan and count the actual inventory of each storage location in the warehouse according to the preset inventory count cycle, compare the actual inventory quantity with the inventory quantity recorded in the system, and calculate the inventory deviation. When the absolute value of the inventory deviation exceeds the preset deviation threshold, an inventory count anomaly report is generated; When the system-recorded inventory of any product falls below a preset safety stock threshold, a replenishment suggestion is generated.

2. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 1, characterized in that, In the dynamic allocation of storage locations, the formula for calculating the adaptation score is: The matching score is calculated as follows: (volume matching coefficient × first weight) + (load-bearing matching coefficient × second weight) + (heat matching coefficient × third weight). Among them, the volume matching coefficient is determined based on the ratio of the commodity volume to the storage space volume, the load-bearing matching coefficient is determined based on the ratio of the commodity weight to the storage space load-bearing limit, and the heat matching coefficient is determined based on the commodity's historical outbound frequency; the first weight, the second weight, and the third weight are preset weight coefficients, and the sum of the three is equal to 1.

3. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 2, characterized in that, In the order receiving and batch processing steps, before classifying and merging all customer orders according to the product names in the order details, an order priority sorting operation is also performed: the order timestamp and delivery time requirements of each customer order are obtained, the comprehensive priority score of each customer order is calculated based on the order of the order timestamps and the urgency of the delivery time requirements, and the customer orders are sorted in descending order of comprehensive priority score.

4. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 3, characterized in that, In the sorting path planning step, the shortest walking path is determined as follows: obtain the starting coordinates of the sorting start point and the ending coordinates of the sorting end point; for N target storage locations in the picking batch, calculate the walking distance from the current coordinate position to the coordinates of the next target storage location in sequence, where N is a positive integer; adopt a dynamic adjustment strategy to determine the access order of the target storage locations, so that the total walking distance from the sorting start point to the sorting end point is minimized; wherein, the initial value of the current coordinate position is the starting coordinate, and after determining the access order of each target storage location, the coordinates of the target storage location are updated to the current coordinate position, until all N target storage locations have been accessed.

5. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 4, characterized in that, In the sorting execution and real-time inventory deduction steps, after each picking operation of a target storage location is completed, the following operations are also performed: obtain the first inventory quantity of the target storage location before the picking operation, obtain the picking quantity taken out during the picking operation, and subtract the picking quantity from the first inventory quantity to obtain the second inventory quantity. Write the second inventory quantity into the system inventory record and generate an inventory deduction log containing the storage location number, product name, quantity picked, and inventory deduction timestamp; The inventory deduction logs are synchronized and uploaded to the cloud server for backup storage.

6. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 5, characterized in that, In the sorting and real-time inventory deduction process, when the goods retrieved from the target location are expiration-sensitive goods, an expiration verification operation is performed before the retrieval operation: the expiration information of each goods stored in the target location is read, the goods in the target location are sorted according to the expiration date, and the goods with the closest expiration date are retrieved first; if the expiration date of a certain goods in the target location is less than the preset expiration warning days from the current date, an expiration warning message is generated and the outbound operation of the goods is suspended until a confirmation release instruction is received.

7. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 6, characterized in that, In the dynamic inventory counting and inventory early warning process, the preset inventory counting cycle is dynamically adjusted based on the historical outbound frequency of the goods: the daily outbound frequency of each goods in the past preset time period is obtained, and the goods are divided into first frequency level, second frequency level and third frequency level according to the daily outbound frequency from high to low; the first frequency level goods use the first inventory counting cycle, the second frequency level goods use the second inventory counting cycle, and the third frequency level goods use the third inventory counting cycle; the first inventory counting cycle is shorter than the second inventory counting cycle, and the second inventory counting cycle is shorter than the third inventory counting cycle.

8. The intelligent sorting and dynamic inventory management method for daily necessities warehousing according to claim 7, characterized in that, In the dynamic inventory count and inventory warning process, the specific method for generating replenishment suggestions is as follows: obtain the product name, current inventory quantity, and preset safety stock threshold of the products whose inventory is lower than the preset safety stock threshold; Calculate the recommended replenishment quantity, which is equal to the preset safety stock threshold minus the current inventory quantity, multiplied by the preset replenishment coefficient, which ranges from 1.2 to 1.

8. Generate a replenishment task order based on the recommended replenishment quantity. The replenishment task order includes the product name, the recommended replenishment quantity, and the recommended replenishment location.

9. A method for intelligent sorting and dynamic inventory management of daily necessities warehouses according to claim 8, characterized in that, In the dynamic inventory counting and inventory early warning process, after generating an inventory count anomaly report, anomaly handling operations are performed: obtaining the abnormal storage location number and abnormal product name involved in the inventory count anomaly report; re-counting the abnormal storage location, and comparing the re-counted inventory quantity with the system-recorded inventory quantity a second time; if the absolute value of the inventory deviation after the second comparison is still greater than the preset deviation threshold, the abnormal storage location is marked as pending verification, and a verification task sheet containing the abnormal storage location number, abnormal product name, system-recorded inventory quantity, actual inventory quantity, and inventory deviation is generated and sent to the management terminal.

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