Comprehensive management method and system for ERP warehouse

Abstract

The invention relates to the technical field of warehouse management, in particular to a comprehensive management method and system for an ERP warehouse, and the method comprises the steps: collecting storage multi-source data, and generating a structured data set through standardized preprocessing; based on the structured data set, initial storage location allocation parameters are obtained through a multi-parameter weighted adaptation algorithm, inventory early warning parameters are obtained by combining a sequential anomaly correction and threshold derivation algorithm with the initial storage location allocation parameters, and high-precision management and control parameters are generated through target screening; constructing a storage full-process execution model based on the high-precision management and control parameters, and outputting a service operation result; according to a service operation result, judging abnormity through a dynamic verification algorithm, and generating a parameter correction instruction and system optimization data; and inputting the high-precision management and control parameters, the system optimization data and the warehousing service scene label into the collaborative management model, and outputting a warehousing management strategy adaptive to the scene. According to the scheme, a scientific and quantitative storage location distribution mechanism is constructed, so that the operation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of warehouse management technology, and in particular to a comprehensive management method and system for ERP warehouses. Background Technology

[0002] In the process of digitalizing enterprise warehouse management, ERP systems have become core management tools. However, existing ERP-based warehouse management models still have many technical bottlenecks, making it difficult to meet the modern warehouse's needs for precise, efficient, and collaborative management.

[0003] First, there are shortcomings in the integration and standardization of multi-source data. Document data (purchase receipts, sales receipts, etc.), basic inventory data (material number, inventory quantity, unit), storage location characteristic data (storage location capacity, distance from the work area), and business configuration data (department permissions, preset operating rules) in warehousing operations are often scattered across different modules of the ERP system. The data format lacks a unified standard, and quantity units are often misused due to input habits, resulting in different records using synonyms like "PCS" and "piece." Coding rules are also inconsistent. Furthermore, there is a lack of automatic correlation mechanisms between documents and inventory / storage location data, requiring manual verification and matching. This not only leads to low data processing efficiency but also makes data corruption prone to human error, failing to provide reliable support for subsequent storage location allocation and business execution.

[0004] Secondly, the scientific nature of the warehouse location allocation mechanism is insufficient. Current warehouse location allocation largely relies on the experience and judgment of warehouse staff, lacking a quantitative model based on objective parameters: Inbound warehouse location selection only considers whether space is available, neglecting the compatibility of remaining warehouse capacity with the total volume of materials, and the impact of the warehouse location's distance from the inbound entrance on handling efficiency. This often results in "small materials occupying large warehouse locations," causing space waste, or "high-frequency materials stored in distant warehouse locations," increasing operating costs. Outbound warehouse location allocation does not combine material turnover rate and the distance of warehouse locations from the outbound entrance for comprehensive ranking, making it difficult to prioritize and match efficient operating warehouse locations, resulting in low overall warehouse space utilization and operational efficiency. Summary of the Invention

[0005] This invention improves operational efficiency by constructing a scientifically quantified warehouse location allocation mechanism.

[0006] The technical solution proposed in this invention is: a comprehensive management method for ERP warehouses, the method comprising: Collect multi-source data from warehousing and generate structured datasets through standardized preprocessing; Based on structured datasets, initial storage location allocation parameters are obtained through a multi-parameter weighted adaptation algorithm. Inventory early warning parameters are obtained by combining the initial storage location allocation parameters with a time-series anomaly correction and threshold derivation algorithm. High-precision control parameters are generated through target screening. A full-process warehouse execution model is built based on high-precision control parameters, and business operation results are output. Based on the results of business operations, anomalies are identified through dynamic verification algorithms, and parameter correction instructions and system optimization data are generated. Input high-precision control parameters, system optimization data, and warehouse business scenario tags into the collaborative management model, and output warehouse management strategies adapted to the scenario.

[0007] Preferably, the specific process for obtaining the structured multi-source dataset is as follows: Collect business document data, basic inventory data, storage location characteristic data, and business configuration data; unify the time format, quantity unit, and coding format; delete data with abnormal time format, logically conflicting data, and redundant and irrelevant data; complete data with missing key fields; link document data and inventory change data through document codes; link storage location data and stored material data through storage location numbers; and form a structured multi-source dataset containing modules for document identification, inventory details, storage location attributes, and control rules.

[0008] Preferably, the specific process for obtaining the initial storage location allocation parameters is as follows: The remaining capacity of storage locations, the total volume of materials to be allocated, the distance of storage locations from the inbound and outbound ports, and the historical turnover rate of materials to be allocated are extracted from the structured multi-source dataset. Capacity fit is calculated using the ratio of remaining storage location capacity to total material volume, and inbound efficiency is calculated using the reciprocal of the normalized distance from the storage location to the inbound port. A weighted score for the storage location fit is calculated by combining capacity fit weights and inbound efficiency weights, and the storage location with the highest fit score is selected as the target storage location. Based on the storage location fit calculation logic, a weighted score for the outbound storage location is calculated by combining capacity fit weights, outbound efficiency weights, and material turnover rate weights. After obtaining the score ranking, the recommended allocation quantity is determined based on the actual inventory of each storage location. The initial storage location allocation parameters are obtained by integrating the target storage location, outbound storage location priority ranking results, and corresponding recommended allocation quantities.

[0009] Preferably, the specific process for obtaining the inventory early warning parameters is as follows: First, calculate the total number of recent holidays, then subtract the holiday days to obtain the effective statistical days for calculation. Calculate the total outbound volume of the material within the effective statistical period to obtain the average daily consumption during this period. Compare the daily outbound volume within the effective statistical period with the initially calculated average daily consumption. If the outbound volume on a certain day exceeds a preset multiple of the average daily consumption, the data for that day is determined to be temporary abnormal data and replaced with the initially calculated average daily consumption. Based on the corrected daily outbound volume, recalculate the total outbound volume within the effective period to obtain the corrected average daily consumption. Combine the corrected average daily consumption with the preset minimum and maximum inventory days to calculate the lower inventory threshold for indicating stockout risk and the upper inventory threshold for indicating overstock risk. Integrate these two thresholds with the corresponding target storage location and material association information to form inventory warning parameters.

[0010] Preferably, the specific process for obtaining the high-precision control parameters is as follows: Based on inventory early warning parameters, the system extracts the material's inbound and outbound records and departmental data for the target storage location within a preset period. The initial inventory is used as the ending inventory of the previous period. The total inbound and outbound volumes that meet the early warning threshold are accumulated, and the ending inventory of the current period is calculated. The system also associates departmental information to form inventory and consumption statistics parameters. Inefficient storage location data with a fit lower than the preset value in the initial storage location allocation parameters, invalid original outbound records after abnormal correction in the inventory early warning parameters, and scattered operation data not associated with departments in the inventory and consumption statistics parameters are removed. The remaining initial storage location allocation parameters, inventory early warning parameters, and inventory and consumption statistics parameters are then integrated to form high-precision warehouse management parameters.

[0011] Preferably, the specific process for obtaining the business operation result is as follows: Using high-precision warehouse management parameters as the core input, a full-process execution model covering core warehouse operations is built. Actual warehouse business requirements are input into this model, triggering corresponding business processing flows. The inbound document management module receives inbound business requirements and sequentially processes inbound document creation, inbound execution, and inbound confirmation, simultaneously calling the initial storage location allocation parameters from the high-precision management parameters to filter target storage locations, and outputting the inbound document status, actual inbound quantity, and corresponding target storage location information. Similarly, the outbound document management module receives outbound business requirements and sequentially processes outbound document creation, outbound allocation, outbound verification, and outbound confirmation, simultaneously calling the initial storage location allocation parameters from the high-precision management parameters to match outbound storage locations, and outputting the outbound document status, actual outbound quantity, and corresponding allocated storage location information, integrating these to form a complete business operation result.

[0012] Preferably, the specific process for obtaining the parameter correction instruction is as follows: The system compares the creation time of inbound documents with the generation time of upstream purchase and return orders, and the creation time of outbound documents with the completion time of their corresponding inbound documents. If a document's creation time is earlier than the upstream order's creation time or the outbound time is earlier than the inbound time, it is determined to be a timing conflict anomaly, and a document time verification rule parameter correction instruction is generated. The system checks whether the actual inbound quantity is greater than 0 and does not exceed the pending inbound quantity, and whether the actual outbound quantity is greater than 0 and does not exceed the available inventory in the storage location. If they exceed the range, it is determined to be a quantity invalidity anomaly, and a quantity verification threshold correction instruction is generated. The system compares the actual remaining inventory in the storage location with the theoretically calculated value of the initial inventory ± the actual inbound and outbound quantities. If the deviation exceeds the preset allowable range, it is determined to be an inventory data deviation anomaly, and an inventory calculation benchmark parameter correction instruction is generated.

[0013] Preferably, the specific process for obtaining the warehouse management strategy is as follows: Based on high-precision warehouse management parameters and system optimization data, and combined with warehouse business scenario tags, the association between data and scenarios is established; a collaborative management model is built, and decision rules are configured for different scenarios; data is input into the model, and a scenario-based framework is generated according to the rules; system optimization data is incorporated to supplement details, forming a complete warehouse management strategy that includes applicable scenarios, execution rules, and data basis.

[0014] The present invention also provides a comprehensive management system for ERP warehouses, the system being used to execute the aforementioned comprehensive management method for ERP warehouses.

[0015] The present invention also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement the aforementioned integrated management method for ERP warehouses.

[0016] The beneficial effects of this invention are: 1. By standardizing the formats (time, unit, code) of warehousing business documents, inventory base, storage location characteristics, and business configuration data, and establishing an automatic association mechanism between documents and inventory / storage location data, the problems of scattered data, chaotic formats, and the need for manual verification in traditional ERP warehouse management are completely solved. This not only saves time spent on manual format conversion and data matching, significantly reducing the risk of data corruption caused by human error, but also provides a real-time and reliable data source for subsequent storage location allocation and business execution, ensuring the accuracy of warehousing decisions and improving overall data processing efficiency.

[0017] 2. A quantitative calculation model is established based on parameters such as remaining storage space capacity, material volume, distance from the work area, and material turnover rate, replacing the traditional experience-based storage space allocation method. Upon receiving goods, storage spaces with suitable capacity and reasonable distance can be accurately matched, avoiding space waste from "small materials occupying large storage spaces" and increased handling costs from "remote storage." Upon outbound goods, storage spaces with high turnover rates and close to the outbound area are prioritized, improving picking efficiency. Simultaneously, the storage space allocation results are linked to subsequent business operations, further optimizing warehouse space utilization, reducing operating costs, and driving the transformation of warehousing operations from "experience-driven" to "data-driven."

[0018] 3. By integrating core inbound and outbound business processes through a unified end-to-end execution model, real-time synchronization of document status and inventory data is achieved, avoiding business disconnect issues such as "inbound completed but inventory not updated" and "outbound allocation of insufficient inventory." Furthermore, when anomalies such as timing conflicts or invalid quantities occur, the root cause can be automatically traced and the verification rules and parameter thresholds corrected, eliminating the need for repeated manual adjustments. This closed loop not only reduces the frequency of business anomalies and ensures smooth warehousing processes but also promotes continuous optimization of system management, enhances the adaptability and stability of ERP warehouse management, and improves overall operational efficiency. Attached Figure Description

[0019] Figure 1 A flowchart illustrating a comprehensive warehouse management method for ERP systems; Figure 2 This is a flowchart illustrating the management process of a comprehensive management method for ERP warehouses. Detailed Implementation

[0020] The following description is intended to disclose the present invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art. The basic principles of the invention defined in the following description can be applied to other embodiments, modifications, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the invention.

[0021] It is understood that the term "a" should be understood as "at least one" or "one or more," that is, in one embodiment, the number of an element can be one, while in another embodiment, the number of the element can be multiple, and the term "a" should not be understood as a limitation on the number.

[0022] like Figure 1 and Figure 2As shown, after logging into the ERP warehouse management system, the user triggers the inbound document creation instruction by calling the "Document Management" interface in the warehouse management function module. The system then displays a set of inbound document options (including purchase inbound documents and return inbound documents). The user selects the corresponding type according to the business scenario. If it is a purchase of raw materials, the user selects "Purchase Inbound Document" and calls the "Supplier Information Association" sub-interface to automatically load the list of suppliers registered by the company. If it is a customer return inbound document, the user selects "Return Inbound Document" and calls the "Customer Information Association" sub-interface to load the list of historical cooperative customers, ensuring that the document type and business information are accurately matched.

[0023] Next, the system calls the "Time Synchronization" sub-interface, which defaults to filling in the current system time (format "YYYY / MM / DDHH:MM:SS") as the document creation time. Users can modify the time using the time adjustment control, but the system will automatically determine through the "Time Sequence Validation" sub-interface that the document creation time must not be earlier than the generation time of the upstream related order (purchase order / return application). If it does not meet the requirement, a "Time Sequence Conflict" prompt will pop up, prohibiting further operations and avoiding business logic time sequence chaos.

[0024] After setting the time, the user calls the "Product Search" sub-interface to retrieve matching product data (including product number, name, and unit) using fuzzy search parameters such as product number, product name, or drawing number. After selecting the target product, the system automatically populates the basic product information into the document list. The user needs to enter the expected quantity to be received (parameter constraints: value > 0, and the unit must match the product's preset unit). The system supports batch addition (up to 50 product records at a time) and single deletion (triggered by the unique identifier of the product record), allowing users to flexibly adjust the product list.

[0025] After all information is filled in, the user clicks "Submit". The system then calls the "Document Code Generation" sub-interface to generate a unique document code according to the "Document Type Code - Timestamp" rule (e.g., if the purchase receipt code is "1201", then the document code is "1201-20240520164500"). Simultaneously, the system calls the "Data Storage" sub-interface to store the basic document information (document code, type, creation time, creator) and product list information (unique product identifier, estimated quantity, unit) into the system database. Subsequently, the system calls the "Status Initialization" sub-interface to set the initial document status to "Incomplete" and sets the permissions through the "Permission Association" sub-interface: in this state, the user only has permissions to modify and delete the document (deletion requires meeting the condition of "no associated receipt record"), and no permissions associated with outbound business operations, ensuring the security and rationality of document operations.

[0026] After creating the inbound document, users can choose between "scan-to-inbound" or "quantity-based inbound" based on their business needs. When choosing scan-to-inbound (suitable for efficient batch processing scenarios), users scan the document code using a scanning device (such as a barcode scanner). The system calls the "Document Recognition" sub-interface to match the document data in the database using the unique identifier of the document code, automatically loading information such as document type, product list, and expected inbound quantity, without requiring manual input. Next, the system displays an information completion interface where users input the inbound time (calling the "Time Verification" sub-interface to ensure the inbound time > document creation time), select the target warehouse (calling the "Warehouse Matching" sub-interface to filter a suitable warehouse list based on material type), select their department (calling the "Department Permissions" sub-interface to display only departments within the user's permission range), and complete supplier / customer information according to document type (calling the "Information Verification" sub-interface to ensure the supplier / customer status is "Normal Cooperation"). Optional remarks are also available (character length ≤ 200 characters).

[0027] After the user clicks "Submit", the system calls the "Storage Location Filtering" sub-interface, where users input material storage parameters (product unit volume, weight) and basic storage location parameters (storage location capacity, length / width / height, distance from the inlet). The system then calculates the storage location suitability using the following formula: ; in: For warehouse location adaptability, Remaining storage space capacity (unit: ), Total volume of material (unit: ), , Distance from storage location to inlet (unit: ), This represents the maximum distance from all storage locations within the current warehouse to the inbound entrance, automatically calculated and stored by the system. Weights of 0.6 (capacity adaptation weight) and 0.4 (distance adaptation weight) were validated through 50 real-world business cases (covering 3 different warehouse types, each case containing 10-15 storage location parameters). Statistical results show that capacity adaptation accounts for 62% of inbound efficiency (inbound delays due to insufficient capacity are more frequent than those caused by distance), while distance adaptation accounts for 38%. Therefore, approximate weights of 0.6 and 0.4 are adopted.

[0028] when hour, If the compatibility decreases, the system will automatically exclude the storage location (to avoid insufficient capacity that would prevent materials from being stored). when When it approaches 0 (theoretically, the storage location next to the inlet), Approaching 0, Approaching infinity, the distance fit score is the highest, which meets the actual business requirement of "prioritizing locations near the warehouse to improve handling efficiency"; when hour, , The distance matching score is the lowest, so avoid choosing the farthest storage location to avoid increasing handling costs.

[0029] For example, a raw material warehouse Total volume of materials Storage location A ( , Storage location B , ): Storage location A: , ; Storage location B: , ; Result: Storage location B has a higher suitability and is given priority in allocation, which is consistent with the actual business requirement of "prioritizing storage locations that meet capacity requirements and are closer in distance".

[0030] The system selects the one with the highest compatibility (and The system selects the desired storage location as the target location. If no suitable storage location is found, a "Storage location insufficient" message will pop up. After the storage location is determined, the system calls the "Inbound Data Association" sub-interface to associate and store the document code, unique storage location identifier, and actual inbound product information, and returns an operation result message "Scanning and inbound successful".

[0031] If quantity-based inbound processing is selected (suitable for precise, small-volume processing scenarios), the user first calls the "Incomplete Document Query" sub-interface, inputs the "Document Type" and "Creation Time Range" parameters, and retrieves a list of inbound documents with a status of "Incomplete". After selecting the target document, the system calls the "Document Details Load" sub-interface to retrieve historical operation data for all products under that document. Subsequently, the system calls the "Quantity Statistics" sub-interface to calculate key quantity parameters using the following formula: ; in: This represents the quantity already received into inventory. For the first The actual quantity of goods received in the previous historical inbound operation. This represents the number of historical operations.

[0032] ; in: The quantity to be received into the warehouse. This represents the estimated quantity to be received into the warehouse.

[0033] After verifying the quantity to be received, the user enters the actual quantity received this time. The system calls the "Quantity Verification" sub-interface to automatically determine: and If the quantity does not meet the requirements, an "Invalid Quantity" message will pop up, preventing submission. After the user clicks "Confirm Inbound," the system calls the "Operation Record Storage" sub-interface to store the data for this inbound operation (document code, product unique identifier, ... The data (including the entry time) is stored in the operation log table, and an operation result message "Quantity successfully entered into inventory" is returned.

[0034] Whether it's barcode scanning for inventory entry or quantity-based inventory entry, the system will automatically call the "Inbound Data Summary" sub-interface after the operation is executed to obtain the key data for this inventory entry (product unique identifier, item number, item name, etc.). The system displays data such as unique warehouse location identifier, inbound time, and unique supplier / customer identifier, presented in a list for user verification. Users check the data line by line. If errors are found (such as quantity discrepancies or incorrect warehouse location allocation), they can click the "Return to Modification" button. The system then calls the "Modification Trigger" sub-interface, redirecting to the corresponding inbound method's operation interface, allowing for re-entry or parameter adjustment. After confirming everything is correct, clicking "Submit Confirmation" calls the "Document Status Update" sub-interface, updating the document status from "Incomplete" to "Completed." Simultaneously, the "Inventory Update" sub-interface is called to synchronize inventory data using the following formula: ; in: This is the updated inventory quantity. The inventory value of the product in the target warehouse before it is received is obtained from the inventory data table; This represents the actual quantity received in this transaction; finally, the "Result Notification" sub-interface is called to display a "Successful Inbound Confirmation" message, along with the displayed information. The warehousing process is now complete.

[0035] For example, let's take the purchase and warehousing of raw materials for an auto parts manufacturing company as an example to verify the feasibility of this solution: After logging into the system, the purchasing personnel select "Purchase Receipt Order," associate the supplier "a supplier in Hangzhou," set the creation time to "2024 / 05 / 20 16:45:00," add the product (item number "10150102272," item name "848E62380," unit "PCS," unit volume 0.005). / PCS) and enter PCS (Total Volume of Materials) After submission, a document code "1201-20240520164500" is generated, and the status is "incomplete".

[0036] The warehouse clerk selects the barcode scanning method for inbound storage, scans the document code with a barcode scanner, and the system loads the document information; the inbound time is added as "2024 / 05 / 2017:00:00", and the target warehouse "Raw Materials Warehouse" is selected. At this point, the system calls the storage location filtering sub-interface: total material volume. Remaining capacity of storage location "Raw Materials Warehouse-A01-0-0" Distance from the warehouse entrance The fitness rate was calculated. Once the target storage location is identified, the system will associate and store the data, returning a "scanned data entry successful" message.

[0037] After the warehouse clerk verifies the data on the receiving confirmation interface and submits it, the system updates the document status to "Completed" and calls the inventory update sub-interface to display the original inventory quantity. PCS, updated inventory quantity PCS ultimately returned a "Confirmation Successful" message. The entire inbound process was error-free, with inventory synchronization delays of less than 10 seconds.

[0038] After completing the inbound process management, users can trigger the outbound document creation command by calling the "Document Management" interface in the warehouse management module. The system displays a set of outbound document options (including sales outbound orders, transfer outbound orders, etc., matching the outbound business scenario in the specified reference file). Users select the corresponding document type according to actual business needs: if it is a product sales outbound to external customers, select "Sales Outbound Order," and the system will automatically load basic information such as the customer name and delivery address that the company has filed; if it is a material transfer between different warehouses within the company, select "Transfer Outbound Order," and the system will load a list of all internal warehouses (including warehouse number, name, and location), ensuring that the document type is accurately matched with the business scenario.

[0039] The system calls the "Time Synchronization" sub-interface, which defaults to filling in the current system time (formatted as "YYYY / MM / DDHH:MM:SS") as the document creation time. Users can modify this time using the time adjustment control to reflect the actual business initiation time. Simultaneously, the system automatically determines through the "Time Sequence Verification" sub-interface that the document creation time must not be earlier than the completion time of the corresponding inbound document (or later than the initiation time of the transfer plan if it's a transfer outbound document), thus avoiding business logic timing conflicts.

[0040] Subsequently, the user calls the "Product Search" sub-interface to locate the target product using the fuzzy search function by item number, product name, or drawing number. After selecting the product, the system automatically fills in basic information such as product name and unit into the document list. The user then needs to manually enter the expected outbound quantity. (Parameter constraints:) The unit must be consistent with the product's default unit, such as "PCS" or "KG". If you need to add multiple outbound products, you can repeat the "Search and select products - enter the expected quantity" operation; if you add the wrong product, you can click the "Delete" button after the corresponding product record to remove it, ensuring that the expected outbound product list is accurate.

[0041] After verifying all information, the user clicks the "Submit" button. The system generates a unique document code according to the rule of "document type code - timestamp" (for example, if the sales outbound order code is "2201", then the document code is "2201-20240521103000"). The system then stores the basic document information (document code, document type, creation time, associated customer / warehouse information) and the expected outbound product list information (product unique identifier, name, unit, expected quantity) in the system database. At the same time, the system calls the "Status Initialization" sub-interface to set the initial status of the outbound document to "Incomplete". In this state, the user can only modify the document (such as adding products or adjusting the expected quantity) or delete it (provided that the document has no associated outbound operation records), and cannot perform subsequent outbound association operations.

[0042] After users enter the outbound allocation interface, the system provides two modes: "automatic allocation" and "manual allocation" to adapt to different business scenario requirements. Automatic allocation mode: The system calls the "Storage Location Filtering and Priority Calculation" sub-interface to comprehensively consider the current inventory situation (the actual inventory quantity of the target product in each storage location). ), distance between the storage location and the outlet ( ,unit: Normalization process , The maximum distance from all storage locations within the current warehouse to the outbound exit, and the material turnover rate ( The calculation method uses three core factors: "total outbound volume of the material within the period / average inventory of the material within the period," to calculate the outbound priority of each storage location. The priority calculation logic is: the closer the storage location, the higher the turnover rate, and the more sufficient the inventory, the higher the priority. The calculation formula is: , Priority scores are assigned. The system sorts products according to their priority scores, automatically matches the optimal outbound storage location, and generates a list of storage location allocation results. The list clearly displays "product name, allocated storage location number, allocated quantity, and remaining inventory." The total inventory of a product across all storage locations is also considered. If the product is out of stock, a separate "out of stock" label will be added after the product record in the allocation results list, along with the "Current Total Inventory / Estimated Outbound Quantity" (e.g., "30PCS / 50PCS"), to remind users to address the out-of-stock issue promptly.

[0043] Manual allocation mode: Users can manually select the outbound storage location and corresponding outbound quantity according to specific business needs (such as customers specifying outbound storage locations, materials needing to be outbound in batches, etc.). During the selection of storage location and input of quantity, the system calls the "Inventory Verification" sub-interface in real time to automatically check the current inventory of the selected storage location. Does it meet the requirements? If the conditions are met, the operation can continue; otherwise (i.e.) If this happens, a "low inventory" message will immediately pop up, displaying the maximum quantity that can be shipped from that storage location (i.e., ...). This helps avoid inventory data confusion caused by issuing excess inventory.

[0044] After the outbound allocation is completed, the outbound verification process begins. Users use a barcode scanner (such as a barcode scanner) to scan the corresponding pallet for the material. ), box code ( The system uses unique identifiers such as "total number of boxes" to call the "code value parsing and data verification" sub-interface to automatically extract the "total number of boxes" contained in the crate. "Quantity per box" included in the box code "and calculate the confirmed outbound quantity." .

[0045] At the same time, the system retrieves the allocation information of the outbound document from the database and automatically verifies the "confirmed quantity". "Is it consistent with the allocated quantity?" "Total number of boxes" "Does the number of boxes match the actual number of boxes loaded?" and "Is the current occupied quantity of storage locations (the quantity allocated but not yet confirmed for shipment) accurate?" If all information matches, the verification passes; if there are inconsistencies (such as...), the verification fails. Less than the allocated quantity If the number of boxes does not match the actual number, the system will immediately display a "data mismatch" message and highlight the discrepancy (e.g., "confirmed quantity 80 PCS < allocated quantity 100 PCS"), guiding the user to rescan the barcode to verify or check the actual materials to avoid misdelivery or omission.

[0046] After the outbound verification is successful, the user will re-verify key information on the outbound confirmation screen, including "product name, item number, and actual outbound quantity (i.e., ...)". This includes information such as "outbound storage location number, associated customer / inbound warehouse information," ensuring that all information is consistent with the actual outbound operations.

[0047] If an error is found, the user can click the "Return to Edit" button to proceed to the corresponding step (outbound allocation or outbound verification) for adjustment. If all information is verified to be correct, the user can click the "Confirm Outbound" button, and the system will trigger the following operations: Call the "Document Status Update" sub-interface to update the status of the outbound document from "Incomplete" to "Completed". After the update, users can no longer modify or delete the document, but can only view the document details. Call the "Inventory Deduction" sub-interface and apply the formula. (in This refers to the quantity of inventory in the warehouse after shipment. This refers to the quantity of inventory in the warehouse before shipment. (This is the actual number of items shipped out this time), and the inventory quantity of the target product in the corresponding warehouse location is deducted simultaneously to ensure that the inventory data is consistent with the actual shipment situation in real time; The system generates an "Outbound Completion Log" which records the document code, outbound time, operator, details of the actual outbound products, and inventory changes. This log is stored in the system log module for easy business traceability and data retrieval.

[0048] Once the system displays a "Outbound Confirmation Successful" message, the entire outbound process is complete. Users can return to the warehouse document management interface to view the updated document status or enter the inventory query module to verify the inventory change results.

[0049] For example, taking the sale of "car dashboards" (part number "20240501", unit "PCS") by a manufacturing company to a "car assembly plant" (core customer) as an example, the specific process is as follows: Outbound document creation: Sales personnel log in to the system, select "Sales Outbound Order", associate the customer "a certain automobile assembly plant", set the document creation time to "2024 / 05 / 21 10:30:00", add product "20240501" by item number search, and enter the expected outbound quantity. After submission, PCS generates document code "2201-20240521103000" with a status of "incomplete".

[0050] Outbound allocation: The warehouse manager selects the "automatic allocation" mode, and the system calculates the priority of each storage location (finished goods warehouse). Inventory in warehouse location "Finished Goods Warehouse-B02-03" PCS, distance from the exit ( Turnover rate The highest priority item is assigned, with a quantity of 100 PCS. The system generates an allocation result list with no out-of-stock notification.

[0051] Outbound verification: The warehouse clerk scans the pallet barcode with a barcode scanner. The system analyzes the total number of boxes. Box, scan box code ( The quantity of a single box is obtained from BC20240521001-01 to 010. PCS, calculation PCS, consistent with the allocated quantity, verification passed.

[0052] Outbound Confirmation: After the warehouse manager verifies that the information is correct, click "Confirm Outbound". The system updates the document status to "Completed", deducts the inventory of "Finished Goods Warehouse-B02-03" (from 150 PCS to 50 PCS), generates an outbound log, and prompts "Outbound confirmation successful", and the process ends.

[0053] After completing the core business processes of receiving and issuing goods, the system achieves dynamic inventory management through the "Inventory Control and Data Statistics" module. All functional logic and operation design are based on specified reference files. The specific process is as follows: After logging into the system, users can access the "Inventory Monitoring" interface through the warehouse management module. The interface displays two tabs by default: "Warehouse Storage Records" and "Storage Location Details." It supports multi-dimensional filtering and data export. The operation process is as follows: The top of the interface features a "multi-condition combination filter area," allowing users to select filter dimensions as needed. Basic filters: Product name (supports fuzzy search; the system automatically matches a list of products containing the keyword after you enter it), Warehouse (select maintained warehouses from the dropdown menu; multiple selections are supported, such as selecting both "Raw Materials Warehouse" and "Finished Products Warehouse"). Time Filter: Query time (offers options for "Today", "Yesterday", "Last 7 Days", and "Custom Date Range". When customizing, you need to select the start and end dates in the format "YYYY / MM / DD"). Advanced Filtering (click "Expand Advanced Filtering" to display): Drawing Number (exact match, enter the complete drawing number to filter), Batch (select material batch from dropdown, only displayed for materials with batch management requirements), Inventory Status (e.g., "Normal Inventory," "Frozen Inventory," single selection supported). After setting the filter criteria, the user clicks "Query," and the system retrieves the corresponding inventory data from the database, displaying it in a list format in the middle of the interface. The columns strictly follow the requirements of the referenced documents: Item Number, Item Name, Drawing Number, Inventory Quantity (distinguishing between "Available Inventory" and "Frozen Inventory"), Unit, Warehouse, and Storage Location Number. The list supports ascending / descending sorting by "Inventory Quantity" and "Item Number," facilitating quick location of materials with high or low inventory.

[0054] Data linkage logic: When a material record is clicked on the "Warehouse Storage Records" tab, the system automatically jumps to the "Storage Location Details" tab and filters the storage status of the material in each storage location by default, displaying information such as "Storage Location Number, Storage Location Capacity, Current Storage Quantity, and Remaining Capacity" to help users accurately grasp the storage location distribution of materials and avoid storage location waste or storage conflicts.

[0055] After retrieving the target inventory data, users can click the "Export" button at the bottom of the interface. A pop-up window will then appear to select the export format (including "PDF" and "Excel" options). When the "PDF" format is selected, the system generates standardized reports by grouping them into "Warehouse-Materials". The reports include filter conditions, export time, and a detailed list of materials. They also support adding company logos and footer notes (such as "Internal inventory report, do not distribute"), which is suitable for paper archiving needs. When the "Excel" format is selected, the exported table contains all display columns and a blank "Remarks" column is reserved for users to edit offline (such as marking the reasons for inventory anomalies). The table automatically enables the filtering function, and users can further filter and statistically analyze it in Excel to meet the needs of internal report integration.

[0056] The "Business Data Statistics" interface includes two functional modules: "Inbound / Outbound Details Query" and "Inbound / Outbound / Inventory Details Statistics." Both modules support multi-condition filtering and data export. Specific improvements are as follows: The filtering dimensions have been refined: In addition to the "record type, document number, product name, business partner, warehouse, and time range" mentioned in the referenced documents, a new "operator" filter has been added (a dropdown menu allows users to select system users to query inbound and outbound records operated by specific personnel) and a "material type" filter (e.g., "raw materials," "semi-finished products," and "finished products," with dropdown menus for the corresponding type). This caters to the enterprise's needs for personnel performance statistics and material classification analysis. The "business partner" filter automatically adapts to document type: when querying inbound details, "business partner" corresponds to "supplier" (a dropdown menu allows users to select partner suppliers); when querying outbound details, it corresponds to "customer" (a dropdown menu allows users to select partner customers), preventing users from selecting invalid options.

[0057] Detailed display rules: The filtered results list strictly displays all dimensions of information required by the referenced documents, and a new "Operation Time" column has been added (displaying the specific time of the inbound operation, in the format "YYYY / MM / DDHH:MM:SS") to facilitate users in tracing the timeline of business transactions; the "Remarks" column prioritizes displaying special instructions filled in during the inbound process (such as "expedited inbound" or "customer return"), and displays "no special instructions" when there are no remarks to ensure information completeness.

[0058] Statistical Period and Dimensions: The system defaults to statistics based on "natural months" (e.g., "May 2024", "June 2024"). Users can select the target month in the "Statistical Period" dropdown menu, or select multiple consecutive months through "Custom Period" (e.g., "March 2024 - May 2024") to meet cross-month statistical needs. In addition to "Product Name" and "Warehouse," a "Department" filter is added (select related departments from the dropdown menu, such as "Purchasing Department" and "Production Department"). This allows for statistical analysis of the inflow, consumption, and inventory of materials under the responsibility of each department, providing data support for departmental inventory responsibility allocation.

[0059] Data calculation logic: The system strictly follows the rules of the referenced files to calculate each value, using the following formulas: Beginning inventory: The inventory quantity on the first day of the statistical period (take the ending inventory quantity of the previous day of the period). Mid-term inbound quantity: The total actual inbound quantity of all inbound operations within the statistical period; Mid-term outbound quantity: The total actual outbound quantity of all outbound operations within the statistical period; Ending inventory = Beginning inventory + Mid-term inbound inventory - Mid-term outbound inventory.

[0060] Identify the number of holiday days in the past 30 days Calculate the number of valid statistical days Total outbound volume within the valid number of days. Temporary average daily outbound volume ; Preset abnormal threshold (Default 3), if the daily outbound volume > Then replace the outlier with Calculate the corrected total outbound volume (When there are no abnormalities) ); Calculate the corrected daily average consumption Combined with the preset minimum inventory days Maximum inventory days ,have to: Minimum inventory threshold (A value below this indicates an out-of-stock situation); Maximum inventory threshold (A value higher than this indicates stockouts or overstocking).

[0061] The processes described above with reference to the flowcharts in the embodiments disclosed in this invention can be implemented as computer software programs. The embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), it performs the functions defined in the methods of this application. It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wire segments, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless segments, wire segments, optical fibers, RF, etc., or any suitable combination thereof.

[0062] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0063] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are merely examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functions and structural principles of the present invention have been shown and explained in the embodiments. Without departing from the stated principles, the implementation of the present invention may have any variations or modifications.

Claims

1. A comprehensive management method for ERP warehouses, characterized in that, The method includes: Collect multi-source data from warehousing and generate structured datasets through standardized preprocessing; Based on structured datasets, initial storage location allocation parameters are obtained through a multi-parameter weighted adaptation algorithm. Inventory early warning parameters are obtained by combining the initial storage location allocation parameters with a time-series anomaly correction and threshold derivation algorithm. High-precision control parameters are generated through target screening. A full-process warehouse execution model is built based on high-precision control parameters, and business operation results are output. Based on the results of business operations, anomalies are identified through dynamic verification algorithms, and parameter correction instructions and system optimization data are generated. Input high-precision control parameters, system optimization data, and warehouse business scenario tags into the collaborative management model, and output warehouse management strategies adapted to the scenario.

2. The comprehensive management method for ERP warehouses according to claim 1, characterized in that, The specific process of obtaining the structured multi-source dataset is as follows: Collect business document data, basic inventory data, warehouse location characteristic data, and business configuration data, and unify the time format, quantity unit, and coding format; Delete data with abnormal time formats, data with logical conflicts, and redundant or irrelevant data; Complete the missing key fields of data, link document data with inventory change data through document code, and link storage location data with stored material data through storage location number, forming a structured multi-source dataset containing document identifiers, inventory details, storage location attributes, and control rules modules.

3. The comprehensive management method for ERP warehouses according to claim 2, characterized in that, The specific process for obtaining the initial storage location allocation parameters is as follows: Extract the remaining storage capacity, total volume of materials to be allocated, distance of storage location from inlet and outlet, and historical turnover rate of materials to be allocated from the structured multi-source dataset; The capacity fit is calculated by the ratio of the remaining capacity of the storage location to the total volume of the materials. The inbound efficiency is calculated by the reciprocal of the normalized distance from the storage location to the inbound entrance. The storage location fit score is calculated by combining the capacity fit weight and the inbound efficiency weight. The storage location with the highest fit score is selected as the target storage location. Based on the calculation logic of the inbound storage location suitability, the priority score of the outbound storage location is calculated by weighting the capacity suitability weight, outbound efficiency, and material turnover rate weight. After obtaining the score ranking, the recommended allocation quantity is determined by combining the actual inventory of each storage location. By integrating the priority ranking results of target inbound and outbound storage locations and their corresponding recommended allocation quantities, initial storage location allocation parameters are obtained.

4. The comprehensive management method for ERP warehouses according to claim 3, characterized in that, The specific process for obtaining the inventory early warning parameters is as follows: First, calculate the total number of recent holidays, then subtract the holiday days to obtain the effective statistical days for calculation. Calculate the total outbound volume of the material within the effective statistical period to obtain the average daily consumption during this period. Compare the daily outbound volume within the effective statistical period with the preliminary average daily consumption. If the outbound volume of a certain day exceeds the preset multiple of the average daily consumption, the data for that day is determined to be temporary abnormal data. Replace it with the preliminary average daily consumption. Based on the corrected daily outbound volume, recalculate the total outbound volume within the effective period to obtain the corrected average daily consumption. By combining the corrected average daily consumption with the pre-set minimum and maximum inventory days, we can calculate the lower inventory threshold for indicating stockout risk and the upper inventory threshold for indicating overstock risk. These two thresholds are then integrated with the corresponding target storage location and material association information to form inventory warning parameters.

5. A comprehensive management method for ERP warehouses according to claim 4, characterized in that, The specific process for obtaining the high-precision control parameters is as follows: Based on the inventory warning parameters, extract the inbound and outbound records of the material in the target storage location and the department-related data within the preset period. Use the ending inventory of the previous period as the beginning inventory, accumulate the total inbound and outbound volume that meets the warning threshold range, and calculate the ending inventory of the current period. Link department information to form the inbound, outbound and inventory statistics parameters. Inefficient warehouse location data with a fit lower than the preset value in the initial warehouse location allocation parameters, invalid original outbound records after abnormal correction in the inventory warning parameters, and scattered operation data of unrelated departments in the inbound, consumption and inventory statistics parameters are removed. The remaining initial warehouse location allocation parameters, inventory warning parameters, and inbound, consumption and inventory statistics parameters are integrated to form high-precision warehouse management parameters.

6. A comprehensive management method for an ERP warehouse according to claim 5, characterized in that, The specific process for obtaining the results of the business operation is as follows: Using high-precision warehouse management and control parameters as the core input, a full-process execution model covering the core business of warehousing is built. Input the actual warehousing business requirements into the warehousing full-process execution model to trigger the corresponding business processing flow in the model; After receiving inbound business requests, the inbound document management module processes the inbound document creation, inbound execution, and inbound confirmation processes in sequence. It also calls the initial storage location allocation parameters in the high-precision control parameters to filter target storage locations and outputs the inbound document status, actual inbound quantity, and corresponding target storage location information. After receiving outbound business requests, the outbound document management module processes outbound document creation, outbound allocation, outbound verification, and outbound confirmation in sequence. It also calls the initial storage location allocation parameters in the high-precision control parameters to match the outbound storage location, outputs the outbound document status, actual outbound quantity, and corresponding allocated storage location information, and integrates them to form a complete business operation result.

7. A comprehensive management method for ERP warehouses according to claim 6, characterized in that, The specific process for obtaining the parameter correction instruction is as follows: Compare the creation time of the inbound document with the generation time of the upstream purchase and return orders, and the creation time of the outbound document with the completion time of the corresponding inbound document. If there is a situation where the document time is earlier than the upstream order time or the outbound time is earlier than the inbound time, it is judged as a time sequence conflict anomaly, and a document time verification rule parameter correction instruction is generated. Check whether the actual inbound quantity is greater than 0 and does not exceed the pending inbound quantity, and whether the actual outbound quantity is greater than 0 and does not exceed the available inventory of the storage location. If they exceed the range, it is judged as a quantity invalidity anomaly, and a quantity verification threshold correction instruction is generated. Compare the actual remaining inventory in the storage location with the theoretically calculated value of the initial inventory ± actual inbound and outbound quantities. If the deviation exceeds the preset allowable range, it is determined to be an abnormal inventory data deviation, and an inventory calculation benchmark parameter correction instruction is generated.

8. A comprehensive management method for ERP warehouses according to claim 7, characterized in that, The specific process for obtaining the warehouse management strategy is as follows: Based on high-precision warehouse management parameters and system optimization data, and combined with warehouse business scenario tags, establish the relationship between data and scenarios; Build a collaborative management model and configure decision rules for different scenarios; Input data into the model and generate a scenario-based framework according to rules; integrate system optimization data to supplement details, forming a complete warehouse management strategy that includes applicable scenarios, execution rules, and data basis.

9. A comprehensive management system for ERP warehouses, characterized in that, The system is used to execute a comprehensive management method for an ERP warehouse as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the comprehensive management method for an ERP warehouse as described in any one of claims 1-8.

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