Near-efficiency period priority warehouse-out system and method based on big data analysis

Abstract

The application discloses a near-expiration-period preferential warehouse-out system and method based on big data analysis, which contains seven core modules of basic data storage, batch inventory management and control, expiration period grading marking, warehouse-out priority sorting, warehouse-out execution management and control, batch compliance traceability and big data statistics. The warehouse-out priority sorting module is internally provided with a queue packaging subunit. Through compliance pre-verification and a composite queue synthesis submodule, a composite structured queue with scheduling and compliance pre-judgment capabilities is generated. The expiration period grading marking module completes batch expiration period grading marking. The warehouse-out execution management and control module generates a picking and warehouse-out instruction in combination with order demand. The batch compliance traceability module realizes full-link GSP compliance verification. The big data statistical analysis module outputs various exportable reports. The application realizes automatic landing of the near-expiration-period preferential rule, synchronously bears scheduling and compliance pre-judgment capabilities, reduces manual intervention, reduces commodity scrap loss, meets GSP supervision and traceability requirements, and improves pharmaceutical warehouse management and control level.

Description

Technical Field

[0001] This invention relates to the field of pharmaceutical warehousing big data processing technology, and in particular to a near-expiry priority outbound system and method based on big data analysis. Background Technology

[0002] Pharmaceutical distribution companies and chain pharmacies must strictly adhere to GSP (Good Supply Practice) standards for pharmaceutical products and consumables warehousing management. Batch expiration date management is a core control aspect of warehousing operations. Existing pharmaceutical warehousing management systems can register incoming pharmaceuticals and consumables, record inventory ledgers, and save batch information. They can also display the expiration dates of goods in stock, and some systems have pop-up warning functions for near-expiration products.

[0003] However, existing technologies still have the following shortcomings in actual business execution: First, the existing system can only display the remaining expiration days for each batch and only provides page alerts. It does not output standardized, structured expiration date level labels that can be called by the outbound scheduling program. The batch outbound selection relies on manual judgment and selection by warehouse staff. In the scenario of multiple specifications and multiple batches of inventory, manual operation can easily skip batches with near expiration dates and prioritize the outbound of medicines with longer expiration dates, resulting in the accumulation of near-expiration products and increasing the risk of medicines expiring and being wasted.

[0004] Second, the existing warehousing system lacks an automated batch sorting logic that prioritizes expiration date and secondarily considers inbound time. It only supports simple date sorting of the inventory list, and the sorting results are only for page viewing. It cannot generate a composite structured priority queue for scheduling and embedding compliance tags, and it cannot force the sorting results into the outbound picking business process. The control rule of prioritizing near-expiration dates is only at the prompt level and cannot be implemented as an automated business action.

[0005] Third, in the existing outbound process, the allocation between order demand and multiple batches of inventory is done manually. The system does not automatically deduct the consumed inventory batch by batch according to the preset priority order. Manual allocation of batches is prone to mismatch, which not only increases the loss of expired drugs, but also makes it difficult to meet the compliance management requirements of GSP for priority outbound of drugs nearing their expiration date.

[0006] Fourth, most existing traceability systems only retain inbound and outbound data in a simple manner, lacking deep integration with the pre-compliance prediction link of the outbound queue. They cannot rely on the built-in risk markers in the queue to carry out automated pre-interception, and can only perform verification on outbound data afterward. At the same time, the two types of verification logic are isolated from each other and lack a two-layer bottom-line control mechanism. In addition, the report export of existing systems only performs general inventory statistics and does not simultaneously read the queue compliance markers or aggregate multi-source big data for integrated risk output.

[0007] In summary, the current pharmaceutical warehousing system relies mainly on manual intervention for expiration date control, lacking a complete closed-loop technical solution that integrates expiration date marking, automatic sorting, composite compliance queue generation, automatic batch allocation, and pre- and post-event dual compliance verification. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of existing technologies, such as the tendency for manual selection of outbound batches to lead to the backlog and scrapping of near-expiry products, the inability of expiry date warnings to drive outbound operations, the fact that compliance verification is only conducted after the fact, the lack of a complete automated closed-loop link with composite scheduling queues, and the inability to uniformly collect risk data. This invention provides a near-expiry priority outbound system and method based on big data analysis, which realizes the automatic marking of medicines and consumables based on expiry date levels, automatic sorting of batch priorities, generation of composite queues with embedded compliance marks, automatic allocation of picking batches by queue, and completion of full-link GSP dual compliance verification. It also synchronously aggregates multi-dimensional data on expiry date, compliance, and outbound to output risk reports.

[0009] To achieve the above-mentioned technical objectives, the technical solution adopted by the present invention is as follows: The near-expiry priority outbound system based on big data analysis includes a basic data storage module, a batch inventory management module, an expiry date classification and marking module, an outbound priority sorting module, an outbound execution management module, a batch compliance traceability module, and a big data statistical analysis module. The basic data storage module is used to store basic drug records, basic medical consumable records, warehousing institution data, supplier records, GSP regulatory rules data, and lists of products subject to sales suspension and control. The batch inventory management module is used to input and maintain the warehousing information, real-time inventory quantity, batch number information, expiration date information, and storage location information of each batch of medicines and consumables, and to respond to warehousing, outbound, transfer, damage reporting, and inventory count business instructions to complete the corresponding batch inventory data changes. The expiration date grading and marking module is used to read the expiration date information of batches of drugs and consumables in stock, and to mark the expiration date grades of the batches in stock according to the preset multi-level expiration date thresholds. The outbound priority sorting module is used to obtain the expiration grade, batch number, inventory quantity, and entry time data of all in-stock batches under the same product specification. It sorts the inventory batches of drugs and consumables of the same product specification according to the main sorting rule of expiration date from near to far, and performs GSP compliance prediction in advance to generate a composite structured outbound priority queue with scheduling and prediction attributes. The outbound execution control module is used to receive various types of outbound orders issued from outside, call the outbound priority queue that matches the corresponding goods, and generate picking and outbound instructions based on the demand of goods in the outbound order and the outbound priority queue. The batch compliance traceability module is used to collect full-chain node data of outbound batches at each stage of warehousing, in-warehouse circulation, and outbound, associate it with electronic supervision code information, and perform compliance verification of the full-chain node data in accordance with GSP regulatory rules. The big data statistical analysis module is used to aggregate raw data on inventory, expiration date, outbound shipment, and compliance verification, and output inventory reports, expiration date early warning reports, and outbound shipment detail reports, and supports report export operations.

[0010] Using the above technical solution, the basic data storage module centrally stores basic business files and regulatory rules, providing a unified data source for the entire system. The batch inventory management module maintains inventory data for all batches of drugs and consumables, ensuring the accuracy of basic batch information. The expiration date grading and marking module marks batch expiration dates based on multi-level thresholds, outputting standardized marked data to provide a basis for subsequent sorting. The outbound priority sorting module sorts batches based on expiration date and warehousing time, conducts pre-emptive GSP compliance prediction, and integrates basic fields and compliance marks to generate a composite structured outbound priority queue, transforming near-expiration priority rules and compliance constraints into callable business data. The outbound execution management module calls the composite structured queue to automatically generate picking and outbound instructions, realizing automatic allocation of outbound batches according to expiration date priority. The batch compliance traceability module completes full-link data collection, regulatory code association, and post-event GSP compliance verification, forming a dual management system of pre-emptive queue prediction and post-outbound verification to meet pharmaceutical regulatory requirements. The big data statistical analysis module aggregates multi-source data and can export reports, realizing integrated statistical output of warehousing business data and constructing a complete business closed loop of expiration date marking, sorting, compound queue generation, outbound, dual compliance traceability, and risk data statistics.

[0011] Furthermore, the expiration date grading and marking module includes a threshold configuration unit, an expiration date calculation unit, and a grade marking unit; The threshold configuration unit is used to receive user-defined configuration operations and save multi-level expiration thresholds. The multi-level expiration thresholds include near-expiration warning thresholds, near-expiration thresholds, and expired thresholds. Different types of thresholds can be set independently for drugs and consumables. When a threshold is modified, the expiration level of the existing batches in stock is recalculated. The expiration date calculation unit is used to read the expiration date information of the batches of medicines and consumables output by the batch inventory control module, calculate the remaining validity period of each batch in the warehouse in combination with the current system time, and filter out the batch data that has been determined to be expired. The grade labeling unit is used to receive the remaining valid duration output by the expiration date calculation unit, complete the batch expiration date grade determination based on the multi-level expiration date threshold, assign the corresponding in-stock batch expiration date grade label, complete the binding of batch number and specification identifier, and output the batch data after binding to the outbound priority sorting module.

[0012] Using the above technical solution, the threshold configuration unit allows users to customize and maintain multi-level expiration thresholds for pharmaceuticals and consumables, including near-expiration warnings, close to expiration dates, and expired dates. This adapts to the differences in expiration date control for different product categories. Furthermore, after adjusting the control threshold parameters, it can automatically trigger the recalculation of the expiration date level for existing batches in stock, eliminating the need for manual batch operations and adapting to scenarios involving changes in enterprise expiration date control standards. The expiration date calculation unit calculates the remaining validity period for each batch based on the system time and filters expired batches to prevent expired data from participating in subsequent outbound calculations. The grade labeling unit determines the expiration date level based on the remaining validity period, generates standardized expiration date level labels, and binds them to batch numbers and product specifications. This transforms the expiration dates, which were originally only viewable manually, into structured label data that the program can recognize, and outputs it to downstream modules. This achieves flexible configuration of expiration date conditions, automatic adaptation and updates after threshold changes, and pre-filtering of expired data, providing a standardized input basis for expiration date judgment in outbound priority ranking.

[0013] Furthermore, the grade labeling unit includes a threshold comparison subunit, a tag binding subunit, and a data forwarding subunit; The threshold comparison subunit is used to receive the remaining valid duration output by the expiration calculation unit, and compare the remaining valid duration with the near-expiration warning threshold, the near-expiration threshold, and the expired threshold respectively to determine the expiration level to which the corresponding batch in stock belongs; The label binding subunit is used to generate a corresponding expiration grade label based on the expiration grade obtained from the threshold comparison subunit, and to associate and bind the expiration grade label with the batch number and specification identifier of the corresponding batch. The data forwarding subunit is used to receive batch data that has been associated and bound, perform formatting processing on the batch data, and output the formatted batch data carrying expiration date label, batch number, and product specification identifier to the outbound priority sorting module.

[0014] Using the above technical solution, the threshold comparison subunit compares the remaining validity period of each batch with various thresholds to accurately determine the expiration date level of each batch in stock. The label binding subunit generates expiration date level labels and associates these labels with batch numbers and specification identifiers, thus linking expiration date attributes with business batch information. The data forwarding subunit formats the bound batch data and outputs it to the downstream outbound priority sorting module after unifying the data format. This solution breaks down the expiration date labeling process, completing expiration date level determination, label binding, and standardized output, providing the downstream sorting module with a batch data source that is uniformly formatted and complete in information, ensuring the reliable execution of subsequent priority sorting operations.

[0015] Furthermore, the outbound priority sorting module includes a batch data acquisition unit, a primary and secondary rule sorting unit, and a priority queue generation unit; The batch data acquisition unit is used to receive batch data with expiration grade label, batch number and product specification identifier output by the expiration date grading marking module, and pull the inventory quantity and warehousing time data of the corresponding batch, and collect all valid in-stock batch data under the same product specification. The primary and secondary sorting unit is used to sort batches under the same specification by using the expiration date from nearest to furthest as the primary sorting rule, and to sort batches with the same expiration date level by using the order of entry into the warehouse as the secondary sorting rule for secondary sorting. The priority queue generation unit is used to receive the batch sequence processed by the main and auxiliary rule sorting unit, filter out zero-inventory batches and perform GSP compliance judgment in advance, integrate basic business fields and compliance tags, and generate a composite structured outbound priority queue that can be called by the outbound execution control module. The generated composite structured outbound priority queue supports short-term cache reuse.

[0016] Using the above technical solution, the batch data acquisition unit collects multi-dimensional data such as expiration date labels, inventory, and warehousing time for all valid batches of the same product specification, completing the data preparation work before sorting. The primary and secondary rule sorting unit uses the expiration date level as the primary sorting criterion, and then sorts based on the warehousing time when the expiration date levels are the same, realizing multi-dimensional joint sorting and avoiding the unreasonable outbound issues caused by a single sorting condition. The priority queue generation unit filters invalid batches with available inventory, synchronously calls regulatory rules to complete the pre-compliance judgment, and integrates inventory information and compliance tags to generate a composite structured queue. The generated composite structured outbound priority queue supports short-term caching and reuse. In the face of multi-order concurrent scenarios, existing queue results can be directly reused to avoid repeated sorting and compliance judgment calculations, improving the system's order processing response efficiency. The dual constraints of prioritizing near-expiration dates and compliance interception are transformed into business-executable data objects, opening up the data link between expiration date tags and outbound execution, and providing standardized batch priority and risk dual basis for subsequent automatic picking and outbound.

[0017] Furthermore, the primary and secondary rule sorting unit includes a primary rule sorting subunit, a secondary sorting subunit of the same level, and a sequence output subunit; The main rule sorting subunit is used to sort all valid in-stock batches of the same specification in the batch data according to the expiration date level label in the batch data, with the expiration date from the nearest to the furthest. The same-level secondary sorting subunit is used to filter batches with the same expiration date level label after the first round of sorting, and complete the secondary sorting according to the order of the batch's entry time. The sequence output subunit is used to organize the same-specification batches after the first round of sorting and the second round of sorting into an ordered batch sequence, and output the ordered batch sequence to the priority queue generation unit.

[0018] Using the above technical solution, the main rule sorting subunit directly completes the first round of sorting based on the expiration date level label, establishing the basic outbound priority of batches based on their expiration dates, unlike the method of directly comparing the original expiration dates. The secondary sorting subunit for batches with the same expiration date level performs a second sorting based on the warehousing time, resolving the issue of uncertain outbound order for batches within the same expiration date level. The sequence output subunit organizes the batches that have undergone two rounds of sorting into a standardized ordered batch sequence and outputs it to the downstream priority queue generation unit. This solution decomposes the complex sorting logic into two levels of sorting and output steps, ensuring that the sorting logic is executed hierarchically and outputting a structurally well-structured batch sequence, providing a reliable ordered data source for subsequent encapsulation of the outbound priority queue.

[0019] Furthermore, the priority queue generation unit includes an inventory verification subunit, a queue encapsulation subunit, and a queue output subunit; The inventory verification subunit is used to receive the ordered batch sequence output by the sequence output subunit, read the available inventory quantity of each batch in the ordered batch sequence, and filter out batches with zero available inventory quantity. The queue encapsulation subunit is used to bind the batches that have passed inventory verification to the corresponding batch's expiration date label, batch number, product specification identifier, and available inventory quantity, and encapsulate them to form a structured queue carrier. The queue output subunit is used to publish the encapsulated composite structured outbound priority queue to the outside world for the outbound execution control module to call. The published composite structured outbound priority queue supports short-term caching.

[0020] Using the above technical solution, the priority queue generation unit completes ordered batch filtering and composite queue encapsulation output through the division of labor among three levels of sub-units. The inventory verification sub-unit removes invalid batches with zero inventory in advance, reducing the data calculation workload of subsequent encapsulation and scheduling, and avoiding empty batches from interfering with the outbound allocation logic. The queue encapsulation sub-unit uniformly integrates core business information such as batch expiration date, batch number, and inventory to form a standardized structured queue carrier, providing a unified and regular data interaction format for downstream modules. The queue output sub-unit publishes the formed composite structured outbound priority queue and performs short-term caching, realizing data decoupling between the sorting link and the outbound execution link. Within the cache validity period, the outbound execution module can directly call the cached queue of the corresponding product specification as needed, without repeating sorting and encapsulation calculations, which greatly improves the outbound order response speed in multi-order concurrent scenarios, while realizing the standardization and reusability of batch scheduling data.

[0021] Furthermore, the queue encapsulation subunit includes a compliance pre-verification subunit and a composite queue synthesis subunit; The compliance pre-verification submodule is used to call the GSP regulatory rules and the list of products to be discontinued stored in the basic data storage module, to conduct a pre-shipment compliance judgment on batches that have passed inventory verification, to simultaneously review the validity period information of the batches, and to generate a compliance mark field that includes an interception identifier and a near-expiration risk warning level. The composite queue synthesis submodule is used to bind the basic business fields of each batch's expiration date label, batch number, product specification identifier, and available inventory quantity, and integrates the basic business fields with the compliance mark fields output by the compliance pre-verification subunit to generate a composite structured outbound priority queue that simultaneously possesses outbound sorting and scheduling attributes and GSP compliance prediction attributes.

[0022] By adopting the above technical solution, compliance verification is moved to the queue encapsulation stage and separated into independent sub-modules, achieving integrated outbound scheduling and risk prediction. The compliance pre-verification sub-module retrieves regulatory rules and the list of discontinued products to screen batches in advance, and also simultaneously reviews the batch expiration information. It provides a fallback identification for expired batches that may have been missed in the earlier expiration grading stage, generating interception and risk grading tags, eliminating the need to wait until the outbound or traceability stage to discover violations. The composite queue synthesis sub-module integrates basic inventory information and compliance identifiers to form a new composite queue. The downstream picking module can directly read risk information to intercept discontinued products, high near-expiration risks, and expired batches in advance. This layered and decoupled architecture facilitates independent iteration of GSP rules without modifying the sorting and outbound logic. It avoids non-compliant outbound behavior from the source, reduces the risk of drug regulatory rectification, strengthens the control of mandatory outbound products with near-expiration dates, reduces the workload of manual verification, and improves the foundation for full-chain compliance data traceability.

[0023] Furthermore, the outbound execution control module includes an order receiving unit, a queue matching and calling unit, a picking instruction generation unit, and an outbound document output unit; The order receiving unit is used to receive multiple types of outbound orders issued from outside, including split outbound orders, and to extract product specifications and product demand information from the outbound orders. The queue matching and calling unit is used to call the outbound priority queue of the corresponding product generated and cached by the outbound priority sorting module according to the extracted product specifications. The picking instruction generation unit is used to generate picking instructions containing batch, storage location, and picking quantity information by deducting the available inventory of the corresponding batch in the order of the outbound priority queue according to the demand quantity of goods in the outbound order. Manual changes to the batch outbound order are prohibited during the picking instruction generation process. The outbound document output unit is used to output outbound business documents corresponding to the picking and outbound instructions.

[0024] Using the above technical solution, the order receiving unit receives various outbound orders, including split-order outbound orders, and parses out the product specifications and demand quantities to complete the data access for outbound operations. The queue matching and calling unit retrieves the corresponding composite structured outbound priority queue according to the product specifications, realizing the association and matching of order with batch priority and compliance risk data. The picking instruction generation unit strictly deducts available inventory according to the batch order preset by the composite queue. Manual changes to the batch outbound order are prohibited during the picking instruction generation process, eliminating the risk of manually skipping near-expiry batches. It simultaneously identifies built-in interceptions and risk markers in the queue, generating picking outbound instructions with batch, storage location, and risk warnings. This implements the dual rules of prioritizing near-expiry batches and intercepting discontinued sales into directly executable picking operation instructions, eliminating the reliance on manual batch selection. The outbound document output unit simultaneously outputs outbound business documents to meet the archiving needs of warehousing operations. All units collaborate to transform composite queue data into actual outbound operation data, realizing automated flow from order receiving to picking document output, ensuring that the rules of prioritizing near-expiry batches and intercepting compliance are enforced in outbound operations.

[0025] Furthermore, the batch compliance traceability module includes a link data acquisition unit, a regulatory code association unit, a GSP compliance verification unit, and a traceability data storage unit; The link data acquisition unit is used to collect batch business node data in the warehousing process, the internal circulation process, and the outbound process, and to obtain the operation time, operation type, and batch identification information corresponding to each business node. The regulatory code association unit is used to bind and associate the collected batch business node data with the corresponding electronic regulatory code information of drugs and consumables; The GSP compliance verification unit is used to call the GSP regulatory rule data stored in the basic data storage module to perform compliance comparison and verification on the full-link node data after binding the electronic supervision code. The verification items include whether the outbound batch matches the outbound priority queue sorting order. The traceability data storage unit is used to store full-chain batch traceability data that has been verified for compliance.

[0026] Using the above technical solution, the link data acquisition unit collects business nodes, operation times, and batch identification information throughout the entire process of warehousing, in-warehouse circulation, and outbound, comprehensively aggregating all original data of batch circulation. The regulatory code association unit binds business node data with electronic regulatory codes, achieving a one-to-one correspondence between business circulation records and regulatory code information. The GSP compliance verification unit calls pre-stored GSP regulatory rules to automatically conduct compliance comparison verification on the entire link data after binding the regulatory code, specifically verifying whether the actual outbound order of the outbound batches is consistent with the sorting order of the outbound priority queue. It can identify abnormal outbound behaviors such as skipping near-expiration batches, forming dual control with pre-queue prediction, going beyond simple data archiving. The traceability data storage unit saves the verified full-link batch traceability data, providing data support for subsequent regulatory verification and problem tracing. The various units cooperate with each other to connect the near-expiration outbound business with the subsequent compliance traceability link, achieving dual compliance control of pre-judgment and post-verification, meeting the regulatory traceability requirements of the pharmaceutical industry.

[0027] The method of prioritizing near-expiry products based on big data analysis includes the following steps: S1. Basic Data Storage: The basic data storage module stores basic drug records, basic medical consumable records, warehousing organization data, supplier records, GSP regulatory rules data, and the list of products subject to sales restrictions. S2. Batch Inventory Maintenance: The batch inventory management module is used to input and maintain the warehousing information, real-time inventory quantity, batch number information, expiration date information, and storage location information for each batch of medicines and consumables. It responds to warehousing, outbound, transfer, damage reporting, and inventory count business instructions to complete the corresponding batch inventory data changes. When the multi-level expiration date threshold is modified, the expiration date level of the existing batch is automatically recalculated. S3, Expiry Date Grading Marking: The expiry date grading marking module reads the expiry date information of batches of drugs and consumables in stock, performs expiry date grading marking on the batches in stock according to the preset multi-level expiry date thresholds, and outputs batch data carrying expiry date grading labels; S4. Outbound queue generation: The outbound priority sorting module sorts batches by expiration date first and entry time second. After filtering out zero-inventory batches, it performs GSP compliance verification in advance, reviews the batch expiration date and generates risk markers, integrates business fields and compliance identifiers, and generates a composite structured priority queue with dual attributes of outbound scheduling and compliance prediction. The composite structured priority queue is cached for a short time for reuse. S5. Picking Instruction Generation: The outbound execution control module receives multiple types of outbound orders from external sources, including split outbound orders. It calls the outbound priority queue that matches the corresponding product cache, and generates picking and outbound instructions based on the product demand of the outbound order and the outbound priority queue. Manual changes to the batch outbound order are prohibited during the process of generating picking and outbound instructions. S6. Full-chain compliance traceability: The batch compliance traceability module collects full-chain node data of each stage of the batch from warehousing, internal circulation and outbound, associates it with electronic supervision code information, and performs compliance verification on the full-chain node data according to GSP supervision rules, and verifies whether the outbound batch matches the composite structured priority queue sorting order. S7. Statistical Report Output: The big data statistical analysis module aggregates raw data on inventory, expiration date, outbound shipment, and compliance verification, and outputs inventory reports, expiration date warning reports, and outbound shipment detail reports, and supports report export operations.

[0028] The above technical solution achieves automated dual compliance control across the entire pharmaceutical warehousing process through the linkage of various modules. First, it uniformly stores basic and regulatory data for all product categories, ensuring consistent business data benchmarks and maintaining batch inventory in real time to guarantee accurate inventory information. When expiration date control thresholds are adjusted, it automatically triggers a recalculation of the expiration date level of existing batches, eliminating the need for manual batch processing. It automatically labels expiration date levels using multi-level thresholds, quantifying expiration date risks. After sorting, it performs GSP compliance screening and simultaneously reviews batch expiration dates, forming a dual-layer protection for expired batches. It integrates business and risk fields to generate a composite structured queue and performs short-term caching for reuse. In multi-order concurrent scenarios, queue results can be directly reused, reducing redundant calculations and embedding scheduling and compliance constraints into the outbound source. It is adaptable to various outbound business types, including split-order outbound orders, automatically allocating picking batches based on the composite queue. The picking instruction generation process prohibits manual changes to the batch outbound order, simultaneously identifying discontinued and near-expiration risks, and eliminating manual skipping of near-expiration dates and illegal outbound operations through process mechanisms. The entire process involves collecting and transferring data, linking it with regulatory codes for post-event verification. The post-event verification checks whether the actual outbound batches match the sorting order of the composite structured priority queue, forming a closed loop of pre-emptive judgment and post-event verification. Multi-source data fusion outputs multi-dimensional risk reports. This entire process significantly reduces manual intervention, proactively intercepts non-compliant outbound behaviors, rigidly implements GSP (Good Supply Practice) near-effect first-out regulations, reduces the risks of drug waste disposal and regulatory inspection rectification, and comprehensively improves the level of digital and compliant automated management of warehousing.

[0029] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention constructs an expiration date grading and marking module, which transforms the original expiration date information into a machine-parseable structured expiration date grade label, realizes automatic batch expiration date identification, and supports automatic recalculation of the expiration date grade label of existing batches after the expiration date control threshold is modified. It adapts to the dynamic adjustment needs of enterprise control standards, weakens the dependence of warehousing operations on human experience, and reduces the business risk of near-expiration goods backlog and scrapping from the data source.

[0030] 2. This invention designs a composite rule-based outbound priority sorting mechanism, encapsulates and outputs a standardized outbound queue that supports short-term caching and reuse, and allows direct reuse of queue results in multi-order concurrent business scenarios, avoiding redundant calculations, improving system processing efficiency, realizing the sinking of expiration date control logic to the business scheduling layer, providing a standardized batch priority data source for the outbound process, and opening up the data path from expiration date determination to outbound execution.

[0031] 3. This invention achieves order matching with priority queues and automated allocation of inventory batches through the outbound execution control module. It can adapt to various types of outbound operations, such as split-out outbound. Manual changes to the batch outbound order are prohibited during the picking instruction generation stage. The control logic of prioritizing near-expiry dates is solidified into picking operation instructions that are enforced by the system, ensuring that GSP-related management requirements are stably implemented in outbound operations and improving the accuracy of outbound batch allocation.

[0032] 4. This invention innovatively separates compliance pre-verification and composite queue dual-module in the queue packaging stage, and sets up a two-layer expiration interception mechanism with expiration date classification filtering and queue expiration date review. GSP compliance prediction is embedded into the scheduling queue in advance, and the ability to sort and mark risks in warehousing is carried out simultaneously. It no longer relies solely on post-warehousing traceability verification, but can identify high-risk batches that are discontinued, expired, or near expiration in advance and achieve pre-warehousing interception. It also outputs complete compliance traceability fields, which greatly reduces the risks of post-event rectification and drug regulatory inspections.

[0033] 5. This invention links batch traceability with the outbound business process, collects full-chain flow data and binds it to electronic supervision codes, and conducts automated GSP compliance verification. The verification process can check whether the actual outbound batch order matches the outbound priority queue sorting, and can identify non-compliant outbound situations such as skipping near-expiry batches and retain abnormal records, which is convenient for regulatory verification and internal quality review.

[0034] 6. The big data statistics module of this invention integrates multi-source business data and outputs four types of reports in one integrated manner: inventory, expiration date warning, outbound details, and compliance risk statistics. This enriches the data dimensions of warehouse management, intuitively displays the distribution of quality risks across the entire warehouse, and provides complete data support for inventory optimization and quality risk prediction.

[0035] 7. This invention is equipped with a complete seven-step standardized business method, which corresponds one-to-one with the system modules. The entire closed-loop process integrates expiration date classification, sorting and scheduling, double-layer expiration interception, pre-compliance screening, automatic picking that supports splitting and dispatching, full-link verification, and data statistics. It can be adapted to both pharmaceutical and consumable warehousing, and comprehensively improve the level of digital, compliant and automated management of pharmaceutical warehousing. Attached Figure Description

[0036] The present invention can be further illustrated by the non-limiting embodiments given in the accompanying drawings; Figure 1 This is a schematic diagram of the overall architecture of the near-expiry priority outbound system based on big data analysis of the present invention; Figure 2 This is a flowchart illustrating the internal data flow of the shelf-life grading and marking module of this invention. Figure 3 This is a flowchart of the internal processing of the outbound priority sorting module of the present invention; Figure 4 This is a schematic diagram of the internal subdivision structure of the priority queue generation unit of the present invention; Figure 5 This is a flowchart illustrating the internal processing of the outbound execution control module of the present invention. Figure 6 This is a schematic diagram of the internal structure of the batch compliance traceability module of the present invention; Figure 7 This is a schematic diagram illustrating the steps of the near-expiry priority delivery method based on big data analysis of the present invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0038] like Figure 1 As shown, the near-expiry priority outbound system based on big data analysis described in this invention consists of seven core modules: a basic data storage module, a batch inventory management module, an expiry date grading and marking module, an outbound priority sorting module, an outbound execution management module, a batch compliance traceability module, and a big data statistical analysis module. These modules work collaboratively through a data flow chain: basic data support, batch inventory maintenance, expiry date grading and marking, composite queue generation, picking instruction execution, dual compliance traceability, and statistical report output. This forms a complete closed-loop technical solution from expiry date marking, automatic sorting, embedded compliance marking composite queue generation, automatic batch allocation, to dual-dimensional compliance traceability.

[0039] The basic data storage module provides unified and standardized underlying data support for the entire system. It employs a hybrid architecture deployment combining a relational database with a big data storage platform, and all data retains complete change logs and operation traces. This module stores six types of core basic data: The first category is basic drug information, which includes information such as drug specification code, generic name, dosage form, specifications, manufacturer, approval number, and storage conditions. The second category is basic data on consumables, which includes information such as the product code, name, specifications, manufacturer, and registration certificate number of the consumables. The third category is warehousing organization data, which includes warehousing space information such as warehouse area number, warehouse area name, warehouse location number, shelf number, and storage location number; The fourth category is supplier profile data, which includes information such as supplier name, unified social credit code, business license number, license validity period, and scope of supply; The fifth category is GSP regulatory rules data, including rules for determining near-expiration dates, rules for discontinuing drug sales, standards for evaluating qualified suppliers, rules for incoming goods inspection, rules for outgoing goods verification, and rules for handling non-conforming products; The sixth category is the list of drugs subject to sales suspension and control, which includes the list of drugs suspended from sale issued by the National Medical Products Administration, the blacklist of drugs suspended from sale as determined by the company's internal management, and the list of suppliers with substandard quality.

[0040] This module provides data query and retrieval services to other modules through standardized data interfaces. All basic data supports CRUD operations and retains a complete data change log.

[0041] This module serves as the single data source for the entire system, its core value lying in ensuring consistency in the versions and sources of basic information accessed by all modules. Drug and consumable records provide a specification matching benchmark for the batch inventory management module, while warehousing facility data provides location information association for the same module. GSP regulatory rules and discontinued product lists provide dual verification basis for the compliance pre-verification sub-module and batch compliance traceability module within the queue encapsulation sub-unit. The basic data storage module centralizes and standardizes the management of dispersed basic information, eliminating data inconsistencies that may arise from independent maintenance of basic data by each module, and providing a reliable data foundation for the execution of business logic in downstream modules.

[0042] The batch inventory management module is responsible for the full lifecycle management of drug and consumable batch inventory and serves as the real-time maintenance entry point for the system's business data. This module inputs and maintains five core data categories for each drug and consumable batch: inbound information, real-time inventory quantity, batch number information, expiration date information, and warehouse location information. Inbound information includes inbound order number, inbound date, inbound quantity, and supplier; batch number information includes production batch number and production date; expiration date information includes expiration date and expiration duration; and warehouse location information includes the current storage area number, shelf number, and storage location number for that batch.

[0043] This module responds to five business commands: inbound, outbound, transfer, damage reporting, and inventory count, completing real-time updates to the corresponding batch inventory data. When an inbound command is triggered, the module adds a new batch inventory record and writes the inbound information. When an outbound command is triggered, the module deducts the available inventory quantity for the corresponding batch. When a transfer command is triggered, the module updates the warehouse location information for the batch. When a damage reporting command is triggered, the module marks part or all of the corresponding batch's inventory as damaged and deducts the available inventory. When an inventory count command is triggered, the module corrects the inventory quantity based on the actual inventory count results. All inventory change operations generate operation logs with timestamps and operator information. This module has a data association with the basic data storage module. Batch data calls basic information such as drug files and consumable files in the basic data storage module through specification codes, ensuring that the specification description of the batch data is consistent with the basic files.

[0044] This module is the only one in the system responsible for maintaining real-time inventory data. The batch expiration date information, batch number information, and warehouse location information it maintains directly provide data input for the expiration date grading and marking module and the outbound execution control module. This module completes real-time updates to inventory data by responding to five types of business instructions, ensuring that the inventory data in the system is consistent with the actual warehousing situation. The expiration date information output by this module is the original data source for the expiration date grading and marking module to determine the expiration date level, and the warehouse location information output by it is the source of the location information when the outbound execution control module generates picking and outbound instructions. The accuracy and real-time performance of the data in this module directly determine the reliability of the processing results of subsequent modules.

[0045] The expiration date grading module is the primary component of this invention for automating the priority release of near-expiration batches. Its core function is to transform expiration date information, which was originally only viewable manually, into structured expiration date grading tags that the program can recognize, while simultaneously completing the first layer of interception for expired batches. Figure 2 As shown, the module consists of three parts: a threshold configuration unit, an expiration date calculation unit, and a grade marking unit. Each unit performs data processing sequentially.

[0046] The threshold configuration unit receives user-defined configuration operations and saves multi-level expiration thresholds. These multi-level thresholds include three types: near-expiration warning threshold, near-expiration threshold, and expired threshold. Taking pharmaceuticals as an example, users can set the near-expiration threshold to 180 days (marking products with ≤180 days remaining as near-expiration), the near-expiration warning threshold to 90 days (marking products with ≤90 days remaining as near-expiration), and the expired threshold to 0 days (marking products with ≤0 days remaining as expired). Different threshold types can be set independently for pharmaceuticals and consumables, as the expiration management requirements for pharmaceuticals and consumables differ. Pharmaceuticals typically require stricter expiration control, while some consumables have relatively more lenient expiration management. After threshold configuration, this unit persistently stores the configuration data. If a user modifies any threshold parameter, the system automatically triggers a recalculation of the expiration dates for all batches in the inventory, synchronously updating the expiration level labels for all batches, eliminating the need for manual batch operations.

[0047] The expiration date calculation unit reads the expiration date information of medicines and consumables batches output by the batch inventory control module, combines it with the current system time, calculates the remaining validity period of each batch in stock, and filters out batches that have been determined to be expired. The formula for calculating the remaining validity period is: Remaining validity period = Expiration date - Current system date, with the result in days. For example, if a batch's expiration date is December 31, 2026, and the current system date is June 30, 2026, then the remaining validity period is 184 days. After calculation, this unit marks batches with a remaining validity period of <0 days as expired and filters them out, achieving the first layer of expiration interception. These expired batches do not participate in subsequent outbound priority sorting and picking allocation, reducing invalid data calculations from the source.

[0048] The grade labeling unit receives the remaining valid duration output by the expiration date calculation unit, determines the batch expiration date grade based on multi-level expiration date thresholds, assigns corresponding expiration date grade labels to the batches in stock, and binds the batch number and specification identifier. The grade labeling unit is further divided into three sub-units: a threshold comparison sub-unit, a label binding sub-unit, and a data forwarding sub-unit.

[0049] The threshold comparison subunit receives the remaining valid duration output by the expiration calculation unit and compares it with the near-expiration warning threshold, the near-expiration threshold, and the expired threshold to determine the expiration level of the corresponding batch in stock. The comparison logic is as follows: If the remaining valid duration ≤ the expired threshold (usually 0 days), it is determined to be expired. If the expired threshold < the remaining valid duration ≤ the near-expiration warning threshold (90 days), it is determined to be near-expiration. If the near-expiration warning threshold < the remaining valid duration ≤ the near-expiration threshold (180 days), it is determined to be near-expiration. If the remaining valid duration > the near-expiration threshold, it is determined to be normal. Taking a batch with a remaining valid duration of 120 days, a near-expiration threshold of 180 days, and a near-expiration threshold of 90 days as an example, if the remaining valid duration ≤ the near-expiration threshold and the remaining valid duration > the near-expiration threshold, it is determined to be near-expiration.

[0050] The label binding sub-unit generates corresponding expiration grade labels based on the expiration grade obtained from the threshold comparison sub-unit, and associates these labels with the batch number and specification identifier of the corresponding batch. The expiration grade labels use a standardized Chinese enumeration value format, including four levels: Normal, Near Expiration, Approaching Expiration, and Expired. Near Expiration indicates that the remaining validity period is close to the near-expiration warning threshold; Near Expiration indicates that the remaining validity period is within the near-expiration threshold range; Expired indicates that the remaining validity period has reached zero or is negative; and Normal indicates that the remaining validity period is still above the near-expiration threshold. After label binding is completed, each batch record carries the three elements of specification identifier, batch number, and expiration grade label, forming structured batch expiration date data.

[0051] The data forwarding subunit receives batch data that has been associated and bound, performs format standardization on the batch data, and outputs the standardized batch data, carrying expiration date labels, batch numbers, and product specification identifiers, to the outbound priority sorting module. Format standardization includes: standardizing date formats, standardizing numerical precision, filling in missing fields, and verifying data integrity.

[0052] This module is one of the key innovations that distinguishes this invention from existing systems. Existing systems only display expiration dates on a page or provide pop-up warnings; the expiration date determination results remain at the user interface level and cannot be accessed by backend business logic. They also do not support automatic updates to the expiration date determination results of existing batches after adjustments to control thresholds. This module, through the collaborative processing of three units—threshold configuration, expiration date calculation, and grade labeling—not only automatically recalculates the expiration date grade of existing batches when threshold parameters change, but also achieves first-level pre-interception of expired batches. It transforms the expiration date information, which was originally only viewable manually, into structured expiration date grade tags that the program can recognize. These expiration date grade tags, as structured enumerated value data, can be directly called and parsed by the downstream outbound priority sorting module, enabling automated batch expiration date determination without manual intervention. This fundamentally solves the technical problems of existing systems where expiration date warnings cannot drive outbound operations and where changes to control standards require manual batch maintenance of batch tags.

[0053] The outbound priority sorting module is the core component of this invention for automating near-expiry priority outbound operations. Its function is to convert the structured expiry date data output by the expiry date grading and marking module into an outbound priority queue that can be directly used by outbound operations. It includes a second layer of overdue interception, such as... Figure 3 , Figure 4 As shown, this module consists of three parts: a batch data acquisition unit, a primary and secondary rule sorting unit, and a priority queue generation unit.

[0054] The batch data acquisition unit receives batch data from the expiration date grading module, which includes expiration date labels, batch numbers, and product specification identifiers. It then retrieves the corresponding batch's inventory quantity and warehousing time data, aggregating all valid in-stock batches under the same product specification. This unit's aggregation operation uses the product specification code as the key, combining all valid batches belonging to the same specification into a batch dataset, providing complete input data for subsequent sorting. During aggregation, this unit also verifies the completeness of each batch's data. If a batch lacks an expiration date label or inventory quantity data, it is marked as abnormal data and logged, and not included in the sorting process. For multi-order concurrent scenarios, a short-term cache is set after the same product specification queue is generated, eliminating the need for repeated sorting operations in subsequent order retrievals, thus improving system throughput efficiency.

[0055] The primary and secondary rule sorting unit is used to sort batches under the same specification by prioritizing expiration dates. For batches with the same expiration date level, secondary sorting is performed by chronological order of warehousing. This unit is further divided into three sub-units: the primary rule sorting sub-unit, the same-level secondary sorting sub-unit, and the sequence output sub-unit.

[0056] The main rule sorting subunit is used to perform the first round of sorting on all valid, in-stock batches of the same specification based on the expiration date level labels in the batch data, from most recent to furthest expiration date. During sorting, the priority order of the expiration date level labels is: near expiration > near expiration > normal. That is, near-expiration batches are ranked first, near-expiration batches second, and normal batches last. The main rule sorting subunit only based on the expiration date level and does not involve comparisons of other dimensions.

[0057] The secondary sorting subunit is used to filter batches with the same expiration date label after the first round of sorting, and completes the secondary sorting according to the order of their entry into the warehouse. For batches with the same expiration date, if multiple batches are marked as near expiration, they are arranged in order of their entry into the warehouse, with the earlier-entered batches listed first and the later-entered batches listed last. This is because, with the same expiration date, the earlier-entered batches have a longer storage time and should be prioritized for release to accelerate inventory turnover. After the secondary sorting, batches within the same expiration date have a clear chronological order.

[0058] The sequence output subunit is used to organize batches of the same specification after the first and second rounds of sorting into an ordered batch sequence, and then output this ordered batch sequence to the priority queue generation unit. The format of the ordered batch sequence is: a list of batches arranged in order, and each batch record includes fields such as specification identifier, batch number, expiration date label, warehousing time, and inventory quantity.

[0059] The priority queue generation unit receives the batch sequence processed by the primary and secondary rule sorting unit, and, based on the available inventory quantity of each batch, generates an outbound priority queue that can be called by the outbound execution control module. This unit is further divided into three sub-units: an inventory verification sub-unit, a queue encapsulation sub-unit, and a queue output sub-unit.

[0060] The inventory verification subunit receives the ordered batch sequence output by the sequence output subunit, reads the available inventory quantity of each batch in the ordered batch sequence, and filters out batches with an available inventory quantity of 0. Batches with an available inventory quantity of 0 may be records that have been emptied but not yet removed from shelves, or batches that have been cleared by transfer or loss reporting operations. These batches have no actual inventory available for shipment, and participating in subsequent calculations would only increase the processing burden; therefore, they are directly removed during the verification stage.

[0061] The queue encapsulation subunit is used to bind the batches that have passed inventory verification to basic business fields such as expiration date label, batch number, product specification identifier, and available inventory. It also includes a compliance pre-verification submodule and a composite queue synthesis submodule. The compliance pre-verification submodule calls the GSP regulatory rules and the list of products subject to sales suspension stored in the basic data storage module to conduct a pre-shipment compliance judgment on each batch that has passed the inventory verification. In addition to verifying the suspension of sales and the supplier's qualifications, it performs a second verification of the batch's validity period. If there are expired batches that were missed in the validity period classification stage, it directly generates an interception mark to complete the second layer of expired fallback interception. Finally, it generates a compliance mark field containing an interception mark (can be shipped, intercepted) and a near-expiration risk warning level (no risk, low risk, medium risk, high risk).

[0062] The composite queue synthesis submodule first binds basic business fields such as expiration date labels, batch numbers, product specifications, and available inventory quantities for each batch. Then, it integrates these basic business fields with the compliance flag fields output by the compliance pre-verification submodule to generate a composite structured outbound priority queue that simultaneously possesses outbound sorting and scheduling attributes and GSP compliance prediction attributes. This queue is a standardized data carrier specifically designed for outbound scheduling, rather than a regular display list, and can be directly parsed and invoked by downstream modules.

[0063] The queue output subunit is used to publish the encapsulated outbound priority queue to the outside world for the outbound execution control module to call. After the queue is published, the outbound execution control module can retrieve the corresponding outbound priority queue based on the product specification code.

[0064] This module is the core component of this invention, enabling automated priority outbound delivery for near-expiry dates. Existing technologies can only perform simple batch sorting on the front-end page, generating lists for manual viewing only. They cannot be standardized for output, integrated into the back-end outbound business process, support queue result caching and reuse, require repeated sorting operations in multi-order concurrent scenarios, and the expiry date control rules remain only at the display level, making rigid implementation difficult. This module relies on the pre-sorted composite results to first filter invalid batches with zero inventory, then completes basic field binding and GSP pre-compliance screening through queue encapsulation sub-units. Simultaneously, it performs a second layer of expiry fallback interception for expired batches missed by the expiry date classification module. By integrating inventory information, expiry date tags, and compliance risk markers, it generates a composite structured outbound priority queue with dual attributes of outbound scheduling and compliance prediction. The generated queue supports short-term caching and reuse. This composite queue differs from traditional page-browsing lists; it is a standardized, callable data object specifically designed for outbound scheduling. It comprehensively carries multi-dimensional information such as batch outbound order, inventory balance, expiration date classification, sales discontinuation interception, near-expiration risk, and expired interception markers. It can be directly parsed by the outbound execution module and automatically complete batch allocation. In multi-order concurrent scenarios, the cached queue can be directly reused, avoiding repeated sorting and compliance judgment calculations, thus improving system response performance. This module synchronously sinks near-expiration priority control rules and GSP compliance constraints to the underlying business scheduling layer, connecting the data link between the expiration date marking stage and the outbound execution stage, forming a two-layer expired interception protection capability. It fundamentally solves the technical shortcomings of traditional systems where expiration date warnings, outbound operations, and compliance verification are fragmented and rely solely on manual intervention, providing core data carrier support for fully automated near-expiration outbound processes without manual intervention.

[0065] The outbound execution control module is the execution stage in this invention that implements the near-expiration priority rule into actual outbound operations. Its functions include receiving outbound orders, matching outbound priority queues, and automatically generating picking and outbound instructions. Figure 5 As shown, the module consists of four parts: an order receiving unit, a queue matching and calling unit, a picking instruction generation unit, and an outbound document output unit.

[0066] The order receiving unit is used to receive various types of outbound orders from external sources, including sales outbound orders, transfer outbound orders, return outbound orders, and split-item outbound orders. It uniformly parses and processes orders from different sources and of different types, extracts the core fields of the order: product specification code and total outbound demand, and separately records the minimum packaging split quantity for split-item outbound orders. After standardizing the order data, it is passed to the next unit.

[0067] The queue matching and calling unit is used to call the corresponding outbound priority queue generated by the outbound priority sorting module based on the extracted product specifications. The specific operation process is as follows: this unit initiates a queue query request to the outbound priority sorting module using the product specification code as the search key. The outbound priority sorting module returns the corresponding outbound priority queue based on the specification code. If there is no valid available queue for the product specification, the queue matching calling unit sends a queue regeneration request to the outbound priority sorting module. If queue generation fails, an exception handling process is triggered, and an alarm is pushed to notify the warehouse management personnel.

[0068] The picking instruction generation unit automatically generates picking instructions by deducting available inventory sequentially according to the batch order of the composite queue, based on the outbound order demand. The execution logic is as follows: starting from the first batch in the queue, inventory is allocated sequentially. If the available inventory of the current batch is greater than or equal to the remaining order demand, the corresponding demand is deducted from that batch, and the allocation ends. If the available inventory of the current batch is less than the remaining order demand, all inventory in that batch is allocated, and the process continues with the next batch until the cumulative allocation meets the order demand. If the cumulative inventory of all batches still cannot meet the demand, an insufficient inventory alarm is triggered.

[0069] Throughout the allocation process, there is no option to manually adjust the batch order, ensuring the strict enforcement of the near-expiration date priority rule. For split-batch outbound scenarios, the picking quantity and smallest packaging unit are separately indicated in the instruction. The final generated picking and outbound instruction includes fields such as instruction number, product name, batch number, warehouse area, shelf, storage location number, picking quantity, expiration date level, and compliance risk indicator, and can be directly pushed to the warehouse management system or handheld picking terminal.

[0070] The outbound document output unit is used to output outbound business documents corresponding to picking and outbound instructions. Outbound business documents include information such as outbound document number, outbound date, receiving unit, product specifications, batch number details, and quantity details, meeting the needs of warehousing business filing and financial accounting. Outbound documents support both paper printing and electronic archiving.

[0071] This module is the execution mechanism for enforcing the near-expiration priority strategy into the picking operation. Existing outbound processes rely on manual batch selection, which is prone to mismatches. Operators may skip near-expiration batches for convenience, selecting batches with longer expiration dates, leading to stockpiling and spoilage of near-expiration goods. Furthermore, traditional processes lack automated adaptation for split-batch picking, requiring separate manual handling. This module, through the collaborative processing of three sub-units—demand reading, batch allocation, and instruction assembly—can adapt to various outbound order types, including split-batch picking. It automatically completes batch inventory allocation and outputs picking instructions strictly according to queue order, without providing an entry point for manual batch selection, fundamentally avoiding the problem of near-expiration batches being skipped due to manual operation. Simultaneously, the module's automated batch allocation mechanism aligns with the GSP (Good Supply Practice) requirements for prioritizing near-expiration goods, transforming regulatory rules into automatically executed business actions.

[0072] The batch compliance traceability module is a key component of this invention, enabling deep integration between near-expiry outbound operations and GSP compliance verification. Its functions include collecting batch data across the entire supply chain, binding electronic regulatory codes, performing automated compliance verification, and saving traceability data. For example... Figure 6 As shown, the module consists of four parts: a link data acquisition unit, a regulatory code association unit, a GSP compliance verification unit, and a traceability data storage unit.

[0073] The data acquisition unit collects batch business node data from the inbound, intra-warehouse circulation, and outbound processes, obtaining the operation time, operation type, and batch identifier information for each business node. Data collected during the inbound process includes inbound order number, inbound date, supplier, batch number, expiration date, and inbound quantity. Data collected during intra-warehouse circulation includes transfer operation time, source warehouse location, target warehouse location, and operator. Data collected during the outbound process includes outbound order number, outbound date, receiving unit, outbound batch, and outbound quantity. This unit automatically collects batch data across the entire process by connecting to the business logs and operation records of the warehouse management system, eliminating the need for manual data entry.

[0074] The regulatory code association unit is used to bind and associate the collected batch business node data with the corresponding electronic regulatory code information of drugs and consumables. The electronic regulatory code is a drug traceability code promoted by the National Medical Products Administration; each smallest unit of drug packaging has a unique regulatory code. This unit obtains the electronic regulatory code corresponding to the batch through scanning or data integration, and maps and binds the business node data one-to-one with the regulatory code, enabling data association where every business operation can be traced back to a specific regulatory code.

[0075] The GSP compliance verification unit is used to call the GSP regulatory rule data stored in the basic data storage module to perform compliance comparison and verification on the data of all nodes in the entire chain after binding the electronic supervision code. The core new verification item for GSP compliance verification is: whether the picking order of outbound batches is consistent with the sorting of the composite structured queue, accurately identifying violations such as skipping near-expiry dates caused by manual intervention and system anomalies. Other verification contents include: whether expired batches are completely intercepted, whether discontinued batches are frozen for outbound, and whether outbound review records are complete. If non-compliant behavior is found during verification, such as expired batches being outbound or near-expiry batches being skipped, this unit generates a compliance anomaly record and triggers an alarm notification.

[0076] The traceability data storage unit is used to store full-chain batch traceability data that has undergone compliance verification. The traceability data is stored in the database in an immutable format, containing complete business node data, regulatory code association data, and compliance verification results. This data can be queried and accessed for subsequent regulatory checks, internal audits, and problem tracing.

[0077] This module differs from existing traceability systems that merely archive and store data without automatic verification. Most existing systems simply retain inbound and outbound data, failing to perform automatic compliance verification for near-expiry batches. They cannot automatically compare the actual outbound order with the preset priority queue, and struggle to automatically identify abnormal behavior such as skipping near-expiry batches. This module, through the collaborative work of three units—linked data collection, regulatory code association, and GSP compliance verification—deeply integrates near-expiry batch outbound operations with compliance verification. During verification, it compares the actual outbound batch order with the composite structured priority queue order, promptly detecting non-compliant behavior in the outbound process, such as near-expiry batches not being prioritized for outbound, expired batches being incorrectly outbound, and near-expiry batches being skipped. This provides complete and traceable batch data for regulatory verification, meeting the traceability requirements of GSP regulations in the pharmaceutical industry.

[0078] The big data statistical analysis module aggregates four types of raw data: inventory, expiration date, outbound shipment, and compliance verification. It outputs three types of business reports: inventory reports, expiration date warning reports, and outbound shipment detail reports, and supports report export. This module extracts raw data from various business modules through a data warehouse or big data analytics platform, cleans, transforms, and loads it, then aggregates and performs statistical calculations according to preset report templates.

[0079] The inventory report includes information such as the current total inventory of each product specification, inventory details for each batch, and warehouse location distribution. The expiration date warning report includes the remaining validity period, expiration grade, remaining days until near expiration or expired for each product specification and batch, and estimated scrap losses. The outbound details report includes the product specification, batch, quantity, outbound date, receiving unit, and picking batch order for each outbound order. The compliance risk statistics report summarizes the quantity of near-expiration and high-risk batches across the entire warehouse, records of sales suspension interception, number of outbound compliance anomalies, and expired interception records, providing a clear view of warehouse quality control risks. All three types of reports support exporting to common file formats such as Excel and PDF, facilitating archiving, printing, or importing into other systems for secondary analysis.

[0080] This module integrates and outputs expiration date distribution, outbound execution status, and compliance risk information in a unified manner. Unlike existing systems where reports mostly focus on a single business dimension and lack specific risk data aggregation mechanisms such as queue interception markers, expired interception records, and outbound sequence anomalies, this module provides comprehensive data support for warehouse managers to conduct inventory control and risk assessment. The expiration date early warning report output by this module helps managers identify near-expiration batches in advance and formulate promotional or adjustment plans. It also aggregates near-expiration high-risk batches, discontinued sales interception records, expired interception records, and outbound compliance anomaly records across the entire warehouse to form risk statistics. Compliance verification-related statistics help managers identify compliance risks in the outbound process and promptly implement quality control and problem correction.

[0081] like Figure 7 As shown, the near-expiry priority delivery method based on big data analysis establishes a one-to-one mapping relationship between each step and system module. The complete workflow is as follows: S1. Basic Data Storage: This step is performed by the basic data storage module. It pre-stores six categories of basic data: drug basic records, consumable basic records, warehousing institution data, supplier records, GSP regulatory rules data, and the list of products subject to sales restrictions. This step provides a unified data source for the entire system; subsequent modules all access this module's basic data through a data interface.

[0082] S2. Batch Inventory Maintenance: Performed by the batch inventory management module. This module inputs and maintains the receiving information, real-time inventory quantity, batch number, expiration date, and warehouse location information for each batch of medicines and consumables. It responds to five business commands—receiving, issuing, transferring, reporting damage, and inventory counting—to complete real-time updates to the corresponding batch inventory data. This step ensures that the batch inventory data in the system is consistent with the actual warehousing situation. If the expiration date threshold is modified, it automatically triggers a recalculation of the expiration date labels for all batches.

[0083] S3. Expiry Date Grading and Marking: Performed by the expiry date grading and marking module. The threshold configuration unit receives user-defined multi-level expiry date threshold configurations. The expiry date calculation unit reads the expiry date information of batches in the inventory, calculates the remaining validity period of each batch based on the current system time, and filters out expired batches. The threshold comparison subunit of the grading and marking unit compares the remaining validity period with the multi-level thresholds to determine the expiry date grade. The label binding subunit generates expiry date grade labels and associates them with the batch number and specification identifier. The data forwarding subunit outputs the batch data carrying the expiry date grade labels. This step transforms the expiry date information, which was originally only viewable manually, into a structured expiry date grade label that the program can recognize.

[0084] S4. Outbound Queue Generation: Executed by the outbound priority sorting module, this module gathers all valid batches of the same product specification and sorts them in two layers, prioritizing expiration date and secondarily by entry time. After filtering out invalid batches with zero inventory, the compliance pre-verification submodule retrieves GSP rules and discontinued product lists to generate interception and risk marking. Then, the composite queue synthesis submodule integrates basic inventory fields and compliance identifiers to generate a composite structured priority queue that combines outbound scheduling and GSP pre-judgment capabilities, and publishes it externally. This encapsulates near-term control and compliance constraints into a standardized data carrier that can be directly accessed.

[0085] S5. Picking Instruction Generation: Executed by the outbound execution control module, it receives various outbound orders and parses the specifications and required quantities, matches them with corresponding composite queues, and the system automatically deducts the inventory of each batch in strict accordance with the queue order until the order requirements are met. It automatically assembles the operation instructions with batch number, storage location, and picking quantity and outputs outbound documents simultaneously, completely eliminating the problem of near-term goods being missed due to manual batch selection, and rigidly implementing the GSP near-term first-out requirement.

[0086] S6. End-to-End Compliance Traceability: Performed by the batch compliance traceability module. The link data acquisition unit collects end-to-end node data for each stage of the batch process, including warehousing, intra-warehouse circulation, and outbound shipment. The regulatory code association unit binds and associates business node data with electronic regulatory code information. The GSP compliance verification unit calls GSP regulatory rules to perform compliance comparison and verification on the end-to-end node data. The traceability data storage unit saves the batch traceability data that has passed compliance verification. This step achieves deep linkage between near-expiry outbound shipment business and compliance verification.

[0087] S7. Statistical Report Output: Performed by the big data statistical analysis module. It aggregates four types of raw data: inventory, expiration date, outbound shipment, and compliance verification, and outputs three types of business reports: inventory report, expiration date early warning report, and outbound shipment details report. Report export is also supported. This step provides comprehensive data support for warehouse management personnel.

[0088] Taking the actual business scenario of a pharmaceutical warehousing company as an example, the complete workflow of the system of the present invention will be illustrated by way of example.

[0089] Scenario setting: Amoxicillin capsules, product code GM001, have three batches in stock. The inventory and expiration date data are as follows: Batch A: Batch number 20250101, expiry date January 1, 2027, stock quantity 500 boxes, warehousing date January 5, 2025; Batch B: Batch number 20250601, expiry date June 1, 2026, stock quantity 300 boxes, warehousing date June 10, 2025; Batch C: Batch number 20250901, expiry date September 1, 2026, stock quantity 200 boxes, warehousing date September 5, 2025.

[0090] The current system date is March 1, 2026. Threshold configurations are as follows: near-expiration threshold for pharmaceuticals is 180 days, near-expiration warning threshold is 90 days, and expired threshold is 0 days. Thresholds can be flexibly adjusted by business personnel according to the control requirements of different product categories.

[0091] S3 Expiry Date Grading and Marking Stage: The expiry date calculation unit calculates the remaining validity period for each batch: Batch A has 640 days remaining, Batch B has 92 days remaining, and Batch C has 184 days remaining. The threshold comparison subunit compares the remaining validity period of each batch with the threshold: Batch A has 640 days > 180 days, so it is judged as normal; Batch C has 184 days > 180 days, so it is judged as normal; Batch B has 92 days > 90 days and ≤ 180 days, so it is judged as near expiry. The label binding subunit generates expiry date grade labels: Batch A is marked as normal, Batch B is marked as near expiry, and Batch C is marked as normal.

[0092] S4 Outbound Queue Generation Stage: The batch data acquisition unit aggregates three batches. The main rule sorting subunit sorts them by expiration date level, with near-expiration batch B ranked first, and normal batches A and C ranked second. The secondary sorting subunit of the same level sorts normal batches by entry time. Batch A, with an entry time of January 5, 2025, is ranked before batch C, with an entry time before September 5, 2025. After the inventory verification subunit filters out batches with zero inventory, the queue encapsulation subunit retrieves GSP rules and the list of discontinued products through the compliance pre-verification submodule to complete the preliminary compliance judgment and generate a near-expiration risk marker. Then, the composite queue synthesis submodule merges the basic inventory fields and compliance markers to generate a composite structured outbound priority queue. The queue order is batch B (near-expiration risk marker, 300 boxes), batch A (normal, 500 boxes), and batch C (normal, 200 boxes).

[0093] S5 Picking Instruction Generation Stage: The order receiving unit receives a sales order requiring 400 boxes of amoxicillin capsules to be shipped. The batch allocation subunit processes the order according to the composite structured priority queue: first, allocate 300 boxes of batch B, all of which are shipped, leaving a remaining order demand of 100 boxes; then allocate 100 boxes of batch A, deducting 100 boxes from the 500 boxes, for a total allocation of 400 boxes to meet the order demand. The instruction assembly subunit generates picking and shipping instructions: Instruction 1: Batch B, location A-03-05, picking quantity 300 boxes, near-delivery priority, high-risk warning. Instruction 2: Batch A, location A-01-02, picking quantity 100 boxes. The remaining 200 boxes of batch C are held in stock. The generated picking and shipping instructions are transmitted to the warehouse management system via an interface to guide the picking personnel in completing the physical picking. The system does not support manual reordering of batches.

[0094] S6 Full-Link Compliance Traceability Phase: The link data acquisition unit collects full-link data for this outbound shipment, from the inbound record to the in-warehouse storage record and then to the outbound allocation record. The regulatory code association unit binds the outbound batch with the electronic regulatory code. The GSP compliance verification unit verifies that this outbound shipment strictly follows the scheduling of the composite structured priority queue and meets both compliance requirements. The near-term risk batch B is prioritized for outbound shipment, and no expired or discontinued batches are mixed in. The compliance verification passes. The traceability data storage unit stores complete traceability data with compliance tags.

[0095] S7 Statistical Report Output Stage: The big data statistical analysis module aggregates the current outbound data and historical data, outputs an expiration date warning report, and marks batch B as having been outbound and cleared, batch C as expiring on September 1, 2026 (184 days remaining), and batch A as having a longer expiration date. Simultaneously, a compliance risk statistical report is output, recording the handling records of near-expiration risks in this outbound process, fully reflecting the outbound business and compliance risk data, and supporting export to Excel for archiving.

[0096] This embodiment fully demonstrates an integrated automated process from expiration date classification marking, including first-layer expired batch interception, composite queue generation with compliance prediction and short-term cache reuse capabilities, second-layer expired fallback interception, automatic picking instruction generation supporting split-out delivery, to end-to-end compliance traceability verification. It verifies that the present invention can achieve dual compliance control of expiration date management, double-layer expired interception, and pre-delivery prediction plus post-delivery review. It solves the technical problems of existing systems that only provide page warnings, rely on manual judgment, perform duplicate calculations for concurrent orders, lack multi-layer protection against expired batches, and are prone to causing near-expiration product backlog and post-delivery compliance can only be verified after the fact.

[0097] The foregoing has provided a detailed description of the near-expiry priority outbound system and method based on big data analysis provided by this invention. The specific embodiments described are only intended to aid in understanding the method and core ideas of this invention. It should be noted that those skilled in the art can make various improvements and modifications to this invention without departing from its principles, and these improvements and modifications also fall within the scope of protection of the claims of this invention.

Claims

1. A near-expiry priority outbound system based on big data analysis, characterized in that: It includes a basic data storage module, a batch inventory management module, an expiration date grading and marking module, an outbound priority sorting module, an outbound execution management module, a batch compliance traceability module, and a big data statistical analysis module; The basic data storage module is used to store basic drug records, basic medical consumable records, warehousing institution data, supplier records, GSP regulatory rules data, and lists of products subject to sales suspension and control. The batch inventory management module is used to input and maintain the warehousing information, real-time inventory quantity, batch number information, expiration date information, and storage location information of each batch of medicines and consumables, and to respond to warehousing, outbound, transfer, damage reporting, and inventory count business instructions to complete the corresponding batch inventory data changes. The expiration date grading and marking module is used to read the expiration date information of batches of drugs and consumables in stock, and to mark the expiration date grades of the batches in stock according to the preset multi-level expiration date thresholds. The outbound priority sorting module is used to obtain the expiration grade, batch number, inventory quantity, and entry time data of all in-stock batches under the same product specification. It sorts the inventory batches of drugs and consumables of the same product specification according to the main sorting rule of expiration date from near to far, and performs GSP compliance prediction in advance to generate a composite structured outbound priority queue with scheduling and prediction attributes. The outbound execution control module is used to receive various types of outbound orders issued from outside, call the outbound priority queue that matches the corresponding goods, and generate picking and outbound instructions based on the demand of goods in the outbound order and the outbound priority queue. The batch compliance traceability module is used to collect full-chain node data of outbound batches at each stage of warehousing, in-warehouse circulation, and outbound, associate it with electronic supervision code information, and perform compliance verification of the full-chain node data in accordance with GSP regulatory rules. The big data statistical analysis module is used to aggregate raw data on inventory, expiration date, outbound shipment, and compliance verification, and output inventory reports, expiration date early warning reports, and outbound shipment detail reports, and supports report export operations.

2. The near-expiry priority outbound system based on big data analysis according to claim 1, characterized in that, The expiration date grading and marking module includes a threshold configuration unit, an expiration date calculation unit, and a grade marking unit; The threshold configuration unit is used to receive user-defined configuration operations and save multi-level expiration thresholds. The multi-level expiration thresholds include near-expiration warning thresholds, near-expiration thresholds, and expired thresholds. Different types of thresholds can be set independently for drugs and consumables. When a threshold is modified, the expiration level of the existing batches in stock is recalculated. The expiration date calculation unit is used to read the expiration date information of the batches of medicines and consumables output by the batch inventory control module, calculate the remaining validity period of each batch in the warehouse in combination with the current system time, and filter out the batch data that has been determined to be expired. The grade labeling unit is used to receive the remaining valid duration output by the expiration date calculation unit, complete the batch expiration date grade determination based on the multi-level expiration date threshold, assign the corresponding in-stock batch expiration date grade label, complete the binding of batch number and specification identifier, and output the batch data after binding to the outbound priority sorting module.

3. The near-expiry priority outbound system based on big data analysis according to claim 2, characterized in that, The grade labeling unit includes a threshold comparison subunit, a tag binding subunit, and a data forwarding subunit; The threshold comparison subunit is used to receive the remaining valid duration output by the expiration calculation unit, and compare the remaining valid duration with the near-expiration warning threshold, the near-expiration threshold, and the expired threshold respectively to determine the expiration level to which the corresponding batch in stock belongs; The label binding subunit is used to generate a corresponding expiration grade label based on the expiration grade obtained from the threshold comparison subunit, and to associate and bind the expiration grade label with the batch number and specification identifier of the corresponding batch. The data forwarding subunit is used to receive batch data that has been associated and bound, perform format normalization on the batch data, and output the normalized batch data carrying expiration date label, batch number, and product specification identifier to the outbound priority sorting module.

4. The near-expiry priority outbound system based on big data analysis according to claim 1, characterized in that, The outbound priority sorting module includes a batch data acquisition unit, a primary and secondary rule sorting unit, and a priority queue generation unit. The batch data acquisition unit is used to receive batch data with expiration grade label, batch number and product specification identifier output by the expiration date grading marking module, and pull the inventory quantity and warehousing time data of the corresponding batch, and collect all valid in-stock batch data under the same product specification. The primary and secondary sorting unit is used to sort batches under the same specification by using the expiration date from nearest to furthest as the primary sorting rule, and to sort batches with the same expiration date level by using the order of entry into the warehouse as the secondary sorting rule for secondary sorting. The priority queue generation unit is used to receive the batch sequence processed by the main and auxiliary rule sorting unit, filter out zero-inventory batches and perform GSP compliance judgment in advance, integrate basic business fields and compliance tags, and generate a composite structured outbound priority queue that can be called by the outbound execution control module. The generated composite structured outbound priority queue supports short-term cache reuse.

5. The near-expiry priority outbound system based on big data analysis according to claim 4, characterized in that, The primary and secondary rule sorting unit includes a primary rule sorting subunit, a secondary sorting subunit of the same level, and a sequence output subunit. The main rule sorting subunit is used to sort all valid in-stock batches of the same specification in the batch data according to the expiration date level label in the batch data, with the expiration date from the nearest to the furthest. The same-level secondary sorting subunit is used to filter batches with the same expiration date level label after the first round of sorting, and complete the secondary sorting according to the order of the batch's entry time. The sequence output subunit is used to organize the same-specification batches after the first round of sorting and the second round of sorting into an ordered batch sequence, and output the ordered batch sequence to the priority queue generation unit.

6. The near-expiry priority outbound system based on big data analysis according to claim 4, characterized in that, The priority queue generation unit includes an inventory verification subunit, a queue encapsulation subunit, and a queue output subunit; The inventory verification subunit is used to receive the ordered batch sequence output by the sequence output subunit, read the available inventory quantity of each batch in the ordered batch sequence, and filter out batches with zero available inventory quantity. The queue encapsulation subunit is used to bind the batches that have passed inventory verification to the corresponding batch's expiration date label, batch number, product specification identifier, and available inventory quantity, and encapsulate them to form a structured queue carrier. The queue output subunit is used to publish the encapsulated composite structured outbound priority queue to the outside world for the outbound execution control module to call. The published composite structured outbound priority queue supports short-term caching.

7. The near-expiry priority outbound system based on big data analysis according to claim 6, characterized in that, The queue encapsulation subunit includes a compliance pre-verification submodule and a composite queue synthesis submodule; The compliance pre-verification submodule is used to call the GSP regulatory rules and the list of products to be discontinued stored in the basic data storage module, to conduct a pre-shipment compliance judgment on batches that have passed inventory verification, to simultaneously review the batch validity information, and to generate a compliance mark field that includes an interception identifier and a near-expiration risk warning level. The composite queue synthesis submodule is used to bind the basic business fields of each batch's expiration date label, batch number, product specification identifier, and available inventory quantity, and integrates the basic business fields with the compliance mark fields output by the compliance pre-verification subunit to generate a composite structured outbound priority queue that simultaneously possesses outbound sorting and scheduling attributes and GSP compliance prediction attributes.

8. The near-expiry priority outbound system based on big data analysis according to claim 1, characterized in that, The outbound execution control module includes an order receiving unit, a queue matching and calling unit, a picking instruction generation unit, and an outbound document output unit. The order receiving unit is used to receive multiple types of outbound orders issued from outside, including split outbound orders, and to extract the product specifications and product demand information from the outbound orders. The queue matching and calling unit is used to call the outbound priority queue of the corresponding product generated and cached by the outbound priority sorting module according to the extracted product specifications. The picking instruction generation unit is used to generate picking instructions containing batch, storage location, and picking quantity information by deducting the available inventory of the corresponding batch in the order of the outbound priority queue according to the demand quantity of goods in the outbound order. Manual changes to the batch outbound order are prohibited during the picking instruction generation process. The outbound document output unit is used to output outbound business documents corresponding to the picking and outbound instructions.

9. The near-expiry priority outbound system based on big data analysis according to claim 1, characterized in that, The batch compliance traceability module includes a link data acquisition unit, a regulatory code association unit, a GSP compliance verification unit, and a traceability data storage unit. The link data acquisition unit is used to collect batch business node data in the warehousing process, the internal circulation process, and the outbound process, and to obtain the operation time, operation type, and batch identification information corresponding to each business node. The regulatory code association unit is used to bind and associate the collected batch business node data with the corresponding electronic regulatory code information of drugs and consumables; The GSP compliance verification unit is used to call the GSP regulatory rule data stored in the basic data storage module to perform compliance comparison and verification on the full-link node data after binding the electronic supervision code. The verification items include whether the outbound batch matches the outbound priority queue sorting order. The traceability data storage unit is used to store full-chain batch traceability data that has been verified for compliance.

10. A method for prioritizing near-expiry date release based on big data analysis, applied to the near-expiry date priority release system based on big data analysis as described in any one of claims 1 to 9, characterized in that, Includes the following steps: S1. Basic Data Storage: The basic data storage module stores basic drug records, basic medical consumable records, warehousing organization data, supplier records, GSP regulatory rules data, and the list of products subject to sales restrictions. S2. Batch Inventory Maintenance: The batch inventory management module is used to input and maintain the warehousing information, real-time inventory quantity, batch number information, expiration date information, and storage location information for each batch of medicines and consumables. It responds to warehousing, outbound, transfer, damage reporting, and inventory count business instructions to complete the corresponding batch inventory data changes. When the multi-level expiration date threshold is modified, the expiration date level of the existing batch is automatically recalculated. S3, Expiry Date Grading Marking: The expiry date grading marking module reads the expiry date information of batches of drugs and consumables in stock, performs expiry date grading marking on the batches in stock according to the preset multi-level expiry date thresholds, and outputs batch data carrying expiry date grading labels; S4. Outbound queue generation: The outbound priority sorting module sorts batches by expiration date first and entry time second. After filtering out zero-inventory batches, it performs GSP compliance verification in advance, reviews the batch expiration date and generates risk markers, integrates business fields and compliance identifiers, and generates a composite structured priority queue with dual attributes of outbound scheduling and compliance prediction. The composite structured priority queue is cached for a short time for reuse. S5. Picking Instruction Generation: The outbound execution control module receives multiple types of outbound orders from external sources, including split outbound orders. It calls the outbound priority queue that matches the corresponding product cache, and generates picking and outbound instructions based on the product demand of the outbound order and the outbound priority queue. Manual changes to the batch outbound order are prohibited during the process of generating picking and outbound instructions. S6. Full-chain compliance traceability: The batch compliance traceability module collects full-chain node data of each stage of the batch from warehousing, internal circulation and outbound, associates it with electronic supervision code information, and performs compliance verification on the full-chain node data according to GSP supervision rules, and verifies whether the outbound batch matches the composite structured priority queue sorting order. S7. Statistical Report Output: The big data statistical analysis module aggregates raw data on inventory, expiration date, outbound shipment, and compliance verification, and outputs inventory reports, expiration date warning reports, and outbound shipment detail reports, and supports report export operations.

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