Fresh product sales distribution system and method

Abstract

The invention discloses a fresh product sales distribution system and method, and relates to the technical field of fresh product supply chain management, and the system comprises an access layer, a front platform, a business layer, a data layer, a database and basic equipment. The business layer serves as a system core, adopts a micro-service architecture, comprises basic data management, plan management, distribution management, report management and system setting, covers the functions of customer archives, order matching, route planning, abnormity alarm and the like, and supports multi-role cooperation; according to the method, an order is submitted through a mobile terminal, a production plan is docked through a primary review and a bilateral matching algorithm, shipment conditions are verified through finance, then production cargo allocation, vehicle distribution, transportation monitoring and abnormal early warning are completed, and finally data visualization analysis is achieved. According to the fresh product sales distribution system and method, order, production, logistics and financial full-link integration is realized, the delivery efficiency and accuracy are improved, the communication and operation cost is reduced, and the system and method are suitable for fresh products with short shelf life.

Description

Technical Field

[0001] This invention relates to the field of fresh food supply chain management technology, and in particular to a fresh food sales and distribution system and method. Background Technology

[0002] With the upgrading of residents' consumption, the market demand for fresh products continues to grow, especially fresh poultry products, which have become core ingredients for families and the catering industry due to their high protein content and ease of cooking. According to industry statistics, my country's annual poultry production exceeds 20 million tons, of which fresh poultry accounts for about 60%. The order delivery efficiency of fresh poultry directly determines the freshness of the product and customer satisfaction.

[0003] Currently, the order delivery model for fresh poultry companies mainly relies on traditional manual operations, supplemented by simple Excel spreadsheets or standalone software for data recording, which presents several prominent problems. Regarding the efficiency of order-production matching, fresh poultry production depends on chicken slaughter plans, and the uniformity of chickens slaughtered in each batch varies, leading to difficulties in matching the actual processed product specifications (such as whole chicken weight and chicken piece size) with customer requirements. Under the existing model, customer needs are conveyed to sales staff via phone or WeChat, who then manually summarize and communicate with the production department. Due to specification discrepancies, orders need to be repeatedly adjusted, with the average matching time for each order exceeding 4 hours, and situations of "overproduction" or "unmet demand" are prone to occur.

[0004] High communication costs due to price fluctuations are another major problem. The price of fresh poultry is affected by regional supply and demand, chicken output, and transportation costs, and prices may be adjusted 1-2 times a day. Under the current model, sales representatives must notify customers of price changes individually. Customers then adjust their order quantities according to the new price and provide feedback to the sales representative, who then summarizes the information and forwards it to the sales office. This process requires an average of 3-5 communications per order, taking over 2 hours. If customers do not receive price change information in a timely manner, orders may be cancelled due to price disputes after confirmation. According to a survey, one company's order cancellation rate due to untimely price communication reached 8%, resulting in direct sales losses.

[0005] Uncontrollable logistics status and low delivery timeliness are also prominent issues. Fresh poultry has a shelf life of only 3-5 days and requires cold chain transportation (0-4℃) throughout the process. Delivery timeliness directly determines whether the product can be sold normally. Under the current model, most transport vehicles are either owned or leased by customers. Loading time, transportation route, and arrival time rely on verbal feedback from drivers, and sales staff and customers cannot obtain real-time logistics status. If vehicles are delayed due to road conditions or loading problems, the remaining shelf life of the product may be less than 1 day when it arrives, resulting in a customer rejection rate of up to 12%. In addition, vehicle loading rate relies on manual estimation, with an average loading rate of only 70%, leading to high transportation costs.

[0006] The disconnect between finance and operations also brings higher shipping risks. Under the current model, customer prepayment balances are stored in the finance department's independent system. Sales staff need to manually check the customer's prepayment status when confirming orders. If the check is not timely or the data synchronization is delayed, it may lead to a situation where "shipments are arranged even though the prepayment is insufficient." The accounts receivable overdue rate reaches 10%, affecting the company's cash flow.

[0007] In summary, existing technologies cannot meet the order delivery requirements of fresh products with short shelf lives, such as fresh poultry. Therefore, there is an urgent need for a full-chain system and method that integrates order processing, production coordination, logistics monitoring, financial verification, and data visualization. Summary of the Invention

[0008] The purpose of this invention is to provide a fresh produce sales and distribution system and method. It adopts a three-tier architecture combined with microservice design to achieve full-link integration of orders, production, logistics and finance, thereby improving order delivery efficiency and accuracy.

[0009] To achieve the above objectives, the present invention provides a fresh produce sales and distribution system, comprising, from top to bottom, an access layer, a front-end platform, a business layer, a data layer, a database, and basic equipment. The business layer adopts a microservice architecture and includes basic data management, planning management, distribution management, report management, and system settings operations. Basic data management includes customer files, material data, vehicle model data, and delivery route data; planning management includes plan processing, plan confirmation, production planning, and raw chicken planning; and delivery management includes delivery route planning, vehicle model planning, load planning, online transportation monitoring, and anomaly alarms. Report management includes regional quantity and price, on-time delivery rate, regional sales structure, regional distribution costs, and regional product anomalies. System settings include user management, dictionary management, and role configuration. Roles include distributors or customers, salespersons, transport drivers, production and warehousing departments, and management personnel.

[0010] Preferably, the access layer includes a web terminal, a large screen terminal, and a mobile terminal. The web terminal is used to perform basic data management, plan management, delivery management, report management, and system settings operations. The large screen terminal is used for data visualization display. The mobile terminal is used by different roles to perform registration and approval of file information, submission, query and approval of sales order plans, delivery management and query of order plans, and transportation tracking operations.

[0011] Preferably, the front-end platform includes a financial shared platform, an SAP system, and a Defan Cloud integrated API platform. The financial shared platform is used to uniformly handle the financial accounting work of various departments and branches of the enterprise, formulate and implement expense reimbursement standards and approval processes, and centrally manage the enterprise's funds, including budget preparation, fund receipt and payment settlement, and integration of enterprise financial data. By analyzing the profitability of different business segments and products, it optimizes business layout and resource allocation. The SAP system is used for supply chain management, financial management, human resource management, and production management. The Defan Cloud integrated API platform is used to synchronize expense reimbursement data from the financial shared platform to the SAP system for financial accounting, and to transmit sales order data from the business layer to the SAP system for production planning and scheduling.

[0012] Preferably, the data layer provides business operations for distributors or customers, salespersons, transport drivers, production and warehousing personnel, and managers, including: Distributors or customers can perform operations such as plan submission confirmation, transportation information inquiry, goods receipt confirmation, turnover box receipt, dispatch and storage, and account transaction inquiry. Sales representatives perform tasks such as plan submission confirmation, transportation information inquiry, sales volume and price inquiry, and volume and price anomaly alarm operation; The transport driver is responsible for receiving waybills, completing transport tasks, and querying waybills. The production and warehousing department is responsible for receiving and executing loading plans, receiving, issuing and storing turnover boxes, querying delivery information, and handling alarms for abnormal arrivals. Managers conduct regional volume and price analysis, on-time delivery rate statistics, regional sales structure analysis, regional distribution cost accounting, and regional product anomaly investigation.

[0013] Preferably, the database uses MySQL and Oracle databases to store and manage structured data, and HBase and Kafka databases to store unstructured data; and Redis is used to store high-concurrency access data, including real-time inventory, daily prices and on-the-go vehicle locations. The basic equipment includes cloud servers, local servers, OSS object storage, OCR and security equipment.

[0014] This invention also provides a method for selling and distributing fresh produce, comprising the following steps: S1. Distributors or customers can submit order plans to the system business layer via a mobile app at the system access layer. S2. Sales staff conduct online preliminary review of order plans in real time on mobile devices; S3. The system business layer automatically summarizes the order plans by region based on the initial review of the salesperson. Through a two-sided matching algorithm, combined with the production plan, available inventory and specifications obtained from the SAP system, the system compares the buyer's order information with the seller's production information, finds the order information that meets the matching conditions, and pushes it to the salesperson for reference. S4. Sales representatives make minor adjustments to order allocation based on actual order demand and production plans. S5. The salesperson pushes the adjusted order to the distributor or customer and requests the distributor or customer to confirm the adjusted order. S6. Once the distributor or customer confirms the adjusted order, the system's business layer will automatically push the confirmed order to the reporting plan and enter S7. S7. Submit the confirmed actual order to the Defan Cloud Integration API platform, and through the financial shared platform and SAP platform, determine whether the shipment conditions are met by associating the information of the distributor or customer, the specifications, quantity, unit price of the purchase order, and the prepayment balance: If the shipping conditions are met, the order information will be sent to the production department; If the shipping conditions are not met, the result will be sent to the distributor or customer. S8. The system obtains production plans and inventory levels through the SAP system and reports them to the production and warehousing department. The production and warehousing department processes and produces goods based on the order data and finally synchronizes the product warehousing information to the sales and distribution system. S9. Determine whether the delivery is to a distributor or customer or for self-pickup. When the delivery is to a distributor or customer, the system will automatically determine the delivery order to the production and warehousing department based on the product quantity, type and delivery area. When the distributor or customer picks up the goods, the delivery note will be synchronized to the distributor's or customer's mobile app. The distributor or customer can then pick up the goods at the warehouse by scanning the code, updating the pickup status, and pushing the notification to the SAP platform. S10. The sales and distribution system generates loading task orders and allocates transport vehicles. S11. After receiving the task order on the mobile device, the transport driver goes to the warehouse to load and pick up the goods according to the task order information, and changes the vehicle status to "awaiting transport" by scanning the code. S12. After scanning the code with the mobile app, the production and warehousing department will synchronize the vehicle loading status to the system business layer in real time. S13. After loading and picking up the goods, the transport driver delivers the goods. At this time, the vehicle status is scanned again to change the vehicle status to "in transit". S14. When the transport driver arrives at the dealer's or customer's delivery location, if the conditions for confirming receipt are met, the customer can be confirmed to have signed for the goods by scanning the QR code on the transport driver's mobile device, and the vehicle status will be automatically changed to delivery completed. After the driver returns to the company, he scans a code to change the vehicle status to "order delivery completed" and pushes the delivery status information to the SAP system; and based on preset time, abnormal warnings are issued for actions that are not completed within the time limit. S15. View regional volume and price, on-time delivery rate, regional sales plan, early warning status, and big data analysis through the system business layer.

[0015] Preferably, in S3, the bilateral matching algorithm includes the following steps: S31. Obtain the order collection after initial review by the salesperson. Order collection Each order Including customer requirements and specifications Quantity required and delivery area ; S32. Obtain the production plan set from the SAP system. Production planning set Each production plan Including product specifications Planned production and production cycle ; S33, Calculate Orders With production plan Specification matching degree If the customer requires specifications With product specifications If the deviation rate is greater than 5%, then the specification matching degree is... ,otherwise ; S34: Calculate orders With production plan Quantity matching degree , ; S35, Calculate Orders With production plan Regional matching degree ,like Corresponding delivery areas and production plans If the production bases have overlapping distribution ranges, then the regional matching degree is... ,otherwise ; S36. Calculate the overall matching degree ,like Then the order is determined. With production plan Match and generate matching results.

[0016] Preferably, in S7, whether the shipping conditions are met is determined by the following steps: S71, Obtaining an Order Total amount ;,in For orders The unit price; S72. Acquiring customers from a financial shared service platform Prepayment balance ; S73, if If the conditions for shipment are met, the order will be sent. To the production and warehousing departments; S74, if If the shipment conditions are not met, an insufficient prepayment reminder will be generated and pushed to the customer via a mobile app. And the corresponding salesperson.

[0017] Preferably, in S10, the allocation of transport vehicles includes the following steps: S101, Area requiring order acquisition Total product weight and volume ; S102. Obtain the set of available vehicles from the data layer. Each available vehicle Including load limit Volume limit and delivery range ; S103, Filter to meet the requirements , and The vehicles generate a candidate vehicle set. ; S104, Calculate candidate vehicles Delivery costs : ; in, Indicates the distance traveled. This indicates the freight cost per unit distance. Costs associated with vehicle idle time; S105, Select The vehicle with the smallest allocation is used as the allocation result to generate a loading task order.

[0018] Preferably, in S14, the anomaly warning includes: Overdue loading warning: If a loading task order is not generated within 2 hours after order confirmation, or if loading and scanning are not completed within 1 hour after the loading task order is assigned, a warning will be triggered. Route deviation warning: If the real-time location of the vehicle deviates from the planned delivery route by more than or equal to 5 kilometers for 5 minutes, a warning will be triggered. Overdue delivery warning: If the delivery is not signed for and scanned within 4 hours of the vehicle arriving at its destination, a warning will be triggered. Warning information is pushed to relevant roles, including drivers, salespersons, and managers, via mobile mini-programs.

[0019] Therefore, the present invention employs the above-mentioned fresh produce sales and distribution system and method, and the beneficial effects are as follows: (1) This invention improves processing efficiency by optimizing order matching and price communication: intelligent algorithms enable automatic matching of orders and production plans, support online adjustments, and eliminate the need for repeated manual communication; prices are dynamically updated and synchronized to the client, allowing customers to directly modify orders, which greatly reduces communication costs and order cancellations due to price disputes.

[0020] (2) This invention can realize controllable logistics and automated counting, ensuring delivery quality; relying on positioning technology to track logistics trajectory in real time, and the abnormal early warning mechanism helps to intervene in delivery problems in a timely manner, improving delivery timeliness; the automated counting module solves the counting problem caused by the irregular shape of poultry meat, ensuring accurate inventory data and reducing product loss and order matching errors.

[0021] (3) This invention can realize real-time linkage between financial data and business systems, automatically verify shipment conditions and warn of insufficient prepayment risks; through real-time sharing of information among multiple roles, and with the assistance of data visualization reports to help formulate strategies, operational efficiency is improved.

[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0023] Figure 1 This is an overall block diagram of an embodiment of a fresh produce sales and distribution system according to the present invention; Figure 2 This is an overall flowchart of an embodiment of a fresh produce sales and distribution method according to the present invention. Detailed Implementation

[0024] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0026] like Figure 1As shown, a fresh produce sales and distribution system includes, from top to bottom, an access layer, a front-end platform, a business layer, a data layer, a database, and basic equipment. The access terminal sends business requests to the front-end platform, which integrates the business requests and forwards them to the business layer. The business layer obtains the operation data of customers, salespersons, transport drivers, production and warehousing personnel, and management personnel from the data layer, and then sends the business results back to the front-end platform. The front-end platform then feeds back the business results to the access terminal for display.

[0027] The business layer of this invention is the core part of the system. It adopts a microservice architecture to split different functional modules into independent microservices. Each microservice is responsible for handling specific business logic. This architecture improves the scalability and maintainability of the system, and allows each microservice to be deployed and upgraded independently.

[0028] like Figure 1 As shown, the specific business layer includes basic data management, planning management, delivery management, report management, and system settings operations. Combined with mobile mini-programs, these modules collaborate to form an efficient and secure supply chain solution, providing merchants with strong business support and market competitiveness.

[0029] Basic data management is used before the system goes live to maintain customer profiles, integrate with the Defan Cloud API platform, add and configure vehicle data and delivery route information, and combine this with traceability information such as product origin, health status, feeding and growth process monitoring to form a closed-loop management system for food safety supply chain information. In addition, the system should support flexible pricing and promotional strategies to adapt to market changes and consumer demands.

[0030] In this invention, basic data management includes customer profile management, material data management, vehicle model data management, and delivery route data management. Customer profile management involves collecting and inputting customer profile information, including user registration and administrator approval of user account applications. Data is integrated through the Defan Cloud API platform to obtain historical user and financial payment information, push order information, push delivery confirmation information, and historical material specification data. Administrators can manually configure these in the backend. Vehicle model data mainly includes basic vehicle information such as license plate number, GPS information, and load capacity, and allows for manual addition, deletion, modification, and querying of vehicle data. Pre-setting delivery routes and delivery points is supported, and manual addition, deletion, modification, and querying of vehicle route data is also possible.

[0031] The planning and management system is the core of the entire system, capable of handling orders from various channels, including online, physical stores, and wholesalers. Through intelligent algorithms, the system can automatically allocate next-day inventory, optimize delivery routes, and reduce logistics costs. Simultaneously, the module supports order matching, automatically matching the sum of unsold inventory and next-day production quantities with the total number of completed orders, improving transaction efficiency and customer satisfaction.

[0032] The planning management in this invention includes planning processing, planning confirmation, production planning, and broiler planning. It can handle various business processes such as order configuration, modification, query, modification, cancellation, receipt and integration, matching, review, adjustment, confirmation, and return. It can achieve closed-loop processing throughout the entire sales order process, with online traceability, providing multi-faceted and multi-dimensional information for problem investigation, and providing decision-making basis for managers.

[0033] Based on the needs of enterprise business development, the delivery management system first completes the automatic matching of the loading capacity of transport vehicles, the flexible merging and splitting of loading orders, and realizes the real-time location and trajectory display of transport vehicles during transportation, as well as the early warning of abnormal situations and remote emergency linkage.

[0034] This invention's delivery management includes delivery route planning, vehicle type planning, load planning, online transportation monitoring, and anomaly alarms. Based on order number rules, the system automatically generates delivery order numbers and links them to sales order data. According to the regional order turnover box requirements, it rationally arranges transport vehicles and selects the most economical or fastest delivery routes. Secondly, it plans loads through optimal cargo combinations to reduce empty runs and wasted space, improving loading rates. It supports visualized cargo tracking, using GPS technology to monitor the real-time location of goods in transit, obtain the location of transport vehicles and personnel, update transportation status, and issue background warnings for vehicles deviating from delivery routes, while simultaneously sending alerts to the driver's mini-program.

[0035] Report management, tailored to user needs, utilizes system data collection, aggregation, analysis, and governance to create a dedicated data brain for sales and distribution, generating data analysis and reports. This invention's report management includes regional volume and price, on-time delivery rate, regional sales structure, regional distribution costs, and regional product anomalies. It performs real-time data analysis, providing decision-makers with a basis for decision-making and generating various statistical reports, facilitating managers' rapid understanding of sales and distribution operations.

[0036] Among them, the Regional Quantity and Price report is used to display the order quantity, sales amount and average unit price of each region; the On-Time Delivery Rate report is used to calculate and display the on-time delivery ratio of orders for each region and each vehicle type; the Delivery Cost report is used to calculate the transportation costs, vehicle damage and labor costs of each delivery route; the Sales Anomaly report is used to record the reasons and quantities of order cancellations, returns and replenishments; all business reports support exporting to Excel format and support filtering by time range, region and product type.

[0037] It can also mine and analyze massive amounts of data in report management, providing enterprises with market trend forecasts, product optimization suggestions, and business expansion directions. For example, it can predict changes in live poultry demand in different seasons and regions, helping enterprises and partners adjust their inventory and procurement strategies in advance. Based on digital twin technology, this invention also provides visualized analysis of sales and delivery order data in the sales coverage area on a daily / monthly / yearly basis.

[0038] The system settings include functions such as user management, dictionary management, and role configuration. Roles include dealers or customers, salespersons, transport drivers, production and warehousing departments, and managers. Different application functions can be configured for each role, enabling data to be hierarchically and hierarchically distributed.

[0039] The access layer includes web, large screen, and mobile terminals. The web terminal is used for basic data management, planning management, delivery management, report management, and system settings. The large screen terminal is used for data visualization. The mobile terminal allows different roles to register and approve file information, submit and query sales orders, query delivery orders, and track transportation. This multi-terminal access setup helps internal staff and distributors / customers handle business and submit order queries anytime, anywhere, replacing the traditional offline telephone, WeChat, or paper-based business processing model. This significantly reduces the time of relevant business personnel, improves user satisfaction, and increases the efficiency of sales and delivery operations.

[0040] The front-end platform includes a financial shared platform, an SAP system, and a Defan Cloud integrated API platform. The financial shared platform is used to uniformly handle the financial accounting work of various departments and branches of the enterprise, formulate and implement expense reimbursement standards and approval processes, centrally manage the enterprise's funds, including budget preparation, fund receipt and payment settlement, and integrate the enterprise's financial data. By analyzing the profitability of different business segments and products, it optimizes business layout and resource allocation.

[0041] SAP systems are used for supply chain management, financial management, human resource management, and manufacturing management. Supply chain management optimizes the entire supply chain process from procurement and production to sales. In procurement, accurate demand forecasting and supplier management reduce procurement costs and ensure timely supply of materials. In production, production plans are rationally arranged and production resource allocation is optimized to improve production efficiency and product quality. In sales, orders are processed efficiently and shipments are arranged to improve customer satisfaction. Financial management overlaps with the financial shared service platform, providing comprehensive financial accounting and management functions, such as general ledger management, accounts receivable and payable management, and fixed asset management. It also has powerful financial analysis and decision support capabilities to meet the financial management needs of enterprises at different levels.

[0042] Human resource management encompasses all aspects of human resource management, including employee recruitment, training, attendance, compensation, and performance appraisal. It helps companies rationally plan their human resources, improve employee satisfaction and work efficiency, and enhance their talent competitiveness. Production and manufacturing management is designed for manufacturing companies. The SAP system can realize functions such as production planning and scheduling, production process monitoring, and quality management, ensuring that production activities are carried out in an orderly manner according to plan, improving product quality and production efficiency, and reducing production costs.

[0043] Defan Cloud's integrated API platform is used to break down data barriers between the financial shared service platform, SAP system, and business layer, enabling smooth data flow and sharing. For example, it can synchronize expense reimbursement data from the financial shared service platform to the SAP system for financial accounting, or transmit sales order data from the business layer to the SAP system for production planning and scheduling, thereby improving the overall operational efficiency of the enterprise.

[0044] The data layer provides a platform for dealers or customers, salespersons, transport drivers, production and warehousing personnel, and managers to conduct business operations, including: Distributors or customers can perform operations such as plan submission confirmation, transportation information inquiry, goods receipt confirmation, turnover box receipt, dispatch and storage, and account transaction inquiry.

[0045] Sales representatives perform tasks such as plan submission confirmation, transportation information inquiry, sales volume and price inquiry, and volume and price anomaly alarm.

[0046] The transport driver is responsible for receiving waybill assignments, completing transport tasks, and performing waybill tracking.

[0047] The production and warehousing department receives and executes loading plans, handles the receipt, dispatch, and storage of turnover boxes, queries delivery information, and issues alarms for abnormal deliveries.

[0048] Managers conduct regional volume and price analysis, on-time delivery rate statistics, regional sales structure analysis, regional distribution cost accounting, and regional product anomaly investigation.

[0049] The database of this invention uses MySQL and Oracle databases to store and manage structured data, and HBase and Kafka databases to store unstructured data; it also uses Redis to store high-concurrency access data, including real-time inventory, daily price, and on-the-go vehicle location. The basic equipment includes cloud servers, local servers, OSS object storage, OCR, and security devices.

[0050] like Figure 2 As shown, a method for selling and distributing fresh produce includes the following steps: S1. Distributors or customers can submit order plans to the system via a mobile app.

[0051] S2. Sales staff can conduct online preliminary review of order plans in real time on their mobile devices.

[0052] S3. The system can automatically summarize the order plans initially reviewed by the salesperson by region, and compare the buyer's order information with the seller's production information by using a two-sided matching algorithm, combined with factors such as production plans, available inventory and specifications obtained from the SAP system. The system will find the order information that meets the matching conditions and push it to the salesperson for reference.

[0053] The two-sided matching algorithm includes the following steps: S31. Obtain the order collection after initial review by the salesperson. Order collection Each order Including customer requirements and specifications Quantity required and demand areas .

[0054] S32. Obtain the production plan set from the SAP system. Production planning set Each production plan Including product specifications Planned production and production cycle .

[0055] S33, Calculate Orders With production plan Specification matching degree ,like and If the deviation rate is greater than 5%, then ,otherwise .

[0056] S34: Calculate orders With production plan Quantity matching degree , .

[0057] S35, Calculate Orders With production plan Regional matching degree ,like Corresponding delivery area and If the distribution ranges of the production bases overlap, then ,otherwise ; S36. Calculate the overall matching degree ,like Then the order is determined. With production plan Match and generate matching results.

[0058] S4. Sales staff can make minor adjustments to order allocation based on actual order demand and production plans.

[0059] S5. The salesperson pushes the adjusted order to the distributor or customer and requests the distributor or customer to confirm the adjusted order.

[0060] S6. Once the distributor or customer confirms the adjusted order, the system will automatically push the order to the reporting plan and proceed to S7.

[0061] S7. Confirmed actual orders are submitted to the Defan Cloud Integration API platform, and through the financial shared platform and SAP platform, the platform is used to determine whether the shipment conditions are met by associating the information of the distributor or customer, the specifications, quantity, unit price of the purchase order, and the prepayment balance. If the shipping conditions are met, the order information will be sent to the production department.

[0062] If the shipping conditions are not met, the result will also be sent to the distributor or customer.

[0063] In this step, whether the shipping conditions are met is determined by the following steps: S71, Obtaining an Order Total amount ;in, For orders The unit price.

[0064] S72. Acquiring customers from a financial shared service platform Prepayment balance ; S73, if If the conditions for shipment are met, the order will be sent. To the production and warehousing department.

[0065] S74, if If the shipment conditions are not met, an insufficient prepayment reminder will be generated and pushed to the customer via a mobile app. And the corresponding salesperson.

[0066] S8. The system obtains production plans and inventory levels through the SAP system and reports them to the production and warehousing departments. The production and warehousing departments process and produce goods according to the order data, and finally put the products into the warehouse and synchronize the information to the sales and distribution system.

[0067] S9. Determine whether the sales and distribution system delivers goods to distributors or customers or allows self-pickup. When delivering goods to distributors or customers, the system automatically determines the warehouse department based on information such as product quantity, type, and delivery area.

[0068] When a distributor or customer picks up the goods, the delivery note will also be synchronized to the distributor's or customer's mobile app. The distributor or customer can then use the delivery note to pick up the goods at the warehouse department, update the pickup status by scanning the code, and push the information to the SAP platform.

[0069] S10. The sales and distribution system generates loading task orders and allocates transport vehicles. Simultaneously, based on factors such as vehicle type and quantity, it automatically dispatches orders to internal transport drivers. The vehicle allocation process includes the following steps: S101, Area requiring order acquisition Total product weight and volume .

[0070] S102. Obtain the set of available vehicles from the data layer. Each available vehicle Including load limit Volume limit and delivery range .

[0071] S103, Filter to meet the requirements , and The vehicles generate a candidate vehicle set. .

[0072] S104, Calculate candidate vehicles Delivery costs : ; in, Indicates the distance traveled. This indicates the freight cost per unit distance. Costs associated with vehicle idle time.

[0073] S105, Select The vehicle with the smallest allocation is used as the allocation result to generate a loading task order.

[0074] Simultaneously, automatic counting is performed in the sorting, boxing, weighing, packaging, and warehousing stages using photoelectric sensors, RFID readers, and data verification units. The specific workflow is as follows: In the sorting process, photoelectric sensors are used to count the sorted fresh produce, generating sorting count data. .

[0075] During the packing process, RFID readers are used to read the RFID tags on each box and record the quantity packed. At the same time, the RFID tags need to be pre-written with product specifications and batch information.

[0076] In the weighing and packaging process, the total weight of the packaged product is obtained using a weighing sensor. Combined with the unit product weight Calculate weighing count data .

[0077] During the warehousing process, the barcodes on the packaging boxes are read using a barcode scanner to record the quantity received. .

[0078] Data verification unit comparison , , and If the deviation rate between any two data points is less than or equal to 1%, the average value is taken as the final counting result; if the deviation rate is greater than 1%, an abnormal counting warning is triggered, and production management personnel are notified to review the data.

[0079] S11. After receiving the task order on their mobile devices, the transport driver can load and pick up the goods at the warehouse according to the task order information, and change the vehicle status to "awaiting transport" by scanning the code.

[0080] S12. After scanning the code with the mobile app, the production and warehousing department will synchronize the vehicle loading status to the system in real time.

[0081] S13. After loading and picking up the goods, the transport driver starts delivering the goods. At this time, scanning the code again can change the vehicle status to "in transit".

[0082] S14. When the transport driver arrives at the dealer's or customer's delivery location, if the conditions for confirming receipt are met, the customer will confirm receipt by scanning the QR code on the transport driver's mobile device, and the vehicle status will be automatically changed to "delivery completed (returning)". After the driver returns to the company, he will scan the code again to change the vehicle status to "order delivery completed", and the receipt status information will also be pushed to the SAP system.

[0083] In this step, anomaly warnings can also be issued for actions that are not completed within the preset time, including: Overdue loading warning: If a loading task order is not generated within 2 hours after order confirmation, or if loading and scanning are not completed within 1 hour after the loading task order is assigned, a warning will be triggered.

[0084] Route Deviation Warning: If the real-time location of the vehicle deviates from the planned delivery route by more than or equal to kilometers for 5 minutes, a warning will be triggered.

[0085] Overdue delivery warning: If the delivery is not signed for and scanned within 4 hours of the vehicle arriving at its destination, a warning will be triggered.

[0086] Warning information is pushed to relevant roles, including drivers, salespersons, and managers, via mobile mini-programs.

[0087] S15. The system summarizes and analyzes data, allowing users to view regional volume and price, on-time delivery rate, regional sales plan, early warning status, and big data analysis, while also providing data visualization on a single chart.

[0088] Example 1 The fresh product order delivery system of this invention was piloted at Xinjiang A Food Co., Ltd. A Food Co., Ltd.'s main business includes breeding chickens, slaughtering and processing commercial chickens, and selling fresh poultry meat. Its daily slaughtering capacity is 55,000 birds, and its annual production of fresh poultry meat is 25,000 tons. Products include whole fresh chickens, chicken pieces, and chicken by-products. Sales cover Urumqi, Changji, Shihezi, and other prefectures in northern Xinjiang, with some products sold to Gansu and Xining. The company implements a "fresh product strategy," ensuring a shelf life of 3-5 days, and relies on 4.2M, 9.6M, and 13M refrigerated trucks for delivery to distributors, specialty stores, and authorized sales points.

[0089] In terms of the hardware environment, this embodiment deploys three Huawei RH2288H V5 application servers, each configured with two Intel Xeon Gold 6248R CPUs, 128GB DDR4 memory, and four 1.2TB SAS hard drives. It also deploys two Huawei RH5885H V5 database servers, each configured with four Intel Xeon Gold 6248R CPUs, 256GB DDR4 memory, and eight 2TB SAS hard drives. The application servers are deployed using a Kubernetes cluster, and the database servers use a master-slave replication architecture.

[0090] In the terminal equipment, managers and sales staff use Lenovo ThinkPad X1 Carbon laptops, which are equipped with Intel Core i7-1260P CPUs, 16GB of RAM and 512GB SSDs; customers, salespersons and transport drivers can use smartphones that support 5G networks and have WeChat mini-programs installed on their phones; in the production process, E3Z-LS63 photoelectric sensors, UR500 RFID readers, HBM Z6 weighing sensors and DS2200 barcode scanners are deployed, and these devices communicate with the application server via industrial Ethernet.

[0091] In terms of network environment, the company uses Huawei S5735-S48T4X core switches to build gigabit Ethernet internally, and connects to the Internet externally via 500M fiber optic cable. It is equipped with Huawei USG6000E firewall and Huawei AR6700 VPN device to ensure data transmission security.

[0092] In terms of software environment, the server uses CentOS 7.9 operating system, the terminal devices are Windows 11 for laptops and Android 12 for mobile phones. The database uses MySQL 8.0 with Redis 6.0 for caching, and RabbitMQ 3.10 is used for message queues.

[0093] In terms of development framework, the web application is developed using React 18 combined with Ant Design Pro, the mini-program application is developed using the native WeChat mini-program framework, and the backend microservices are developed using Spring Boot 2.7 combined with Spring Cloud Alibaba. Company A has also deployed the Fanyun Integration API Platform V6.0, the SAP Production Management Platform S / 4HANA 2021, and the Yonyou U9 Cloud Financial Shared Service Platform. This system integrates with these external systems through API interfaces.

[0094] System deployment and configuration were carried out in phases: In the environment preparation phase, server initialization was completed, CentOS 7.9 operating system was installed, and IP addresses, firewall rules, and SSH services were configured to ensure normal communication between servers; Docker 20.10.17 and Kubernetes 1.24 were installed on the application server to deploy a Spring Cloud Alibaba microservice cluster; MySQL 8.0 and Redis 6.0 were installed on the database server, and master-slave replication and sentinel mode were configured; RabbitMQ 3.10 was installed on the message queue server, and six business queues and a dead-letter queue were created; the interface with external platforms was debugged using the Postman tool to ensure normal bidirectional data transmission.

[0095] During the system deployment phase, the microservices for order processing, production integration, logistics monitoring, financial integration, and data visualization were packaged into Docker images and uploaded to the Kubernetes cluster, with resource limits and automatic scaling rules configured. The web-side code was packaged into static resources and deployed to an Nginx 1.21 server with a reverse proxy configured. The mini-program code was submitted to the WeChat Official Accounts Platform for review and approval before going live. Data files of 500 customers were synchronized from the Defan Integration API Platform, production plan data for the next 7 days was synchronized from the SAP system, and vehicle data for 30 refrigerated trucks and 20 delivery routes were manually entered.

[0096] During the system configuration phase, user roles and permissions are set on the web interface, and warning thresholds are configured. The weights of the two-sided matching algorithm are configured in the order processing microservice, and the cost parameters of the vehicle allocation algorithm are configured in the logistics monitoring microservice. The price update rules are configured in the order processing microservice, and new prices are obtained from the financial shared service platform at 8:00 AM and 2:00 PM daily and updated to the mini-program.

[0097] Comprehensive testing and verification work was carried out: During the functional testing phase, a customer submitted an order plan for 100 boxes of whole chickens weighing 1.5-1.6kg in a certain region. After the salesperson's initial review, the system called a two-sided matching algorithm to match a production plan for 200 boxes of whole chickens weighing 1.5-1.7kg, generating a comprehensive matching score of 0.9. After the salesperson made adjustments, the order was pushed to the customer for confirmation and then pushed to the SAP system, verifying that the entire order processing process was normal. At the same time, the production docking, logistics monitoring, financial integration, and data visualization functions were all verified to be normal.

[0098] During the performance testing phase, JMeter was used to simulate 100 customers submitting orders simultaneously, 10 salespersons conducting initial reviews simultaneously, and 5 sales support staff viewing reports simultaneously. The system response time was 2.5 seconds and the error rate was 0, meeting the requirements. When importing 100,000 historical order data, the database query time was 0.8 seconds and the report generation time was 4 seconds, meeting the standards. The system was run continuously for 72 hours to simulate daily business operations without crashes or data loss.

[0099] During the security testing phase, Burp Suite was used to test the external interface and found no SQL injection or XSS attack vulnerabilities. Data transmission was encrypted using HTTPS, and the database password was encrypted using MD5 and accessible only to authorized users. Simulated access to the web-based system settings by a salesperson was denied, indicating that the security performance met the standards.

[0100] During the personnel training phase, training was conducted for different groups: Management personnel received 2 hours of training on web-based system settings, business report queries, and data monitoring functions, using a combination of theoretical explanations and practical demonstrations; sales staff received 3 hours of training on basic web-based data management and business report export functions, using a combination of practical exercises and Q&A sessions; sales personnel received 2 hours of training on the mini-program's order initial review, adjustment, and production progress query functions, using a combination of on-site practice and case analysis; transport drivers received 1 hour of training on the mini-program's task receiving and loading barcode scanning functions, using a combination of video tutorials and practical demonstrations; customers received 0.5 hours of training on mini-program order operations through online manuals and customer service guidance, using a combination of self-study and online Q&A; and production personnel received 1 hour of training on the operation of the automated counting module and exception handling, using a combination of on-site practice and equipment demonstrations.

[0101] During the trial operation phase, the region covered three core areas in northern Xinjiang: Urumqi, Changji, and Shihezi, involving 200 customers, 10 sales representatives, 15 drivers, and 2 production workshops. The business encompassed the entire process of fresh whole chickens with feathers, chicken pieces, and chicken by-products. Two technical staff were assigned daily to handle issues, and 20 feedback items were collected, including 12 operational issues and 8 functional issues. For operational issues, the mini-program's QR code recognition algorithm was optimized to a 99.9% success rate, and prompts were added. For functional issues, product type filtering conditions were added to reports, and data formats were optimized. All issues were resolved within 24 hours.

[0102] During the trial operation, a total of 2,400 orders were processed, 30,000 boxes of products were produced, 900 delivery trips were made, and 30 million yuan in financial receipts were collected. Key indicators showed significant improvement: the order processing cycle was shortened from 8 hours to 3 hours, a reduction of 62.5%; the order matching accuracy rate increased from 65% to 90%, an increase of 25 percentage points; the on-time delivery rate increased from 78% to 98%, an increase of 20 percentage points; the counting error rate decreased from 5%-8% to 0.1%, a reduction of more than 98%; and the accounts receivable overdue rate decreased from 10% to 1%, a reduction of 90%.

[0103] Therefore, the present invention adopts the above-mentioned fresh product sales and distribution system and method, which effectively solves the industry pain points such as inefficient order matching, logistics out-of-control, inaccurate counting, and financial disconnect in the sales and distribution of fresh products through the integration of the whole chain, combined with intelligent algorithms and multi-terminal collaborative design. It is especially suitable for short-shelf-life fresh products such as poultry, fruits and vegetables, and provides strong technical support for enterprises to reduce costs and increase efficiency.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A fresh produce sales distribution system characterized by: The system comprises, from top to bottom, an access layer, a front-end platform, a service layer, a data layer, a database, and basic equipment, the service layer adopts a micro-service architecture and comprises basic data management, plan management, distribution management, report management, and system setting operations; The basic data management comprises customer archives, material data, vehicle model data, and distribution route data, the plan management comprises plan processing, plan confirmation, production plan, and raw chicken plan, the distribution management comprises distribution route planning, vehicle model planning, loading planning, online transportation monitoring, and abnormal alarm; The report management comprises regional quantity and price, delivery timeliness, regional sales structure, regional distribution cost, and regional product anomaly, the system setting comprises user management, dictionary management, and role configuration, the roles comprise distributors or customers, salespersons, transportation drivers, production and storage departments, and management personnel.

2. A fresh product vending system according to claim 1, wherein: The access layer comprises a web end, a large-screen end, and a mobile end, the web end is used for performing basic data management, plan management, distribution management, report management, and system setting operations, the large-screen end is used for visual display of data, and the mobile end is used for registration and audit of archive information, submission, query, and audit of sales order plans, distribution management and query of order plans, and transportation tracking operations by different roles.

3. A fresh product vending system according to claim 1, wherein: The front-end platform comprises a financial shared platform, an SAP system, and a Dafang cloud integration API platform, the financial shared platform is used for unified processing of financial accounting of departments and branches of an enterprise, formulation and execution of expense reimbursement standards and approval processes, centralized management of enterprise funds including budget preparation, payment and settlement of funds, and integration of enterprise financial data, optimization of business layout and resource allocation through analysis of profitability of different business blocks and different products; The SAP system is used for supply chain management, financial management, human resource management, and production and manufacturing management, the Dafang cloud integration API platform is used for synchronizing expense reimbursement data in the financial shared platform to the SAP system for financial accounting, and transmitting sales order data of the service layer to the SAP system for production plan scheduling.

4. A fresh product vending system according to claim 1, wherein: The data layer is used for business operations by distributors or customers, salespersons, transportation drivers, production and storage departments, and management personnel, including: Distributors or customers perform plan submission and confirmation, transportation information query, receipt confirmation, turnover frame receiving and storage, and account flow query operations; Salespersons perform plan submission and confirmation, transportation information query, sales volume and price query, and quantity and price anomaly alarm operations; Transportation drivers are responsible for receiving transportation order tasks, completing transportation tasks, and transportation order query operations; Production and storage departments perform loading plan receiving and execution, turnover frame receiving and storage, distribution information query, and arrival anomaly alarm operations; Management personnel perform regional quantity and price analysis, delivery timeliness statistics, regional sales structure analysis, regional distribution cost accounting, and regional product anomaly investigation operations.

5. A fresh product vending system according to claim 1, wherein: The database adopts MySQL and Oracle databases to store and manage structured data, adopts HBase and Kafka databases to store unstructured data, and adopts Redis to store high-concurrency access data including real-time inventory, current price, and in-transit vehicle location; and the basic equipment comprises cloud servers, local servers, OSS object storage, OCR, and security equipment.

6. A method of distributing fresh produce sales, characterized by, The method comprises the following steps: S1. The dealer or customer submits an order plan to the system business layer through the mobile applet of the system access layer; S2. The salesperson performs online preliminary review of the order plan on the mobile terminal; S3. The system business layer automatically performs regional aggregation according to the order plan preliminarily reviewed by the salesperson, and finds the order information meeting the matching conditions by comparing the order information of the buyer with the production information of the seller through a two-sided matching algorithm combined with the production plan and available inventory obtained from the SAP system, and pushes the order information to the salesperson for reference; S4. The salesperson performs fine adjustment of the order according to the actual order demand and production plan; S5. The salesperson pushes the adjusted order to the dealer or customer and requests the dealer or customer to confirm the adjusted order; S6. The dealer or customer confirms the adjusted order, and the system business layer automatically pushes the confirmed order to the reporting plan to enter S7; S7. The confirmed actual order is reported to the DeFeng Cloud integrated API platform, and is associated with the archive information of the dealer or customer, the specification quantity unit price of the procurement order and the prepayment balance through the financial sharing platform and the SAP platform to determine whether the delivery condition is met: If the delivery condition is met, the order information is pushed to the production department; If the delivery condition is not met, the result is pushed to the dealer or customer; S8. The system obtains the production plan and inventory from the SAP system and reports them to the production and storage department, which processes and delivers the products according to the order data, and finally synchronizes the product storage information to the sales distribution system; S9. It is determined whether the dealer or customer will receive the goods or pick up the goods. When the dealer or customer receives the goods, the system automatically determines the warehouse-out order to the production and storage department according to the product quantity, type and delivery area; When the dealer or customer picks up the goods, the warehouse-out order is synchronized to the mobile applet of the dealer or customer, and the dealer or customer picks up the goods at the storage department by scanning the code, modifies the state of picking up the goods, and pushes it to the SAP platform; S10. The sales distribution system generates a loading task sheet and allocates a transport vehicle; S11. After receiving the task sheet on the mobile terminal, the transport driver goes to the storage department to load and pick up the goods according to the task sheet information, and changes the vehicle state to ready for transportation by scanning the code; S12. After scanning the code on the mobile applet, the production and storage department synchronizes the loading state of the vehicle to the system business layer in real time; S13. When the transport driver arrives at the delivery location of the dealer or customer, he performs the delivery, and then scans the code again to change the vehicle state to in transit; S14. When the transport driver arrives at the delivery location of the dealer or customer, he performs the delivery, and then scans the code again to change the vehicle state to in transit; S14. When the transport driver arrives at the delivery location of the dealer or customer, he performs the delivery, and then scans the code again to change the vehicle state to in transit; When the driver returns to the company, he changes the vehicle state to order distribution completed by scanning the code, and pushes the receipt state information to the SAP system; and according to the preset time, an abnormal warning is given for the action not completed within the time. S15, view regional volume and price, delivery timeliness, regional sales plan, early warning and big data analysis through system business layer.

7. A method of selling and distributing fresh produce as claimed in claim 6 wherein, In S3, the bilateral matching algorithm includes the following steps: S31. Obtain the order collection after initial review by the salesperson. Order collection Each order Including customer requirements and specifications Quantity required and delivery area ; S32, obtaining a production plan set from the SAP system , the production plan set , each production plan in the production plan set includes a product specification , a planned yield , and a production cycle S33, calculating the order with the production plan , if the deviation rate of the customer demand specification from the product specification is greater than 5%, the specification matching degree , otherwise ;​ S34: Calculate order With production plan Quantity matching degree , ; S35、calculate order with production plan area matching degree , if the corresponding distribution area and the production base distribution range of the production plan overlap, the area matching degree , otherwise ; S36, calculate the comprehensive matching degree If , determine that the order matches the production plan , and generate a matching result.

8. A method of selling and distributing fresh produce as claimed in claim 7, wherein, In S7, whether the shipment condition is met is determined by the following steps: S71, obtaining an order total amount of money ; wherein unit price of the order ; S72, obtaining a prepayment balance of the customer from the financial sharing platform ;​ S73, if then determine that the shipping condition is satisfied, and push the order to the production warehouse department ; S74, if If the condition is not met, a reminder of insufficient prepayment is generated and pushed to the customer through the mobile app and the corresponding salesperson.

9. A method of selling and distributing fresh produce as claimed in claim 8, wherein, In S10, the transport vehicle allocation includes the following steps: S101、Obtain the demand area of the order , total weight of products and volume ; S102、obtain a set of available vehicles from the data layer each available vehicle including a load upper limit a volume upper limit and a delivery range ; S103, screening vehicles satisfying , and , generating a candidate vehicle set ; S104、Calculate the delivery cost of the candidate vehicle :​ ； wherein, denotes the transport mileage, denotes the freight per unit of mileage, is the vehicle idle cost; S105, selecting The smallest vehicle as a distribution result, generates a loading task order.

10. The method of claim 9, wherein, In S14, the abnormal early warning includes: Overdue non-loading warning: if the loading task order is not generated within 2 hours after the order is confirmed, or the loading code scanning is not completed within 1 hour after the loading task order is assigned, the early warning is triggered; Off-route warning: if the distance deviation between the real-time position of the vehicle and the planned distribution route is greater than or equal to 5 kilometers, and lasts for 5 minutes, the early warning is triggered; Overdue non-signing warning: if the vehicle arrives at the destination and the signing code scanning is not completed within 4 hours, the early warning is triggered; The early warning information is pushed to the corresponding roles including the driver, the salesperson and the management personnel through the mobile terminal applet.

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