Purchase order automatic generation and warehouse management method

Abstract

According to the purchase order automatic generation and warehouse management method provided by the invention, through multi-stage linkage of product model analysis, BOM matching, supplier matching, order generation and material warehouse management, full-process automation from model analysis to material warehouse is realized. According to the invention, from purchasing order placing to the material warehouse, warehousing personnel can call order data according to order numbers, manual input is avoided, upstream and downstream data are communicated, and one-stop data transmission is realized. According to the one-stop purchasing and warehouse management method and system, automatic generation of the purchasing order is realized through the preset product model and the raw material matching rule, and seamless connection with the warehousing system is realized. By establishing the preset matching rule base of the product models and the raw materials / components, the system can automatically generate the purchase order, and the time-consuming steps of manual raw material selection, inventory checking, purchase order creation and the like in a traditional mode are eliminated.

Description

Technical Field

[0001] This invention relates to the field of enterprise supply chain management technology, and in particular to a method for automatically generating purchase orders and managing warehouses. Background Technology

[0002] The current raw material procurement and warehouse management processes in traditional manufacturing industries have the following pain points:

[0003] 1. Inefficient manual operation: In the traditional model, purchasing personnel need to manually break down the product BOM (Bill of Materials), calculate raw material requirements, manually summarize purchase requests, match suppliers, and check prices and inventory. This is time-consuming and prone to omissions or quantity errors due to lack of experience.

[0004] 2. Fragmented processes: The processes of procurement application, approval, and order placement are disconnected, lacking end-to-end automation;

[0005] 3. Severe data silos: Purchase orders are disconnected from the warehousing system, orders are out of sync with inventory, and warehouses need to repeatedly enter data;

[0006] 4. Low efficiency: In the traditional model, a single procurement request task involves multiple contracts and materials for multiple different models of products. Multiple people need to be assigned to complete the raw material procurement order, which is time-consuming and labor-intensive, and the work cannot achieve a response time of seconds. Summary of the Invention

[0007] The purpose of this invention is to provide a method for automatically generating purchase orders and managing warehouses.

[0008] To address the above problems, this invention provides a method for automatically generating purchase orders and managing warehouses, comprising:

[0009] Establish a database that maps product models to raw material details;

[0010] Establish a supplier information database and a database of standard procurement delivery dates for suppliers' raw materials;

[0011] The system retrieves the product model selected by the user and obtains the corresponding raw material details from the database that maps product models to raw material details. Based on the corresponding raw material details, supplier information database, standard procurement delivery time database, and intelligent supplier recommendation algorithm, the system generates order information containing suppliers and corresponding raw materials in the procurement system.

[0012] Furthermore, in the above method, the product model includes: a unique product identifier, a product name, and product specifications.

[0013] The raw material details include: raw material name, raw material model, raw material specifications, raw material material, standard usage of raw materials, and recommended raw material suppliers.

[0014] Furthermore, in the above method, the supplier information database includes: supplier name, supplier qualifications, range of raw materials supplied by the supplier, historical delivery records, and supplier quality rating.

[0015] The supplier's standard procurement delivery time database for raw materials includes: production cycle and transportation time.

[0016] Furthermore, in the above method, the product model selected by the user is obtained, and the raw material details corresponding to the product model are retrieved from the database of correspondence between product models and raw material details. Based on the corresponding raw material details, supplier information database, standard procurement delivery time database, and supplier intelligent recommendation algorithm, order information containing suppliers and corresponding raw materials is generated in the procurement system, including:

[0017] After obtaining the product model selected by the user, the system automatically parses the product model, calls the database to match the raw material details, and automatically generates a purchase list based on the theoretical purchase quantity of the raw materials. Finally, the system uses the raw material details, supplier information database, standard purchase delivery time database, and supplier intelligent recommendation algorithm and different material order templates to split the purchase list into suppliers to generate order information.

[0018] Furthermore, in the above method, the intelligent supplier recommendation algorithm recommends the optimal supplier group based on factors such as raw material demand, supplier inventory, historical order data, and delivery speed.

[0019] Furthermore, in the above method, after generating order information containing suppliers and corresponding raw materials in the procurement system, the following steps are also included:

[0020] The system automatically verifies the completeness and format compliance of order information. If the verification fails, it will display an error message and block the order from being placed, while also logging the information for future investigation.

[0021] Furthermore, in the above method, after generating order information containing suppliers and corresponding raw materials in the procurement system, the following steps are also included:

[0022] Push order information from the procurement system to the warehouse management system;

[0023] After receiving purchase order information, the warehouse management system automatically creates warehouse tasks and generates electronic warehouse orders containing raw material information, suppliers, and target storage locations.

[0024] By scanning the labels of raw materials, the raw materials are put on the shelves according to the target storage location corresponding to the scanned label information, and the warehouse management system automatically updates the inventory ledger.

[0025] Furthermore, in the above method, after generating the electronic warehouse order containing raw material information, supplier, and target warehouse location, it also includes:

[0026] By scanning the labels of raw materials, the scanned label information is automatically compared with the electronic warehouse order. If the actual quantity of raw materials received does not match the electronic warehouse order, the discrepancy is marked in the warehouse management system and automatically fed back to the purchasing system, triggering the order information correction process in the purchasing system.

[0027] Furthermore, in the above method, after pushing the order information from the procurement system to the warehouse management system, the following steps are also included:

[0028] Each order is assigned a unique tracking number, and a complete operation log is recorded from the purchase order to the warehouse, including the order time, approver, transportation status, and warehouse time.

[0029] Furthermore, in the above method, after pushing the order information from the procurement system to the warehouse management system, the following steps are also included:

[0030] When the inventory level of raw materials in the warehouse management system exceeds the safety threshold, duplicate purchase orders are automatically blocked; when the inventory level of raw materials in the warehouse management system is less than the inventory warning level, an automatic purchase order is generated.

[0031] Compared with existing technologies, this invention achieves full-process automation from model analysis to material warehousing through multi-level linkage of "product model analysis → BOM matching → supplier matching → order generation → material warehousing".

[0032] This invention enables warehouse staff to retrieve order data from the purchase order to the material warehouse simply by using the order number, avoiding manual data entry and connecting upstream and downstream data to achieve one-stop data transmission.

[0033] This invention provides a one-stop procurement and warehouse management method and system that automates the generation of purchase orders by pre-setting product model-raw material matching rules and seamlessly integrates with the warehousing system. It is suitable for scenarios requiring high-frequency procurement, such as manufacturing and e-commerce.

[0034] This invention establishes a pre-defined matching rule library between product models and raw materials / components, enabling the system to automatically generate purchase orders and eliminating time-consuming steps such as manually selecting raw materials, checking inventory, and creating purchase orders in the traditional model. Compared to the traditional process, this invention can reduce the purchasing and ordering work of 3-4 people to one person and complete it in seconds, reducing the error rate to near zero. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of a method for automatically generating purchase orders and managing warehouses according to an embodiment of the present invention. Detailed Implementation

[0036] The present invention will now be described in further detail with reference to the accompanying drawings.

[0037] In a typical configuration of this application, the terminal, the device of the service network, and the trusted party all include one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0038] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0039] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media, such as modulated data signals and carrier waves.

[0040] This invention provides a method for automatically generating purchase orders and managing warehouses, the method comprising:

[0041] Step S1: Establish a database (BOM) that maps product models to raw material details;

[0042] Here, a standardized database of product models can be established, containing information such as the unique identifier, product name, and product specifications for each product model.

[0043] In addition, a structured BOM table can be built to record the details of raw materials for each product model, such as raw material name, raw material model, raw material specifications, raw material material, standard usage of raw materials, and raw material supplier recommendations. The association between product models and raw materials can be realized through database relational tables.

[0044] A version management mechanism can be introduced to support dynamic updates and historical tracking of the BOM table.

[0045] Step S2: Establish a supplier information database and a standard procurement delivery date database for suppliers' raw materials;

[0046] Here, you can maintain a supplier database, including: supplier name, supplier qualifications, range of raw materials supplied by the supplier, historical delivery records, and supplier quality rating.

[0047] It has a pre-defined database of standard procurement delivery dates for each raw material from suppliers, such as production cycle and transportation time, and supports dynamic adjustment of standard procurement delivery dates based on the supplier's real-time production capacity.

[0048] Step S3: Obtain the product model selected by the user; retrieve the raw material details corresponding to the product model selected by the user from the database of the correspondence between product model and raw material details; based on the corresponding raw material details, supplier information database, standard procurement delivery time database and supplier intelligent recommendation algorithm, generate order information containing suppliers and corresponding raw materials in the procurement system.

[0049] Preferably, step S3 may include: after obtaining the product model selected by the user, automatically parsing the product model, calling the database to match the raw material details, automatically generating a purchase list based on the theoretical purchase quantity of the raw materials, and finally splitting the purchase list into suppliers to generate order information based on the raw material details, supplier information database, standard purchase delivery time database, and supplier intelligent recommendation algorithm and different material order templates.

[0050] Here, a rules engine can be developed to automatically parse the product model selected by the user and match the corresponding BOM table through preset logic, such as product model coding rules and raw material substitution strategies.

[0051] It supports complex matching logic, such as filtering specific raw material lists by product series, version, or customization requirements.

[0052] Preferably, the intelligent supplier recommendation algorithm can recommend the optimal supplier combination based on factors such as raw material demand, supplier inventory, historical order data, and delivery speed.

[0053] It allows procurement personnel to manually adjust supplier selections and supports saving frequently used supplier combinations as templates.

[0054] Ideally, a visual user interface should be developed, allowing purchasing personnel to select the target product model via drop-down menus or search functions, and the system should load the BOM data for that model in real time.

[0055] A "One-Click Order" button can be provided in the user interface. Clicking it will trigger the following automated process:

[0056] Generate a raw material / component procurement list based on the BOM, and automatically calculate the total quantity and total amount;

[0057] The supplier recommendation algorithm is invoked to generate suggested suppliers and corresponding raw material allocation plans;

[0058] Automatically fill in basic information such as order date and delivery date (based on the delivery date database).

[0059] In addition, this invention supports order preview, allowing purchasing personnel to modify suppliers, adjust quantities, or add remarks. It can also integrate electronic approval processes, automatically pushing orders to approvers, and generating formal purchase orders upon approval.

[0060] Order data is stored in standardized formats (such as XML and JSON) and can be exported to PDF, Excel and other formats.

[0061] In one embodiment of the automatic purchase order generation and warehouse management method of the present invention, after generating order information containing suppliers and corresponding raw materials in the purchasing system, the method further includes step S4: verifying the completeness and format compliance of the order information automatically. If the verification fails, an error is prompted and the order is blocked, and a log is recorded for subsequent investigation.

[0062] Here, the system can automatically verify the completeness and format compliance of order information, such as whether the quantity is a positive integer and whether the supplier is valid. If the verification fails, the system will display an error message and block the order from being placed, while also logging the information for subsequent investigation.

[0063] In one embodiment of the automatic purchase order generation and warehouse management method of the present invention, after generating order information including suppliers and corresponding raw materials in the purchasing system, the method further includes:

[0064] Step S51: Push the order information from the procurement system to the warehouse management system;

[0065] Here, an integration interface can be developed between the procurement system and the warehouse management system, using API or middleware technology to achieve real-time synchronization of order data.

[0066] Define data transmission standards to ensure that key information such as the name, quantity, supplier, and order number of raw materials in the purchase order is accurately transmitted to the warehouse management system.

[0067] Purchase order information is automatically synchronized to the warehouse management system. Fields include raw material code, raw material name, raw material model and specifications, raw material quantity, raw material supplier, and estimated arrival time of raw materials. From the time the purchase order is placed to the material warehouse, warehouse personnel can retrieve the order information using the order number, avoiding manual entry. This seamless data flow between upstream and downstream processes enables one-stop data transmission.

[0068] Step S52: After receiving the purchase order information, the warehouse management system automatically creates a warehouse task and generates an electronic warehouse order containing raw material information, supplier, and target storage location.

[0069] Step S53: By scanning the labels of raw materials, the raw materials are put on the shelves according to the target storage location corresponding to the scanned label information. The warehouse management system automatically updates the inventory ledger without the need for manual data entry.

[0070] In one embodiment of the automatic purchase order generation and warehouse management method of the present invention, an electronic warehouse order containing raw material information, supplier and target storage location is generated. The method further includes step S6, which involves scanning the labels of raw materials and automatically comparing the scanned label information with the electronic warehouse order. If the actual quantity of raw materials delivered does not match the electronic warehouse order, the discrepancy data is marked in the warehouse management system and automatically fed back to the purchasing system, triggering the order information correction process of the purchasing system.

[0071] This allows for integration with IoT devices (such as barcode scanners and RFID readers), enabling warehouse staff to quickly verify information by scanning the labels on raw materials.

[0072] In one embodiment of the automatic purchase order generation and warehouse management method of the present invention, after pushing the order information from the purchase system to the warehouse management system, the method further includes:

[0073] Each order is assigned a unique tracking number, and a complete operation log is recorded from the purchase order to the warehouse, including the order time, approver, transportation status, warehouse time, etc.

[0074] Here, you can check the order status by tracking number to achieve transparent management of procurement, logistics, and warehousing.

[0075] In addition, this invention can also provide a standardized interface to support integration with third-party systems such as ERP, OA systems, financial systems, and supply chain collaboration platforms to achieve data closure (such as automatic synchronization of order costs to the financial system).

[0076] Furthermore, this invention can also employ a microservice architecture, allowing for the individual upgrading or replacement of a functional module, such as a supplier recommendation algorithm or a BOM database, thereby reducing system maintenance complexity.

[0077] This invention can also be used to develop mobile applications or lightweight interfaces, enabling purchasing personnel to complete operations such as model selection and order approval via mobile phones or tablets, thereby improving flexibility.

[0078] In one embodiment of the automatic purchase order generation and warehouse management method of the present invention, after pushing the order information from the purchase system to the warehouse management system, the method further includes:

[0079] When the inventory level of raw materials in the warehouse management system exceeds the safety threshold, duplicate purchase orders are automatically blocked; when the inventory level of raw materials in the warehouse management system is less than the inventory warning level, an automatic purchase order is generated.

[0080] like Figure 1 The diagram shown is a flowchart of an embodiment of the present invention.

[0081] This invention achieves order generation in seconds through a multi-level linkage of "product model parsing → BOM matching → supplier matching → order generation → material warehousing". Example: After selecting the product model "SGCR200", the system automatically parses the 200 specification products under the SGCR model, matches them with the corresponding 22 types of raw materials in 8 categories, and splits them into 8 orders according to different suppliers. It also supports selecting multiple models at once, and the quantities of the same raw material are automatically merged and summarized when generating orders.

[0082] This invention achieves full-process automation from model analysis to material warehousing through multi-level linkage of "product model analysis → BOM matching → supplier matching → order generation → material warehousing".

[0083] This invention enables warehouse staff to retrieve order data from the purchase order to the material warehouse simply by using the order number, avoiding manual data entry and connecting upstream and downstream data to achieve one-stop data transmission.

[0084] This invention provides a one-stop procurement and warehouse management method and system that automates the generation of purchase orders by pre-setting product model-raw material matching rules and seamlessly integrates with the warehousing system. It is suitable for scenarios requiring high-frequency procurement, such as manufacturing and e-commerce.

[0085] This invention establishes a pre-defined matching rule library between product models and raw materials / components, enabling the system to automatically generate purchase orders and eliminating time-consuming steps such as manually selecting raw materials, checking inventory, and creating purchase orders in the traditional model. Compared to the traditional process, this invention can reduce the purchasing and ordering work of 3-4 people to one person and complete it in seconds, reducing the error rate to near zero.

[0086] This invention integrates a supplier database and preset matching rules, supports one-click selection of suppliers and generation of orders, and achieves automatic order allocation through preset delivery date rules, solving problems such as scattered supplier connections and opaque pricing in traditional procurement. It can also achieve automatic adaptation of dynamic pricing strategies.

[0087] The purchase order information of this invention is automatically transmitted to the warehousing module through the system interface, avoiding errors caused by manual secondary entry and realizing one-stop connection of upstream and downstream data.

[0088] This invention combines a real-time inventory update mechanism, which can automatically trigger replenishment warnings or automatically deduct inventory based on the number of sales contracts to generate a purchase recommendation quantity. This reduces the risk of stockouts or overstocking caused by lag in manual statistics and promotes enterprises to upgrade to a "zero inventory" management model.

[0089] This invention replaces traditional, highly experience-intensive procurement operations with automated processes, reducing reliance on personnel expertise and lowering labor costs.

[0090] This invention provides end-to-end data tracking, supports procurement decision optimization and supplier performance evaluation, enhances supply chain collaboration and traceability, and provides a data foundation for enterprises to build a smart supply chain ecosystem.

[0091] This invention solves the core problems of traditional supply chain management, such as excessive manual intervention, severe data silos, and low efficiency, through a fully automated design that integrates intelligent procurement decision-making, automatic order generation, and data-driven warehouse management. It provides reusable standardized solutions for manufacturing, pharmaceuticals, e-commerce, and other fields, helping enterprises achieve cost reduction, efficiency improvement, and digital transformation.

[0092] This invention, based on preset product model and raw material matching rules, reduces the procurement ordering process, which originally required 3-4 people, to one person, achieving a response time in seconds and improving processing efficiency by over 90%. Procurement personnel only need to select the product model and click a button, and the system automatically generates a purchase order containing a list of raw materials, quantities, and amounts, completely eliminating the tedious steps of manual querying, verification, and data entry.

[0093] This invention allows for one-click ordering. Through a standardized database and automated matching rules, it avoids errors in matching models and raw materials that may occur due to manual operation, reducing the order error rate by more than 80%.

[0094] This invention enables seamless transmission of purchase order data from the source to the warehousing module through a one-click material warehouse, eliminating data deviations caused by repeated data entry and ensuring real-time consistency of data throughout the entire chain.

[0095] This invention constructs an end-to-end automated process covering procurement and warehousing, realizing full-chain digital integration from order generation to warehouse, and promoting the intelligent and unmanned advancement of enterprise supply chain management.

[0096] This invention significantly reduces the reliance on human experience in business processes by using preset rules and automatic system execution, enabling new employees to quickly get started with complex procurement tasks.

[0097] This invention saves approximately 4.5 man-hours per order in the procurement and order placement process, and reduces data entry time for warehouse personnel, resulting in an overall operating cost reduction of 30%-50%. It also reduces order processing delays caused by manual operations, accelerates the procurement cycle, and improves supply chain responsiveness.

[0098] The end-to-end digitalization of this invention has accumulated a large amount of procurement and inventory data, providing a precise data foundation for enterprises to optimize supplier management and inventory turnover analysis, and helping to achieve more scientific supply chain decisions.

[0099] The modular design of this invention supports seamless integration with existing enterprise ERP and warehouse management systems, can be quickly adapted to different business scenarios, and reserves ample room for future expansion in the digital upgrade of the supply chain.

[0100] In summary, this invention restructures the traditional procurement and warehousing process through technological innovation, achieving breakthroughs in efficiency, accuracy, and cost control, and providing a powerful supply chain automation solution for enterprise digital transformation.

[0101] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0102] It should be noted that the present invention can be implemented in software and / or a combination of software and hardware, for example, using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In one embodiment, the software program of the present invention can be executed by a processor to implement the steps or functions described above. Similarly, the software program of the present invention (including associated data structures) can be stored in a computer-readable recording medium, such as RAM memory, a magnetic or optical drive, a floppy disk, or similar devices. Furthermore, some steps or functions of the present invention can be implemented in hardware, for example, as circuitry that works with a processor to perform the various steps or functions.

[0103] Furthermore, a portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. The program instructions invoking the methods of the invention may be stored in a fixed or removable recording medium, and / or transmitted via a data stream in a broadcast or other signal-carrying medium, and / or stored in the working memory of a computer device operating according to the program instructions. Here, an embodiment of the invention includes an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein, when the computer program instructions are executed by the processor, the apparatus is triggered to operate the methods and / or technical solutions based on the foregoing embodiments of the invention.

[0104] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims. Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in the apparatus claims may also be implemented by a single unit or device in software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any particular order.

Claims

1. A method for automatically generating purchase orders and managing warehouses, characterized in that, include: Establish a database that maps product models to raw material details; Establish a supplier information database and a database of standard procurement delivery dates for suppliers' raw materials; The system retrieves the product model selected by the user and obtains the corresponding raw material details from the database that maps product models to raw material details. Based on the corresponding raw material details, supplier information database, standard procurement delivery time database, and intelligent supplier recommendation algorithm, the system generates order information containing suppliers and corresponding raw materials in the procurement system.

2. The method for automatically generating purchase orders and managing warehouses as described in claim 1, characterized in that, The product model includes: a unique product identifier, a product name, and product specifications. The raw material details include: raw material name, raw material model, raw material specifications, raw material material, standard usage of raw materials, and recommended raw material suppliers.

3. The method for automatically generating purchase orders and managing warehouses as described in claim 1, characterized in that, The supplier information database includes: supplier name, supplier qualifications, range of raw materials supplied by the supplier, historical delivery records, and supplier quality rating; The supplier's standard procurement delivery time database for raw materials includes: production cycle and transportation time.

4. The method for automatically generating purchase orders and managing warehouses as described in claim 1, characterized in that, The system retrieves the product model selected by the user and obtains the corresponding raw material details from a database that maps product models to raw material details. Based on the corresponding raw material details, supplier information database, standard procurement delivery time database, and intelligent supplier recommendation algorithm, the system generates order information in the procurement system, including supplier and corresponding raw material details. After obtaining the product model selected by the user, the system automatically parses the product model, calls the database to match the raw material details, and automatically generates a purchase list based on the theoretical purchase quantity of the raw materials. Finally, the system uses the raw material details, supplier information database, standard purchase delivery time database, and supplier intelligent recommendation algorithm and different material order templates to split the purchase list into suppliers to generate order information.

5. The method for automatically generating purchase orders and managing warehouses as described in claim 1, characterized in that, The intelligent supplier recommendation algorithm recommends the optimal supplier group based on factors such as raw material demand, supplier inventory, historical order data, and delivery speed.

6. The method for automatically generating purchase orders and managing warehouses as described in claim 1, characterized in that, After generating order information containing suppliers and corresponding raw materials in the procurement system, it also includes: The system automatically verifies the completeness and format compliance of order information. If the verification fails, it will display an error message and block the order from being placed, while also logging the information for future investigation.

7. The method for automatically generating purchase orders and managing warehouses as described in claim 1, characterized in that, After generating order information containing suppliers and corresponding raw materials in the procurement system, it also includes: Push order information from the procurement system to the warehouse management system; After receiving purchase order information, the warehouse management system automatically creates warehouse tasks and generates electronic warehouse orders containing raw material information, suppliers, and target storage locations. By scanning the labels of raw materials, the raw materials are put on the shelves according to the target storage location corresponding to the scanned label information, and the warehouse management system automatically updates the inventory ledger.

8. The method for automatically generating purchase orders and managing warehouses as described in claim 7, characterized in that, After generating the electronic warehouse order, which includes raw material information, supplier, and target storage location, it also includes: By scanning the labels of raw materials, the scanned label information is automatically compared with the electronic warehouse order. If the actual quantity of raw materials received does not match the electronic warehouse order, the discrepancy is marked in the warehouse management system and automatically fed back to the purchasing system, triggering the order information correction process in the purchasing system.

9. The method for automatically generating purchase orders and managing warehouses as described in claim 7, characterized in that, After pushing order information from the procurement system to the warehouse management system, the process also includes: Each order is assigned a unique tracking number, and a complete operation log is recorded from the purchase order to the warehouse, including the order time, approver, transportation status, and warehouse time.

10. The method for automatically generating purchase orders and managing warehouses as described in claim 7, characterized in that, After pushing order information from the procurement system to the warehouse management system, the process also includes: When the inventory level of raw materials in the warehouse management system exceeds the safety threshold, duplicate purchase orders are automatically blocked; when the inventory level of raw materials in the warehouse management system is less than the inventory warning level, an automatic purchase order is generated.

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