Cross-factory production scheduling method, device and computer equipment for semiconductor manufacturing

Abstract

The application relates to a cross-factory production scheduling method, device and computer equipment for semiconductor manufacturing. The method comprises the following steps: acquiring factory production information of each factory and customer order information of a customer, and constructing a factory collaborative task model of each factory; identifying production task information of the customer, and verifying and disassembling the production task information of the customer through the factory collaborative task model to obtain a factory manufacturing work order; then, a collaborative review scheduling strategy is used to generate a collaborative scheduling work order of each factory, and current task execution information of each collaborative scheduling work order of each factory is acquired; based on the current task execution information of each factory, a cross-factory collaborative scheduling strategy is used to update the collaborative scheduling work order of each factory, a new collaborative scheduling work order of each factory is obtained, and the current task execution information of each collaborative scheduling work order of each factory is acquired until the factory manufacturing work order is completed. The method can effectively improve the cross-factory scheduling optimization effect.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence network technology, and in particular to a method, apparatus and computer equipment for cross-plant production scheduling in semiconductor manufacturing. Background Technology

[0002] In the context of globalization and precision manufacturing in the semiconductor industry, the entire process from wafer fabrication to chip packaging and testing often requires collaboration across multiple factories located in different regions, encompassing highly specialized stages such as wafer fabrication, chip design, and packaging and testing. However, production planning data and business process logic, as core corporate secrets, are typically strictly restricted to internal circulation and cannot be achieved through external third-party platforms for cross-factory collaboration. This makes cross-factory production planning collaboration difficult and the construction of a full-process traceability system challenging. Therefore, improving the efficiency of cross-factory collaboration and building a full-process traceability system are current research priorities.

[0003] Existing technologies often use traceability management systems to adapt corresponding plant scheduling schemes to a company's own production processes and business needs. However, this approach often focuses solely on plant scheduling and lacks the ability to coordinate scheduling across plants. Systems capable of coordinating scheduling across plants often require precise traceability of each process and each wafer in a single plant's semiconductor production process, resulting in poor optimization of cross-plant scheduling. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for cross-plant production scheduling in semiconductor manufacturing, addressing the aforementioned technical problems.

[0005] In a first aspect, this application provides a cross-plant production scheduling method for semiconductor manufacturing, including:

[0006] Obtain production information from each factory area and customer order information from each customer, and construct a collaborative task model for each factory area based on the production information from each factory area.

[0007] Based on the customer's order information, the customer's production task information is identified, and the production task information is verified and decomposed through the factory collaborative task model to obtain the factory manufacturing work order.

[0008] Based on the manufacturing work orders in the factory area, collaborative scheduling work orders for each factory area are generated through a collaborative review and scheduling strategy, and the current task execution information of each factory area for each collaborative scheduling work order is obtained.

[0009] Based on the current task execution information of each plant area, the collaborative scheduling work orders of each plant area are updated through the cross-plant collaborative scheduling strategy to obtain the new collaborative scheduling work orders of each plant area, and the current task execution information of each plant area for each collaborative scheduling work order is obtained until the plant area manufacturing work order is completed.

[0010] Optionally, the step of constructing a collaborative task model for each of the aforementioned factory areas based on their production information includes:

[0011] For each factory area, the factory area production information is broken down into the factory area's basic information, the factory area's task strategy information, the factory area's production process information, and the factory area's material consumption information.

[0012] Based on the basic information of the factory area, the task strategy information of the factory area, the production process information of the factory area, and the material consumption information of the factory area, a factory area model, a strategy model, a production process model, and a material consumption model are constructed respectively.

[0013] The factory area model, the factory area strategy model, the factory area production process model, and the factory area material consumption model are used as the factory area collaborative task model.

[0014] Optionally, identifying the customer's production task information based on the customer's customer order information includes:

[0015] Based on the customer's customer order information, identify the customer's order demand information;

[0016] Based on the customer's order demand information, in the factory area collaborative task model of each factory area, the production process model of each target factory area and the material consumption model of each target factory area are matched, and based on the production process model of each target factory area and the material consumption model of each target factory area, the production execution task corresponding to the order demand information is generated.

[0017] The production execution task is used as the customer's production task information.

[0018] Optionally, the step of verifying and decomposing the customer's production task information through the factory collaborative task model to obtain the factory manufacturing work order includes:

[0019] Identify the process logic of the production execution task, and according to the process logic, break down the production execution task into sub-tasks through the production process model of each of the factories;

[0020] Identify the task information for each subtask, and based on the task information for each subtask, verify the missing information of the current production conditions through the factory area model of each factory area;

[0021] If the missing information of the current production conditions exists, the missing information of the current production conditions is fed back to the user client. After the user updates the production conditions information, the task information based on each subtask is returned. The steps of checking the missing information of the current production conditions are checked through the system verification strategy until the missing information of the current production conditions does not exist.

[0022] Based on the task information of each subtask, a manufacturing work order for each subtask is constructed, and all manufacturing work orders of the subtasks are used as the factory area manufacturing work order.

[0023] Optionally, the step of generating collaborative scheduling work orders for each of the factory areas based on factory manufacturing work orders and through a collaborative review and scheduling strategy includes:

[0024] The manufacturing work orders of each subtask are reviewed and verified to obtain the work order exception information of each manufacturing work order. Based on the work order exception information of each manufacturing work order, the work order is adjusted to obtain the target manufacturing work order of each subtask.

[0025] Based on the target manufacturing work orders of each subtask, in each target factory area, the execution factory area corresponding to each subtask is adapted, and based on the target manufacturing work orders of each subtask, through the dispatching process of the execution factory area corresponding to each subtask, a scheduling work order for each execution factory area and a collaborative requirement work order for each execution factory area are generated.

[0026] Based on the collaborative work orders of each execution plant, identify the collaborative plants required by each execution plant, and generate collaborative work orders for each collaborative plant required by each execution plant based on the collaborative work orders of each execution plant.

[0027] The scheduling work orders for each execution plant area and the collaborative work orders for each cooperating plant area required by each execution plant area are taken as the collaborative scheduling work orders for each plant area.

[0028] Optionally, the step of updating the collaborative scheduling work orders of each of the plant areas based on the current task execution information of each plant area, and obtaining new collaborative scheduling work orders for each plant area through a cross-plant collaborative scheduling strategy, includes:

[0029] Based on the current task execution information of each plant area, the current task execution effect of each plant area is identified through the progress inspection strategy, and the target manufacturing work order of each sub-task is updated based on the current task execution effect of each plant area to obtain the new target manufacturing work order of each sub-task.

[0030] Replace the target manufacturing work order of each subtask with the new target manufacturing work order of each subtask, and return to execute the target manufacturing work order based on each subtask. In each target factory area, adapt the execution factory area steps corresponding to each subtask to obtain the new collaborative scheduling work order of each factory area.

[0031] Secondly, this application also provides a cross-plant production scheduling device for semiconductor manufacturing, comprising:

[0032] The acquisition module is used to acquire the production information of each factory area and the customer order information of the customers, and to construct the factory area collaborative task model based on the production information of each factory area.

[0033] The disassembly module is used to identify the customer's production task information based on the customer's customer order information, and to perform verification and disassembly processing on the customer's production task information through the factory collaborative task model to obtain the factory manufacturing work order;

[0034] The generation module is used to generate collaborative scheduling work orders for each of the factory areas based on the factory area manufacturing work orders and through collaborative review and scheduling strategies, and to obtain the current task execution information of each factory area for each of the collaborative scheduling work orders.

[0035] The execution module is used to update the collaborative scheduling work orders of each of the plant areas based on the current task execution information of each plant area, through a cross-plant collaborative scheduling strategy, to obtain the new collaborative scheduling work orders of each plant area, and to execute the acquisition of the current task execution information of each plant area for each collaborative scheduling work order until the plant area manufacturing work order is completed.

[0036] Optionally, the acquisition module is specifically used for:

[0037] For each factory area, the factory area production information is broken down into the factory area's basic information, the factory area's task strategy information, the factory area's production process information, and the factory area's material consumption information.

[0038] Based on the basic information of the factory area, the task strategy information of the factory area, the production process information of the factory area, and the material consumption information of the factory area, a factory area model, a strategy model, a production process model, and a material consumption model are constructed respectively.

[0039] The factory area model, the factory area strategy model, the factory area production process model, and the factory area material consumption model are used as the factory area collaborative task model.

[0040] Optionally, the disassembly module is specifically used for:

[0041] Based on the customer's customer order information, identify the customer's order demand information;

[0042] Based on the customer's order demand information, in the factory area collaborative task model of each factory area, the production process model of each target factory area and the material consumption model of each target factory area are matched, and based on the production process model of each target factory area and the material consumption model of each target factory area, the production execution task corresponding to the order demand information is generated.

[0043] The production execution task is used as the customer's production task information.

[0044] Optionally, the disassembly module is specifically used for:

[0045] Identify the process logic of the production execution task, and according to the process logic, break down the production execution task into sub-tasks through the production process model of each of the factories;

[0046] Identify the task information for each subtask, and based on the task information for each subtask, verify the missing information of the current production conditions through the factory area model of each factory area;

[0047] If the missing information of the current production conditions exists, the missing information of the current production conditions is fed back to the user client. After the user updates the production conditions information, the task information based on each subtask is returned. The steps of checking the missing information of the current production conditions are checked through the system verification strategy until the missing information of the current production conditions does not exist.

[0048] Based on the task information of each subtask, a manufacturing work order for each subtask is constructed, and all manufacturing work orders of the subtasks are used as the factory area manufacturing work order.

[0049] Optionally, the generation module is specifically used for:

[0050] The manufacturing work orders of each subtask are reviewed and verified to obtain the work order exception information of each manufacturing work order. Based on the work order exception information of each manufacturing work order, the work order is adjusted to obtain the target manufacturing work order of each subtask.

[0051] Based on the target manufacturing work orders of each subtask, in each target factory area, the execution factory area corresponding to each subtask is adapted, and based on the target manufacturing work orders of each subtask, through the dispatching process of the execution factory area corresponding to each subtask, a scheduling work order for each execution factory area and a collaborative requirement work order for each execution factory area are generated.

[0052] Based on the collaborative work orders of each execution plant, identify the collaborative plants required by each execution plant, and generate collaborative work orders for each collaborative plant required by each execution plant based on the collaborative work orders of each execution plant.

[0053] The scheduling work orders for each execution plant area and the collaborative work orders for each cooperating plant area required by each execution plant area are taken as the collaborative scheduling work orders for each plant area.

[0054] Optionally, the execution module is specifically used for:

[0055] Based on the current task execution information of each plant area, the current task execution effect of each plant area is identified through the progress inspection strategy, and the target manufacturing work order of each sub-task is updated based on the current task execution effect of each plant area to obtain the new target manufacturing work order of each sub-task.

[0056] Replace the target manufacturing work order of each subtask with the new target manufacturing work order of each subtask, and return to execute the target manufacturing work order based on each subtask. In each target factory area, adapt the execution factory area steps corresponding to each subtask to obtain the new collaborative scheduling work order of each factory area.

[0057] Thirdly, this application provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described in any one of the first aspects.

[0058] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0059] Fifthly, this application provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0060] The aforementioned cross-plant production scheduling method, apparatus, and computer equipment for semiconductor manufacturing acquires plant production information and customer order information from each plant, and constructs a plant collaborative task model for each plant based on the plant production information. Based on the customer order information, it identifies the customer's production task information and verifies and decomposes the customer's production task information using the plant collaborative task model to obtain plant manufacturing work orders. Based on the plant manufacturing work orders, it generates collaborative scheduling work orders for each plant through a collaborative review and scheduling strategy, and acquires the current task execution information of each plant for each collaborative scheduling work order. Based on the current task execution information of each plant, it updates the collaborative scheduling work orders of each plant through a cross-plant collaborative scheduling strategy to obtain new collaborative scheduling work orders for each plant, and continues to acquire the current task execution information of each plant for each collaborative scheduling work order until the plant manufacturing work order is completed. This solution constructs a collaborative task model for each factory area to verify and break down customer production task information, generating factory manufacturing work orders. This achieves accurate and intelligent breakdown of customer order information, avoiding the inefficiency and errors of manual work order dispatch. Furthermore, the solution can acquire and verify the current task execution information of each factory area in real time and update the collaborative scheduling work orders in real time. This dynamically optimizes the completion status of customer orders in each factory area, effectively improving the accuracy and dynamic optimization effect of multi-factory collaborative scheduling. Finally, this solution enables the acquisition of dynamic information throughout the entire task execution process of each factory area (i.e., real-time acquisition of the current task execution information of each factory area), ensuring accurate traceability of work order scheduling and task execution throughout the entire process. In summary, by constructing a factory area collaborative task model, optimizing the real-time accurate dispatch of collaborative scheduling work orders in each factory area, dynamically adjusting and optimizing them, and collecting real-time data on the implementation of tasks in each factory area, this solution effectively improves the optimization effect of cross-factory scheduling. Attached Figure Description

[0061] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 This is a flowchart illustrating a cross-plant production scheduling method for semiconductor manufacturing in one embodiment;

[0063] Figure 2 This is a flowchart illustrating an example of cross-plant production scheduling for semiconductor manufacturing in one embodiment;

[0064] Figure 3 This is a structural block diagram of a cross-plant production scheduling device for semiconductor manufacturing in one embodiment;

[0065] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0067] The cross-plant production scheduling method for semiconductor manufacturing provided in this application embodiment can be applied to cross-plant production scheduling systems for semiconductor manufacturing. This system can be applied to terminals, including but not limited to various personal computers, laptops, mid-range computers, etc. Specifically, the terminal constructs a collaborative task model for each plant area to verify and break down customer production task information, generating plant manufacturing work orders. This achieves the technical effect of accurately and intelligently breaking down customer order information, avoiding the inefficiency and errors of manual work order dispatch. Furthermore, this solution can acquire and verify the current task execution information of each plant area in real time and update the collaborative scheduling work orders of each plant area in real time, thereby dynamically optimizing the completion status of customer order information in each plant area and effectively improving the accuracy and dynamic scheduling optimization effect of multi-plant collaborative scheduling. Finally, this solution can achieve full-process dynamic information acquisition of each plant area during task execution (i.e., real-time acquisition of the current task execution information of each plant area), thereby ensuring that the work order scheduling and task execution of each plant area can be accurately traced throughout the entire process. In summary, by constructing a collaborative task model for the factory area, optimizing the real-time and accurate dispatch of collaborative scheduling work orders in each factory area, and dynamically optimizing and adjusting the model, it is also possible to collect the execution status of tasks in each factory area in real time, thereby effectively improving the optimization effect of cross-factory area scheduling.

[0068] In one exemplary embodiment, such as Figure 1 As shown, a cross-plant production scheduling method for semiconductor manufacturing is provided. Taking the application of this method to a terminal as an example, the method includes the following steps S101 to S104. Wherein:

[0069] Step S101: Obtain the production information of each factory area and the customer order information of the customers, and construct the factory area collaborative task model based on the production information of each factory area.

[0070] In this embodiment, the terminal responds to the information input operation of the staff and obtains the production information of each factory area. This production information includes, but is not limited to, basic factory information, such as the factory production structure and production line information; production strategy information, such as production rules, resource constraints, and priority settings; production process information, such as the production process flow for all product categories, breaking down the input / output standards, operating procedures, time parameters, and quality inspection nodes for each process; and material consumption list information, such as linking product processes with material requirements, clarifying the specifications, usage, and alternative materials required for each process. Then, the terminal obtains customer order information input by the staff. This customer order information includes the product model, quantity, delivery date, and quality requirements requested by the customer. Finally, based on the factory production information of each factory area, the terminal constructs a factory collaborative task model for each factory area. This collaborative task model includes, but is not limited to, a factory model, a strategy model, a production process model, and a material consumption model. The factory area model serves as the foundation for constructing information such as the production lines and architecture of the factory, providing basic data for subsequent production planning. The strategy model, based on production rules, resource constraints, and priority settings, builds strategies for task allocation, work order scheduling, and exception handling, defining the logical basis for the system's automatic decision-making. The production process model streamlines the production process flow for all product categories, breaking down the input / output standards, operating procedures, time parameters, and quality inspection nodes for each process to form a standardized process template. The material consumption model, by linking product processes with material requirements, constructs a precise material consumption list, clarifying the specifications, quantities, and substitute materials required for each process, achieving precise matching between material requirements and production processes. The specific construction process will be explained in detail later.

[0071] Step S102: Based on the customer's customer order information, identify the customer's production task information, and through the factory collaborative task model, verify and decompose the customer's production task information to obtain the factory manufacturing work order.

[0072] In this embodiment, the terminal identifies the customer's production task information based on the customer's order information, and performs verification and decomposition processing on the customer's production task information through a factory collaborative task model to obtain a factory manufacturing work order. This production task information is the overall target, delivery node, and resource requirements applicable to factory production, obtained after refining and filtering the customer order information. The verification and decomposition method involves first breaking down the production task information into sub-tasks corresponding to different processes, and then verifying the production conditions of each sub-task separately. This process is the production process. The specific verification and decomposition process will be explained in detail later.

[0073] Step S103: Based on the manufacturing work orders in the factory area, generate collaborative scheduling work orders for each factory area through collaborative review and scheduling strategies, and obtain the current task execution information of each factory area for each collaborative scheduling work order.

[0074] In this embodiment, the terminal generates collaborative scheduling work orders for each factory area based on the factory area manufacturing work orders, and obtains the current task execution information of each factory area for each collaborative scheduling work order. The collaborative review and scheduling strategy verifies the manufacturing work order for each sub-task, focusing on the accuracy of key information such as the bill of materials, process requirements, and delivery nodes to avoid production losses due to work order errors. After approval, the terminal identifies the applicable factory area for each sub-task and generates a scheduling work order for each factory area, as well as collaborative work orders for the required collaborating factories, through the dispatching process of that factory area. The specific generation process will be explained in detail later. The current task execution information for each factory area for each collaborative scheduling work order is the real-time record of the execution status of each factory area's collaborative scheduling work orders, which includes, but is not limited to, information such as production progress, quality inspection results, and material consumption.

[0075] Step S104: Based on the current task execution information of each factory area, update the collaborative scheduling work orders of each factory area through the cross-factory area collaborative scheduling strategy to obtain the new collaborative scheduling work orders of each factory area, and execute to obtain the current task execution information of each factory area for each collaborative scheduling work order until the factory area manufacturing work order is completed.

[0076] In this embodiment, the terminal updates the collaborative scheduling work orders of each factory area based on the current task execution information of each factory area through a cross-factory collaborative scheduling strategy, obtains new collaborative scheduling work orders for each factory area, and executes the process of obtaining the current task execution information of each factory area for each collaborative scheduling work order until the factory area manufacturing work order is completed. The cross-factory collaborative scheduling strategy first checks the progress of the current task execution information of each factory area, verifying whether the production completion status, product quality status, material consumption status, and production record completeness of each factory area for the collaborative scheduling work order meet preset standards. If the preset standards are not met, the manufacturing work orders of each sub-task are readjusted according to the check results, and steps S103 to S104 are iteratively executed until all preset standards are met, at which point the terminal determines that the factory area manufacturing work order is completed. In another embodiment, the terminal summarizes the current task execution information of each factory area collected each time, the new collaborative scheduling work order after each update, and the record information of each factory area's production completion status, product quality status, material consumption status, and production record integrity status of the collaborative scheduling work order into the order report template to obtain the customer's customer order production report.

[0077] Based on the above solution, by constructing a collaborative task model for each factory area, the customer's production task information is verified and broken down to generate factory manufacturing work orders. This achieves the technical effect of accurately and intelligently breaking down customer order information, avoiding the inefficiency and errors of manual work order dispatch. Furthermore, this solution can acquire and verify the current task execution information of each factory area in real time and update the collaborative scheduling work orders of each factory area in real time. This allows for dynamic optimization of the completion status of customer order information in each factory area, effectively improving the accuracy of multi-factory collaborative scheduling and the dynamic scheduling optimization effect. Finally, this solution can achieve full-process dynamic information acquisition for each factory area during task execution (i.e., real-time acquisition of the current task execution information of each factory area), ensuring that work order scheduling and task execution in each factory area can be accurately traced throughout the entire process. In summary, by constructing a factory area collaborative task model, optimizing the real-time accurate dispatch of collaborative scheduling work orders in each factory area, dynamically optimizing and adjusting them, and collecting the implementation task execution status of each factory area in real time, the optimization effect of cross-factory scheduling is effectively improved.

[0078] Optionally, based on the production information of each factory area, a collaborative task model for each factory area is constructed, including: for each factory area, the factory area production information is broken down into basic information, task strategy information, production process information, and material consumption information; based on the basic information, task strategy information, production process information, and material consumption information, a factory area model, a strategy model, a production process model, and a material consumption model are constructed respectively; the factory area model, strategy model, production process model, and material consumption model are used as the collaborative task model for each factory area.

[0079] In this embodiment, the terminal breaks down the production information of each factory area into basic information, task strategy information, production process information, and material consumption information. Then, based on these information, the terminal constructs a factory model, a strategy model, a production process model, and a material consumption model for each factory area. Specifically, the terminal adds a unified standardized interface and an adaptation engine for data interaction with each factory's Manufacturing Execution System (MES) based on the basic information. The MES, standardized interface, and adaptation engine of each factory area serve as the factory model for seamless integration and data collaboration between heterogeneous systems. This approach supports protocol integration with mainstream MES and ERP (Enterprise Resource Planning) systems, breaking down information silos and providing underlying technical support for unified management across factory areas. Based on production process information, the terminal constructs a semiconductor industry standard process suite, covering standardized process models for common production scenarios such as wafer manufacturing and packaging testing. This serves as a production process model, ensuring production compliance and efficiency. Simultaneously, this model supports hot-swapping of customized business suites, allowing for rapid response to personalized needs without interrupting existing production processes, balancing the dual requirements of "standardization and flexibility." The terminal builds a strategy adaptation engine based on object attributes and rule dimensions in task strategy information, serving as a strategy model. This allows for the rapid generation and adjustment of corresponding management strategies for different production entities, business scenarios, and control requirements. This model pre-sets hundreds of production scheduling rules, including constraints for rules such as prioritizing urgent orders, balancing equipment load, and optimizing material consumption, achieving precise and dynamic production management. Finally, the terminal generates a Bill of Materials (BOM) model by mapping the entire process nodes of different production processes within the plant to material consumption data, thereby achieving precise matching of material requirements with production stages. This model supports automatic expansion of multi-level BOMs, replacing intelligent material recommendations, avoiding material redundancy or shortages, and optimizing inventory management and material allocation efficiency.

[0080] Finally, the terminal uses the plant area model, the plant area strategy model, the plant area production process model, and the plant area material consumption model as the plant area collaborative task model.

[0081] Based on the above approach, this solution constructs different models for bill of materials, task strategies, production processes, and plant collaboration. These models are used to break down customer orders into plant tasks from different perspectives and then collaboratively schedule tasks across different plant areas. This effectively improves the accuracy of task coordination and scheduling across different plant areas, as well as the execution effect of tasks in each plant area after scheduling.

[0082] Optionally, based on the customer's customer order information, identify the customer's production task information, including: based on the customer's customer order information, identify the customer's order demand information; based on the customer's order demand information, match the production process model and material consumption model of each target factory in the factory collaborative task model of each factory, and generate production execution tasks corresponding to the order demand information based on the production process model and material consumption model of each target factory; and use the production execution tasks as the customer's production task information.

[0083] In this embodiment, the terminal identifies the customer's order requirements based on the customer's order information. The order requirements information includes key requirements such as product model, quantity, delivery date, and quality requirements in the customer's order information.

[0084] Then, based on the customer's order demand information, the terminal matches the production process model and material consumption model of each target factory in the factory collaborative task model of each factory area. Based on these models, it generates the production execution task corresponding to the order demand information. Specifically, the terminal first identifies target factories capable of fulfilling some of the content in the order demand information based on the factory models of each factory area. This identification method involves each factory area's factory model including basic factory information, which contains all or part of the processes for each product model that the factory can produce / process / handle. The terminal then designates the factory capable of producing the product models in the customer's order information as the target factory area. Next, based on the production process model of each target factory area, the terminal identifies the processing / production / handling procedures for each product model in the order demand information for each target factory area. Finally, based on the material consumption model of each target factory area, the terminal identifies the material consumption information corresponding to different steps / process nodes during the processing / production / handling of each product model. Finally, the terminal uses the processing / production / handling procedure information for each product model in the order demand information, the material consumption information corresponding to different steps / process nodes during processing / production / handling for each product model, and the delivery node for each product model as the production execution task corresponding to the order demand information. Finally, the terminal uses the production execution task as the customer's production task information.

[0085] Based on the above solution, by combining the plant area model, material consumption model, and production process model of each plant area, customer order information is divided into the processing / production / processing information of each product model required by the customer, the consumption information of each material corresponding to different steps / process nodes during processing / production / processing of each product model, and the delivery node of each product model. This improves the comprehensiveness of the analysis of customer demand information and the accuracy of the generation of production execution tasks.

[0086] Optionally, the production task information of customers is verified and decomposed through the factory area collaborative task model to obtain the factory area manufacturing work order. This includes: identifying the process logic of the production execution task, and according to the process logic, breaking down the production execution task into sub-tasks through the production process model of each factory area; identifying the task information of each sub-task, and based on the task information of each sub-task, checking for missing information of the current production conditions through the factory area model of each factory area; if the missing information of the current production conditions exists, feeding back the missing information of the current production conditions to the user client, and after the user updates the production condition information, returning to execute the steps based on the task information of each sub-task, and checking for missing information of the current production conditions through the system verification strategy until the missing information of the current production conditions no longer exists; constructing the manufacturing work order of each sub-task based on the task information of each sub-task, and using the manufacturing work orders of all sub-tasks as the factory area manufacturing work order.

[0087] In this embodiment, the terminal identifies the process logic of the production execution task and, according to the process logic, breaks down the production execution task into sub-tasks based on the production process models of each factory area. Specifically, the terminal breaks down the production execution task according to the processing / production / processing process information for each product model, thus dividing it into sub-tasks corresponding to different process information for different product models. Each sub-task corresponds to a factory area, and the process information corresponding to each sub-task is the process information of that factory area when producing / processing / processing the product signal.

[0088] Then, the terminal identifies the task information for each subtask and, based on this information, checks for missing information in the current production conditions using the plant area models of each plant. This task information includes the material information required by the task, the equipment information for the required plant area, the execution metadata for the task, and the corresponding process document information. The manufacturing execution system (MES) in each plant area's plant area model includes the current material reserves, equipment status (idle or not), personnel status (working or not), and the scope of process documents for each plant area. The terminal then identifies whether the materials, equipment, personnel, and process documents of the plant area corresponding to the subtask meet the requirements of the task information according to the plant area model. If not, the terminal treats the missing materials, equipment, personnel, or process documents as missing information in the current production conditions.

[0089] If information regarding missing production conditions exists, the terminal sends this information back to the user client. After the user updates the production condition information, the terminal returns to execute task information based on each subtask. The system's verification strategy checks the steps related to the missing production conditions until the missing information is resolved. Finally, based on the task information of each subtask, the terminal constructs a manufacturing work order for each subtask and combines all the subtask manufacturing work orders into a single factory manufacturing work order. Specifically, this manufacturing work order is created by the terminal using the process information of the factory corresponding to each subtask and the consumption information of each material for that subtask. The terminal generates core content for each factory, including subtask number, product information, process requirements, and a bill of materials. All the core content corresponding to each subtask is then combined into a factory manufacturing work order.

[0090] Based on the above scheme, by using the factory area model of each factory area, we can initially check whether each factory area meets the production / processing / handling requirements of the sub-tasks. If not, we can promptly provide feedback to the staff to ensure that each factory area meets the requirements for executing each sub-task. Finally, we can generate the core content corresponding to each sub-task, thereby improving the task preparation completion rate of the sub-tasks and the execution accuracy of each sub-task.

[0091] Optionally, based on the manufacturing work orders of each factory area, a collaborative scheduling work order for each factory area is generated through a collaborative review and scheduling strategy. This includes: reviewing and verifying the manufacturing work orders of each sub-task to obtain work order exception information for each manufacturing work order; adjusting each manufacturing work order based on the work order exception information to obtain the target manufacturing work order for each sub-task; adapting the execution factory area corresponding to each sub-task to each target factory area based on the target manufacturing work orders of each sub-task, and generating a scheduling work order for each execution factory area and a collaborative requirement work order for each execution factory area based on the dispatching process of the execution factory area corresponding to each sub-task; identifying the collaborative factory areas required by each execution factory area based on the collaborative requirement work orders of each execution factory area, and generating collaborative work orders for each collaborative factory area required by each execution factory area; and using the scheduling work order for each execution factory area and the collaborative work orders for each collaborative factory area required by each execution factory area as the collaborative scheduling work order for each factory area.

[0092] In this embodiment, the terminal reviews and verifies the manufacturing work orders for each sub-task, obtaining work order anomaly information for each work order. Based on this anomaly information, the terminal adjusts each manufacturing work order to obtain the target manufacturing work order for each sub-task. The review and verification process involves the terminal sending the manufacturing work order for each sub-task back to the responsible client and receiving the review results transmitted from the responsible client. These results include secondary verification confirmation information from the responsible client regarding key information such as the bill of materials, process requirements, and delivery milestones. The terminal then identifies any anomalies in the secondary verification confirmation information as work order anomaly information. These anomalies could include discrepancies between the bill of materials and the required material information for the sub-task, or the process documents not including the required process documents for the sub-task, or the delivery milestone differing from the required delivery milestone for the sub-task.

[0093] Based on the target manufacturing work orders for each sub-task, the terminal adapts the execution plant corresponding to each sub-task within each target plant area. Then, based on the target manufacturing work orders for each sub-task, and through the dispatching process of the corresponding execution plant area, it generates a scheduling work order and a collaboration requirement work order for each execution plant area. Based on the collaboration requirement work orders for each execution plant area, the terminal identifies the collaborative plants required by each execution plant area and generates collaboration work orders for each of the collaborative plants required by each execution plant area. Specifically, since each execution area may require other factories to transport / transfer the required semi-finished products or component materials to it before it can properly execute the target manufacturing work order for each sub-task, the terminal identifies the collaborative work orders provided by other cooperating factories when the factory needs to execute the target manufacturing work order, based on the factory model of each factory. These collaborative work orders can be semi-finished products produced / processed by the preceding sub-task, or component material information required by the execution area when executing the target manufacturing work order. Then, based on the collaborative work orders corresponding to each cooperating factory, the terminal generates a collaborative work order for each cooperating factory through the dispatching process of each cooperating factory. The terminal then generates a scheduling work order for each execution factory based on the target manufacturing work order and the dispatching process of that execution factory. The collaborative work order or scheduling work order includes information on the specific production team and personnel assigned to that factory to execute the sub-task.

[0094] Finally, the scheduling work orders of each execution plant area and the collaborative work orders of each cooperating plant area required by each execution plant area are taken as the collaborative scheduling work orders of each plant area.

[0095] Based on the above scheme, not only can the scheduling work order of the execution plant area for each sub-task be accurately generated, but also the collaborative work order of the cooperating plant area corresponding to the semi-finished products produced / processed / processed by the preceding sub-task required by each execution plant area, or the component material information required by the execution plant area when executing the target manufacturing work order, effectively improving the accuracy of cross-plant collaborative scheduling.

[0096] Optionally, based on the current task execution information of each plant area, the collaborative scheduling work orders of each plant area are updated through a cross-plant area collaborative scheduling strategy to obtain new collaborative scheduling work orders for each plant area. This includes: based on the current task execution information of each plant area, identifying the current task execution effect of each plant area through a progress verification strategy, and updating the target manufacturing work order of each sub-task based on the current task execution effect of each plant area to obtain a new target manufacturing work order for each sub-task; replacing the target manufacturing work order of each sub-task with the new target manufacturing work order of each sub-task, and returning to execute the target manufacturing work order based on each sub-task. In each target plant area, the execution plant area steps corresponding to each sub-task are adapted to obtain new collaborative scheduling work orders for each plant area.

[0097] In this embodiment, the terminal, based on the current task execution information of each factory area, identifies the current task execution effect of each factory area through a progress inspection strategy. Based on the current task execution effect of each factory area, it updates the target manufacturing work order for each sub-task, obtaining a new target manufacturing work order for each sub-task. The current task execution effect includes production progress, quality inspection results, and material consumption information. The progress inspection strategy includes production progress evaluation programs, quality inspection programs, and material consumption calculation programs preset by staff on the terminal for each product model. Then, the terminal uses the above programs to inspect the current task execution information collected each time, thereby generating the current task execution effect for each sub-task. Based on the quality inspection results, the terminal determines whether the produced / processed / handled product meets the quality requirements of the customer order information. If it does not meet the requirements, the production progress of the product is reset to zero, and the target manufacturing work order for that sub-task is not updated. If it meets the requirements, the terminal modifies the process information and material requirement information in the target manufacturing work order based on the production progress and material consumption information, so that the updated target manufacturing work order can complete the remaining production progress exactly when the materials are consumed.

[0098] Then, the terminal replaces the target manufacturing work order of each subtask with the new target manufacturing work order of each subtask, and returns the execution of the target manufacturing work order based on each subtask. In each target factory area, the execution factory area steps corresponding to each subtask are adapted to obtain the new collaborative scheduling work order of each factory area.

[0099] Based on the above scheme, the target manufacturing work order is dynamically updated according to the current task execution effect of each factory area collected in real time, thereby ensuring that each factory area can not only complete the sub-task according to the customer's customer order information, but also ensure real-time collaborative scheduling of each factory area.

[0100] This application also provides an example of cross-plant production scheduling for semiconductor manufacturing, such as... Figure 2 As shown, the specific processing procedure includes the following steps:

[0101] Step S201: Obtain production information for each factory area and customer order information for each customer.

[0102] Step S202: For each factory area, the factory area production information is broken down into basic information of the factory area, task strategy information of the factory area, production process information of the factory area, and material consumption information of the factory area.

[0103] Step S203: Based on the basic information of the plant area, the task strategy information of the plant area, the production process information of the plant area, and the material consumption information of the plant area, construct the plant area model, the strategy model, the production process model, and the material consumption model of the plant area respectively.

[0104] Step S204: The plant area model, the plant area strategy model, the plant area production process model, and the plant area material consumption model are used as the plant area collaborative task model.

[0105] Step S205: Identify customer order demand information based on customer order information.

[0106] Step S206: Based on the customer's order demand information, match the production process model and material consumption model of each target factory in the factory collaborative task model of each factory area, and generate the production execution task corresponding to the order demand information based on the production process model and material consumption model of each target factory area.

[0107] Step S207: The production execution task is used as the customer's production task information.

[0108] Step S208: Identify the process logic of the production execution task, and according to the process logic, break down the production execution task into sub-tasks through the production process model of each plant area.

[0109] Step S209: Identify the task information of each subtask, and based on the task information of each subtask, verify the missing information of the current production conditions through the factory area model of each factory area.

[0110] Step S210: If the current production condition missing information exists, the current production condition missing information is fed back to the user client. After the user updates the production condition information, the task information based on each subtask is returned. The current production condition missing information step is checked through the system verification strategy until the current production condition missing information no longer exists.

[0111] Step S211: Based on the task information of each subtask, construct the manufacturing work order for each subtask, and use the manufacturing work orders of all subtasks as the factory area manufacturing work order.

[0112] Step S212: Review and verify the manufacturing work orders of each subtask to obtain the work order exception information of each manufacturing work order. Based on the work order exception information of each manufacturing work order, adjust the work order of each manufacturing work order to obtain the target manufacturing work order of each subtask.

[0113] Step S213: Based on the target manufacturing work orders of each sub-task, adapt the execution plant corresponding to each sub-task in each target plant area, and generate the scheduling work order and the collaborative requirement work order of each execution plant area based on the target manufacturing work orders of each sub-task through the dispatching process of the execution plant area corresponding to each sub-task.

[0114] Step S214: Based on the collaborative work order of each execution plant area, identify the collaborative plants required by each execution plant area, and generate the collaborative work order of each collaborative plant area required by each execution plant area based on the collaborative work order of each execution plant area.

[0115] Step S215: The scheduling work orders of each execution plant area and the collaborative work orders of each cooperating plant area required by each execution plant area are taken as the collaborative scheduling work orders of each plant area.

[0116] Step S216: Based on the current task execution information of each factory area, the current task execution effect of each factory area is identified through the progress inspection strategy, and the target manufacturing work order of each sub-task is updated based on the current task execution effect of each factory area to obtain the new target manufacturing work order of each sub-task.

[0117] Step S217: Replace the target manufacturing work order of each subtask with the new target manufacturing work order of each subtask, and return to execute the target manufacturing work order based on each subtask. In each target factory area, adapt the execution factory area steps corresponding to each subtask to obtain the new collaborative scheduling work order of each factory area.

[0118] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0119] Based on the same inventive concept, this application also provides a cross-plant production scheduling apparatus for semiconductor manufacturing, used to implement the cross-plant production scheduling method for semiconductor manufacturing described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations of one or more embodiments of the cross-plant production scheduling apparatus for semiconductor manufacturing provided below can be found in the limitations of the cross-plant production scheduling method for semiconductor manufacturing described above, and will not be repeated here.

[0120] In one exemplary embodiment, such as Figure 3 As shown, a cross-plant production scheduling device for semiconductor manufacturing is provided, comprising: an acquisition module 310, a disassembly module 320, a generation module 330, and an execution module 340, wherein:

[0121] The acquisition module 310 is used to acquire the production information of each factory area and the customer order information of the customers, and to construct a factory area collaborative task model for each factory area based on the production information of each factory area.

[0122] The disassembly module 320 is used to identify the customer's production task information based on the customer's customer order information, and to perform verification and disassembly processing on the customer's production task information through the factory collaborative task model to obtain the factory manufacturing work order.

[0123] The generation module 330 is used to generate collaborative scheduling work orders for each of the factory areas based on the factory area manufacturing work orders and through a collaborative review and scheduling strategy, and to obtain the current task execution information of each factory area for each of the collaborative scheduling work orders.

[0124] The execution module 340 is used to update the collaborative scheduling work orders of each of the plant areas based on the current task execution information of each plant area, through a cross-plant collaborative scheduling strategy, to obtain the new collaborative scheduling work orders of each plant area, and to obtain the current task execution information of each plant area for each collaborative scheduling work order until the plant area manufacturing work order is completed.

[0125] Optionally, the acquisition module 310 is specifically used for:

[0126] For each factory area, the factory area production information is broken down into the factory area's basic information, the factory area's task strategy information, the factory area's production process information, and the factory area's material consumption information.

[0127] Based on the basic information of the factory area, the task strategy information of the factory area, the production process information of the factory area, and the material consumption information of the factory area, a factory area model, a strategy model, a production process model, and a material consumption model are constructed respectively.

[0128] The factory area model, the factory area strategy model, the factory area production process model, and the factory area material consumption model are used as the factory area collaborative task model.

[0129] Optionally, the disassembly module 320 is specifically used for:

[0130] Based on the customer's customer order information, identify the customer's order demand information;

[0131] Based on the customer's order demand information, in the factory area collaborative task model of each factory area, the production process model of each target factory area and the material consumption model of each target factory area are matched, and based on the production process model of each target factory area and the material consumption model of each target factory area, the production execution task corresponding to the order demand information is generated.

[0132] The production execution task is used as the customer's production task information.

[0133] Optionally, the disassembly module 320 is specifically used for:

[0134] Identify the process logic of the production execution task, and according to the process logic, break down the production execution task into sub-tasks through the production process model of each of the factories;

[0135] Identify the task information for each subtask, and based on the task information for each subtask, verify the missing information of the current production conditions through the factory area model of each factory area;

[0136] If the missing information of the current production conditions exists, the missing information of the current production conditions is fed back to the user client. After the user updates the production conditions information, the task information based on each subtask is returned. The steps of checking the missing information of the current production conditions are checked through the system verification strategy until the missing information of the current production conditions does not exist.

[0137] Based on the task information of each subtask, a manufacturing work order for each subtask is constructed, and all manufacturing work orders of the subtasks are used as the factory area manufacturing work order.

[0138] Optionally, the generation module 330 is specifically used for:

[0139] The manufacturing work orders of each subtask are reviewed and verified to obtain the work order exception information of each manufacturing work order. Based on the work order exception information of each manufacturing work order, the work order is adjusted to obtain the target manufacturing work order of each subtask.

[0140] Based on the target manufacturing work orders of each subtask, in each target factory area, the execution factory area corresponding to each subtask is adapted, and based on the target manufacturing work orders of each subtask, through the dispatching process of the execution factory area corresponding to each subtask, a scheduling work order for each execution factory area and a collaborative requirement work order for each execution factory area are generated.

[0141] Based on the collaborative work orders of each execution plant, identify the collaborative plants required by each execution plant, and generate collaborative work orders for each collaborative plant required by each execution plant based on the collaborative work orders of each execution plant.

[0142] The scheduling work orders for each execution plant area and the collaborative work orders for each cooperating plant area required by each execution plant area are taken as the collaborative scheduling work orders for each plant area.

[0143] Optionally, the execution module 340 is specifically used for:

[0144] Based on the current task execution information of each plant area, the current task execution effect of each plant area is identified through the progress inspection strategy, and the target manufacturing work order of each sub-task is updated based on the current task execution effect of each plant area to obtain the new target manufacturing work order of each sub-task.

[0145] Replace the target manufacturing work order of each subtask with the new target manufacturing work order of each subtask, and return to execute the target manufacturing work order based on each subtask. In each target factory area, adapt the execution factory area steps corresponding to each subtask to obtain the new collaborative scheduling work order of each factory area.

[0146] The modules in the aforementioned cross-plant production scheduling device for semiconductor manufacturing can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0147] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a cross-plant production scheduling method for semiconductor manufacturing. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0148] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0149] In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program that, when executed by the processor, implements the steps of a cross-plant production scheduling method for semiconductor manufacturing.

[0150] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program being executed by a processor to implement steps of a cross-plant production scheduling method for semiconductor manufacturing.

[0151] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of a cross-plant production scheduling method for semiconductor manufacturing.

[0152] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0153] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0154] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0155] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A cross-plant production scheduling method for semiconductor manufacturing, characterized in that, The method includes: Obtain production information from each factory area and customer order information from each customer, and construct a collaborative task model for each factory area based on the production information from each factory area. Based on the customer's order information, the customer's production task information is identified, and the production task information is verified and decomposed through the factory collaborative task model to obtain the factory manufacturing work order. Based on the manufacturing work orders in the factory area, collaborative scheduling work orders for each factory area are generated through a collaborative review and scheduling strategy, and the current task execution information of each factory area for each collaborative scheduling work order is obtained. Based on the current task execution information of each plant area, the collaborative scheduling work orders of each plant area are updated through the cross-plant collaborative scheduling strategy to obtain the new collaborative scheduling work orders of each plant area, and the current task execution information of each plant area for each collaborative scheduling work order is obtained until the plant area manufacturing work order is completed.

2. The method according to claim 1, characterized in that, The construction of a collaborative task model for each of the aforementioned factory areas, based on the factory area production information, includes: For each factory area, the factory area production information is broken down into the factory area's basic information, the factory area's task strategy information, the factory area's production process information, and the factory area's material consumption information. Based on the basic information of the factory area, the task strategy information of the factory area, the production process information of the factory area, and the material consumption information of the factory area, a factory area model, a strategy model, a production process model, and a material consumption model are constructed respectively. The factory area model, the factory area strategy model, the factory area production process model, and the factory area material consumption model are used as the factory area collaborative task model.

3. The method according to claim 2, characterized in that, The step of identifying the customer's production task information based on the customer's customer order information includes: Based on the customer's customer order information, identify the customer's order demand information; Based on the customer's order demand information, in the factory area collaborative task model of each factory area, the production process model of each target factory area and the material consumption model of each target factory area are matched, and based on the production process model of each target factory area and the material consumption model of each target factory area, the production execution task corresponding to the order demand information is generated. The production execution task is used as the customer's production task information.

4. The method according to claim 3, characterized in that, The process of verifying and decomposing the customer's production task information through the factory collaborative task model to obtain the factory manufacturing work order includes: Identify the process logic of the production execution task, and according to the process logic, break down the production execution task into sub-tasks through the production process model of each of the factories; Identify the task information for each subtask, and based on the task information for each subtask, verify the missing information of the current production conditions through the factory area model of each factory area; If the missing information of the current production conditions exists, the missing information of the current production conditions is fed back to the user client. After the user updates the production conditions information, the task information based on each subtask is returned. The steps of checking the missing information of the current production conditions are checked through the system verification strategy until the missing information of the current production conditions does not exist. Based on the task information of each subtask, a manufacturing work order for each subtask is constructed, and all manufacturing work orders of the subtasks are used as the factory area manufacturing work order.

5. The method according to claim 4, characterized in that, The process of generating collaborative scheduling work orders for each factory area based on factory manufacturing work orders, through a collaborative review and scheduling strategy, includes: The manufacturing work orders of each subtask are reviewed and verified to obtain the work order exception information of each manufacturing work order. Based on the work order exception information of each manufacturing work order, the work order is adjusted to obtain the target manufacturing work order of each subtask. Based on the target manufacturing work orders of each subtask, in each target factory area, the execution factory area corresponding to each subtask is adapted, and based on the target manufacturing work orders of each subtask, through the dispatching process of the execution factory area corresponding to each subtask, a scheduling work order for each execution factory area and a collaborative requirement work order for each execution factory area are generated. Based on the collaborative work orders of each execution plant, identify the collaborative plants required by each execution plant, and generate collaborative work orders for each collaborative plant required by each execution plant based on the collaborative work orders of each execution plant. The scheduling work orders for each execution plant area and the collaborative work orders for each cooperating plant area required by each execution plant area are taken as the collaborative scheduling work orders for each plant area.

6. The method according to claim 5, characterized in that, The process of updating the collaborative scheduling work orders of each of the aforementioned factory areas based on the current task execution information and through a cross-factory area collaborative scheduling strategy to obtain new collaborative scheduling work orders for each of the aforementioned factory areas includes: Based on the current task execution information of each plant area, the current task execution effect of each plant area is identified through the progress inspection strategy, and the target manufacturing work order of each sub-task is updated based on the current task execution effect of each plant area to obtain the new target manufacturing work order of each sub-task. Replace the target manufacturing work order of each subtask with the new target manufacturing work order of each subtask, and return to execute the target manufacturing work order based on each subtask. In each target factory area, adapt the execution factory area steps corresponding to each subtask to obtain the new collaborative scheduling work order of each factory area.

7. A cross-plant production scheduling device for semiconductor manufacturing, characterized in that, The device includes: The acquisition module is used to acquire the production information of each factory area and the customer order information of the customers, and to construct the factory area collaborative task model based on the production information of each factory area. The disassembly module is used to identify the customer's production task information based on the customer's customer order information, and to perform verification and disassembly processing on the customer's production task information through the factory collaborative task model to obtain the factory manufacturing work order; The generation module is used to generate collaborative scheduling work orders for each of the factory areas based on the factory area manufacturing work orders and through collaborative review and scheduling strategies, and to obtain the current task execution information of each factory area for each of the collaborative scheduling work orders. The execution module is used to update the collaborative scheduling work orders of each of the plant areas based on the current task execution information of each plant area, through a cross-plant collaborative scheduling strategy, to obtain the new collaborative scheduling work orders of each plant area, and to execute the acquisition of the current task execution information of each plant area for each collaborative scheduling work order until the plant area manufacturing work order is completed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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