A method, system, medium, and product for online quality assurance in the final assembly process of complex products.

Abstract

This application provides a method, system, medium, and product for online quality assurance in the final assembly process of complex products, relating to the field of intelligent manufacturing technology. The method includes: associating collected final assembly process data with key inspection points in a received key inspection point table to generate a key inspection process association model; using the key inspection process association model to track the execution progress of the final assembly process of the complex product, and generating pending confirmation tasks for key inspection points based on the execution progress; assigning the pending confirmation tasks to a quality analysis and confirmation terminal, obtaining the quality confirmation results generated by the quality analysis and confirmation terminal after performing quality analysis on the pending confirmation tasks using a preset intelligent quality inspection model in a preset online manner; and controlling the flow progress of the final assembly process of the complex product based on the quality confirmation results. This solves the technical problem of poor quality control responsiveness in the final assembly process of complex products in related technologies, achieving the effect of improving the quality control responsiveness of the final assembly process of complex products.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent production, and in particular to a complex product assembly process quality online guarantee method and system, medium and product. BACKGROUND

[0002] With the rapid development of complex product manufacturing industry, the quality guarantee requirement in the assembly process is getting higher and higher. Especially in the fields of aerospace, high-end equipment, etc., higher requirements of real-time, accuracy and intelligence are put forward for the quality control of complex product assembly process.

[0003] In the related art, the production data acquisition and statistical analysis method is usually used for quality management. The specific implementation process is as follows: first, determine the key quality control items according to the product process requirements; then, periodically collect the production data of each process in the production process, including process parameters, processing records and other information; then, statistical calculation is performed on the collected data to generate quality trend charts; finally, based on the statistical analysis results, the quality management personnel assesses the quality status and formulates corresponding management measures. At present, many manufacturing enterprises have begun to introduce manufacturing execution system (Manufacturing Execution System, MES) to manage the production process. However, the existing MES system mainly faces the production execution management of the factory, lacks the real-time data interaction capability with external units such as design units and quality guarantee departments, and still relies on manual on-site tracking, paper records and telephone communication by designers and quality guarantee personnel. This way not only is inefficient, but also is difficult to grasp the production progress, quality information and material matching situation in real time.

[0004] However, by using the above method, since the quality management relies on periodic statistical analysis, and there is a time difference between the analysis results and the actual production state, it may lead to the inability to discover and handle quality abnormalities in time, so as to be difficult to meet the real-time requirement of the complex product assembly process for quality guarantee, and further lead to poor response of the quality control of the complex product assembly process in the related art. SUMMARY

[0005] The present application provides a complex product assembly process quality online guarantee method, system, medium and product, which is used for improving the quality control responsiveness of the complex product assembly process.

[0006] In a first aspect, the application provides a method for online quality assurance of a complex product assembly process, applied to the assembly process online quality assurance system. The method comprises: collecting assembly production process data of the complex product, and in the case of receiving a design file including a critical point table output by the design end, associating the assembly production process data with the critical inspection points in the critical point table to generate a critical process association model; tracking the assembly process execution progress of the complex product using the critical process association model, and generating pending confirmation tasks of the critical inspection points according to the assembly process execution progress; assigning the pending confirmation tasks to the quality analysis confirmation end to obtain quality confirmation results generated by the quality analysis confirmation end after quality analysis of the pending confirmation tasks using a preset intelligent quality inspection model in a preset online manner; and controlling the assembly process flow progress of the complex product according to the quality confirmation results.

[0007] By adopting the above technical solution, the assembly production process data of the complex product and the critical inspection points in the critical point table are associated with each other to form a critical process association model, which can establish an accurate mapping relationship between production data and quality control nodes. The critical process association model interacts with the assembly process execution progress to realize real-time tracking of the complex product assembly process, and automatically generates pending confirmation tasks of the critical inspection points when a specific execution progress is reached. The pending confirmation tasks form a cooperative mechanism with the quality analysis confirmation end, and the quality analysis confirmation end performs quality analysis of the pending confirmation tasks using a preset intelligent quality inspection model in a preset online manner to generate quality confirmation results. The quality confirmation results and the assembly process flow progress of the complex product form a closed-loop control, thereby realizing process flow control based on real-time quality analysis. Thus, the technical problem of poor quality control responsiveness of the complex product assembly process in related technologies is solved, and the technical effect of improving the quality control responsiveness of the complex product assembly process is achieved.

[0008] Optionally, the total assembly production process data of the complex product is collected, and in the case that the design file including the critical point table is received from the design end, the total assembly production process data is associated with the critical inspection points in the critical point table to generate a critical process association model, specifically including: collecting the total assembly production process data in the target MES system by using the ETL integrated interface in a preset data collection period; in the case that the critical point table is received, sending the critical point table to the process end; obtaining the process file prepared by the process end according to the critical point table, the process file including the association relationship between the process steps and the critical inspection points; sending the obtained process file to the total assembly end to obtain the manufacturing data association record generated by the total assembly end in the process of associating the process steps with the corresponding manufacturing data according to the process file; analyzing the critical inspection points in the manufacturing data association record to determine the key inspection points and the mandatory inspection points, the key inspection points being the process nodes that need to be quality confirmed in the total assembly process of the complex product and do not affect the total assembly process flow progress of the complex product, and the mandatory inspection points being the process nodes that need to be quality confirmed in the total assembly process of the complex product and affect the total assembly process flow progress; and associating the key inspection points and the mandatory inspection points according to the total assembly process flow sequence based on the total assembly production process data, the process file and the manufacturing data association record to generate the critical process association model.

[0009] By using the above technical solution, the ETL integrated interface and the target MES system interact with each other to continuously collect the total assembly production process data in a preset data collection period, ensuring the real-time and completeness of the data. The critical point table and the process end form a cooperative relationship, and the process end prepares the process file including the association relationship between the process steps and the critical inspection points according to the critical point table. The process file and the production process of the total assembly end are combined with each other, and the total assembly end associates the process steps with the corresponding manufacturing data to generate the manufacturing data association record. The critical inspection points in the manufacturing data association record are divided into the key inspection points and the mandatory inspection points after analysis, the former not affecting the total assembly process flow progress and the latter affecting the total assembly process flow progress. The total assembly production process data, the process file and the manufacturing data association record synergistically associate the key inspection points and the mandatory inspection points according to the total assembly process flow sequence to generate the critical process association model with complete logical structure.

[0010] Optionally, the key inspection points and the mandatory inspection points are associated according to the general assembly production process data, the process file and the manufacturing data association record in the order of the general assembly process flow, to generate a key-mandatory process association model, specifically including: classifying the general assembly production process data according to the action attribute, to determine process control data and quality confirmation data, the process control data including production plan data, production progress data and material matching information, the quality confirmation data including key quality confirmation data and mandatory quality confirmation data, the key quality confirmation data including routine quality inspection data and routine video interpretation record, the mandatory quality confirmation data including key quality inspection data and key video interpretation record; performing first association processing on the process control data and the routine quality inspection data and the routine video interpretation record and the key inspection points according to the manufacturing data association record, to obtain a first association result; performing second association processing on the key quality inspection data and the key video interpretation record and the mandatory inspection points according to the manufacturing data association record, to obtain a second association result; configuring the first association result in the key inspection points, and configuring the second association result in the mandatory inspection points; in a case where the key inspection points are configured with the first association result and the mandatory inspection points are configured with the second association result, sorting the key inspection points and the mandatory inspection points according to the general assembly process flow according to the process file, to generate a key-mandatory process association model.

[0011] By adopting the technical solution, the general assembly production process data is accurately divided into two categories of process control data and quality confirmation data after being classified according to the action attribute, wherein the process control data includes production plan data, production progress data and material matching information, and the quality confirmation data is further divided into key quality confirmation data and mandatory quality confirmation data. The manufacturing data association record acts as an association bridge, interacts with the process control data and the routine quality inspection data and the routine video interpretation record, establishes an association relationship with the key inspection points through first association processing, and obtains a first association result. Similarly, the manufacturing data association record interacts with the key quality inspection data and the key video interpretation record, establishes an association relationship with the mandatory inspection points through second association processing, and obtains a second association result. After the first association result is configured with the key inspection points and the second association result is configured with the mandatory inspection points, the process file guides the key inspection points and the mandatory inspection points to be sorted according to the general assembly process flow, and finally a key-mandatory process association model with complete data and clear structure is generated.

[0012] In a second aspect, an embodiment of the present application provides a total assembly process quality online guarantee system, the total assembly process quality online guarantee system comprising: one or more processors and a memory; the memory being coupled to the one or more processors, the memory being configured to store computer program codes, the computer program codes comprising computer instructions, the one or more processors invoking the computer instructions to cause the total assembly process quality online guarantee system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0013] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions which, when executed on a total assembly process quality online guarantee system, cause the total assembly process quality online guarantee system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0014] In a second aspect, an embodiment of the present application provides a total assembly process quality online guarantee system, the total assembly process quality online guarantee system comprising: one or more processors and a memory; the memory being coupled to the one or more processors, the memory being configured to store computer program codes, the computer program codes comprising computer instructions, the one or more processors invoking the computer instructions to cause the total assembly process quality online guarantee system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0015] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions which, when executed on a total assembly process quality online guarantee system, cause the total assembly process quality online guarantee system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0016] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium comprising instructions which, when executed on a total assembly process quality online guarantee system, cause the total assembly process quality online guarantee system to perform the method described in the first aspect and any possible implementation manner of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a flowchart of a total assembly process quality online guarantee method in an embodiment of the present application;

[0018] Figure 2 is a flowchart of a total assembly process quality online guarantee method in an embodiment of the present application;

[0019] Figure 3 is an architectural diagram of a total assembly process quality online guarantee system in an embodiment of the present application;

[0020] Figure 4is a structural schematic diagram of an ETL collection framework in an embodiment of the present application;

[0021] Figure 5 is a structural schematic diagram of a WebService integration framework in an embodiment of the present application;

[0022] Figure 6 is a structural schematic diagram of an entity device of an online quality assurance system for a complex product assembly process in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The terminology used in the following embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in the specification and the appended claims, the singular forms "a," "an" and "the" are intended to include both singular and plural forms, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or," as used in the specification and in the claims, is used to mean one or more of the listed items can be employed by itself or in some combination with one another.

[0024] Hereinafter, the terms "first", "second", "third", "fourth", "fifth", "sixth", "seventh" and "eighth" are used only for the purpose of description, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second", "third", "fourth", "fifth", "sixth", "seventh" and "eighth" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0025] The present application provides a complex product assembly process quality online assurance method, referring to Figure 1 , Figure 1 is a flow schematic diagram of a complex product assembly process quality online assurance method in an embodiment of the present application, comprising the following steps:

[0026] Step S101, collecting assembly production process data of a complex product, and in the case of receiving a design file output by a design end, including a critical point table, associating the assembly production process data with the critical inspection points in the critical point table to generate a critical process association model;

[0027] Step S102, tracking the assembly process execution progress of the complex product by using the critical process association model, and generating a to-be-confirmed task of the critical inspection point according to the assembly process execution progress;

[0028] Step S103, distributing the to-be-confirmed task to a quality analysis confirmation end to obtain a quality confirmation result generated by the quality analysis confirmation end after performing quality analysis on the to-be-confirmed task by using a preset intelligent quality inspection model in a preset online manner;

[0029] Step S104, controlling the assembly process flow progress of the complex product according to the quality confirmation result.

[0030] The complex product represents a manufacturing product involving the cooperation of multiple processes and multiple departments, such as high-end manufacturing products such as spacecraft, aircraft, and automobiles. The assembly production process data refers to various data information generated during the assembly process of the complex product, including production plan data, production progress data, material matching information, quality inspection data, and audio-visual interpretation records. The design end refers to a functional module responsible for design information input and management in the complex product assembly process quality online guarantee system, which can specifically include a design file management module, a critical point table generation module, and a design change management module. Its main functions include outputting design files containing critical point tables, receiving critical point confirmation to-do tasks, and performing remote quality confirmation. The critical point table is used to represent the design file containing critical inspection point and mandatory inspection point information, which specifically includes inspection requirements, inspection standards, and inspection timing. The critical process correlation model refers to a data model that accurately maps critical inspection points and process flow. The to-be-confirmed task refers to a task item that needs quality confirmation automatically generated according to the process execution progress. The quality analysis and confirmation end refers to the operation end responsible for quality analysis and confirmation, including the key quality analysis end and the mandatory quality analysis end. The preset intelligent quality inspection model refers to a proprietary quality inspection AI model constructed based on a deep learning image recognition algorithm.

[0031] During the start-up phase of the complex product assembly, a complete quality control system and data collection mechanism need to be established. Specifically, first, the assembly production process data is collected from the MES system through the ETL (Extract-Transform-Load) integration interface to establish a data source foundation. After receiving the design files output by the design end, including the critical point table, the assembly production process data is correlated and analyzed with the critical inspection points in the critical point table to identify key quality control nodes and generate a critical process correlation model. This model establishes an accurate mapping relationship between production data and quality control nodes. Based on this model, the assembly process execution progress of the complex product can be tracked in real time, and the completion status of each process node can be monitored. When the assembly process execution progress reaches a preset threshold, the corresponding to-be-confirmed tasks are automatically generated according to the critical inspection points. These to-be-confirmed tasks are assigned to the corresponding quality analysis and confirmation end. The quality analysis and confirmation end uses the preset intelligent quality inspection model to perform in-depth quality analysis on the to-be-confirmed tasks according to the preset online method, generating quality confirmation results containing detailed quality evaluation information. Finally, the assembly process flow progress of the complex product is intelligently controlled according to the specific content of the quality confirmation results, realizing quality-driven production process management and control.

[0032] In some embodiments, the technical architecture deployment of the overall quality assurance method can be implemented in various ways: alternatively, a distributed system architecture is adopted, the data interaction layer and the data presentation layer are deployed at the design unit, the data source layer, the data service layer and the data resource center are deployed at the factory, real-time data transmission is realized through network connection, the ETL tool is set to a 15-minute collection period, the WebService interface is used for second-level sound and image data collection, the data integrity and real-time performance are ensured, and a multi-level data backup and disaster recovery mechanism is established, including local backup, off-site backup and cloud backup, to ensure stable operation of the system and data security; alternatively, a centralized cloud platform architecture is adopted, all system components are deployed on a unified cloud platform, the design end and the factory end are accessed through a web browser or a mobile terminal, the elastic computing capability of the cloud platform is used to process large-scale data collection and analysis tasks, an AI quality inspection model service is integrated to provide intelligent quality interpretation capability, and a micro-service architecture design is adopted to modularize deployment of the task center, quality assurance, production data aggregation, quality three single and other functional modules, facilitating system expansion and maintenance. It can be understood that other hybrid architecture methods can also be used to implement the system deployment of the quality assurance method, which is not limited here.

[0033] Through the above steps, the assembly production process data of the complex product is associated with the critical inspection points in the critical point table, forming a critical process association model. The critical process association model can establish an accurate mapping relationship between the production data and the quality control nodes. The critical process association model interacts with the assembly process execution progress, which can realize real-time tracking of the assembly process of the complex product, and automatically generate a to-be-confirmed task of the critical inspection point when a specific execution progress is reached. The to-be-confirmed task and the quality analysis confirmation end form a cooperative mechanism, and the quality analysis confirmation end uses a preset intelligent quality inspection model to perform quality analysis on the to-be-confirmed task according to a preset online mode, and generates a quality confirmation result. The quality confirmation result and the assembly process flow progress of the complex product form a closed-loop control, so that process flow control based on real-time quality analysis can be realized. Thus, the technical problem of poor quality control responsiveness of the assembly process of the complex product in the related art is solved, and the technical effect of improving the quality control responsiveness of the assembly process of the complex product is achieved.

[0034] The execution subject of the above steps can be a system, such as an assembly process quality online assurance system, or a control device, or a controller or processor in a device or system, or a separate controller or processor, or other processing devices or processing units with similar processing functions, but is not limited thereto.

[0035] In an optional embodiment, total assembly production process data of a complex product is collected, and in the case that a design file including a critical point table is output by a design end, the total assembly production process data is associated with critical inspection points in the critical point table to generate a critical process association model, specifically including: collecting total assembly production process data in a target MES system by using an ETL integrated interface in a preset data collection period; in the case that the critical point table is received, sending the critical point table to a process end; obtaining a process file prepared by the process end according to the critical point table, the process file including an association relationship between a process step and a critical inspection point; sending the obtained process file to a total assembly end to obtain manufacturing data association records generated by the total assembly end in association of the process step and corresponding manufacturing data according to the process file in a total assembly production process; analyzing the critical inspection points in the manufacturing data association records to determine key inspection points and mandatory inspection points, the key inspection points being process nodes that need to be quality confirmed and do not affect the total assembly process flow progress of the complex product in the total assembly process of the complex product, and the mandatory inspection points being process nodes that need to be quality confirmed and affect the total assembly process flow progress; and associating the key inspection points and the mandatory inspection points according to the total assembly production process data, the process file and the manufacturing data association records in a total assembly process flow sequence to generate a critical process association model.

[0036] In the preset data collection period, the total assembly production process data in the target MES system is collected by using the ETL integrated interface. In the case that the critical point table is received, the critical point table is sent to the process end. The process file prepared by the process end according to the critical point table is obtained. The process file includes an association relationship between a process step and a critical inspection point. The obtained process file is sent to the total assembly end to obtain manufacturing data association records generated by the total assembly end in association of the process step and corresponding manufacturing data according to the process file in a total assembly production process. The critical inspection points in the manufacturing data association records are analyzed to determine key inspection points and mandatory inspection points. The key inspection points are process nodes that need to be quality confirmed and do not affect the total assembly process flow progress of the complex product in the total assembly process of the complex product. The mandatory inspection points are process nodes that need to be quality confirmed and affect the total assembly process flow progress. The key inspection points and the mandatory inspection points are associated according to the total assembly production process data, the process file and the manufacturing data association records in a total assembly process flow sequence to generate a critical process association model.

[0037] After receiving the criticality point table output by the design end, the data collection and association model construction process is started. Specifically, within the preset data collection period, the target MES system is connected using the ETL integrated interface, and the assembly production process data is collected through data view, including production plan, progress status, equipment operation, quality detection and other multi-dimensional information. After receiving the criticality point table, it is sent to the process end for processing. The process end compiles detailed process documents based on the criticality point table, establishes a clear association between process steps and criticality inspection points, and ensures that each inspection point has corresponding process support. The process documents are sent to the assembly end, which strictly follows the process documents in actual production, associates each process step with the corresponding manufacturing data, and generates complete manufacturing data association records. The criticality inspection points in the manufacturing data association records are analyzed in depth, and according to the influence of the inspection points on the process flow, they are divided into key inspection points and mandatory inspection points. The former does not affect the assembly process flow progress but requires quality confirmation, and the latter affects the assembly process flow progress and must pass quality confirmation. Finally, integrate the assembly production process data, process documents and manufacturing data association records three aspects of information, according to the assembly process flow sequence, the key inspection points and the mandatory inspection points are associated in order, and the criticality process association model with complete structure and clear logic is generated.

[0038] In some embodiments, the data collection and correlation model generation process can be implemented in various ways: optionally, a real-time streaming data collection architecture is adopted, a Kafka message queue system is deployed to receive real-time production data pushed by the MES system, a Storm streaming processing engine or a Flink streaming processing engine is used for data cleaning and preprocessing, a Redis cache layer is established to improve data access efficiency, an Elasticsearch search engine is deployed to support multi-dimensional data query, a process management system is used by the process side to compile process files containing detailed process parameters, inspection requirements, operation specifications, etc., manufacturing data is input in real time by the assembly side through mobile terminals or workstation computers, and the system automatically performs data verification and correlation analysis; optionally, a batch data processing architecture is adopted, a timing task is set to extract data from the MES system in batches every 15 minutes, a Hadoop distributed storage and a Spark big data processing framework are used for data processing, a data warehouse is established to store historical data and intermediate results, a standardized template is used by the process side to compile process files to ensure uniform data format, manufacturing data is automatically collected by the assembly side through barcode scanning, RFID identification, etc., to reduce manual input errors, and the system uses machine learning algorithms to automatically identify and classify inspection points. It can be understood that other data collection and processing technologies can also be used to achieve the functional requirements of this step, which are not limited here.

[0039] In an optional embodiment, the key inspection points and the mandatory inspection points are associated according to the total assembly production process data, the process file and the manufacturing data association record in the order of the total assembly process flow to generate the key-process association model, specifically including: classifying the total assembly production process data according to the action attribute to determine the process to be controlled data and the quality to be confirmed data, the process to be controlled data including the production plan data, the production progress data and the material matching information, the quality to be confirmed data including the key quality to be confirmed data and the mandatory quality to be confirmed data, the key quality to be confirmed data including the routine quality inspection data and the routine video interpretation record, the mandatory quality to be confirmed data including the key quality inspection data and the key video interpretation record; performing first association processing on the process to be controlled data and the routine quality inspection data and the routine video interpretation record with the key inspection points according to the manufacturing data association record to obtain the first association result; performing second association processing on the key quality inspection data and the key video interpretation record with the mandatory inspection points according to the manufacturing data association record to obtain the second association result; configuring the first association result in the key inspection points, and configuring the second association result in the mandatory inspection points; and sorting the key inspection points and the mandatory inspection points according to the total assembly process flow under the condition that the key inspection points are configured with the first association result and the mandatory inspection points are configured with the second association result according to the process file to generate the key-process association model.

[0040] In the above embodiment, the action attribute classification refers to classifying the data according to the role and attribute of the data in the production process; the process to be controlled data represents the data type that needs to be controlled and managed in the production process, specifically including the production plan data, the production progress data, the material matching information and the like; the quality to be confirmed data is used to represent the data type that needs to be quality confirmed, which is further divided into the key quality to be confirmed data and the mandatory quality to be confirmed data; the key quality to be confirmed data refers to the quality data related to the key inspection points, specifically including the routine quality inspection data, the routine video interpretation record and the like; the mandatory quality to be confirmed data represents the quality data related to the mandatory inspection points, specifically including the key quality inspection data, the key video interpretation record and the like; the first association processing and the second association processing represent the data association processing mode for different types of inspection points.

[0041] In the fine stage of the construction of the association model of the strong process, the collected data need to be classified and associated in depth. Specifically, first, the assembly production process data are classified according to the function, and are divided into process control data and quality confirmation data according to the function of the data in the production control. The process control data includes production plan data (planned start time, planned completion time, planned working hours, etc.), production progress data (actual start time, completion progress percentage, remaining working hours, etc.) and material matching information (material arrival state, inventory quantity, shortage list, etc.), which are mainly used for production process progress control and resource allocation. The quality confirmation data are further divided into key quality confirmation data and mandatory quality confirmation data. The former includes routine quality inspection data (dimension measurement, appearance inspection, function test, etc.) and routine video interpretation records (assembly process photos, inspection videos, etc.), and the latter includes key quality inspection data (key dimension accurate measurement, important interface inspection, safety performance test, etc.) and key video interpretation records (key assembly node photos, important inspection process videos, etc.). According to the manufacturing data association records, the process control data, the routine quality inspection data and the routine video interpretation records are associated with the key inspection points for the first association processing, a complete data support system of the key inspection points is established, and the first association result is obtained. At the same time, the key quality inspection data and the key video interpretation records are associated with the mandatory inspection points for the second association processing, so as to ensure that the mandatory inspection points have sufficient quality judgment basis, and the second association result is obtained. The first association result is configured in the key inspection points, and the second association result is configured in the mandatory inspection points, so as to enrich the data connotation of the inspection points. After the data configuration of the inspection points is completed, the key inspection points and the mandatory inspection points are sorted according to the assembly process sequence according to the process file, and a data complete, structure clear and logic rigorous strong process association model is generated.

[0042] In some embodiments, the data classification and association processing function can be implemented in various ways: optionally, a rule engine-based data classification method is adopted, a complete data classification rule library is established, including data type identification rules, attribute label allocation rules, and association relationship establishment rules, etc., and a Drools rule engine or a self-developed rule engine is used for automatic data classification, while a data blood relationship map is established to track data flow process and ensure the accuracy of the association relationship, a data quality monitoring mechanism is established to detect data integrity, consistency, accuracy, etc. in real time, and abnormal data is automatically marked and manually audited, a multi-level data verification mechanism is established, including field-level verification, record-level verification, and business-level verification, etc.; optionally, an intelligent data classification method based on machine learning is adopted, a data classification model is trained using historical data, including Naive Bayes classifier, random forest classifier, deep neural network classifier, etc., to realize automatic classification and label allocation of data, and clustering algorithm is used to identify the implicit association relationship between data to establish a more accurate association model, reinforcement learning algorithm is used to optimize data association strategy, and association rules are continuously adjusted according to actual application effect to improve association accuracy, a data feature engineering pipeline is established to automatically extract data features and select features to improve model performance. It can be understood that other data processing and artificial intelligence technologies can also be used to realize the data classification and association function of this step, which is not limited here.

[0043] In an optional embodiment, the complex product assembly process execution progress is tracked by using the process association model, and the to-be-confirmed tasks of the process inspection points are generated according to the assembly process execution progress, specifically including: obtaining a current process node being performed in the whole process flow, and determining the to-be-executed key inspection points and the to-be-executed mandatory inspection points corresponding to the current process node according to the process association model; obtaining process execution state information of the current process node, and determining the assembly process execution progress of the current process node according to the process execution state information; if the assembly process execution progress reaches a preset completion state of the current process node, generating a to-be-confirmed key task according to the to-be-executed key inspection points, and generating a to-be-confirmed mandatory task according to the to-be-executed mandatory inspection points, wherein the to-be-confirmed task includes the to-be-confirmed key task and the to-be-confirmed mandatory task.

[0044] The process flow indicates the complete flow of all processes in the complex product assembly process; the current process node refers to the process node being performed in the process flow; the to-be-executed key inspection point indicates the key inspection point to be executed in the current process node; the to-be-executed mandatory inspection point is used to indicate the mandatory inspection point to be executed in the current process node; the process execution state information refers to various types of information reflecting the execution state of the current process node, specifically including process start time, completion progress, resource occupation state, abnormal situation record, and the like; the assembly process execution progress indicates the overall completion progress of the current process node; the preset completion state is used to indicate the process completion judgment standard preset by the system, specifically including progress threshold, quality qualification standard, time node requirement, and the like; the to-be-confirmed key task and the to-be-confirmed mandatory task respectively indicate the to-be-confirmed tasks generated according to different types of inspection points.

[0045] In the assembly process execution process, it is necessary to monitor the process progress in real time and generate quality confirmation tasks in a timely manner. Specifically, through the real-time data interface with the MES system, the current process node information in the process flow is obtained, including process identification, process name, execution personnel, start time and the like. Based on the process association model, the to-be-executed key inspection point and the to-be-executed mandatory inspection point corresponding to the current process node are accurately determined, and a dynamic mapping relationship between the process node and the inspection point is established. The process execution state information of the current process node is continuously obtained, including process completion percentage, quality detection result, equipment running state, personnel operation state and the like, and the assembly process execution progress of the current process node is determined through a data analysis algorithm. When it is detected that the assembly process execution progress reaches the preset completion state of the current process node, the task generation mechanism is automatically triggered, and the to-be-confirmed key task containing detailed information such as inspection item, inspection standard and inspection method is generated according to the specific requirements and inspection content of the to-be-executed key inspection point. At the same time, the to-be-confirmed mandatory task containing key information such as mandatory inspection item, key quality index and qualification judgment standard is generated according to the strict requirements of the to-be-executed mandatory inspection point. The generated to-be-confirmed tasks include the to-be-confirmed key task and the to-be-confirmed mandatory task, which provide clear task guidance for subsequent quality analysis and confirmation work.

[0046] In some embodiments, the process progress tracking and task generation function can be implemented in various ways: optionally, an event-driven architecture is used for process progress tracking, an event listener is deployed in the MES system, an event message is pushed immediately when the process state changes, the progress update and task generation logic are triggered after receiving the event, a complex event processing (CEP) engine is used to analyze the process execution mode, identify abnormal situations and automatically alert, a process progress prediction model is established, the process completion time is predicted based on historical data and current execution state, and tasks to be confirmed are generated in advance, a task priority management mechanism is established, the task priority is dynamically adjusted according to the importance, urgency, dependency relationship and other factors of the inspection points, and key tasks are ensured to be processed in priority; optionally, a timing polling mechanism is used for process progress tracking, a timing task is set to query the process state of the MES system every 5 minutes, the progress change is identified by state comparison, the task generation is triggered when the progress reaches the preset threshold, a state machine model is used to manage the process flow process, ensuring that the process is executed according to the predetermined flow, a task template library is established, different types of inspection point corresponding task templates are predefined, including inspection items, inspection methods, quality standards, etc., the corresponding template is automatically applied when a task needs to be generated, the task generation efficiency and standardization level are improved, and a task generation log recording mechanism is established to record the task generation process and results in detail. It can be understood that other process monitoring and task management techniques can also be used to implement the progress tracking and task generation function of this step, which is not limited here.

[0047] In an optional embodiment, the task to be confirmed is assigned to the quality analysis confirmation end to obtain a quality confirmation result generated by the quality analysis confirmation end after performing quality analysis on the task to be confirmed according to a preset online mode using a preset intelligent quality inspection model, specifically including: receiving quality analysis end configuration information input by the process end, and determining a quality analysis confirmation end according to the quality analysis end configuration information, the quality analysis confirmation end including a key quality analysis end and a forced quality analysis end; assigning the key task to be confirmed to the key quality analysis end to obtain a key quality confirmation result generated by the key quality analysis end after performing first quality analysis on the key task to be confirmed according to a first preset online mode using the preset intelligent quality inspection model, and assigning the forced task to be confirmed to the forced quality analysis end to obtain a forced quality confirmation result generated by the forced quality analysis end after performing second quality analysis on the forced task to be confirmed according to a second preset online mode using the preset intelligent quality inspection model, wherein the quality confirmation result includes the key quality confirmation result and the forced quality confirmation result, and the preset online mode includes the first preset online mode and the second preset online mode.

[0048] The quality analysis end configuration information indicates configuration parameters for determining the quality analysis confirmation end, and specifically includes analyst information, device configuration, permission settings, working mode, etc. The key quality analysis end refers to a quality analysis terminal responsible for processing tasks related to key inspection points, and specifically includes a key quality inspection workstation, a conventional detection device, and a general quality analyst. The mandatory quality analysis end is used to indicate a quality analysis terminal responsible for processing tasks related to mandatory inspection points, and specifically includes a key quality inspection workstation, a conventional detection device, and a general quality analyst. The first preset online mode indicates an online operation mode of the key quality analysis end for processing tasks, supporting parallel processing of multiple tasks. The second preset online mode refers to an online operation mode of the mandatory quality analysis end for processing tasks, using serial processing to ensure rigor. The first quality analysis and the second quality analysis respectively indicate quality analysis processes for different types of tasks. The key quality confirmation result and the mandatory quality confirmation result respectively indicate quality confirmation conclusions of two different rigor levels.

[0049] After the to-be-confirmed task is generated, the task needs to be reasonably assigned to the corresponding quality analysis confirmation end for processing. Specifically, first, the quality analysis end configuration information input by the process end is received, which specifies the processing requirements, personnel qualification requirements, device configuration standards, and other key parameters of different types of tasks in detail. Based on these configuration information, the specific composition of the quality analysis confirmation end is determined, including the key quality analysis end and the mandatory quality analysis end. An intelligent task scheduling algorithm is used to assign the to-be-confirmed key task to the key quality analysis end, which is equipped with conventional quality inspection equipment and quality analysts with corresponding qualifications. The key quality analysis end receives tasks according to the first preset online mode, which supports parallel processing of multiple tasks, improves processing efficiency, and uses a preset intelligent quality inspection model to perform first quality analysis on the to-be-confirmed key task, including data verification, standard comparison, and abnormality identification. Finally, the key quality confirmation result is generated, including analysis conclusions, quality ratings, and improvement suggestions. At the same time, the to-be-confirmed mandatory task is assigned to the mandatory quality analysis end, which is equipped with precision detection equipment and senior quality experts. The mandatory quality analysis end processes tasks according to the second preset online mode, using a serial processing mode to ensure that each task is fully focused, and using a preset intelligent quality inspection model to perform second quality analysis, executing more rigorous quality evaluation standards, and generating a mandatory quality confirmation result containing detailed analysis reports, risk assessment, and processing suggestions. Finally, the quality confirmation result includes the key quality confirmation result and the mandatory quality confirmation result, and the preset online mode includes the first preset online mode and the second preset online mode, forming a complete quality analysis system.

[0050] In some embodiments, the task allocation and quality analysis function can be implemented in various ways: optionally, an intelligent task allocation mechanism based on load balancing is adopted, a quality analysis end capability evaluation model is established, including personnel skill level, equipment performance parameters, historical processing efficiency and other indicators, genetic algorithm or particle swarm algorithm is used for optimal allocation of tasks, to ensure load balancing of each analysis end, a task priority queue management is established, the processing order is dynamically adjusted according to the task urgency, importance, dependency and other factors, a real-time monitoring mechanism is established to track the task processing progress, when processing abnormalities or delays are found, automatic task re-allocation is performed, a variety of AI models including image recognition, natural language processing, data mining and other technologies are integrated to improve the intelligent level of quality analysis; optionally, a task processing mechanism based on workflow engine is adopted, a quality analysis workflow is designed using BPMN modeling tool, including task receiving, analysis execution, result review, exception handling and other links, a workflow engine such as Activiti or Camunda is deployed to manage task flow, to ensure standardized execution of the process, a task processing time estimation model is established, based on historical data and task characteristics to predict processing time, to provide reference for production planning, a quality analysis knowledge base is established, to accumulate quality analysis experience and cases, to provide decision support for analysis personnel, an analysis result quality evaluation mechanism is established, to ensure the accuracy and reliability of the analysis results through cross-validation, expert review and other methods. It can be understood that other task management and quality analysis technologies can also be used to implement the task allocation and analysis function of this step, which is not limited here.

[0051] In an optional embodiment, the to-be-confirmed key task is assigned to the key quality analysis end to obtain a key quality confirmation result generated by the key quality analysis end after performing first quality analysis on the to-be-confirmed key task according to a first preset online mode by using a preset intelligent quality inspection model, and the to-be-confirmed mandatory task is assigned to the mandatory quality analysis end to obtain a mandatory quality confirmation result generated by the mandatory quality analysis end after performing second quality analysis on the to-be-confirmed mandatory task according to a second preset online mode by using the preset intelligent quality inspection model, the quality confirmation result includes the key quality confirmation result and the mandatory quality confirmation result, and the preset online mode includes the first preset online mode and the second preset online mode, and specifically includes: assigning the to-be-confirmed key task to the key quality analysis end to enable the key quality analysis end to sequentially perform the following operations: the key quality analysis end views the first video and audio recording information corresponding to the to-be-confirmed key task through the first preset online mode, and a plurality of to-be-confirmed key tasks are configured as tasks processed in parallel; the key quality analysis end performs first quality analysis on the first video and audio recording information by using the preset intelligent quality inspection model, generates a first video and audio to-be-confirmed interface, and confirms the first video and audio to-be-confirmed interface; the key quality analysis end confirms the first check item form corresponding to the to-be-confirmed key task after confirming the first video and audio to-be-confirmed interface; the key quality analysis end processes the key inspection point signature task according to a preset confirmation mode after the key quality analysis end processes the key inspection point signature task; the key quality confirmation result generated by the key quality analysis end after processing the key inspection point signature task is obtained; the to-be-confirmed mandatory task is assigned to the mandatory quality analysis end to enable the mandatory quality analysis end to sequentially perform the following operations: the mandatory quality analysis end views the second video and audio recording information corresponding to the to-be-confirmed mandatory task through the second preset online mode, and a plurality of to-be-confirmed mandatory tasks are configured as tasks processed in series; the mandatory quality analysis end performs second quality analysis on the second video and audio recording information by using the intelligent quality inspection model, generates a second video and audio to-be-confirmed interface, and confirms the second video and audio to-be-confirmed interface; the mandatory quality analysis end confirms the second check item form corresponding to the to-be-confirmed mandatory task after confirming the second video and audio to-be-confirmed interface; the mandatory quality analysis end processes the mandatory inspection point signature task according to the preset confirmation mode after confirming the second check item form; and the mandatory quality confirmation result generated by the mandatory quality analysis end after processing the mandatory inspection point signature task is obtained.

[0052] The first sound image record information indicates sound image data related to the to-be-confirmed key task, and specifically includes assembly process photos, inspection process videos, audio records, etc. The parallel processing refers to a working mode in which multiple to-be-confirmed key tasks can be processed simultaneously. The first sound image to-be-confirmed interface is used to indicate a key task confirmation interface generated after intelligent quality inspection model analysis, and specifically includes analysis result display, abnormality marking, quality evaluation, etc. The first inspection item form indicates a quality inspection item form related to the to-be-confirmed key task, and specifically includes an inspection item list, standard requirements, inspection results, etc. The key inspection point signature task refers to a task that needs to be confirmed and signed at a key inspection point. The second sound image record information indicates sound image data related to the to-be-confirmed mandatory task. The serial processing is used to indicate a strict mode in which the to-be-confirmed mandatory task needs to be processed one by one in sequence. The second sound image to-be-confirmed interface, the second inspection item form, and the mandatory inspection point signature task correspond to related processing contents of the mandatory inspection point, respectively. The preset confirmation mode indicates a signature confirmation operation mode preset by the system, and specifically includes electronic signature, digital certificate verification, multi-identity authentication, etc.

[0053] After the to-be-confirmed task is received at the quality analysis confirmation end, a detailed quality analysis processing procedure needs to be performed. Specifically, the to-be-confirmed key task is assigned to the key quality analysis end, triggering the key quality analysis end to perform a series of standardized operations. First, the key quality analysis end views the first video and audio record information corresponding to the to-be-confirmed key task through a first preset online mode, including assembly site photos, inspection process videos, quality detection data and other multimedia information, and configures multiple to-be-confirmed key tasks in a parallel processing mode, allowing the analyst to process multiple relatively independent key tasks simultaneously, thereby improving processing efficiency. The key quality analysis end uses a preset intelligent quality inspection model to perform in-depth analysis on the first video and audio record information, including image feature recognition, defect detection, quality evaluation and other intelligent processing, to generate a first video and audio to-be-confirmed interface containing analysis conclusions, risk prompts and improvement suggestions, which is carefully reviewed and confirmed by the analyst. After confirming the first video and audio to-be-confirmed interface, the key quality analysis end continues to process the first inspection item form corresponding to the to-be-confirmed key task, which contains detailed inspection items, quality standards, inspection methods and other information, which is checked and confirmed by the analyst item by item. After completing the form confirmation, the key quality analysis end processes the key inspection point signature task according to a preset confirmation mode, including identity verification, electronic signature, timestamp recording and other operations, and finally generates a key quality confirmation result. At the same time, the to-be-confirmed mandatory task is assigned to the mandatory quality analysis end, which performs operations according to a more stringent processing procedure. The mandatory quality analysis end views the second video and audio record information corresponding to the to-be-confirmed mandatory task through a second preset online mode, and multiple to-be-confirmed mandatory tasks are configured in a serial processing mode to ensure that each task receives sufficient attention and strict analysis. The mandatory quality analysis end uses the intelligent quality inspection model to perform more detailed second quality analysis on the second video and audio record information, generates a second video and audio to-be-confirmed interface and strictly confirms it, then processes the second inspection item form, and finally processes the mandatory inspection point signature task according to the preset confirmation mode to generate a mandatory quality confirmation result.

[0054] In some embodiments, the detailed quality analysis processing function can be implemented in various ways: optionally, a multi-modal analysis method based on deep learning is adopted, a convolutional neural network is integrated for image analysis, a recurrent neural network is used to process sequence data, an attention mechanism is adopted to improve the key feature recognition capability, a multi-level quality evaluation model is established including pixel-level detection, region-level analysis, and overall-level evaluation, an augmented reality auxiliary analysis system is established, AR glasses or tablet devices are used to provide real-time standard comparison, historical case query, expert suggestion push, and other auxiliary functions for analysts, voice recognition and natural language processing technology are used to support voice input confirmation results, operation convenience is improved, blockchain technology is integrated to ensure the non-tamperability and traceability of signature tasks; optionally, a knowledge-driven analysis method based on an expert system is adopted, a complete quality analysis knowledge base is established including inspection standards, judgment rules, and processing experience, a reasoning engine is used for intelligent decision support, a case reasoning system is established to provide references for current analysis through similar case matching, a collaborative analysis platform is established to support online collaboration of multiple experts, remote collaborative analysis is realized through video conferencing, screen sharing, real-time labeling, and other functions, an analysis result consistency verification mechanism is established to improve the reliability of the results through multiple rounds of verification and cross-confirmation, digital signature and timestamp services are integrated to ensure the legal effectiveness and timeliness of the analysis process. It can be understood that other artificial intelligence and digital technologies can also be used to implement the detailed quality analysis processing function of this step, which is not limited here.

[0055] In an optional embodiment, the assembly process flow progress of the complex product is controlled according to the quality confirmation result, specifically including: performing first correlation analysis on the quality confirmation result by using the correlation process correlation model, to determine that the quality confirmation result includes a key quality confirmation result corresponding to a key inspection point, and then executing a next process node of a current process node; performing second correlation analysis on the quality confirmation result by using the correlation process correlation model, to determine that the quality confirmation result includes a mandatory quality confirmation result corresponding to a mandatory inspection point, and then executing the next process node when the mandatory quality confirmation result is a quality confirmation pass; or, determining that the quality confirmation result includes the mandatory quality confirmation result corresponding to the mandatory inspection point by using the correlation process correlation model, and then not executing the next process node when the mandatory quality confirmation result is a quality confirmation fail, and forwarding the received re-inspection application to the re-inspection end.

[0056] The first correlation analysis represents an analysis and processing of the key quality confirmation result by using the correlation-strong process correlation model; the second correlation analysis represents an analysis and processing of the forced quality confirmation result by using the correlation-strong process correlation model; the next process node refers to a subsequent process node of the current process node in the process flow; the quality confirmation pass represents a state that the forced quality confirmation result meets the preset quality standard; the quality confirmation fail represents a state that the forced quality confirmation result does not meet the preset quality standard; the re-inspection application represents a re-inspection application submitted when the quality confirmation fails, and specifically includes a re-inspection reason, a re-inspection requirement, a re-inspection time, and the like; and the review end refers to a department or system responsible for processing the re-inspection application and performing a review confirmation, and specifically includes a senior quality expert, a review workstation, a special review process, and the like.

[0057] After obtaining the complete quality confirmation result, the assembly process flow progress of the complex product needs to be intelligently controlled according to the confirmation result. Specifically, the quality confirmation result is analyzed by using the correlation-strong process correlation model for the first correlation analysis, which includes steps such as result type identification, inspection point matching, and process influence evaluation. When it is determined that there is a key quality confirmation result corresponding to a key inspection point in the quality confirmation result, due to the characteristic that the key inspection point does not affect the process flow progress, the next process node of the current process node is automatically executed, ensuring the continuity and efficiency of the production process. Meanwhile, the quality confirmation result is analyzed by using the correlation-strong process correlation model for the second correlation analysis, focusing on the confirmation result related to the forced inspection point. When it is determined that there is a forced quality confirmation result corresponding to the forced inspection point in the quality confirmation result, and the state of the forced quality confirmation result is quality confirmation pass, it indicates that the quality requirement of the forced inspection point has been met, and the next process node is allowed to be executed, maintaining the normal production rhythm. However, when it is determined that there is a forced quality confirmation result corresponding to the forced inspection point in the quality confirmation result by using the correlation-strong process correlation model, and the forced quality confirmation result is quality confirmation fail, the execution of the next process node is immediately prevented to prevent the quality problem from being passed to the subsequent process. At this time, the received re-inspection application is automatically forwarded to the review end, triggering a special review process, and a more in-depth analysis and processing decision is made by a higher-level quality expert or a review department. This differential process control mechanism based on the quality confirmation result not only guarantees the production efficiency but also ensures the strictness of quality control.

[0058] In some embodiments, the quality confirmation result control process flow function can be implemented in multiple ways: Optionally, a rule engine-based intelligent process control method is adopted, establishing a complete process control rule base including process flow conditions, quality access control standards, exception handling processes, etc. A complex event processing engine is used to monitor changes in quality confirmation results in real time, triggering corresponding process control actions immediately when a critical event is detected. A multi-level quality access control mechanism is established, including process-level access control, stage-level access control, and product-level access control. Simultaneously, a workflow engine is integrated to manage the verification and review processes, including task allocation, processing time limits, escalation mechanisms, etc. A quality problem traceability system is established, recording complete information such as problem discovery, processing, and resolution results. Continuous improvement provides data support; optionally, a state machine-based process flow management approach can be adopted, using a finite state machine model to define various states and transition conditions of process flow, establishing a state transition matrix to clarify the process actions corresponding to various quality confirmation results, integrating a decision support system to provide decision suggestions for complex situations, and establishing a real-time monitoring and early warning module to immediately issue early warning notifications to relevant personnel when process flow anomalies or quality problems are detected. An automated message push mechanism should be established to promptly notify relevant stakeholders of information such as process status changes, quality problems, and processing results. Mobile applications should be integrated to support process monitoring and decision-making anytime, anywhere, and a data visualization dashboard should be established to display the process flow status and quality control situation in real time. It is understood that other process management and quality control technologies can also be used to implement the process flow control function for this step; this is not limited here.

[0059] It should be noted that the embodiments described above are only some embodiments of this application, and not all embodiments. The present application will be described in detail below with reference to specific embodiments.

[0060] This application provides an embodiment of an online quality assurance business process, see reference. Figure 2 , Figure 2 This is a flowchart illustrating an online quality assurance method for complex product assembly processes in this application, comprising the following steps:

[0061] Step S201, Begin;

[0062] Step S202: The designer (i.e. the design end) prepares the design documents, which include a key point table;

[0063] Step S203: The designer outputs the compiled key point table to the process engineer (i.e., the process end).

[0064] In step S204, the process engineer compiles the process through the critical point table, and generates process documents by associating the process steps with the critical points. Alternatively, the online quality assurance system for the final assembly process can adaptively associate the process steps with the critical points to generate process documents, and so on.

[0065] Step S205, the total assembly personnel according to the process requirements in the process file for assembly;

[0066] Step S206, according to the process of manufacturing data;

[0067] Step S207, one post, two post, inspection post (i.e. total assembly end) signed strong point confirmation to do file;

[0068] Step S208, process received one post, two post, inspection post push strong point confirmation to do;

[0069] Step S209, one post, two post, inspection post to see, confirm, in the total assembly process quality online guarantee system in the field of strong point confirmation signature, and execute step S220;

[0070] Step S210, scheduling / quality personnel to see the pending allocation results;

[0071] Step S211, designer received one post, two post, inspection post push strong point confirmation to do;

[0072] Step S212, the first judgment is made to determine whether the need for on-site confirmation;

[0073] Step S213, in the above first judgment result is yes, the designer to see, confirm, and in the total assembly process quality online guarantee system in the field of strong point confirmation signature;

[0074] Step S214, in the above first judgment result is no, remote view, confirm;

[0075] Step S215, the second judgment is made to determine whether the need for review;

[0076] Step S216, in the above second judgment result is yes, the designer initiates the review application, generates review to do task;

[0077] Step S217, in the above second judgment result is no, the designer submits the confirmation result, and in the total assembly process quality online guarantee system in the field of strong point signature, and execute step S220;

[0078] Step S218, according to the review to do task, the third judgment is made to determine whether to agree to review the application;

[0079] Step S219, in the above third judgment result is yes, the reviewer submits the confirmation result, and remote strong point signature;

[0080] Step S220, end.

[0081] The following describes the operation of each link in the online quality assurance business process:

[0082] I. Designer link:

[0083] 1. Start: The starting point of the online quality assurance business process, the designer starts work, prepares the design file (including the critical point table), and after completion, enters the next link, outputs the design file and critical point information to the subsequent process.

[0084] 2. Output design file (including critical point table): Complete the design file preparation as the source of information, and push the file and information to the subsequent critical point confirmation to be done link to trigger the subsequent process.

[0085] 3. Receive critical point confirmation to be done: Receive the to-be-done task from the process flow, determine whether it needs to be confirmed on site according to the task, which is a key decision node, and decide the subsequent execution path (on-site / remote).

[0086] If on-site confirmation is required: Go to the site, perform on-site viewing and confirmation (fill out / change, confirm signature) operations, and after completion, submit the confirmation results, which are linked to the submission of confirmation results (fill out / change, confirm signature);

[0087] If on-site confirmation is not required: View and confirm remotely, and then determine whether re-inspection is required. If so, initiate a re-inspection application and enter the review link. If not, directly submit the results.

[0088] 4. Submit confirmation results (fill out / change, confirm signature): After on-site or remote confirmation, submit the results with signature as a key step for process closure, and link to the end of the process.

[0089] II. Process engineer link:

[0090] 1. Import critical point table: Receive the critical point table output by the designer as the basis for compilation, and link to the compilation of the process (associate process steps with critical points).

[0091] 2. Compile process (associate process steps with critical points): Associate process steps with critical points based on the table to form a process file, and link to the critical point confirmation to be done node, which is pushed by the assembly and other links. When the process engineer receives the to-be-done task.

[0092] 3. Receive critical point confirmation to be done: Trigger the process engineer's on-site work, and link to on-site viewing and confirmation (fill out / change, confirm signature).

[0093] 4, On-site viewing, confirmation (filling / changing, confirmation signature): the process engineer goes to the site, views and confirms the process execution, etc., and signs, completes the role task, and the process is pushed to the end.

[0094] III. Assembly personnel link:

[0095] 1. Assembling according to process requirements: based on the process file output by the process engineer, the assembly operation is carried out, which is the core link of manufacturing execution, and the manufacturing data is associated according to the process steps.

[0096] 2. Associate manufacturing data with process steps: in assembly, associate manufacturing data with process steps to provide basis for inspection, etc., and link one post, two posts and inspection post (key point confirmation / to do).

[0097] 3. One post, two post and inspection post (key point confirmation / to do): complete inspection, mark the state of key point (generate to do), link the viewing of to do assignment results (dispatch / quality link), and promote the process to the dispatch / quality role.

[0098] IV. Dispatch / quality link:

[0099] Viewing the to-do assignment results is a key action of the dispatch / quality role, which is responsible for receiving the inspection to-do output by the assembly personnel, viewing and assigning, coordinating the process flow between roles, ensuring the process to proceed in order, and the executor is the dispatch / quality post personnel.

[0100] V. Review personnel link:

[0101] 1. Whether to agree (reinspection link): receive the reinspection application initiated by the designer, judge whether to agree, which is a key decision point of the reinspection process, decide whether to enter the submission of confirmation results (filling / changing, confirmation signature), and the executor is the review personnel.

[0102] 2. Submit confirmation results (filling / changing, confirmation signature) (after review): if you agree to reinspect, go through the review process, finally submit the confirmation results, complete the entire manufacturing process loop, and the executor is the review personnel (or in cooperation with the designer, etc., according to the actual process).

[0103] The entire process revolves around product production guarantee business, and is connected in series through to-do task transmission + role node operation (including on-site / remote, decision judgment), to ensure that the links from design output to manufacturing execution, inspection confirmation and possible reinspection are in order. Through the operation of each role at the key node (such as confirmation of to-do processing, on-site / remote decision), the product manufacturing process is standardized and operated.

[0104] The following is the core technical path of the complex product assembly process quality online guarantee method in the embodiment of the application:

[0105] 1) Data collection and integration: The design unit integrates the ETL tool with the factory MES system to collect key information such as production plan, production progress, material set, quality data, and voice interpretation records in real time. The collection frequency is 15 minutes, and the network condition ensures that all data collection and calculation activities can be completed within 5 minutes. Through the development of unstructured data collection and storage services, remote collection and local storage of factory voice records (such as photos) are realized, and the collection frequency is second-level, which ensures the completeness, real-time and accuracy of quality assurance data.

[0106] 2) Data visualization: Based on the collected production data, a visual board is built to display production progress, material set, and quality data in real time, and supports multi-dimensional query and display by model, set, and process.

[0107] 3) Remote collaboration and online confirmation: Through innovative inspection point and process association, daily assembly process execution process tracking SOP (Standard Operating Procedure), intelligent interpretation technology based on voice data, structured and unstructured process information fusion viewing, and other innovations, combined with unified rapid development platform, ETL tool, Webservice technology, data governance technology, visual recognition technology, remote online communication technology, real-time data search and analysis technology, etc., the quality data, voice records and quality inspection results of each process are collected, and the confirmation tasks are automatically generated according to the inspection point confirmation requirements and pushed to the designer and quality assurance personnel interface. The design unit, quality assurance personnel and other remote real-time viewing and post-tracing production data are supported, and the online confirmation of quality inspection points is realized through the system. According to different states, reminders can be made to ensure that quality problems can be discovered and handled in a timely manner.

[0108] 4) Intelligent quality inspection and interpretation: The proprietary quality inspection AI model is integrated with the deep learning-based image recognition algorithm, which can automatically identify quality problems and intelligently judge whether the assembly result meets the requirements. It also supports comparison with manual interpretation results to improve quality inspection efficiency and accuracy.

[0109] 5) Data download and export: The production data, quality data, and voice records can be exported as files to facilitate the design unit, quality assurance personnel, and other personnel to prepare reports and schemes.

[0110] The embodiment of the application provides a total assembly process quality online guarantee system, which is referred to Figure 3 , Figure 3is a schematic diagram of an architecture of an online quality assurance system for a general assembly process in an embodiment of the present application. The online quality assurance system for the general assembly process mainly consists of six parts:

[0111] 1) Data source layer: mainly refers to various business information systems of design units and factories, including MES systems, and can support subsequent ERP (Enterprise Resource Planning) systems, TDM (Test Data Management) systems, CAPP (Computer Aided Process Planning) systems, project management systems, etc., and also includes related information systems to be implemented or prepared in the future. The integrated data types include technical drawing data, structured data, semi-structured data, images, videos, etc.

[0112] 2) Data service layer: provides data service components and collection components. The service components include process management, data exchange, business rules, etc. The collection components provide ETL, integrated interfaces, file systems (directly read EXCEL, CSV, etc.), and other differentiated data integration means, and also provide preliminary data collection, cleaning, and conversion capabilities.

[0113] 3) Data resource center: provides data governance capabilities, including data modeling, data development, data indicators, data quality (data specification), etc. Meanwhile, data warehouses and data marts including ODS (Operational Data Store), DW (Data Warehouse), and DM (Data Mart) are constructed to form large-scale data themes.

[0114] 4) Data application layer: establishes data tags according to business application fields, aggregates theme data, and provides production and maintenance business function logic to realize online production and maintenance business functions, etc.

[0115] 5) Data presentation layer: provides intuitive and comprehensive production process data visualization capabilities based on models.

[0116] 6) Data interaction layer: undertakes the tasks of design unit and factory business collaboration and data interaction, realizes the on-demand distribution of various production process data collected and sorted by the factory to the data center or other business information systems of the design unit, and provides interactive business function applications.

[0117] The online quality assurance system for the general assembly process mainly consists of four core business functions:

[0118] 1) Task center:

[0119] Through MES data pushing, the user receiving the task is automatically matched according to the model, and a task list is formed; the corresponding to-be-done task is displayed according to the model, and searching and screening are supported according to the title, sending personnel, notification type, reading state, state and sending time;

[0120] The total to-be-done task quantity can be displayed, and display and sorting are supported according to the title, product number, drawing number, sending personnel, task allocation personnel, task receiving personnel, reading state, state and sending time;

[0121] After data pushing is completed, the user can click to delegate and send the task to a user for processing.

[0122] 2) Quality assurance:

[0123] According to business needs, it is divided into two parts of key inspection points and mandatory inspection points, mainly providing online data query, online communication, inspection point confirmation and data download capabilities for key inspection points and mandatory inspection points of quality assurance work carried out online;

[0124] Online communication function is provided, the system sends the inspection point confirmation to-do message to the designer or quality assurance personnel in the form of email, which can conveniently view the task attribute information such as task allocation time, belonging process, and desired confirmation time, as well as the basic information of the type number, set, and product number of the inspection point, and in the viewing process, the point-to-point message function on the right side can be used to communicate with the factory;

[0125] Inspection point summary viewing function is provided, which supports quick query and screening according to the type number, set, drawing number, confirmation type, signature state, etc., can count the number of different inspection point signature states, and can view the inspection item table and photograph point record and details related to the inspection point according to the type number, set, process, process, and inspection point;

[0126] The sound and video record details collected are provided for viewing, which can be compared with the sample, and the AI model intelligent interpretation ability is provided;

[0127] Online confirmation function is provided in the inspection point, form, sound and video viewing links, after all sound and video are confirmed, all forms can be confirmed, after all forms are confirmed, the inspection point can be confirmed, one-key quick confirmation and multi-item confirmation progress viewing function are provided;

[0128] The sound and video record and other information can be downloaded to the local.

[0129] 3) Production data summary:

[0130] Mainly provide summary information, production plan progress, production set situation, production process quality and production process data display;

[0131] Summary information: summary of product quantity, production progress query, work log viewing function, provides specified time within the specified model or set of total assembly manufacturing completion rate and total time query ability;

[0132] Production plan progress: display the production plan and progress of the relevant model through Gantt chart, show the process according to the model, and can view and filter the process set information and process quality data. The process quality selection data can view the corresponding detail display;

[0133] Production set situation: display the product material information and set state of a certain model or set;

[0134] Production process quality: show the specific and detailed data of process quality according to model and set;

[0135] Production process data entry: MES system source data quick view entry.

[0136] 4) Quality three single:

[0137] Mainly provides the number and trend of production process quality problem feedback, and provides problem information feedback summary, plant material substitution single and unqualified product feedback summary, which can be directly drilled into OA system for detailed inquiry;

[0138] Quality information summary: production site problem feedback information statistics and item detail information query function, show the number of items of reported site information feedback sheet and unqualified product handling sheet, support normal state and over 14 days state analysis display;

[0139] Three single details: through the quality three single data, through the filtering condition query material substitution single, information feedback single and unqualified product handling single detail data, select the corresponding row data, support calling OA interface, get the detailed data in OA system, and display.

[0140] The main function structure of the assembly process quality online guarantee system is:

[0141] Task center:

[0142] 1) Message details: form details (including audio and video photo details), shooting point details, collection point details, personnel assignment, operation record;

[0143] 2) Online communication.

[0144] 2, quality assurance:

[0145] 1) Forced inspection point summary confirmation:

[0146] Step: inspection point record (including collection point details), shooting point record (including shooting point details);

[0147] Inspection point (including inspection item): Form details (including audio-visual photo details), photographing point details, collection point details;

[0148] Form: Table set summary, form details (including audio-visual photo details);

[0149] Audio-visual: Photographing point details, collection point details, photo export.

[0150] 2) Key inspection point summary confirmation:

[0151] Step: Inspection point record (including collection point details), photographing point record (including photographing point details);

[0152] Inspection point (including inspection item): Form details (including audio-visual photo details), photographing point details, collection point details;

[0153] Form: Table set summary, form details (including audio-visual photo details);

[0154] Audio-visual: Photographing point details, collection point details, photo export.

[0155] 3, Production data summary:

[0156] 1) Production plan progress: Process quality (including collection point details, photographing point details), process set information, production plan progress tracking;

[0157] 2) Production set situation;

[0158] 3) Production process quality: Inspection point record (including collection point details), photographing point record (including photographing point details);

[0159] 4) Production process data entry: Quality process (including collection point details), photographing record (including photographing point details).

[0160] 4, Quality three single:

[0161] 1) Quality information summary;

[0162] 2) Substation material substitution single detail;

[0163] 3) Substation information feedback single detail;

[0164] 4) Substation unqualified treatment single detail.

[0165] The embodiment of the application provides an ETL collection framework, refer to Figure 4 , Figure 4is a structural schematic diagram of the ETL collection framework in the embodiment of the present application, which is the framework of the ETL component Kettle used in the embodiment of the present application. In the framework, the ETL serves as a central processing engine, responsible for coordinating and processing information flow from multiple data sources. Three main upstream data sources are shown: the configuration file interacts with the ETL through save configuration and load configuration operations, the component library provides component information to the ETL through load component and fold flow operations, and the flow file (.job format) transmits flow definition to the ETL system through the save flow operation. After the ETL processing is completed, the function of creating / modifying a flow is output to the user end through a configuration parameter, the running state is fed back to the user, and the processing result is stored in the file system through the read data operation. The entire framework embodies a typical data integration processing mode, in which the ETL undertakes the core responsibilities of data extraction, cleaning, conversion and loading, realizes a complete data processing flow from multiple heterogeneous data to unified data storage, and provides a standardized data service interface for the upper layer application. The file system refers to the MES system and the online production and quality assurance system (i.e., the total assembly process quality online assurance system), that is, the data of the MES system can be read by the ETL and provided to the online production and quality assurance system for use, and the data in different tables of the online production and quality assurance system can be collected, processed and then loaded into another table for use. The resource library refers to a combination of data collection, storage, conversion and job formed after the ETL tool is configured and developed, which can be directly called and executed by the ETL tool. The essence of the ETL lies in the workflow (job), which realizes the process of data analysis. The ETL includes a designer and an execution engine. The ETL data extraction steps are as follows.

[0166] Step 1: Full table query input operation is performed on the source data and the target data;

[0167] Step 2: Sorting is performed respectively;

[0168] Step 3: The sorted data of the two tables is merged and compared;

[0169] Step 4: The compared data is added with a self-defined mapping increase, deletion and modification mark value;

[0170] Step 5: Whether the record is changed is filtered. If not, an empty operation is performed, and if yes, subsequent operations are continued to be performed;

[0171] Step 6: System time is obtained for verification;

[0172] Step 7: Whether the record is marked for increase is filtered. If yes, the output field is selected and output, and if not, subsequent operations are continued to be performed;

[0173] Step 8: Whether the record is marked for deletion is filtered. If yes, the output field is selected and deleted, and if not, the output field is selected and updated;

[0174] Since the ETL tool itself is not suitable for real-time information interaction and feedback, the embodiment also builds the message notification, information interaction, state feedback, etc. capabilities of quality assurance collaborative business with WebService protocol, which can realize the rapid special delivery of message data. The sound and image data collection is also realized through the writing of WebService interface service, which is stored through independent file service in the assembly process quality online assurance system.

[0175] Referring to Figure 5 , Figure 5 is a structural schematic diagram of the WebService integration framework in the embodiment of the application, and the structural framework includes:

[0176] 1) MES system:

[0177] Message notification module: responsible for generating and sending various production-related notification information, such as process state change, quality inspection task, etc.

[0178] Information interaction module: handles the bidirectional transmission of production data, including production plan, process parameters, quality data, etc. structured information.

[0179] Sound and image file module: manages the unstructured multimedia data such as pictures and videos generated in the production process.

[0180] 2) WebService-based interface:

[0181] Message interface: handles the transmission and forwarding of various notification information.

[0182] Information interaction interface: responsible for bidirectional transmission and format conversion of structured data.

[0183] Sound and image delivery interface: handles the transmission and storage of multimedia files.

[0184] 3) Online quality assurance system:

[0185] Message response module: receives and processes various notifications from MES, and performs corresponding display and processing.

[0186] Information processing module: analyzes, stores and displays the received production data.

[0187] Sound and image display module: displays and manages the multimedia records of the production process.

[0188] This architecture realizes real-time sharing and remote collaboration of production data, ensures the reliability and security of data transmission through standardized WebService interface, and supports online monitoring and quality assurance of the production process.

[0189] Through the embodiment of the present application, real-time acquisition, visual display and remote collaboration of production data are realized through digital means, and the transparency and control efficiency of the production process are improved.

[0190] The total assembly process quality online guarantee system in the embodiment of the present application is described from the perspective of hardware processing, and reference is made to Figure 6 , Figure 6 is a schematic diagram of an entity device structure of the total assembly process quality online guarantee system in the embodiment of the present application.

[0191] It should be noted that Figure 6 The structure of the total assembly process quality online guarantee system shown is only an example, and should not bring any limitation to the function and use range of the embodiment of the present application.

[0192] As Figure 6 shown, the total assembly process quality online guarantee system includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 602 or loaded from a storage portion 608 to a random access memory (RAM) 603, such as performing the method described in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored.

[0193] The CPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0194] The following components are connected to the I / O interface 605: an input portion 606 including an audio input device, a button switch, and the like; an output portion 607 including a liquid crystal display (LCD), an audio output device, an indicator, and the like; a storage portion 608 including a hard disk and the like; and a communication portion 609 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is mounted on the drive 610 as needed, so that a computer program read therefrom is installed in the storage portion 608 as needed.

[0195] In particular, the processes described above with reference to the flow charts can be implemented as computer software programs in accordance with embodiments of the present application. For example, embodiments of the present application include a computer program product which includes a computer program tangibly embodied on a computer readable medium, the computer program containing instructions for executing the methods illustrated by the flow charts. In such embodiments, the computer program can be downloaded and installed from a network via the communication portion 609 and / or installed from a removable media 611. When the computer program is executed by the central processing unit (CPU) 601, various functions defined in the present application are performed.

[0196] Note that specific examples of computer readable storage media can include without limitation: electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read only memory (EPROM or Flash memory), a portable compact disc read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing. In the present application, a computer readable storage medium can be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0197] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functional processes and operations that can be implemented in computer software, hardware, or a combination thereof. Each block in the flow diagrams and the block diagrams can represent a module, a segment, or a portion of code that comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the flow diagrams or the block diagrams can occur out of the order noted in the figures.

[0198] In particular, the assembly process quality online assurance system of the present embodiment includes a processor and a memory, and the memory stores a computer program, and the computer program is executed by the processor to implement the complex product assembly process quality online assurance method provided by the above embodiment.

[0199] As another aspect, the present application also provides a computer readable storage medium, which can be included in the total assembly process quality online guarantee system described in the above embodiments, or can exist independently without being assembled into the total assembly process quality online guarantee system. The above storage medium carries one or more computer programs, which, when executed by a processor of the total assembly process quality online guarantee system, enable the total assembly process quality online guarantee system to implement the complex product assembly process quality online guarantee method provided in the above embodiments.

[0200] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features, and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

[0201] Those skilled in the art can understand that all or part of the processes in the above embodiments can be implemented by a computer program to instruct relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The foregoing storage medium includes ROM or random storage memory RAM, magnetic disc or optical disc, and various program code storage media.

Claims

1. A method for online assurance of quality in complex product assembly processes, characterized in that, The method comprises the following steps: Collecting assembly production process data of a complex product, and associating the assembly production process data with critical inspection points in a critical inspection point table in a design file output by a design end to generate a critical process association model in the case of receiving the design file; Tracking assembly process execution progress of the complex product by using the critical process association model, and generating to-be-confirmed tasks of the critical inspection points according to the assembly process execution progress; Assigning the to-be-confirmed tasks to a quality analysis confirmation end to obtain quality confirmation results generated by the quality analysis confirmation end by using a preset intelligent quality inspection model to perform quality analysis on the to-be-confirmed tasks in a preset online manner; Controlling assembly process flow progress of the complex product according to the quality confirmation results; The collecting assembly production process data of a complex product, and associating the assembly production process data with critical inspection points in a critical inspection point table in a design file output by a design end to generate a critical process association model in the case of receiving the design file specifically comprises the following steps: Collecting the assembly production process data in a target MES system by using an ETL integrated interface in a preset data collection period; In the case of receiving the critical inspection point table, sending the critical inspection point table to a process end; Obtaining a process file prepared by the process end according to the critical inspection point table, the process file comprising an association relationship between process steps and the critical inspection points; Sending the obtained process file to an assembly end to obtain manufacturing data association records generated by associating the process steps with corresponding manufacturing data in the assembly production process according to the process file; Analyzing the critical inspection points in the manufacturing data association records to determine key inspection points and mandatory inspection points, the key inspection points being process nodes that need to be quality confirmed and do not affect assembly process flow progress of the complex product in the assembly process of the complex product, and the mandatory inspection points being process nodes that need to be quality confirmed and affect the assembly process flow progress in the assembly process of the complex product; Associating the key inspection points and the mandatory inspection points according to assembly process flow sequences according to the assembly production process data, the process file and the manufacturing data association records to generate the critical process association model; The associating the key inspection points and the mandatory inspection points according to assembly process flow sequences according to the assembly production process data, the process file and the manufacturing data association records to generate the critical process association model specifically comprises the following steps: Classifying the assembly production process data according to action attributes to determine process to-be-controlled data and quality to-be-confirmed data, the process to-be-controlled data comprising production plan data, production progress data and material set information, and the quality to-be-confirmed data comprising key quality to-be-confirmed data and mandatory quality to-be-confirmed data, the key quality to-be-confirmed data comprising regular quality inspection data and regular video interpretation records, and the mandatory quality to-be-confirmed data comprising key quality inspection data and key video interpretation records; According to the manufacturing data association record, the process to be controlled data, the routine quality inspection data, the routine acoustic interpretation record and the key inspection point are first associated to obtain a first association result; According to the manufacturing data association record, the key quality inspection data and the key acoustic interpretation record are second associated with the mandatory inspection point to obtain a second association result; The first association result is configured in the key inspection point, and the second association result is configured in the mandatory inspection point; In a case where it is determined that the key inspection point has configured the first association result and the mandatory inspection point has configured the second association result, the key inspection point and the mandatory inspection point are sorted according to the assembly process sequence flow in the process file to generate the assembly process association model.

2. The method of claim 1, wherein, The assembly process execution progress of the complex product is tracked by using the assembly process association model, and the to-be-confirmed task of the key inspection point is generated according to the assembly process execution progress, and specifically includes: A current process node being performed in the process flow is acquired, and the to-be-executed key inspection point and the to-be-executed mandatory inspection point corresponding to the current process node are determined according to the assembly process association model; Process execution state information of the current process node is acquired, and the assembly process execution progress of the current process node is determined according to the process execution state information; If the assembly process execution progress reaches a preset completion state of the current process node, a to-be-confirmed key task is generated according to the to-be-executed key inspection point, and a to-be-confirmed mandatory task is generated according to the to-be-executed mandatory inspection point, wherein the to-be-confirmed task includes the to-be-confirmed key task and the to-be-confirmed mandatory task.

3. The method of claim 2, wherein, The to-be-confirmed task is distributed to a quality analysis confirmation end to obtain a quality confirmation result generated by the quality analysis confirmation end after quality analysis of the to-be-confirmed task is performed by using a preset intelligent quality inspection model in a preset online manner, and specifically includes: Quality analysis end configuration information input by a process end is received, and the quality analysis confirmation end is determined according to the quality analysis end configuration information, wherein the quality analysis confirmation end includes a key quality analysis end and a mandatory quality analysis end; The to-be-confirmed key task is distributed to the key quality analysis end to obtain a key quality confirmation result generated by the key quality analysis end after first quality analysis of the to-be-confirmed key task is performed by using the preset intelligent quality inspection model in a first preset online manner, and the to-be-confirmed mandatory task is distributed to the mandatory quality analysis end to obtain a mandatory quality confirmation result generated by the mandatory quality analysis end after second quality analysis of the to-be-confirmed mandatory task is performed by using the preset intelligent quality inspection model in a second preset online manner, the quality confirmation result includes the key quality confirmation result and the mandatory quality confirmation result, and the preset online manner includes the first preset online manner and the second preset online manner.

4. The method of claim 3, wherein, The to-be-confirmed key task is assigned to the key quality analysis end to obtain a key quality confirmation result generated by the key quality analysis end after performing first quality analysis on the to-be-confirmed key task according to a first preset online mode by using the preset intelligent quality inspection model, and the to-be-confirmed mandatory task is assigned to the mandatory quality analysis end to obtain a mandatory quality confirmation result generated by the mandatory quality analysis end after performing second quality analysis on the to-be-confirmed mandatory task according to a second preset online mode by using the preset intelligent quality inspection model, wherein the quality confirmation result includes the key quality confirmation result and the mandatory quality confirmation result, and the preset online mode includes the first preset online mode and the second preset online mode, and specifically includes: The to-be-confirmed key task is assigned to the key quality analysis end to make the key quality analysis end sequentially perform the following operations: the key quality analysis end views the first video and audio recording information corresponding to the to-be-confirmed key task through the first preset online mode, and a plurality of to-be-confirmed key tasks are configured as tasks processed in parallel; the key quality analysis end performs first quality analysis on the first video and audio recording information by using a preset intelligent quality inspection model, generates a first video and audio to-be-confirmed interface, and confirms the first video and audio to-be-confirmed interface; the key quality analysis end confirms the first check item form corresponding to the to-be-confirmed key task after confirming the first video and audio to-be-confirmed interface; and the key quality analysis end processes the key inspection point signature task according to a preset confirmation mode after confirming the first check item form. The key quality confirmation result generated by the key quality analysis end after processing the key inspection point signature task is obtained. The to-be-confirmed mandatory task is assigned to the mandatory quality analysis end to make the mandatory quality analysis end sequentially perform the following operations: the mandatory quality analysis end views the second video and audio recording information corresponding to the to-be-confirmed mandatory task through the second preset online mode, and a plurality of to-be-confirmed mandatory tasks are configured as tasks processed in series; the mandatory quality analysis end performs second quality analysis on the second video and audio recording information by using the intelligent quality inspection model, generates a second video and audio to-be-confirmed interface, and confirms the second video and audio to-be-confirmed interface; the mandatory quality analysis end confirms the second check item form corresponding to the to-be-confirmed mandatory task after confirming the second video and audio to-be-confirmed interface; and the mandatory quality analysis end processes the mandatory inspection point signature task according to the preset confirmation mode after confirming the second check item form. The mandatory quality confirmation result generated by the mandatory quality analysis end after processing the mandatory inspection point signature task is obtained.

5. The method of claim 4, wherein, The total assembly process flow progress of the complex product is controlled according to the quality confirmation result, and specifically includes: performing a first correlation analysis on the quality confirmation result by using the correlation model of the key process, to determine whether the quality confirmation result includes the key quality confirmation result corresponding to the key inspection point; and performing a second correlation analysis on the quality confirmation result by using the correlation model of the key process, to determine whether the quality confirmation result includes the mandatory quality confirmation result corresponding to the mandatory inspection point, and whether the mandatory quality confirmation result is a quality confirmation pass; and determining whether the quality confirmation result includes the mandatory quality confirmation result corresponding to the mandatory inspection point, and whether the mandatory quality confirmation result is a quality confirmation pass, by using the correlation model of the key process; and 6. A system for online assurance of assembly process quality, characterized by The assembly process quality online assurance system includes one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program codes, the computer program codes include computer instructions, and the one or more processors invoke the computer instructions to enable the assembly process quality online assurance system to perform the method according to any one of claims 1-5.

7. A computer-readable storage medium comprising instructions, characterized in that, The instructions enable the assembly process quality online assurance system to perform the method according to any one of claims 1-5 when the instructions run on the assembly process quality online assurance system.

8. A computer program product, characterised in that, The computer program product enables the assembly process quality online assurance system to perform the method according to any one of claims 1-5 when the computer program product runs on the assembly process quality online assurance system.

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