Electronic module production whole-process data acquisition and quality tracing system

Abstract

This invention relates to a data acquisition and quality traceability system for the entire production process of electronic modules, belonging to the field of intelligent electronic manufacturing management technology. The method includes: acquiring electronic module mounting data through SMT and establishing a process data index; selecting the corresponding test program for the electronic module to be tested through an ICT testing unit and outputting upstream board bonding information; automatically retrieving the mounting status of the upstream electronic modules, determining the completion status of the insertion process, verifying the matching status of the soldering process data with the preset wave soldering window parameters, and generating a jig removal process record; real-time acquisition and recording of the burning process log; classifying the electronic module production process based on the burning results; loading test fixtures and test cases through a verification testing unit; for electronic modules that pass the test, inputting the conformal coating unit, and inspecting the conformal coating coverage status according to the electronic module qualification standards, generating an electronic module quality inspection traceability report.

Description

Technical Field

[0001] This invention belongs to the field of intelligent electronic manufacturing management technology, specifically involving a data acquisition and quality traceability system for the entire production process of electronic modules. Background Technology

[0002] With the rapid development of the electronics and information industry, electronic modules, as key components in communication equipment, industrial control systems, automotive electronics, aerospace equipment, and smart terminal products, directly impact the operational quality of the entire system due to their performance stability and product reliability. The production process of electronic modules typically involves multiple steps, including raw material inspection, component assembly, welding, functional testing, aging testing, and factory verification. These steps involve complex data relationships, generating a large amount of process parameters, equipment operating data, test results, and quality records. How to effectively collect, manage, and utilize this production data to achieve full-process monitoring of product quality and rapid problem traceability has become a crucial technical problem that the electronics manufacturing industry urgently needs to solve.

[0003] Most existing electronic module production management systems employ information platforms such as Manufacturing Execution Systems (MES), Enterprise Resource Planning (ERP), and Quality Management Systems (QMS) to manage the production process. While these systems can record production data, manage process flows, and store quality inspection information, the data from different systems is often independent, lacking a unified data association mechanism. When quality anomalies occur during subsequent testing or use, it is difficult to quickly establish a correlation between the quality problem and historical process data, resulting in low efficiency in quality traceability and increasing the difficulty of troubleshooting and liability determination.

[0004] Meanwhile, existing quality traceability methods typically rely on batch management or single-process inspection results, relying on manual historical record searches for problem analysis. This approach is not only time-consuming and labor-intensive, but also struggles to identify the quality evolution process resulting from the combined effects of multiple processes and factors. Especially in complex electronic module manufacturing scenarios, quality defects may originate in preceding processes and gradually accumulate and propagate through multiple production stages, only manifesting in subsequent testing phases. Traditional traceability technologies lack the ability to analyze the dynamic evolution of quality status, making it difficult to accurately pinpoint the root cause of anomalies.

[0005] Furthermore, with the development of intelligent manufacturing technology, some enterprises have begun to introduce industrial big data analysis and digital management methods. However, most solutions focus on production monitoring or equipment management, lacking a quality traceability mechanism covering the entire product lifecycle, making it difficult to achieve a deep correlation between production data, testing data, and quality responsibility. At the same time, the analysis of quality anomalies typically remains at the statistical level, lacking the technical means to simulate quality propagation paths and verify the degree of root cause impact. This leads to inaccurate identification of responsible processes, hindering the implementation of quality improvement efforts.

[0006] Therefore, there is an urgent need to provide a data acquisition and quality traceability system for the entire production process of electronic modules, which can uniformly collect and manage data throughout the entire production process, establish a data link covering the entire product life cycle, realize quality status evolution analysis, trace the root cause of anomalies, and accurately locate the responsible process, thereby improving the quality management level and efficiency of quality problem handling in the electronic module production process. Summary of the Invention

[0007] To address the aforementioned problems in the existing technology, this invention provides a data acquisition and quality traceability system for the entire production process of electronic modules. The objective of this invention can be achieved through the following technical solutions: Plug-in Index Building Module: Electronic module mounting data is obtained through SMT. Based on the communication connection, the electronic module mounting data is automatically entered into the mounting and binding stage of the generated process registration model, and a process data index is established using the electronic module serial number as a unique identifier. Test coating quality inspection module: Organize the equipment parameters and data acquisition work orders of the mounting and binding stage, and use the process data index as the binding constraint. Through the ICT test unit, select the corresponding test program of the electronic module to be tested and output the upstream single board binding information. Plug-in welding confirmation module: Based on the upstream single board binding information, it automatically retrieves the upstream electronic module mounting status, determines the completion status of the plug-in process, calls the wave soldering detection window, collects welding process data, verifies the matching status of the welding process data with the preset wave soldering window parameters, generates a welding parameter sequence, and combines the product inspection results fed back by the jig removal detection unit to perform correlation analysis on the welding parameter sequence and generate a jig removal process record; Test Coating Inspection Module: Performs comprehensive visual inspection of electronic modules, compares them with qualified samples, calls the corresponding electronic module programming program version, and collects the programming process log in real time; classifies the electronic module production process based on the programming results, loads test fixtures and test cases through the verification test unit, inputs qualified electronic modules into the conformal coating unit, and inspects the conformal coating coverage according to the electronic module qualification standards, generating an electronic module quality inspection traceability report.

[0008] Specifically, the process of automatically inputting and generating the electronic module mounting data to register the model mounting and binding stage includes the following steps: The electronic module mounting data is collected in real time by the barcode scanning device on the SMT production line. The electronic module mounting data includes: the PCB width of the electronic module, the position of the board feeder frame, the coordinate data of the pick-and-place machine, and the component BOM information. The collected electronic module mounting data is automatically pushed to the process registration model, the data is uniformly verified for format, the execution process of the mounting and binding stage is recorded, and a traceable mounting and binding record is generated.

[0009] Specifically, the process of establishing the process data index includes the following steps: Using the electronic module serial number as the index key, all process parameters, equipment IDs, and operation timestamps in the mounting stage are associated, and a multi-dimensional process data index table is established based on a relational database index structure. Through a time-series alignment algorithm, a pre-sequence-post-sequence correspondence is established between the mounting data and subsequent ICT test data, forming a process data index that supports fast retrieval throughout the entire process.

[0010] Specifically, the process of organizing the equipment parameters and data acquisition work orders includes the following steps: The equipment parameters and data acquisition work orders during the mounting and bonding phase are structured and organized to establish a mapping relationship between equipment parameters and work order tasks. Furthermore, by combining historical process baseline data, the system distinguishes between instantaneous fluctuations and systematic deviations in sampling. Based on the analysis results, abnormal parameters are marked, and the process timestamp information is archived and stored according to the electronic module serial number and production batch, generating process data records for the mounting and binding stage.

[0011] Specifically, the selection process for the corresponding test program of the electronic module to be tested includes the following steps: Read the product model and serial number information of the electronic module to be tested, query the corresponding product configuration file in the process data index, match the corresponding ICT test program version according to the product configuration file, and verify the consistency between the test program version and the requirements of the current production work order. The successfully matched test program will be automatically loaded into the ICT test unit, a test program call record will be generated, and the upstream board binding information of the corresponding electronic module will be output.

[0012] Specifically, the process of automatically retrieving the mounting status of the upstream electronic module and determining the completion status of the insertion process includes the following steps: Obtain the mounting and binding records and mounting completion status of the corresponding electronic modules based on the upstream single-board binding information; Extract component reference number information, placement result information and defect alarm information recorded during the placement stage to determine whether there are any missing, incorrect, or abnormal alarm records. When all mounting processes are completed and there are no abnormal alarm records, the insertion process is deemed to be ready for execution, and an insertion process release instruction is generated; otherwise, an abnormal interception record is generated and a warning message is issued.

[0013] Specifically, the verification process for the matching status of the welding process data with the preset wave soldering window parameters includes the following steps: The welding process data is collected in real time through the wave soldering inspection window, the preset wave soldering window parameters for the corresponding product model are called, and the correspondence between the welding process data and the preset wave soldering window parameters is established. The welding process data includes parameters such as preheating temperature, tin pot temperature, conveying speed, and immersion time. The deviation between the welding process data and the preset wave soldering window parameters is calculated item by item. When the deviation is within the allowable range, it is considered a successful match. Otherwise, abnormal parameter items are recorded and welding abnormality records are generated.

[0014] Specifically, the process of generating the jig disassembly process record includes the following steps: Obtain the product appearance inspection results and functional inspection results output by the disassembly fixture inspection unit, and simultaneously retrieve the welding parameter sequence generated by the corresponding electronic module in the wave soldering process; Based on the electronic module serial number, a mapping relationship is established between product inspection results and welding parameter sequences to locate welding position parameters that affect the disassembly quality and generate disassembly fixture process records.

[0015] Specifically, the process of calling the corresponding electronic module programming program version includes the following steps: Read the electronic module serial number, product model information, and current production work order information, and match the corresponding software configuration file according to the product model information; Based on the software configuration file, query the program version library to obtain the corresponding program file, perform integrity verification on the program file, and verify the matching relationship between the program version and the electronic module hardware version and production work order requirements. When the verification result meets the preset conditions, the binding relationship between the electronic module and the program version is automatically established, the corresponding program is loaded into the program device, and a second version verification is performed on the program result after the program is completed, and a program record is generated.

[0016] Specifically, the process of classifying the electronic module production process includes the following steps: Using the electronic module serial number as the associated identifier, the system obtains the burning results, functional test results, ICT test results, and production history data of each process. The system divides the status judgment window according to the process completion time corresponding to the electronic module production process, and within the status judgment window, the data generated by the same electronic module in each process is collected into the same quality judgment unit.

[0017] Specifically, the process of loading test fixtures and test cases into the verification test unit includes the following steps: For electronic modules that pass the test, the verification and testing unit automatically loads the matching EOL detection fixture and test case set according to the serial number and performs full-process testing; it collects running data in real time and compares it with the preset pass standard, and only outputs a pass signal to electronic modules that pass the test.

[0018] Specifically, the verification process for the conformal coating status includes the following steps: The system acquires surface image data and coating process parameter data of the electronic module collected by the conformal coating unit, retrieves the conformal adhesive coverage standard template of the corresponding product model, and establishes the correspondence between image data and coating process parameters based on the electronic module serial number. The image data is segmented and contours are extracted to identify the actual coverage area of ​​the conformal coating. The actual coverage area is then matched with the coverage standard template. When all detection indicators meet the electronic module's qualification standards, the conformal coating coverage status information is output.

[0019] The beneficial effects of this invention are as follows: By unifying and managing data collection across production processes such as SMT assembly, ICT testing, component soldering, programming testing, EOL testing, and conformal coating, and using the electronic module serial number as the unique traceability identifier, a process data index covering the entire production cycle is established, enabling automatic flow and precise correlation of data from each process.

[0020] The system can automatically acquire mounting data, equipment parameters, test results, and process history information, reducing errors caused by manual data entry and improving the accuracy and real-time performance of production data collection. Simultaneously, by monitoring and verifying key quality data such as wave soldering parameters, programming program version, functional test results, and conformal adhesive coverage throughout the entire process, it can promptly detect production anomalies and intercept them at each stage, reducing the risk of defective products flowing into the next process.

[0021] Furthermore, by establishing a mapping relationship between product testing results and process parameters, the system enables rapid location and root cause tracing of quality issues, improving problem analysis efficiency and quality control capabilities. In addition, the automatic generation of quality inspection traceability reports and complete production histories facilitates transparent management of the production process, enhances product consistency, reliability, and production management levels, and provides reliable data support for quality control, process optimization, and after-sales traceability in the electronic module manufacturing process. Attached Figure Description

[0022] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0023] Figure 1 This is a schematic diagram of the framework of the electronic module production process data acquisition and quality traceability system of the present invention.

[0024] Figure 2 This is a schematic diagram illustrating the process of determining the completion status of the plug-in process in the electronic module production full-process data acquisition and quality traceability system of the present invention. Detailed Implementation

[0025] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description of the specific implementation methods, structures, features and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0026] Please see Figure 1 The present invention also provides a data acquisition and quality traceability system for the entire production process of electronic modules, specifically including: Plug-in Index Building Module: Electronic module mounting data is obtained through SMT. Based on the communication connection, the electronic module mounting data is automatically entered into the mounting and binding stage of the generated process registration model, and a process data index is established using the electronic module serial number as a unique identifier. Test coating quality inspection module: Organize the equipment parameters and data acquisition work orders of the mounting and binding stage, and use the process data index as the binding constraint. Through the ICT test unit, select the corresponding test program of the electronic module to be tested and output the upstream single board binding information. Plug-in welding confirmation module: Based on the upstream single board binding information, it automatically retrieves the upstream electronic module mounting status, determines the completion status of the plug-in process, calls the wave soldering detection window, collects welding process data, verifies the matching status of the welding process data with the preset wave soldering window parameters, generates a welding parameter sequence, and combines the product inspection results fed back by the jig removal detection unit to perform correlation analysis on the welding parameter sequence and generate a jig removal process record; Test Coating Inspection Module: Performs comprehensive visual inspection of electronic modules, compares them with qualified samples, calls the corresponding electronic module programming program version, and collects the programming process log in real time; classifies the electronic module production process based on the programming results, loads test fixtures and test cases through the verification test unit, inputs qualified electronic modules into the conformal coating unit, and inspects the conformal coating coverage according to the electronic module qualification standards, generating an electronic module quality inspection traceability report.

[0027] The specific plan is as follows: This embodiment takes an automotive electronic control unit (ECU) module produced by an automotive parts company as an example. It includes major processes such as chip mounting, soldering, aging testing, functional testing, and packaging, involving the collaborative production of multiple production lines and batches of materials from multiple suppliers.

[0028] System overall architecture and data acquisition deployment; Industrial IoT sensors, visual inspection equipment, PLC data interfaces, and RFID / QR code readers are deployed at each production workstation to achieve real-time data acquisition throughout the entire process. Data types include: Process parameters (temperature, pressure, time, voltage, etc.); Equipment status (speed, current, vibration); Quality inspection results (AOI optical inspection, ICT circuit testing, functional test pass rate); Material batch information (chip, PCB board, solder batch); Operators and environmental parameters (temperature, humidity).

[0029] All data is uploaded to a unified multi-terminal collaborative cloud production synchronization platform to achieve data synchronization across factory, supplier, and client terminals.

[0030] Traceability label generation module; Building a data chain for the entire product lifecycle; The process parameters for each step are uniformly coded, for example: “P01-T=245℃-t=3.5s-SN=BatchA-202506041025”, with timestamp.

[0031] Cross-process time-series alignment of structured event sequences: using the ECU serial number (SN: ECU20250604001) as a unique identifier, batch transfer records and test results are associated.

[0032] Establish a directed connection: P01 (mount) → P02 (soldering) → P03 (burn-in) → P04 (functional testing) → P05 (packaging), forming a complete directed data chain.

[0033] Time-series matching and traceability tag generation; Multimodal fusion and clock synchronization are performed on heterogeneous data sources (PLC data, visual images, test reports) (with preset global clock reference accuracy).

[0034] Using the ECU's "signal delay less than preset time" as a performance anchor point label, the deviation propagation path of each node's data is decoupled.

[0035] Example of generating a quality traceability label: Tag ID: QT-ECU20250604001-v1.2; Key features: Welding peak temperature deviation, aging pass rate, contribution rating: P02 contribution; Causal traceability: High.

[0036] Quality evolution analysis module; Process data extraction layer: The dimensions are divided according to the process sequence: mounting dimension (positional accuracy, pressure), soldering dimension (temperature profile, solder joint volume), and testing dimension (electrical parameters). Construct association mapping relationships to form a process feature dataset, and establish a three-dimensional index of time-process-batch.

[0037] Quality state evolution layer: Perform time-series retrieval on the process feature dataset; Set quality status transition rules (e.g., if the welding temperature is higher than the preset temperature, it enters the "high risk" state). Identifying abnormal evolution nodes: It was discovered that abnormal temperature fluctuations occurred in the P02 welding process over a certain period of time; Extract the production evolution sequence.

[0038] The production evolution sequence is as follows: [Normal] → [P02 Temperature fluctuation, state deviation] → [P04 Functional test slight decline] → [Final health].

[0039] Graph structure modeling mapping: Establish a process association topology network: nodes are P01~P05, and the weight of the directed edge is dynamically calculated according to the process association degree (P01→P02). Implicit association compensation mapping is performed on non-adjacent processes (such as P01 and P04); The output of the electronic module quality feature vector after multi-hop aggregation is as follows: Key components of the quality feature vector: [welding defect propagation, aging stability, functional consistency, ...].

[0040] Traceability report generation module; Automatically perform factory verification: Retrieve production evolution sequences and root cause records; Construct a multi-dimensional verification index system (electrical performance, environmental tolerance, reliability life); Perform multi-level verification: automatically re-inspect abnormal items (welding temperature deviation), and trace back to process P02 using the topology network; Scope of risk impact confirmed: Affects ECU modules in the same batch.

[0041] Full lifecycle quality traceability report generation: Based on the quality feature vector and the factory verification results, a quality risk probability density function is constructed. Product health status rating: A- (minor welding risk); By mapping similar historical cases in reverse, the responsible party was determined to be the welding process team. Output a complete traceability report (including a QR code) and push it to the responsible party's terminal.

[0042] Twin responsibility location verification module: Build a full-process backtracking twin mechanism; Digital twin mirror logic: Establish a time-series mirror link for ECU20250604001, which can reproduce the entire process status at any time in real time; Causal deduction and responsibility locking logic: Backtracking from the P04 functional test anomaly in the twin environment.

[0043] Traverse the topology network in reverse from the abnormal node P04; Calculate the upstream backpropagation contribution: P02 welding has the highest contribution; Causal intervention simulation: After virtually reducing the temperature fluctuation of PO2, the quality evolution result returned to health. Root cause identified: solder formula of material batch B + deviation of P02 temperature control parameters.

[0044] In this embodiment, as Figure 2 As shown, the process of automatically retrieving the mounting status of the upstream electronic module and determining the completion status of the insertion process includes the following steps: Obtain the mounting and binding records and mounting completion status of the corresponding electronic modules based on the upstream single-board binding information; Extract component reference number information, placement result information and defect alarm information recorded during the placement stage to determine whether there are any missing, incorrect, or abnormal alarm records. When all mounting processes are completed and there are no abnormal alarm records, the insertion process is deemed to be ready for execution, and an insertion process release instruction is generated; otherwise, an abnormal interception record is generated and a warning message is issued.

[0045] Tracing back to historical detection data sources: Quickly query historical test records for the same batch using a three-dimensional index of time, space, and batch; After replaying the simulation, an auditable chain of evidence is generated to verify the degree of matching between the current anomaly and the historical pattern.

[0046] Responsibility identification and notification: The push and distribution unit prioritizes traceability reports (high) and pushes them to welding team supervisors, quality directors, and supplier terminals.

[0047] Example 1: Scenarios for tracing the welding quality of communication modules; In the production process of a certain communication electronic module, the process involves component mounting, reflow soldering, AOI inspection, functional testing, and aging testing.

[0048] The traceability label generation module collects production process data such as pick-and-place machine operating parameters, welding temperature profiles, AOI inspection images, and functional test results to construct a data chain covering the entire product lifecycle. By uniformly calibrating the timestamps of each process, corresponding quality traceability labels are generated.

[0049] When intermittent failures were detected in the communication module during the aging test phase, the quality evolution analysis module used a quality evolution characterization model to extract the production evolution sequence and combined it with process-related topology network analysis to identify the anomaly propagation path. Analysis revealed a high correlation between localized temperature fluctuations in the reflow soldering process and subsequent functional anomalies.

[0050] The twin responsibility location verification module simulates the quality evolution results under different welding temperature conditions in a digital twin mirror environment, and finally confirms that the anomaly comes from the welding temperature control deviation, thus achieving precise location of the responsible process.

[0051] Example 2: Batch anomaly tracing scenario of automotive electronic control modules; Specific case: After a batch of automotive electronic control modules were completed and shipped, customers reported that some products had abnormal startup issues.

[0052] Execution process: The system retrieves the corresponding quality traceability label based on the product serial number and obtains raw material batch information, production equipment operating parameters and testing records through the full lifecycle data chain.

[0053] The quality evolution analysis module compared and analyzed abnormal and normal products, finding that the abnormal products all came from the same batch of components. Subsequently, the process association topology network further identified parameter drift in this batch of components during the high-temperature aging stage.

[0054] The twin responsibility location verification module replaces component parameters through virtual intervention, verifies the disappearance of abnormal phenomena, thereby determining that the root cause is the performance degradation problem caused by the fluctuation of raw material quality, and forming a chain of evidence for responsibility location.

[0055] Example 3: Automatic verification scenario for power modules at the factory; Specific example: After a power electronic module is assembled, it enters the factory testing stage.

[0056] Execution process: The traceability report generation module automatically retrieves the production evolution sequence, quality feature vector and historical test records to construct a multi-dimensional verification index system, including output voltage stability, ripple parameters, conversion efficiency and thermal stability indexes.

[0057] When the system performed automatic verification, it found that the ripple parameter of a certain module exceeded the preset range, and then triggered the automatic re-inspection and cross-verification process. Through process association topology network analysis, it was found that the anomaly was strongly related to the preceding capacitor welding process.

[0058] The system automatically generates quality risk assessment results and calculates the product health status level based on the quality risk probability density function. Finally, it pushes the abnormal information and traceability report to the production supervisor terminal and the quality management terminal simultaneously.

[0059] Example 4: Multi-factory collaborative production traceability scenario; Specific case: An electronic module manufacturer adopts a multi-factory collaborative manufacturing model, in which factory A is responsible for PCB assembly and factory B is responsible for overall testing and packaging.

[0060] Execution process: The multi-terminal collaborative cloud production synchronization platform synchronizes the production data of the two factories in real time and builds a unified product lifecycle data chain. The data generated by each factory is used to generate quality traceability labels through unified coding rules.

[0061] When factory B detects an anomaly in the performance of a batch of products, the system can trace back to the corresponding batch in factory A, examining the surface mount process parameters and equipment operation records. The quality evolution analysis module identifies an abnormally large increase in surface mount offset as a significant factor leading to subsequent performance degradation.

[0062] Ultimately, the system generates a cross-factory full lifecycle quality traceability report and sends the responsibility attribution results to the corresponding factory management terminal through the push and distribution unit, thereby achieving collaborative quality management.

[0063] Example 5: Historical Anomaly Reproduction and Responsibility Determination Scenarios; Specific case: An electronic module failed after six months of use by the customer. Execution process: The system retrieves historical inspection data sources based on the product code and quickly locates the production records of products in the same batch using a time-space-batch three-dimensional index. Subsequently, the quality evolution trajectory of the product from production to delivery is reenacted in a digital twin mirror environment.

[0064] The backpropagation contribution of each upstream process is calculated by traversing the process-related topology network in reverse.

[0065] Further parameter replacement and path blocking simulations were performed to verify that the quality problem did not reappear after the abnormal workstation was restored to normal. This identified the responsible process and generated an auditable chain of evidence, providing a basis for after-sales responsibility allocation and quality improvement.

[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A data acquisition and quality traceability system for the entire production process of electronic modules, characterized in that: include: Plug-in Index Building Module: Electronic module mounting data is obtained through SMT. Based on the communication connection, the electronic module mounting data is automatically entered into the mounting and binding stage of the generated process registration model, and a process data index is established using the electronic module serial number as a unique identifier. Test coating quality inspection module: Organize the equipment parameters and data acquisition work orders of the mounting and binding stage, and use the process data index as the binding constraint. Through the ICT test unit, select the corresponding test program of the electronic module to be tested and output the upstream single board binding information. Plug-in welding confirmation module: Based on the upstream single board binding information, it automatically retrieves the upstream electronic module mounting status, determines the completion status of the plug-in process, calls the wave soldering detection window, collects welding process data, verifies the matching status of the welding process data with the preset wave soldering window parameters, generates a welding parameter sequence, and combines the product inspection results fed back by the jig removal detection unit to perform correlation analysis on the welding parameter sequence and generate a jig removal process record; Test Coating Inspection Module: Performs comprehensive visual inspection of electronic modules, compares them with qualified samples, calls the corresponding electronic module programming program version, and collects the programming process log in real time; classifies the electronic module production process based on the programming results, loads test fixtures and test cases through the verification test unit, inputs qualified electronic modules into the conformal coating unit, and inspects the conformal coating coverage according to the electronic module qualification standards, generating an electronic module quality inspection traceability report.

2. The system according to claim 1, characterized in that, The process of automatically entering and generating electronic module mounting data to register the model mounting and binding stage includes the following steps: The electronic module mounting data is collected in real time by the barcode scanning device on the SMT production line. The electronic module mounting data includes: the PCB width of the electronic module, the position of the board feeder frame, the coordinate data of the pick and place machine, and the component BOM information. The collected electronic module mounting data is automatically pushed to the process registration model, the data is uniformly verified, the execution process of the mounting and binding stage is recorded, and a traceable mounting and binding record is generated.

3. The system according to claim 1, characterized in that, The process of establishing the process data index includes the following steps: Using the electronic module serial number as the index key, all process parameters, equipment ID, and operation timestamps in the mounting stage are associated, and a multidimensional process data index table is established based on the relational database index structure. By using a time-series alignment algorithm, a pre-sequence to post-sequence correspondence is established between the mounting data and subsequent ICT test data, forming a process data index that supports rapid retrieval throughout the entire process.

4. The system according to claim 1, characterized in that, The process of organizing the equipment parameters and data acquisition work orders includes the following steps: The equipment parameters and data acquisition work orders during the mounting and bonding phase are structured and organized to establish a mapping relationship between equipment parameters and work order tasks. Furthermore, by combining historical process baseline data, the system distinguishes between instantaneous fluctuations and systematic deviations in sampling. Based on the analysis results, abnormal parameters are marked, and the process timestamp information is archived and stored according to the electronic module serial number and production batch, generating process data records for the mounting and binding stage.

5. The system according to claim 1, characterized in that, The selection process for the corresponding test program of the electronic module to be tested includes the following steps: Read the product model and serial number information of the electronic module to be tested, query the corresponding product configuration file in the process data index, match the corresponding ICT test program version according to the product configuration file, and verify the consistency between the test program version and the requirements of the current production work order. The successfully matched test program will be automatically loaded into the ICT test unit, a test program call record will be generated, and the upstream board binding information of the corresponding electronic module will be output.

6. The system according to claim 1, characterized in that, The process of automatically retrieving the mounting status of upstream electronic modules and determining the completion status of the insertion process includes the following steps: Obtain the mounting and binding records and mounting completion status of the corresponding electronic modules based on the upstream single-board binding information; Extract component reference number information, placement result information and defect alarm information recorded during the placement stage to determine whether there are any missing, incorrect, or abnormal alarm records. When all mounting processes are completed and there are no abnormal alarm records, the insertion process is deemed to be ready for execution, and an insertion process release instruction is generated; otherwise, an abnormal interception record is generated and a warning message is issued.

7. The system according to claim 1, characterized in that, The verification process for the matching status between the welding process data and the preset wave soldering window parameters includes the following steps: The welding process data is collected in real time through the wave soldering inspection window, the preset wave soldering window parameters for the corresponding product model are called, and the correspondence between the welding process data and the preset wave soldering window parameters is established. The welding process data includes parameters such as preheating temperature, tin pot temperature, conveying speed, and immersion time. The deviation between the welding process data and the preset wave soldering window parameters is calculated item by item. When the deviation is within the allowable range, it is considered a successful match. Otherwise, abnormal parameter items are recorded and welding abnormality records are generated.

8. The system according to claim 1, characterized in that, The process of generating the jig disassembly process record includes the following steps: Obtain the product appearance inspection results and functional inspection results output by the disassembly fixture inspection unit, and simultaneously retrieve the welding parameter sequence generated by the corresponding electronic module in the wave soldering process; Based on the electronic module serial number, a mapping relationship is established between product inspection results and welding parameter sequences to locate welding position parameters that affect the disassembly quality and generate disassembly fixture process records.

9. The system according to claim 1, characterized in that, The process of calling the corresponding electronic module programming program version includes the following steps: Read the electronic module serial number, product model information, and current production work order information, and match the corresponding software configuration file according to the product model information; Based on the software configuration file, query the program version library to obtain the corresponding program file, perform integrity verification on the program file, and verify the matching relationship between the program version and the electronic module hardware version and production work order requirements. When the verification result meets the preset conditions, the binding relationship between the electronic module and the program version is automatically established, the corresponding program is loaded into the program device, and a second version verification is performed on the program result after the program is completed, and a program record is generated.

10. The system according to claim 1, characterized in that, The process of classifying the electronic module production process includes the following steps: Using the electronic module serial number as the associated identifier, the system obtains the burning results, functional test results, ICT test results, and production history data of each process. The system divides the status judgment window according to the process completion time corresponding to the electronic module production process, and within the status judgment window, the data generated by the same electronic module in each process is collected into the same quality judgment unit.

11. The system according to claim 1, characterized in that, The process of loading test fixtures and test cases into the verification test unit includes the following steps: For electronic modules that pass the test, the verification and testing unit automatically loads the matching EOL detection fixture and test case set according to the serial number and performs full-process testing; it collects running data in real time and compares it with the preset pass standard, and only outputs a pass signal to electronic modules that pass the test.

12. The system according to claim 1, characterized in that, The verification process for the conformal coating status includes the following steps: The system acquires surface image data and coating process parameter data of the electronic module collected by the conformal coating unit, retrieves the conformal adhesive coverage standard template of the corresponding product model, and establishes the correspondence between image data and coating process parameters based on the electronic module serial number. The image data is segmented and contours are extracted to identify the actual coverage area of ​​the conformal coating. The actual coverage area is then matched with the coverage standard template. When all detection indicators meet the electronic module's qualification standards, the conformal coating coverage status information is output.

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