Dynamic auditing system and method for digital twin intelligent manufacturing quality system

Abstract

The invention discloses a dynamic auditing system and method for a digital twin intelligent manufacturing quality system, and the system comprises a physical layer which comprises a production line, manufacturing equipment on the production line, and a sensor network disposed on the manufacturing equipment, and is used for collecting the multi-source real-time data of a manufacturing process; according to the method, the crossing from'periodic static auditing 'to'continuous dynamic auditing' is realized, the deviation in the system operation can be found in time, the sampling risk and human subjective factors are avoided, the auditing conclusion is more objective and comprehensive, the quality risk can be predicted, the early warning is given out before the problem occurs, the conversion from'post correction 'to'pre-prevention' is realized, and the safety of the system is improved. By using a digital thread technology, the problem source can be quickly traced, the problem analysis and decision-making time is greatly shortened, the workload of manual auditing is greatly reduced, the auditing efficiency and precision are improved, and the quality cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial intelligent manufacturing, and in particular to a digital-twin-based intelligent manufacturing quality system dynamic auditing system and method. BACKGROUND

[0002] In the manufacturing industry, the quality system (such as ISO 9001, IATF 16949) is the core to ensure product consistency and reliability. The traditional quality system audit mainly relies on manual work, and the process is usually as follows: formulating an audit plan, on-site file review, record sampling, personnel interview, and on-site observation, and finally formulating an audit report. This method has significant limitations, such as hysteresis: the audit is periodic (such as once a year), which cannot reflect the real running state of the system during the interval period, and it is too late to find problems, sampling risk: the review based on sampling cannot cover all data and processes, and key problems are easily missed, strong subjectivity: it is heavily dependent on the personal experience and judgment of the auditors, and the standard is difficult to unify, static and one-sided: the audit result is a "static snapshot" at a certain point in time, which cannot reflect the dynamic fluctuations and evolution trend of the production system, low efficiency: it consumes a large amount of manpower, time, and cost In view of the above problems, the present application is improved. SUMMARY

[0003] The present application provides a digital-twin-based intelligent manufacturing quality system dynamic auditing system and method, which solves the above problems in the prior art.

[0004] The technical scheme of the present application is as follows: a digital-twin-based intelligent manufacturing quality system dynamic auditing system, comprising: A physical layer, the physical layer includes a production line and manufacturing equipment on the production line and a sensor network deployed thereon, for collecting multi-source real-time data of the manufacturing process; The production line is composed of a numerical control machine tool, a machining center, and a labeling conveying center and is arranged in sequence, a labeling mechanical arm is slidably installed above the labeling conveying center, a transfer mechanical arm is arranged between the numerical control machine tool, the machining center, and the labeling conveying center, a transfer mechanical arm is arranged on the outer side of the transfer mechanical arm, the numerical control machine tool comprises a numerical control machine tool main body placed on the ground, a machine tool cover is hingedly arranged on one side of the numerical control machine tool main body, a guide rail is fixedly installed on one side of the numerical control machine tool main body, the machine tool cover is slidably installed on the guide rail, an electric push rod one is fixedly installed on the bottom of the numerical control machine tool main body, the output end of the electric push rod one is fixedly installed on the guide rail, a driving device is fixedly installed on one side of the top of the numerical control machine tool main body, a grabbing mechanical arm is slidably installed on the surface of the driving device, and two mechanical claws are movably installed at the bottom end of the grabbing mechanical arm; The side of the numerical control machine tool body is fixedly installed with a support, the top of the support is fixedly installed with a workpiece positioning frame, one side of the workpiece positioning frame is fixedly installed with an electric push rod two, one side of the top of the support is fixedly installed with a feeding channel, the bottom of the support is fixedly installed with an electric push rod three, the output end of the electric push rod three is fixedly installed with a top plate sliding on the support, the top plate is located between the workpiece positioning frame and the feeding channel, one side of the top of the support is fixedly installed with a discharging channel, one side of the top of the support is placed with a receiving frame located below the discharging channel; a digital twin construction module for constructing a virtual model corresponding to the physical production line, the virtual model comprising at least a geometric model, a behavior model and a rule model, wherein the rule model is used to digitize quality system standards into executable audit rules; a data acquisition and communication module for receiving multi-source real-time data uploaded on the physical layer and mapping the data to the virtual model in the digital twin construction module; a dynamic audit engine as a core processing unit of the system, configured to: a) receive the mapped real-time data; b) invoke the audit rules in the rule model; c) perform real-time and continuous comparison analysis between the real-time data and the audit rules to dynamically evaluate the compliance of the quality system; d) generate audit warning information when the comparison result deviates; a user interaction module for visualizing the running state of the digital twin model, the quality system compliance evaluation result and the audit warning information.

[0005] The intelligent manufacturing quality system dynamic audit system for a digital twin as described above, the rule model converts the provisions in the quality system file into computer executable code containing conditional judgment logic, and the control objects involved in the provisions include one or more of personnel qualification, equipment parameter, process parameter, material information, environmental condition and product quality characteristic.

[0006] The intelligent manufacturing quality system dynamic audit system for a digital twin as described above, the dynamic audit engine further comprises a root cause analysis unit, configured to: when generating audit warning information, automatically associate and present the historical data records related to the warning information, the historical data records including device operation log, process parameter change record, material batch information and operator information.

[0007] The dynamic auditing engine further includes a predictive auditing unit configured to simulate the manufacturing process based on the digital twin model and analyze historical data trends using a machine learning algorithm to predict future quality system risks and generate a predictive early warning.

[0008] The user interaction module further includes an automatic report generation unit configured to automatically generate a quality system auditing report containing all auditing findings, evidence data and compliance statistical analysis within a time period according to user instructions or a preset period.

[0009] A dynamic auditing method for an intelligent manufacturing quality system based on digital twinning, the method comprising the following steps: Step S101: constructing a digital twin model corresponding to a physical production line and converting quality system standards into digital auditing rules integrated in the model; Step S102: collecting multi-source data in the production process in real time through a sensor network; Step S103: mapping the collected real-time data to the digital twin model to drive the model to run synchronously; Step S104: in the digital twin environment, real-time and automatic comparison of real-time data and digital auditing rules; Step S105: dynamically determining the real-time compliance status of the quality system according to the comparison result; Step S106: when the determination is not compliant, generating and issuing a warning information, and visualizing the management interface.

[0010] In step S104 of the dynamic auditing method for an intelligent manufacturing quality system based on digital twinning as described above, the comparison is continuously performed, thereby realizing 7x24 hour uninterrupted auditing of the quality system.

[0011] The dynamic auditing method for an intelligent manufacturing quality system based on digital twinning as described above further includes step S107 after step S106: in response to the warning information, automatically tracing and associating the relevant process data chain causing the warning to assist in root cause analysis.

[0012] In step S104 of the dynamic auditing method for an intelligent manufacturing quality system based on digital twinning as described above, process simulation is performed using the digital twin model, and prediction analysis is performed in combination with historical data trends, and the system risk is predicted in the digital twin before the non-compliant item occurs in the physical world and a predictive early warning is issued.

[0013] The present invention provides a dynamic audit method for a digital twin-based intelligent manufacturing quality system, further comprising step S108: automatically generating a structured audit report periodically or on demand, the report including a list of non-conformities, related evidence, compliance statistics, and trend analysis charts.

[0014] In summary, the beneficial effects of the present invention are as follows: 1. This invention achieves a leap from "periodic static auditing" to "continuous dynamic auditing," enabling the immediate detection of deviations in system operation, avoiding sampling risks and subjective human factors, resulting in more objective and comprehensive audit conclusions. It can predict quality risks, issue early warnings before problems occur, and realize the transformation from "post-event correction" to "pre-event prevention." Utilizing digital thread technology, it can quickly trace the root cause of problems, significantly shortening the time for problem analysis and decision-making, greatly reducing the workload of manual auditing, improving audit efficiency and accuracy, and lowering quality costs.

[0015] 2. This invention, through the setup of a workpiece positioning frame, electric push rod two, electric push rod three, a top plate, an infeed channel, and an outfeed channel, can achieve automatic feeding without manual intervention, improving feeding efficiency and accuracy, and reducing labor costs. During operation, the workpiece is placed into the infeed channel, and at the same time, electric push rod three is activated to lift the top plate upwards. At this time, the workpiece falling to the top of the top plate will roll into the workpiece positioning frame. It should be noted that the top of the top plate is provided with a slope. Then, electric push rod two is activated to push the workpiece to contact the inner wall of the workpiece positioning frame to adjust its position. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 A schematic diagram showing the layout of the three-dimensional structure of the machining center; Figure 3 This is a three-dimensional structural diagram of a CNC machine tool; Figure 4 This is a partial three-dimensional structural diagram of a CNC machine tool; Figure 5 A three-dimensional assembly diagram of the workpiece positioning frame; Figure 6 A three-dimensional structural diagram of the transfer robotic arm; Figure 7 This is a three-dimensional structural diagram of a machining center; Figure 8 This is a system block diagram of the present invention; Figure 9 This is a schematic diagram of the review process of the review system of the present invention; Figure 10 This is a flowchart illustrating the working process of the dynamic auditing engine.

[0018] In the diagram: 1. CNC machine tool, 2. Machining center, 3. Labeling and conveying center, 4. Labeling robotic arm, 5. Transfer robotic arm, 6. Guardrail, 101. CNC machine tool body, 102. Machine tool cover, 103. Electric push rod one, 104. Guide rail, 105. Drive device, 106. Grabbing robotic arm, 107. Mechanical claw, 108. Support, 109. Workpiece positioning frame, 110. Electric push rod two, 111. Electric push rod three, 112. Top plate, 113. Feed channel, 114. Discharge channel, 115. Receiving frame. Detailed Implementation

[0019] The following will refer to the appendices in the embodiments of the present invention. Figures 1-10 The technical solutions in the embodiments of the present invention are clearly and completely described herein. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention. Example

[0020] A digital twin-based intelligent manufacturing quality system dynamic audit system includes: a physical layer, which includes a production line, manufacturing equipment on the production line, and a sensor network deployed thereon, for collecting multi-source real-time data of the manufacturing process; The production line consists of a CNC machine tool 1, a machining center 2, and a labeling conveyor center 3, arranged sequentially. A labeling robotic arm 4 is slidably mounted above the labeling conveyor center 3. A transfer robotic arm 5 is arranged between the CNC machine tool 1, the machining center 2, and the labeling conveyor center 3. A transfer robotic arm 5 is located on the outer side of the transfer robotic arm 5. The CNC machine tool 1 includes a CNC machine tool body 101 placed on the ground. A machine tool cover 102 is provided on one side of the CNC machine tool body 101. A guide rail 104 is fixedly installed on one side of the CNC machine tool body 101. The machine tool cover 102 is slidably installed on the guide rail 104. An electric push rod 103 is fixedly installed at the bottom of the CNC machine tool body 101. The output end of the electric push rod 103 is fixedly installed on the guide rail 104. A drive device 105 is fixedly installed on one side of the top of the CNC machine tool body 101. A gripping robot arm 106 is slidably installed on the surface of the drive device 105. Two mechanical claws 107 are movably installed at the bottom end of the gripping robot arm 106. A bracket 108 is fixedly installed on one side of the CNC machine tool body 101. A workpiece positioning frame 109 is fixedly installed on the top of the bracket 108. An electric push rod 110 is fixedly installed on one side of the workpiece positioning frame 109. A feeding channel 113 is fixedly installed on one side of the top of the bracket 108. An electric push rod 111 is fixedly installed on the bottom of the bracket 108. A top plate 112 that slides on the bracket 108 is fixedly installed at the output end of the electric push rod 111. The top plate 112 is located between the workpiece positioning frame 109 and the feeding channel 113. A discharge channel 114 is fixedly installed on one side of the top of the bracket 108. A receiving frame 115 located below the discharge channel 114 is placed on one side of the top of the bracket 108. The specific usage process is as follows: The workpiece is placed on the labeling conveyor center 3 and conveyed forward through the labeling conveyor center 3. During operation, the labeling robot arm 4 moves back and forth on the labeling conveyor center 3 and labels the workpiece on the labeling conveyor center 3 before processing, so that it can be scanned and identified for subsequent work. Then, the transfer robot arm 5 transfers the transferred workpiece to the machining center 2 for processing. Then, the processed workpiece on the machining center 2 is taken out and placed into the CNC machine tool 1 for processing. The workpiece is placed into the feeding channel 113. At the same time, the electric push rod 111 is started to lift the top plate 112 upward. At this time, the workpiece falling on the top of the top plate 112 will roll into the workpiece positioning frame 109. It should be noted that the top of the top plate 112 is provided with a slope. Then, the electric push rod 110 is started to push the workpiece to contact the inner wall of the workpiece positioning frame 109 to adjust its position. The drive device 105 drives the gripping robot arm 106 to move. The robotic arm 106 moves to the bottom of the workpiece, and the robotic gripper 107 moves down. The corresponding robotic gripper 107 picks up the workpiece and sends it into the CNC machine tool body 101 for processing. After the robotic gripper 107 places the workpiece, it moves again to the top of the workpiece positioning frame 109 to pick up the workpiece. The corresponding robotic gripper 107 picks up the workpiece again and sends it into the CNC machine tool body 101. Before placing it, the robotic arm 106 drives the robotic gripper 107 to rotate 180 degrees, and the two robotic grippers 107 switch positions. The robotic gripper 107 picks up the processed workpiece, and then rotates 180 degrees again to put the unprocessed workpiece into the CNC machine tool body 101. Then it moves out of the CNC machine tool body 101, and the robotic gripper 107 puts the processed workpiece into the discharge channel 114. The workpiece rolls into the receiving frame 115 and is collected. The empty robotic gripper 107 picks up the workpiece again and sends it into the CNC machine tool body 101, and so on.

[0021] This invention represents a leap from "periodic static auditing" to "continuous dynamic auditing," enabling the immediate detection of deviations in system operation. It avoids sampling risks and subjective human factors, resulting in more objective and comprehensive audit conclusions. It can predict quality risks, issue early warnings before problems occur, and achieve a shift from "post-event correction" to "pre-event prevention." Utilizing digital thread technology, it can quickly trace the root cause of problems, significantly shortening the time for problem analysis and decision-making, greatly reducing the workload of manual auditing, improving audit efficiency and accuracy, and lowering quality costs.

[0022] A digital twin building module is used to construct a virtual model corresponding to a physical production line. The virtual model includes at least a geometric model, a behavioral model, and a rule model, wherein the rule model is used to digitize quality system standards into executable audit rules. The data acquisition and communication module is used to receive multi-source real-time data uploaded by the physical layer and map the data to the virtual model in the digital twin construction module. The dynamic auditing engine, as the core processing unit of the system, is configured as follows: a) Receive mapped real-time data; b) Invoke the audit rules in the rule model; c) The real-time data is compared and analyzed with the audit rules in real time and continuously to dynamically assess the compliance of the quality system; d) When the comparison results deviate, an audit warning message is generated; The user interaction module is used to visually display the operating status of the digital twin model, the results of the quality system compliance assessment, and audit warning information.

[0023] It should be noted that the construction of the digital twin model enables Unity Technologies' UnityIndustrial platform to build a digital twin model of the production line.

[0024] Geometric Model: Using CAD drawings of production line equipment, a 1:1 three-dimensional geometric model is created to accurately reproduce the appearance, layout, and movement relationships of the equipment.

[0025] Behavioral / Physical Model: Assign behavioral logic to key equipment. For example, define the kinematic relationship of a CNC lathe model so that its virtual spindle can rotate synchronously according to the received real-time speed data.

[0026] Rule Model: This is key to digitizing quality system standards. We use the built-in rule engine or integrate the open-source Drools rule engine to write system requirements as rules, such as (Equipment Maintenance Audit: Trigger warnings: 1. Tooling is out of service, violating preventive maintenance procedure WI-PM-001, 2. Tooling life exceeds limit; Process Parameter Compliance Audit: 1. Determine if the real-time spindle speed is within the allowable range specified in process card PC-2024, 2. Trigger warning: Process parameter deviation, violating control plan CP-005, 3. Abnormal spindle speed; First Article Inspection Audit: 1. When the first product of a new material batch arrives at the measurement station, 2. and there are non-conforming items in the measurement results, 3. However, production is not automatically paused or waiting for quality release instructions, 4. Trigger critical warning: Violation of non-conforming product control procedure QP-008, 5. First article inspection fails but production continues).

[0027] The rule model transforms the clauses in the quality system documents into computer-executable code containing conditional judgment logic. The control objects involved in the clauses include one or more of the following: personnel qualifications, equipment parameters, process parameters, material information, environmental conditions, and product quality characteristics.

[0028] The dynamic audit engine also includes a root cause analysis unit, which is configured to automatically associate and present historical data records related to the audit warning information when an audit warning is generated. The historical data records include equipment operation logs, process parameter change records, material batch information, and operator information.

[0029] The dynamic audit engine also includes a predictive audit unit, which is configured to: simulate the manufacturing process based on the digital twin model, and use machine learning algorithms to analyze historical data trends in order to predict future quality system risks and generate predictive warnings.

[0030] The workflow of the dynamic auditing engine: Data Mapping and Synchronization: After receiving real-time data, the system server drives the corresponding virtual entity in the digital twin model to update its state according to predefined mapping relationships. For example, the real-time spindle speed value is mapped to the spindle model of the virtual CNC lathe, causing it to rotate at the corresponding speed in the 3D view.

[0031] Real-time comparison and dynamic auditing: The rule engine continuously monitors data changes in the digital twin model. Once data (such as spindle speed value) triggers a rule condition (such as the speed value exceeding the allowable range), the rule engine immediately executes the "then" part of the rule, generating an audit finding. This finding includes evidence such as a description of the non-compliance, the triggered rule ID, timestamp, device ID, and real-time values.

[0032] Root Cause Analysis: When the rule "Tool Life Monitoring" triggers an alert, the system automatically executes the root cause analysis process. It queries the historical data chain related to that tool, including: The IDs and batches of all workpieces processed by this tool.

[0033] The historical processing parameters of these workpieces (whether there have been any abnormal fluctuations).

[0034] This includes the tool's historical replacement records and wear measurement data.

[0035] These related data are presented to the operator to help them determine whether the shortened lifespan is due to tool quality issues, abnormal material hardness, or improper process parameter settings.

[0036] Predictive auditing: The system periodically (e.g., weekly) performs machine learning analysis (e.g., using the time series prediction algorithm Prophet) on spindle vibration data. If the algorithm predicts that the vibration amplitude will tend to exceed the control limits within the next 72 hours, the predictive auditing unit will proactively generate a predictive warning, indicating that "the CNC_Lathe_01 spindle bearing has a potential failure risk, which may affect machining accuracy and lead to non-conformities," thereby reminding maintenance personnel to intervene in advance and achieving predictive maintenance and proactive control of system risks.

[0037] The user interaction module also includes an automatic report generation unit, which is configured to automatically generate a quality system audit report containing all audit findings, evidence data, and compliance statistical analysis within a time period, based on user instructions or a preset cycle.

[0038] It should be noted that users log in to the system via a web browser. The main interface displays a 3D visualization model of the entire production line, with equipment colors representing the health status of the system (green for compliance, yellow for warnings, and red for serious non-compliance). The right panel displays real-time compliance rates, warning type distribution, and ranking of top non-compliance items in chart form.

[0039] Warning Handling: When a warning is generated, a pop-up notification will appear on the interface, and a task work order will be generated and assigned to the relevant person in charge. The person in charge can click on the warning to view the details and the root cause analysis data provided by the system, and then process and record the corrective measures.

[0040] Automatic report generation: At the end of each month, the system's automatic report generation unit will perform the following operations: This summarizes all audit findings from the month (including both closed and open audits).

[0041] Calculate statistical indicators such as the overall monthly compliance rate and the compliance rate of each clause.

[0042] Generate trend charts, such as "Monthly Trend of Spindle Speed ​​Parameter Compliance Rate".

[0043] Fill all the content into a predefined Word / PDF report template to generate a complete "Monthly Quality System Dynamic Audit Report," which can be automatically sent to the quality manager. A dynamic auditing method for a digital twin-based intelligent manufacturing quality system, the method comprising the following steps: Step S101: Construct a digital twin model corresponding to the physical production line, and integrate the quality system standards into the model by converting them into digital audit rules; Step S102: Collect multi-source data in real time during the production process through a sensor network; Step S103: Map the collected real-time data to the digital twin model to drive the model to run synchronously; Step S104: In the digital twin environment, compare real-time data with digital audit rules in real time and automatically; Step S105: Based on the comparison results, dynamically determine the real-time compliance status of the quality system; Step S106: When a non-compliance is determined, generate and issue an early warning message, and visualize the management interface.

[0044] In step S104, the comparison is performed continuously, thereby achieving 24 / 7 uninterrupted auditing of the quality system.

[0045] Following step S106, step S107 is also included: in response to the warning information, automatically trace and associate the relevant process data chain that triggered the warning to assist in root cause analysis.

[0046] In step S104, the process simulation is performed using a digital twin model, and predictive analysis is conducted in conjunction with historical data trends. Before non-compliance occurs in the physical world, system risks are predicted in the digital twin and predictive warnings are issued.

[0047] The method further includes step S108: automatically generating structured audit reports periodically or on demand, the reports including a list of non-conformities, related evidence, compliance statistics, and trend analysis charts.

[0048] It should be noted that the functions to be implemented by each hardware component in this invention are supported by a large number of mature technologies and belong to the prior art. The essence of this invention is to optimize and combine existing hardware and its connection methods for specific application scenarios to meet the adaptation requirements of specific application scenarios and solve the problems raised in the background technology (without involving improvements to the internal software of the hardware).

[0049] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic auditing system for intelligent manufacturing quality system based on digital twins, characterized in that, include: The physical layer includes the production line, the manufacturing equipment on the production line, and the sensor network deployed thereon, for collecting multi-source real-time data of the manufacturing process; The production line consists of a CNC machine tool (1), a machining center (2), and a labeling conveyor center (3), arranged in sequence. A labeling robotic arm (4) is slidably installed above the labeling conveyor center (3). A transfer robotic arm (5) is arranged between the CNC machine tool (1), the machining center (2), and the labeling conveyor center (3). A transfer robotic arm (5) is set on the outside of the transfer robotic arm (5). The CNC machine tool (1) includes a CNC machine tool body (101) placed on the ground. A machine tool cover (102) is opened and closed on one side of the CNC machine tool body (101). A guide rail (104) is fixedly installed on one side of the CNC machine tool body (101). The machine tool cover (102) is slidably installed on the guide rail (104). An electric push rod (103) is fixedly installed at the bottom of the CNC machine tool body (101). The output end of the electric push rod (103) is fixedly installed on the guide rail (104). A drive device (105) is fixedly installed on one side of the top of the CNC machine tool body (101). A gripping robot arm (106) is slidably installed on the surface of the drive device (105). Two mechanical claws (107) are movably installed at the bottom end of the gripping robot arm (106). A bracket (108) is fixedly installed on one side of the main body (101) of the CNC machine tool. A workpiece positioning frame (109) is fixedly installed on the top of the bracket (108). An electric push rod (110) is fixedly installed on one side of the workpiece positioning frame (109). A feeding channel (113) is fixedly installed on one side of the top of the bracket (108). An electric push rod (111) is fixedly installed on the bottom of the bracket (108). A top plate (112) that slides on the bracket (108) is fixedly installed at the output end of the electric push rod (111). The top plate (112) is located between the workpiece positioning frame (109) and the feeding channel (113). A discharge channel (114) is fixedly installed on one side of the top of the bracket (108). A receiving frame (115) located below the discharge channel (114) is placed on one side of the top of the bracket (108). A digital twin building module is used to construct a virtual model corresponding to a physical production line. The virtual model includes at least a geometric model, a behavioral model, and a rule model, wherein the rule model is used to digitize quality system standards into executable audit rules. The data acquisition and communication module is used to receive multi-source real-time data uploaded by the physical layer and map the data to the virtual model in the digital twin construction module. The dynamic auditing engine, as the core processing unit of the system, is configured as follows: a) Receive mapped real-time data; b) Invoke the audit rules in the rule model; c) The real-time data is compared and analyzed with the audit rules in real time and continuously to dynamically assess the compliance of the quality system; d) When the comparison results deviate, an audit warning message is generated; The user interaction module is used to visually display the operating status of the digital twin model, the results of the quality system compliance assessment, and audit warning information.

2. The dynamic audit system for intelligent manufacturing quality system based on digital twins according to claim 1, characterized in that, The rule model transforms the clauses in the quality system documents into computer-executable code containing conditional judgment logic. The control objects involved in the clauses include one or more of the following: personnel qualifications, equipment parameters, process parameters, material information, environmental conditions, and product quality characteristics.

3. A dynamic audit system for intelligent manufacturing quality system based on digital twins according to claim 1 or 2, characterized in that, The dynamic audit engine also includes a root cause analysis unit, which is configured to automatically associate and present historical data records related to the audit warning information when an audit warning is generated. The historical data records include equipment operation logs, process parameter change records, material batch information, and operator information.

4. The dynamic audit system for intelligent manufacturing quality system based on digital twins according to claim 1, characterized in that, The dynamic audit engine also includes a predictive audit unit, which is configured to: simulate the manufacturing process based on the digital twin model, and use machine learning algorithms to analyze historical data trends in order to predict future quality system risks and generate predictive warnings.

5. The dynamic audit system for intelligent manufacturing quality system based on digital twins according to claim 1, characterized in that, The user interaction module also includes an automatic report generation unit, which is configured to automatically generate a quality system audit report containing all audit findings, evidence data, and compliance statistical analysis within a time period, based on user instructions or a preset cycle.

6. A dynamic auditing method for a digital twin-based intelligent manufacturing quality system, applied to a dynamic auditing system for a digital twin-based intelligent manufacturing quality system as described in any one of claims 1-5, characterized in that, The method includes the following steps: Step S101: Construct a digital twin model corresponding to the physical production line, and integrate the quality system standards into the model by converting them into digital audit rules; Step S102: Collect multi-source data in real time during the production process through a sensor network; Step S103: Map the collected real-time data to the digital twin model to drive the model to run synchronously; Step S104: In the digital twin environment, compare real-time data with digital audit rules in real time and automatically; Step S105: Based on the comparison results, dynamically determine the real-time compliance status of the quality system; Step S106: When a non-compliance is determined, generate and issue an early warning message, and visualize the management interface.

7. The method for dynamic auditing of a digital twin-based intelligent manufacturing quality system according to claim 6, characterized in that, In step S104, the comparison is performed continuously, thereby achieving 24 / 7 uninterrupted auditing of the quality system.

8. The method for dynamic auditing of a digital twin-based intelligent manufacturing quality system according to claim 6, characterized in that, Following step S106, step S107 is also included: in response to the warning information, automatically trace and associate the relevant process data chain that triggered the warning to assist in root cause analysis.

9. A dynamic auditing method for a digital twin-based intelligent manufacturing quality system according to claim 6, characterized in that, In step S104, the process simulation is performed using a digital twin model, and predictive analysis is conducted in conjunction with historical data trends. Before non-compliance occurs in the physical world, system risks are predicted in the digital twin and predictive warnings are issued.

10. A dynamic auditing method for a digital twin-based intelligent manufacturing quality system according to claim 6, characterized in that, The method further includes step S108: automatically generating structured audit reports periodically or on demand, the reports including a list of non-conformities, related evidence, compliance statistics, and trend analysis charts.

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