Terminal device and device fault diagnosis control method

Abstract

The application provides a terminal device and a device fault diagnosis control method, relates to the technical field of household appliance production quality analysis, and the terminal device stores a root cause database containing a mapping relationship of an equipment fault event and an FMEA database, an electronic control plan and an electronic work instruction book. The terminal device can generate a risk calculation model integrating multiple risk dimensions based on the root cause database. After collecting real-time state parameters, the risk value is determined based on two-stage calculation of temporary detection degree. When the risk value exceeds the threshold, a fault diagnosis strategy is generated and executed. Then, the control parameters of the FMEA database, the electronic control plan and the electronic work instruction book are updated according to the execution result and the mapping relationship. The temporary detection degree is effective for a single time without changing the basic detection degree value of the FMEA. The application can respond to the changes of the real-time running state of the equipment, realize accurate diagnosis of the manufacturing equipment fault, guarantee the consistency of the control tool, and improve the fault diagnosis efficiency and accuracy.

Description

Technical Field

[0001] This application relates to the field of home appliance production quality analysis technology, and in particular to a terminal device and a device fault diagnosis and control method. Background Technology

[0002] During the equipment production process, the diagnosis of equipment failures has become a core requirement for quality supervision. Root cause analysis, risk assessment, and the linkage of control tools are the key technical paths to achieve the above requirements, which can be widely applied to automated production lines in industries such as automobiles, home appliances, and electronics.

[0003] Fault diagnosis in equipment production relies on independent control tools and post-event feedback mechanisms. By pre-setting parameters such as potential faults and detectability through the Failure Mode and Effects Analysis (FMEA) database, and combining fixed thresholds in the electronic control plan with static operating procedures in the electronic work instructions, a preliminary risk prevention and control system can be constructed.

[0004] However, the above-mentioned fault diagnosis method, due to the interdependent logical loop between detectability and risk value, can only manually preset a static detectability parameter in the FMEA database to calculate the risk value, and cannot respond to changes in the real-time operating status of the equipment (such as sensor drift, cumulative running time exceeding the limit), thus affecting the accuracy of fault diagnosis. Furthermore, the FMEA database, electronic control plan and electronic work instructions operate independently. After the parameters of one tool are updated, other control tools will still use the old parameters, making it difficult to ensure logical consistency, resulting in reduced efficiency and accuracy of fault diagnosis. Summary of the Invention

[0005] This application provides a terminal device and a device fault diagnosis and control method to solve the problems of low efficiency and accuracy in fault diagnosis.

[0006] In a first aspect, this application provides a terminal device, including:

[0007] The memory is configured to store a root cause database, which includes equipment failure events and a mapping relationship between the equipment failure events and management tools. The management tools include a Failure Mode and Effects Analysis (FMEA) database, electronic control plans, and electronic work instructions. The FMEA database includes severity, occurrence, and basic detectability.

[0008] The controller, connected to the memory, is configured to:

[0009] A risk calculation model is generated based on the root cause database. The risk calculation model is used to integrate the state parameters of manufacturing equipment in different risk dimensions.

[0010] Collect real-time status parameters of the manufacturing equipment;

[0011] The real-time status parameters are input into the risk calculation model;

[0012] Based on the risk calculation model, the first risk value is calculated according to the basic detectability.

[0013] A temporary detection degree is determined based on the first risk value and the basic detection degree; the temporary detection degree is greater than or equal to the basic detection degree, the temporary detection degree is effective only once, and the temporary detection degree is not used to update the basic detection degree of the FMEA database;

[0014] Based on the risk calculation model, a second risk value is calculated according to the temporary detectivity.

[0015] If the second risk value is greater than or equal to the risk threshold, a fault diagnosis strategy is generated based on the risk level corresponding to the second risk value, and the fault diagnosis strategy is executed.

[0016] Based on the mapping relationship between the execution result of the fault diagnosis strategy and the root cause database, the control parameters of the management tool are updated.

[0017] The above technical solution has the following beneficial effects or advantages:

[0018] Terminal equipment can resolve the cyclical dependency problem between detectability and risk value, accurately obtaining the instantaneous degradation of equipment detection capabilities through two-stage risk calculation; temporary detectability takes effect only once and does not change the basic data of FMEA, ensuring the standardization and traceability of the FMEA database; it can realize the collaborative updates of various control tools, breaking down the silos between control tools, improving the accuracy and efficiency of fault diagnosis, and promoting the transformation of fault diagnosis from post-event interception to pre-event prevention, thereby reducing the failure rate.

[0019] In some embodiments of this application, the controller is specifically configured to determine a temporary detection rate based on the first risk value and the basic detection rate as follows:

[0020] Read the trigger threshold of the temporary probeness;

[0021] If the first risk value is greater than or equal to the trigger threshold, the sum of the basic detectivity and the preset adjustment value is set as the temporary detectivity;

[0022] If the first risk value is less than the trigger threshold, the basic detectivity is set to the temporary detectivity.

[0023] The above technical solution has the following beneficial effects or advantages:

[0024] Terminal devices can dynamically adjust the detectivity based on trigger thresholds; when the risk reaches a critical value, the detectivity is increased to quantify the instantaneous deterioration, and when the critical value is not reached, the basic detectivity is used to ensure the stability of risk assessment, thus avoiding excessive intervention and ensuring that no risk is missed.

[0025] In some embodiments of this application, the risk dimension includes the physical state associated with the manufacturing equipment, environmental disturbances, FMEA dynamic weights, and state drift trends. The controller executes a risk calculation model generated based on the root cause database, specifically configured as follows:

[0026] Based on the historical fault root cause nodes corresponding to the manufacturing equipment in the root cause database, at least one of the cumulative number of detections, the runtime after the previous calibration, and the real-time torque fluctuation rate is read to obtain the first set of state parameters of the body state.

[0027] Read at least one of the following: workshop temperature, humidity, and supplier quality score associated with material batches, to obtain the second set of state parameters for the environmental disturbance;

[0028] The severity, occurrence, and basic detectability of the FMEA database are read, and a basic risk priority number is calculated based on the severity, occurrence, and basic detectability to obtain the third set of state parameters for the FMEA dynamic weights.

[0029] The slope of the sliding window for the torque value and the sigma level of the control chart in the statistical process are read, and the degradation rate is calculated based on the slope of the sliding window for the torque value and the sigma level of the control chart to obtain the fourth set of state parameters for the state drift trend.

[0030] The risk calculation model is constructed based on the first set of state parameters, the second set of state parameters, the third set of state parameters, and the fourth set of state parameters.

[0031] The above technical solution has the following beneficial effects or advantages:

[0032] Terminal devices can filter parameters based on four risk dimensions: the device itself, the external environment, FMEA dynamic data, and state drift trends. The parameter filtering process is based on historical fault root causes to ensure a causal relationship with the fault and to cover the multi-dimensional impact of the fault.

[0033] In some embodiments of this application, the controller performs the calculation of a first risk value based on the basic detectivity, specifically configured as follows:

[0034] Read the weighting coefficients, which include a first coefficient, a second coefficient, a third coefficient, and a fourth coefficient, and the sum of the first coefficient, the second coefficient, the third coefficient, and the fourth coefficient is 1;

[0035] Calculate the first product of the first coefficient and the normalized value corresponding to the first state parameter set;

[0036] Calculate the second product of the second coefficient and the normalized value corresponding to the second state parameter set;

[0037] Calculate the third product of the third coefficient and the normalized value corresponding to the third state parameter set;

[0038] Calculate the fourth product of the fourth coefficient and the normalized value corresponding to the fourth state parameter set;

[0039] The sum of the first product, the second product, the third product, and the fourth product is determined as the first risk value.

[0040] The above technical solution has the following beneficial effects or advantages:

[0041] The terminal device uses a weighted fusion algorithm to achieve quantitative fusion of multi-dimensional parameters. The weight coefficients satisfy the constraint that the sum is 1 to ensure the accuracy of the calculation. Normalization is used to eliminate the differences between different parameters to ensure the accuracy of the first risk value calculation.

[0042] In some embodiments of this application, the controller is configured to perform the calculation of a second risk value based on the temporary detectivity, as follows:

[0043] Read the severity and occurrence from the FMEA database;

[0044] Calculate a dynamic risk priority number based on the severity, the occurrence, and the provisional detection rate;

[0045] Calculate the fifth product of the third coefficient and the normalized value corresponding to the dynamic risk priority number;

[0046] The sum of the first product, the second product, the fourth product, and the fifth product is determined as the second risk value.

[0047] The above technical solution has the following beneficial effects or advantages:

[0048] Based on the initial risk value calculation, the terminal equipment incorporates a dynamic risk priority number corresponding to the temporary detectability to achieve a secondary risk value calculation. The secondary calculated risk value can reflect the comprehensive risk level of the equipment's instantaneous operating status and detection capability, thereby improving the accuracy of fault diagnosis.

[0049] In some embodiments of this application, the controller executes a fault diagnosis strategy based on the risk level corresponding to the second risk value, specifically configured as follows:

[0050] Read the risk level threshold, which includes a first level threshold and a second level threshold, wherein the first level threshold is less than the second level threshold;

[0051] If the second risk value is less than the first level threshold, a first fault diagnosis strategy is generated based on the FMEA database. The first fault diagnosis strategy is used to instruct the maintenance of the current operation of the manufacturing equipment.

[0052] If the second risk value is greater than or equal to the first level threshold and the second risk value is less than the second level threshold, a second fault diagnosis strategy is generated according to the FMEA database. The second fault diagnosis strategy is used to prompt the corresponding operation steps in the electronic work instruction, generate preventive maintenance work orders, and increase the sampling inspection ratio of the manufacturing equipment.

[0053] If the second risk value is greater than or equal to the second level threshold, a third fault diagnosis strategy is generated based on the FMEA database. The third fault diagnosis strategy is used to instruct the disconnection of the output signal of the manufacturing equipment, display the fault tree analysis guidance of the FMEA database, and send a re-inspection instruction.

[0054] The above technical solution has the following beneficial effects or advantages:

[0055] The terminal device implements corresponding fault diagnosis strategies based on risk levels to intervene and handle equipment failure events; the fault diagnosis strategies are bound to management tools to ensure the compliance and accuracy of the fault diagnosis strategies.

[0056] In some embodiments of this application, the controller performs the update of control parameters for the management tool, specifically configured as follows:

[0057] The target root cause node of the fault is determined based on the execution results;

[0058] Based on the mapping relationship between the root cause database and the FMEA database, query the failure mode items in the FMEA database that have a mapping relationship with the target failure root cause node to obtain the target item;

[0059] Update the target project based on the execution result;

[0060] Update the FMEA database according to the updated target project;

[0061] Specifically, the controller is configured to update the target project based on the execution result.

[0062] If the execution result indicates an improving trend in the pass rate of the quality indicator, the occurrence rate of the target item will be lowered.

[0063] If the number of times the temporary detection rate is triggered within the preset period is greater than or equal to the frequency threshold, the base detection rate of the target project is increased.

[0064] If the execution result indicates a downward trend in the pass rate of the quality indicator, the severity of the target project is increased.

[0065] The above technical solution has the following beneficial effects or advantages:

[0066] Terminal devices can adjust severity, occurrence, and basic detection based on the actual effects of the execution results, transforming the FMEA database from a static document into a dynamically updated risk benchmark, thereby improving the fault diagnosis capabilities of the FMEA database.

[0067] In some embodiments of this application, the controller is configured to update the control parameters of the management tool as follows:

[0068] Based on the mapping relationship between the root cause database and the electronic control plan, the control items in the electronic control plan that have a mapping relationship with the target fault root cause node are queried to obtain the target control items; the target control items include the equipment calibration cycle, parameter control limits and triggering conditions of the reaction plan of the manufacturing equipment.

[0069] Update the target control item based on the execution result;

[0070] The electronic control plan is updated according to the updated target control items;

[0071] Specifically, the controller is configured to update the target control item based on the execution result.

[0072] If the execution result indicates a decreasing trend in the failure rate, the calibration cycle should be shortened.

[0073] If the correlation between the execution result characterizing the parameter control limit and the failure rate is greater than the correlation threshold, then the parameter control limit should be reduced.

[0074] If the execution result indicates that the response time of the reaction plan is greater than a time threshold, the triggering condition of the reaction plan is updated.

[0075] The above technical solution has the following beneficial effects or advantages:

[0076] Terminal equipment can update the calibration cycle, parameter control limits, and reaction plan triggering conditions based on the actual effect of the execution results, transforming the electronic control plan from a static document into a dynamically updated risk benchmark, thereby improving the fault diagnosis capability of the electronic control plan.

[0077] In some embodiments of this application, the controller is configured to update the control parameters of the management tool as follows:

[0078] Based on the mapping relationship between the root cause database and the electronic work instruction, query the operation steps in the electronic work instruction that have a mapping relationship with the target fault root cause node to obtain the target steps;

[0079] Update the target step based on the execution result;

[0080] Update the electronic work instructions according to the updated target steps;

[0081] Specifically, the controller is configured to perform the step of updating the target based on the execution result as follows:

[0082] If the execution result indicates that the failure blocking rate of the target step is greater than the first blocking rate threshold, a flashing prompt, an operation video link, or an additional verification item is written into the target step.

[0083] If the execution result indicates that the failure blocking rate of the target step is less than the second blocking rate threshold, the prompt information of the target step is removed; the second blocking rate threshold is less than the first blocking rate threshold.

[0084] The above technical solution has the following beneficial effects or advantages:

[0085] Terminal devices can update operation steps based on the actual effects of execution results, transforming electronic work instructions from static documents into dynamically updated risk benchmarks, thereby improving the fault diagnosis capabilities of electronic work instructions.

[0086] Secondly, this application also provides a method for equipment fault diagnosis and control, comprising:

[0087] A risk calculation model is generated based on a root cause database. The root cause database includes equipment failure events and the mapping relationship between the equipment failure events and management tools. The management tools include a Failure Mode and Effects Analysis (FMEA) database, electronic control plans, and electronic work instructions. The FMEA database includes severity, occurrence, and basic detectability. The risk calculation model is used to integrate the state parameters of manufacturing equipment in different risk dimensions.

[0088] Collect real-time status parameters of the manufacturing equipment;

[0089] The real-time status parameters are input into the risk calculation model;

[0090] Based on the risk calculation model, the first risk value is calculated according to the basic detectability.

[0091] A temporary detection degree is determined based on the first risk value and the basic detection degree; the temporary detection degree is greater than or equal to the basic detection degree, the temporary detection degree is effective only once, and the temporary detection degree is not used to update the basic detection degree of the FMEA database;

[0092] Based on the risk calculation model, a second risk value is calculated according to the temporary detectivity.

[0093] If the second risk value is greater than or equal to the risk threshold, a fault diagnosis strategy is generated based on the risk level corresponding to the second risk value, and the fault diagnosis strategy is executed.

[0094] Based on the mapping relationship between the execution result of the fault diagnosis strategy and the root cause database, the control parameters of the management tool are updated.

[0095] As can be seen from the above technical solutions, the terminal device and equipment fault diagnosis and control method provided in this application embodiment relate to the field of root cause analysis technology. The terminal device stores a root cause database containing mapping relationships between equipment fault events and FMEA database, electronic control plan, and electronic work instructions. The terminal device can generate a risk calculation model integrating multiple risk dimensions based on the root cause database. After collecting real-time status parameters, it calculates and determines the risk value based on a two-stage calculation of temporary detectivity. When the risk value exceeds a threshold, a fault diagnosis strategy is generated and executed. Then, the control parameters of FMEA database, electronic control plan, and electronic work instructions are updated according to the execution result and mapping relationship. The temporary detectivity does not change the basic detectivity value of FMEA when it is activated only once. This application can respond to changes in the real-time operating status of equipment, achieve accurate diagnosis of manufacturing equipment faults, ensure the consistency of control tools, and improve the efficiency and accuracy of fault diagnosis. Attached Figure Description

[0096] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0097] Figure 1 This application provides schematic diagrams of the architecture of terminal devices for some embodiments.

[0098] Figure 2 A schematic diagram illustrating the construction process of the root cause database provided for some embodiments of this application;

[0099] Figure 3 A flowchart illustrating a device fault diagnosis and control method provided in some embodiments of this application;

[0100] Figure 4A flowchart illustrating the determination of temporary detectivity provided for some embodiments of this application;

[0101] Figure 5 A flowchart illustrating the process of updating the FMEA database provided for some embodiments of this application;

[0102] Figure 6 A flowchart illustrating the updated electronic control plan provided for some embodiments of this application;

[0103] Figure 7 A flowchart illustrating the process of updating electronic work instructions provided in some embodiments of this application;

[0104] Figure 8 Display diagrams illustrating the target steps provided in some embodiments of this application;

[0105] Figure 9 The diagram shows the updated interactive features of the electronic work instructions provided in some embodiments of this application. Detailed Implementation

[0106] The embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described below do not represent all embodiments consistent with this application. They are merely examples of systems and methods consistent with some aspects of this application as detailed in the claims.

[0107] In this application embodiment, manufacturing equipment generally refers to equipment in intelligent manufacturing scenarios that has production, processing, testing, and verification functions, and that needs to ensure product quality through risk assessment and fault diagnosis. For example, manufacturing equipment includes, but is not limited to, helium mass spectrometer leak detectors, chip mounters, precision machine tools, online testing terminals, welding robots, painting equipment, automated assembly station equipment, airtightness testing equipment, and electronic devices such as automobiles, televisions, and projectors.

[0108] The term "terminal equipment" broadly refers to control devices used in intelligent manufacturing scenarios for risk assessment, fault diagnosis, and quality control tool linkage optimization of manufacturing equipment. Examples of terminal equipment include, but are not limited to, manufacturing equipment quality feedforward controllers, production line quality monitoring terminals, equipment fault diagnosis control units, quality system tool linkage control devices, intelligent manufacturing quality control gateways, and intelligent display devices.

[0109] In related technologies, fault diagnosis is achieved through quality supervision of manufacturing equipment, and the methods include root cause analysis, risk assessment, and the linkage of control tools. These control tools include an FMEA database, electronic control plans, and electronic standard operating procedures (eSOPs). The FMEA database presets failure modes and their corresponding severity (S), occurrence (O), and detection (D); the electronic control plan fixes calibration cycles, parameter limits, and other fixed thresholds; and the electronic operating procedure provides standardized static operating steps. All three operate independently.

[0110] However, the FMEA database, electronic control plan, and electronic work instructions are all static documents, disconnected from the operational status of manufacturing equipment, leading to a decrease in the timeliness and accuracy of fault diagnosis. The FMEA database requires calculating a risk value based on detectability (D), which characterizes the ability of current measures to detect faults. A higher risk value results in a lower detectability, and D should be increased accordingly; conversely, a lower risk value should result in a lower D. This creates a logical loop of interdependence between risk value and detectability. However, the risk value in the FMEA database needs to be calculated based on D first. Therefore, engineers can only set a static value in the FMEA database based on experience to calculate the risk value, making it impossible to adjust D in advance based on the risk value. This ignores the impact of real-time equipment operating status on detectability, resulting in decreased accuracy in fault diagnosis.

[0111] Furthermore, since the FMEA database, electronic control plan, and electronic work instructions are independently operating management tools, when the parameters of one management tool are updated, the other management tools will still use the old parameters. Due to the complexity of the parameters between different management tools, manually modifying the FMEA database, electronic control plan, and electronic work instructions one by one is highly complex and makes it difficult to ensure logical consistency, affecting the efficiency and accuracy of fault diagnosis.

[0112] To address the aforementioned issues, this application provides a terminal device that, by constructing a root cause database containing a mapping relationship between equipment failure events and management tools, a calculation model integrating multi-dimensional risks, and a two-stage risk assessment mechanism, can respond to changes in the real-time operating status of equipment and achieve synchronous updates of different management tools, thereby improving the accuracy and efficiency of fault diagnosis.

[0113] like Figure 1 As shown, in some embodiments, the terminal device 100 may include a memory 110 and a controller 120, with the memory 110 and the controller 120 connected together.

[0114] In some embodiments, the controller 120 may include at least one of a central processing unit, a video processor, an audio processor, a graphics processor, and a power processor, and a first to an nth interface for input / output. The controller 120 controls the operation of the terminal device 100 through various software control programs stored in the memory 110.

[0115] In some embodiments, the memory 110 is configured to store a root cause database. The root cause database includes equipment failure events and a mapping between these events and management tools. The management tools include an FMEA database, electronic control plans, and electronic work instructions. The FMEA database contains severity, occurrence, and basic detectability.

[0116] Among them, the basic detectability is a static baseline parameter preset for a specific failure mode in the FMEA database. The value can be 1-10 (1 means the strongest detection capability and 10 means no detection at all), which is used to characterize the detection capability of potential faults.

[0117] like Figure 2 As shown, in some embodiments, the root cause database stored in memory 110 is constructed by terminal device 100 through controller 120. The controller 120 of terminal device 100 constructs the root cause database, specifically including the following steps:

[0118] S201. Collect raw data.

[0119] Raw data can include data from different systems, such as final inspection systems, after-sales quality systems, equipment operation and maintenance systems, and Manufacturing Execution Systems (MES).

[0120] S202. Perform structured processing on the raw data to obtain equipment fault events.

[0121] Terminal device 100 can extract some data from the collected raw data according to preset structured extraction rules to form structured data, which can be used as equipment failure events (or root cause analysis cases).

[0122] In some implementations, the terminal device 100 can perform structured processing on the raw data through different dimensions, such as quality defects, process traceability, determination of root cause nodes (a), identification of defense nodes (k), and contextual information, to obtain structured and attribute-associatable equipment failure events.

[0123] S203. Establish a mapping relationship between equipment failure events and management tools.

[0124] After the terminal device 100 identifies the aforementioned equipment failure events, it establishes a mapping relationship between the equipment failure events and the FMEA database, electronic control plan, and electronic work instructions.

[0125] In some implementations, the terminal device 100 associates the description of the device failure event's 'a' node with the FMEA failure mode item (or described as a failure mode entry) through keyword semantic matching (such as word segmentation and synonym expansion) to establish a mapping relationship between the device failure event and the FMEA. Simultaneously, if a new failure mode is added, the S, O, and D values ​​of the FMEA failure mode item are also initialized.

[0126] In some implementations, the terminal device 100 associates the k-node description of the device failure event with target fields of the electronic control plan, such as the "control method" or "response plan" fields, to establish a mapping relationship between the device failure event and the electronic control plan.

[0127] In some implementations, the terminal device 100 associates the a-node description of a device failure event with the target steps of the eSOP, such as device operation steps or device maintenance steps, to establish a mapping relationship between the device failure event and the eSOP.

[0128] In some implementations, the terminal device can also mark the target steps of the eSOP as high-risk operation points.

[0129] S204. Store the equipment failure events and mapping relationships in the memory.

[0130] After the controller 120 of the terminal device 100 completes the construction of the above mapping relationship, it stores the determined device fault events and mapping relationships in the memory 110 for subsequent call processing.

[0131] For example, the mapping relationship between equipment failure events and control tools can include: the event identifier of the equipment failure event, the quality defect, the root cause node (a) of the equipment failure event, the defense line node (k) of the equipment failure event, the mapping relationship between the equipment failure event and the electronic control plan, the mapping relationship between the equipment failure event and FMEA, the mapping relationship between the equipment failure event and eSOP, and contextual information. For example, equipment failure event KA-AC2026-20260801-001: AC-2026 model air conditioner was found to have refrigerant leakage (severity level 4) at the commercial inspection station. Tracing back to the airtightness testing station, the root cause a was determined to be sensor sensitivity drift of the LeakTester-07 equipment, and the failure defense line k was the lack of calibration cycle monitoring; the associated FMEA failure mode item FMEA-AC2026-087 (initial RPN=96), control item CP-AC2026-LeakTest-01, and the eSOP step eSOP-LeakTest-Calib-Step3.

[0132] In some embodiments, in the event of a new device failure event, the controller 120 of the terminal device 100 automatically triggers the execution of the above steps S201-S204 and stores the newly updated device failure event and mapping relationship in the memory 110.

[0133] For ease of distinction and description, in this embodiment of the application, the D of the FMEA database stored in memory 110 is represented as the basic probe degree.

[0134] like Figure 3 As shown, in some embodiments, the controller 120 is configured to perform the following program steps:

[0135] S301. Generate a risk calculation model based on the root cause database.

[0136] Terminal device 100 can generate a risk calculation model corresponding to the manufacturing equipment based on the root cause database stored in memory 110. The risk calculation model is used to integrate the state parameters of the manufacturing equipment in different risk dimensions.

[0137] In some embodiments, risk dimensions include the physical state of the manufacturing equipment, environmental disturbances, FMEA dynamic weights, and state drift trends.

[0138] In some implementations, the terminal device 100 can automatically identify the risk dimension and obtain the status parameters corresponding to the risk dimension based on the a node corresponding to the equipment type of the current manufacturing equipment in the root cause database.

[0139] For example, regarding the dimension of ontological state: obtain the device operation counters or sensor readings directly related to node a. Regarding the dimension of environmental disturbances: based on the Internet of Things (IoT) or Enterprise Resource Planning (ERP) systems, obtain the external factors affecting the stability of manufacturing equipment. Regarding the dimension of FMEA dynamic weights: obtain the current S, O, and D values ​​of associated FMEA items and calculate the Dynamic Risk Priority Number (RPN). Regarding the dimension of state drift trends: calculate the degradation rate based on the time series of historical sensor data.

[0140] In some embodiments, the state parameters of the ontological state are determined as a first set of state parameters, the state parameters of the environmental disturbance are determined as a second set of state parameters, the state parameters of the FMEA dynamic weights are determined as a third set of state parameters, and the set of parameters of the state drift trend is determined as a fourth set of state parameters.

[0141] In some embodiments, when the terminal device 100 generates a risk calculation model based on the root cause database, it can obtain a first set of state parameters for the physical state by reading at least one of the following: the cumulative number of tests, the runtime after the previous calibration, and the real-time torque fluctuation rate, based on the historical fault root cause nodes corresponding to the manufacturing equipment in the root cause database. It can also obtain a second set of state parameters for environmental disturbances by reading at least one of the following: workshop temperature, humidity, and supplier quality scores associated with material batches.

[0142] The severity, occurrence, and basic detectability of the FMEA database are read, and a basic risk priority number is calculated based on these values ​​to obtain the third set of state parameters for FMEA dynamic weights. The sliding window slope of the torque value and the sigma level of the control chart in the statistical process are read, and the degradation rate is calculated based on these values ​​to obtain the fourth set of state parameter parameters for state drift trends. Based on the first, second, third, and fourth state parameter sets, a risk calculation model is constructed to integrate state parameters from different risk dimensions.

[0143] In some implementations, the severity (S) can be 1-10, the occurrence (O) can be 1-10, the detection (D) can be 1-10, and the dynamic RPN can be the product of S, O, and D.

[0144] S302. Collect real-time status parameters of manufacturing equipment.

[0145] After the terminal device 100 generates the risk calculation model, it also collects the real-time status parameters of the manufacturing equipment, enabling timely acquisition of the actual operating status of the manufacturing equipment. Among them, the real-time status parameters are the status parameters of the manufacturing equipment based on different risk dimensions during actual operation, such as the status of the equipment itself, environmental disturbances, FMEA dynamic weights, and status drift trend dimensions.

[0146] In some embodiments, when the terminal device 100 collects real-time status parameters of the manufacturing equipment, it also performs lightweight edge preprocessing on the collected real-time status parameters, including but not limited to noise suppression, missing data processing, range verification, and unit normalization.

[0147] For example, noise suppression: a sliding window mid-range filter (window size = 5) is used for sensor time-series data to effectively remove transient interference; missing data handling: a single missing data is handled by "keeping the previous valid value"; if there are more than 3 consecutive missing data, "data source abnormal" is marked and the equipment self-test is triggered; range verification: whether the parameters are within the reasonable range of the process (such as temperature 0℃~50℃), data exceeding the limit is marked as invalid and an anomaly log is recorded.

[0148] S303. Input the real-time status parameters into the risk calculation model.

[0149] After the terminal device 100 collects the real-time status parameters of the manufacturing equipment, it inputs the real-time status parameters into the risk calculation model, so that the risk calculation model can perform fault diagnosis on the manufacturing equipment based on the real-time status parameters.

[0150] In some embodiments, the terminal device 100 calculates the risk value R based on a risk calculation model using a weighted fusion method as shown in the following formula: R = α × f 设备 +β×f 环境 +γ×RPN 归一化 +δ×Trend 归一化 Where α, β, γ, and δ are weighting coefficients, and the sum of α, β, γ, and δ is 1, f 设备 f is the normalized value of the first set of state parameters. 环境 RPN is the normalized value of the second state parameter set. 归一化 For the normalized values ​​of the third state parameter set, Trend 归一化 This is the normalized value of the fourth state parameter set.

[0151] In some implementations, terminal device 100 calculates f 设备 At that time, calculate X for each state parameter (device parameter) in the first state parameter set. i Relative consumption: f 设备i = , where X imax To set thresholds for the control plan, and then adjust the settings based on the weights of the equipment parameters. f 设备i Perform a weighted average to obtain f 设备 .

[0152] In some implementations... f 设备 The normalized value is obtained by... f 设备 Linearly map to the interval [0, 1].

[0153] In some implementations, terminal device 100 calculates f 环境 At that time, based on each state parameter (environmental parameter) E in the second state parameter set... j The disturbance coefficients are determined from a preset disturbance coefficient table, and then a weighted average is taken of the product of the disturbance coefficients and the environmental parameters to obtain the result. f 环境 The perturbation coefficient is compressed to the [0, 1] interval by the Sigmoid function.

[0154] In some implementations, terminal device 100 calculates RPN. 归一化 At that time, based on the third state parameter set, the RPN value of the associated FMEA project is read, and the RPN value is linearly normalized. For example, the RPN is obtained by calculating the ratio of the RPN value to a preset value. 归一化 .

[0155] In some implementations, terminal device 100 calculates the trend. 归一化 At that time, the state parameters of the fourth state parameter set are calculated, the linear regression slope of the nearest N points is obtained, and then the degradation rate score is converted based on the linear regression slope. Finally, the trend is obtained by exponential decay normalization. 归一化 .

[0156] S304. Based on the risk calculation model, calculate the first risk value according to the basic detectability.

[0157] After the terminal device 100 inputs the real-time status parameters into the risk calculation model, it assesses the risk of the current manufacturing equipment based on the risk calculation model and the basic detectivity recorded in the FMEA database, that is, it calculates the first risk value.

[0158] The basic detectability can be used to calculate the first risk value because the first risk value needs to reflect the basic risk level of the equipment when there is no instantaneous degradation. As a fixed static parameter, the basic detectability can provide a stable benchmark for the initial risk assessment and avoid calculation distortion caused by dynamic fluctuations in detectability.

[0159] Similarly to the above embodiments, in some embodiments, when the terminal device 100 calculates the first risk value according to the basic detectivity, it reads the weight coefficients. The weight coefficients include a first coefficient, a second coefficient, a third coefficient, and a fourth coefficient. The sum of the first coefficient, the second coefficient, the third coefficient, and the fourth coefficient is 1. For example, if the first coefficient is α, the second coefficient is β, the third coefficient is γ, and the fourth coefficient is δ, the sum of α, β, γ, and δ is 1.

[0160] The controller 120 calculates the first product of the first coefficient and the normalized value corresponding to the first state parameter set, the second product of the second coefficient and the normalized value corresponding to the second state parameter set, the third product of the third coefficient and the normalized value corresponding to the third state parameter set, and the fourth product of the fourth coefficient and the normalized value corresponding to the fourth state parameter set. The sum of the first, second, third, and fourth products is then determined as the first risk value.

[0161] For example, the first risk value R1 can be calculated using the following formula: R1 = α × f 设备 +β×f 环境 +γ×(S×O×D 基础 ) 归一化+δ×Trend 归一化 D 基础 This refers to the detectivity recorded in FMEA.

[0162] In other words, the calculation of the first risk value can be represented as the first determination stage of the risk value. The first determination stage is used to determine how to dynamically adjust the detectivity in combination with the current state of the manufacturing equipment, thereby realizing the setting of dynamic detectivity.

[0163] S305. Determine the temporary detectivity based on the first risk value and the basic detectivity.

[0164] After the terminal device 100 calculates the first risk value, it calculates the temporary detection value based on the first risk value and the basic detection value. The temporary detection value is greater than or equal to the basic detection value. The temporary detection value is effective only once and is not used to update the basic detection value in the FMEA database.

[0165] Temporary detectability is used to calculate the risk value of the current state of the manufacturing equipment, i.e., the second risk value. Therefore, temporary detectability reflects the instantaneous degradation of the manufacturing equipment's current detection capability. Temporary detectability is a one-time event and does not modify the base detectability stored in the FMEA database. This ensures the standardization and data traceability of the FMEA database while preventing subsequent calculations from deviating from the true risk level and causing over-intervention due to changes in the detectability caused by a single instantaneous fluctuation in the manufacturing equipment's state.

[0166] like Figure 4 As shown, in some embodiments, when terminal device 100 determines temporary detectivity based on a first risk value and a base detectivity, controller 120 is configured to perform the following steps:

[0167] S401, Read the trigger threshold of temporary probe.

[0168] The terminal device 100 reads the trigger threshold of the temporary detectivity, where the trigger threshold serves as a critical threshold for triggering an increase in the temporary detectivity. This threshold can be a preset threshold or one dynamically calculated by the terminal device; this application does not impose any restrictions on this. For example, the trigger threshold can be 0.8.

[0169] S402. If the first risk value is greater than or equal to the trigger threshold, set the sum of the basic detectivity and the preset adjustment value as the temporary detectivity.

[0170] Terminal device 100 compares the first risk value with the trigger threshold. If the first risk value is greater than or equal to the trigger threshold, it indicates that the current risk level of the manufacturing equipment has reached a critical point. This means that the basic risk level of the manufacturing equipment, after considering its physical state, environmental disturbances, FMEA dynamic weights, and state drift trends, has reached a critical point. In this case, terminal device 100 needs to increase the detectivity, using the increased basic detectivity as a new temporary detectivity to quantify the instantaneous degradation of the manufacturing equipment's detection capability and provide accurate data support for the calculation of the second risk value. When increasing the detectivity, terminal device 100 uses the sum of the basic detectivity and the preset adjustment value as the temporary detectivity.

[0171] The aforementioned trigger threshold setting provides a critical standard for risk grading assessment, reducing ineffective adjustments and updates to detectability. If the first risk value is greater than or equal to the trigger threshold, it indicates that the basic risk level of the manufacturing equipment, after integrating its physical state, environmental disturbances, FMEA dynamic weights, and state drift trends, has reached a critical point. At this time, the equipment's detection capability may decrease due to instantaneous degradation. The terminal device 100 superimposes the basic detectability with a preset adjustment value as a temporary detectability. This achieves basic risk screening through the first risk value, providing dynamically adapted detectability for the calculation of the second risk value. In some embodiments, the superposition value of the basic detectability and the preset adjustment value is less than the maximum value of the detectability to ensure the feasibility of risk value calculation.

[0172] For example, the preset adjustment value is 1, the trigger threshold is 0.8, the first risk value is R1, and the maximum detectability is 10. When R1 ≥ 0.8, the terminal device 100 will temporarily set the detectability D. 临时 Set to D 临时 =min(D 基础 +1, 10).

[0173] S403. If the first risk value is less than the trigger threshold, set the basic detection rate to the temporary detection rate.

[0174] If the first risk value is less than the trigger threshold, it means that the current risk level of the manufacturing equipment has not reached the critical point, and there is no need to increase the detection rate. In this case, the value of the basic detection rate can be set as the temporary detection rate.

[0175] For example, the preset adjustment value is 1, the trigger threshold is 0.8, the first risk value is R1, and the maximum detectability is 10. When R1 < 0.8, the terminal device 100 will temporarily set the detectability D. 临时 Set to D 基础 .

[0176] S306. Based on the risk calculation model, calculate the second risk value according to the temporary detectability.

[0177] After the terminal device 100 determines the temporary detectivity, it calculates the second risk value based on the temporary detectivity, using the same logic as the calculation of the first risk value.

[0178] In some embodiments, when the terminal device 100 calculates the second risk value based on the temporary detectability, the controller 120 reads the severity (S) and occurrence (O) from the FMEA database, then calculates the dynamic risk priority number based on the severity, occurrence, and temporary detectability, and calculates the fifth product of the third coefficient and the normalized value corresponding to the dynamic risk priority number. The sum of the first product, the second product, the fourth product, and the fifth product is determined as the second risk value.

[0179] For example, the second risk value R2 can be calculated using the following formula: R2 = α × f 设备 +β×f 环境 +γ×(S×O×D 临时 ) 归一化 +δ×Trend 归一化 D 临时 This is a temporary detectability determined based on the first risk value R1. It is effective only once, will not participate in the next fault diagnosis, and will not modify the parameters recorded in the FMEA.

[0180] In other words, the calculation of the second risk value can be represented as the second determination stage of the risk value. The second determination stage can be used to accurately reflect the instantaneous deterioration state of the equipment's detection capability, ensuring the accuracy of fault diagnosis.

[0181] By employing a two-stage risk value calculation involving both a first and a second risk value, the cyclical dependency between detectability and risk value is broken. The first risk value serves as the basis for dynamically adjusting detectability, while the second risk value becomes the standard for subsequent graded fault diagnosis strategies. This ensures that risk assessment neither overlooks instantaneous degradation risks nor leads to excessive intervention, thereby improving the timeliness and accuracy of fault diagnosis. Conversely, assessing equipment failure risk solely through a single-stage risk value fails to respond to real-time changes in the equipment, ignores instantaneous degradation of manufacturing equipment, and impacts the accuracy of fault diagnosis.

[0182] Based on the above embodiments, the terminal device 100 in this application embodiment performs a two-stage risk calculation through a first determination stage and a second determination stage. First, it calculates a first risk value based on the FMEA base detectability. Then, it dynamically determines a temporary detectability by combining the first risk value with a trigger threshold (adjusting the value if the risk meets the standard, and using the base value if it doesn't). Finally, it calculates a second risk value based on the temporary detectability. This breaks the logical loop of mutual dependence between risk value and detectability, ensuring the accuracy of the calculation. Furthermore, it accurately reflects the instantaneous degradation of the device's detection capability through the temporary detectability, avoiding modifications to the FMEA base detectability due to single state fluctuations, and ensuring the standardization and traceability of the FMEA database.

[0183] It should be noted that the risk value described in the embodiments of this application can represent the probability of a certain failure of the manufacturing equipment. That is, the risk value is used to characterize the probability of a certain equipment failure event occurring in the manufacturing equipment. The higher the risk value, the higher the probability of the manufacturing equipment failing.

[0184] S307. If the second risk value is greater than or equal to the risk threshold, generate a fault diagnosis strategy based on the risk level corresponding to the second risk value and execute the fault diagnosis strategy.

[0185] Terminal device 100 calculates a second risk value based on temporary detectability. If the second risk value is greater than or equal to a risk threshold, it indicates a significant risk of failure in the manufacturing equipment. Terminal device 100 then generates a corresponding fault diagnosis strategy based on the risk level corresponding to the second risk value (e.g., low-risk maintenance, medium-risk enhanced monitoring, high-risk shutdown for maintenance) to enable timely intervention in equipment failures and ensure production quality. The fault diagnosis strategy is based on the mapping relationship of the root cause database and is deeply integrated with FMEA, electronic control plans, and eSOPs, enabling automated traceability of fault issues. For example, if the risk threshold is 0.7 and R² ≥ 0.7, a corresponding fault diagnosis strategy is generated based on the risk level.

[0186] In some embodiments, when the terminal device 100 generates a fault diagnosis strategy based on the risk level corresponding to the second risk value, it reads a risk level threshold, wherein the risk level threshold includes a first level threshold and a second level threshold, and the first level threshold is less than the second level threshold. For example, the first level threshold can be equal to the risk threshold, such as 0.7 for the first level threshold and 0.9 for the second level threshold.

[0187] If the second risk value is less than the first level threshold, such as R² < 0.7, indicating a low risk level, then a first fault diagnosis strategy is generated based on the FMEA database. This first fault diagnosis strategy instructs that the current operation of the manufacturing equipment be maintained without modification. For example, the first fault diagnosis strategy might state that the equipment is operating normally, and the eSOP displays the standard operating interface.

[0188] If the second risk value is greater than or equal to the first level threshold and the second risk value is less than the second level threshold, such as 0.7≤R2<0.9, the risk level is medium risk. A second fault diagnosis strategy is generated based on the FMEA database. The second fault diagnosis strategy is used to prompt the corresponding operation steps in the electronic work instructions, generate preventive maintenance work orders, and increase the sampling inspection ratio of the manufacturing equipment.

[0189] For example, the second fault diagnosis strategy is to highlight "Calibration cycle is approaching" in the "Daily Inspection" step and insert an additional operation item "Verify detection sensitivity using standard leaks" (eSOP dynamic reconstruction), automatically generate preventive maintenance work orders, associate them with the ID of the FMEA project (linked with the enterprise asset management system), and increase the sampling inspection ratio of the subsequent 5 manufacturing equipment to 100% (MES linkage).

[0190] If the second risk value is greater than or equal to the second-level threshold (e.g., R² ≥ 0.9), the risk level is considered high, and a third fault diagnosis strategy is generated based on the FMEA database. This third fault diagnosis strategy is used to instruct the disconnection of the manufacturing equipment's output signal, display the fault tree analysis guidance from the FMEA database, and send a re-inspection command.

[0191] For example, the third fault diagnosis strategy includes cutting off the "pass" signal output permission of the helium detector (physical level lock), prohibiting product release, automatically switching the eSOP to "fault handling mode", displaying the fault tree analysis associated with FMEA and customized maintenance guidance, and sending a re-inspection instruction to MES, etc.

[0192] In some embodiments, the terminal device 100 may generate a processing notification based on a first fault diagnosis strategy, a second fault diagnosis strategy, and a third fault diagnosis strategy, and send the processing notification to the corresponding device (manufacturing equipment or control device of manufacturing equipment) for processing via a communication device.

[0193] S308. Based on the mapping relationship between the execution results of the fault diagnosis strategy and the root cause database, update the control parameters of the management and control tools.

[0194] After the terminal device 100 generates and executes the fault diagnosis strategy, it can automatically update the control parameters of each control tool based on the mapping relationship between the execution result of the fault diagnosis strategy and the root cause database. This achieves automated synchronization and ensures the consistency and accuracy of the parameters in each control tool, thereby improving the accuracy of subsequent fault diagnosis.

[0195] In some embodiments, after the terminal device 100 executes the fault diagnosis strategy, the controller 120 also generates an event log based on the fault diagnosis strategy. The event log includes the risk level, trigger time, execution action, associated FMEA failure mode item ID, operator ID, and product serial number range corresponding to the fault diagnosis strategy.

[0196] In some embodiments, the controller 120 of the terminal device 100 further determines the execution result based on event logs, quality verification data of the manufacturing equipment, and real-time status parameters. The quality verification data includes the serial number of the manufacturing equipment, re-inspection results, and the pass rate of quality indicators. The execution result includes relevant parameters associated with the manufacturing equipment, including but not limited to the trend (increase or decrease) of the pass rate of quality indicators, the number of times temporary detection is triggered, the correlation between parameter control limits and failure rate, the response time of the reaction plan, and the fault prevention rate.

[0197] For updates to the FMEA database, such as Figure 5 As shown, in some embodiments, the controller 120 of the terminal device 100 is configured to perform the following steps:

[0198] S501. Determine the root cause node of the target fault based on the execution results.

[0199] Terminal device 100 can determine the root cause node (i.e. the target fault root cause node) corresponding to the fault based on the execution result of the fault diagnosis strategy. For example, the target fault root cause node may be the sensitivity drift of the helium detector sensor or the calibration deviation of the torque tester exceeding the allowable range.

[0200] S502. Based on the mapping relationship between the root cause database and the FMEA database, query the failure mode items in the FMEA database that have a mapping relationship with the target failure root cause node to obtain the target item.

[0201] After the terminal device 100 identifies the target fault root cause node, it can query failure mode items that have a mapping relationship with the target fault root cause node based on the mapping relationship between the target fault root cause node in the root cause database and the FMEA database, so as to identify the target item.

[0202] For example, if the target root cause node is "helium detector sensor sensitivity drift", the FMEA failure mode item that has a mapping relationship with this target root cause node is "decrease in the detection accuracy of the airtightness detection equipment, resulting in undetected refrigerant leakage". Read the ID of this failure mode item.

[0203] S503. Update the target item based on the execution results.

[0204] After the terminal device 100 identifies the target item, it can update the target item based on the execution results to improve the fault diagnosis capability of the FMEA database.

[0205] Specifically, when the controller 120 updates the target item based on the execution result, if the execution result indicates an improving trend in the quality indicator pass rate, the occurrence degree of the target item will be lowered. For example, if the quality indicator pass rate of the manufacturing equipment increases by more than or equal to 15%, the occurrence degree of the target item will be lowered.

[0206] If the number of times the temporary detection rate is triggered within the preset period is greater than or equal to the frequency threshold, the base detection rate of the target item will be increased. For example, if the preset period is 7 days and the frequency threshold is 5 times, and the number of triggers calculated by the temporary detection rate is greater than 5 within 7 days, the terminal device 100 will increase the base detection rate corresponding to the target item.

[0207] If the execution results indicate a downward trend in the pass rate of quality indicators, the severity of the target item should be increased. For example, if the pass rate of quality indicators for manufacturing equipment decreases, the severity of the target item should be increased.

[0208] S504. Update the FMEA database according to the updated target project.

[0209] After the terminal device 100 completes the update of the above target items, it synchronously updates the control parameters of this failure mode item in the FMEA database according to the updated target items, so as to complete the update of the FMEA database.

[0210] In some embodiments, after updating the FMEA database, the terminal device 100 also updates the version number of the FMEA database synchronously.

[0211] For updates to electronic control plans, such as Figure 6 As shown, in some embodiments, the controller 120 of the terminal device 100 is configured to perform the following steps:

[0212] S601. Based on the mapping relationship between the root cause database and the electronic control plan, query the control items in the electronic control plan that have a mapping relationship with the target fault root cause node to obtain the target control item.

[0213] After identifying the target fault root cause node, the terminal device 100 can query the control items that have a mapping relationship with the target fault root cause node based on the mapping relationship between the target fault root cause node and the electronic control plan in the root cause database, thereby identifying the target control item. The control item may include the equipment calibration cycle of the manufacturing equipment, parameter control limits, and triggering conditions of the reaction plan.

[0214] S602. Update the target control items based on the execution results.

[0215] After the terminal device 100 determines the target control item, it can update the target control item based on the execution result to improve the fault diagnosis capability of the electronic control plan.

[0216] When the controller 120 updates the target control item based on the execution result, if the execution result indicates a decreasing trend in the failure rate, the calibration cycle is shortened. For example, after executing the fault diagnosis strategy, if the terminal device 100 determines that the failure rate has decreased, the calibration cycle of the target control item is adjusted downwards to shorten the calibration cycle.

[0217] If the execution result indicates that the correlation between the parameter control limit and the failure rate is greater than the correlation threshold, the parameter control limit will be reduced. For example, after executing a fault diagnosis strategy, if the terminal device 100 determines that the correlation between the parameter control limit and the fault exceeds the correlation threshold, the range of the parameter control limit will be reduced.

[0218] If the execution result indicates that the response time of the reaction plan is greater than the time threshold, the triggering conditions of the reaction plan are updated. For example, after executing the fault diagnosis strategy, if the terminal device 100 determines that the response time of the reaction plan is greater than the time threshold, it indicates that there is a delay, and the triggering conditions of the reaction plan need to be updated.

[0219] S603. Update the electronic control plan according to the updated target control items.

[0220] After the terminal device 100 completes the update of the above-mentioned target control item, it synchronously updates the control parameters of this control item in the electronic control plan according to the updated target control item, so as to complete the update of the electronic control plan.

[0221] For eSOP updates, such as Figure 7 As shown, in some embodiments, the controller 120 of the terminal device 100 is configured to perform the following steps:

[0222] S701. Based on the mapping relationship between the root cause database and the electronic work instruction, query the operation steps in the electronic work instruction that have a mapping relationship with the target fault root cause node to obtain the target steps.

[0223] After the terminal device 100 determines the target fault root cause node, it can query the operation steps that have a mapping relationship with the target fault root cause node based on the mapping relationship between the target fault root cause node and eSOP in the root cause database, so as to determine the target step.

[0224] S702. Update the target steps based on the execution results.

[0225] After the terminal device 100 determines the target step, it can update the target step based on the execution result to improve the fault diagnosis capability of the eSOP.

[0226] When controller 120 executes the update of the target step based on the execution result, if the execution result indicates that the fault blocking rate of the target step is greater than a first blocking rate threshold, a flashing prompt, an operation video link, or additional verification items are written into the target step. For example, after executing the fault diagnosis strategy, if the fault blocking rate of the target step is greater than 50%, indicating that the target step has a significant effect on blocking the fault, then a flashing prompt, an operation video link, or additional verification items are written into the target step to strengthen this operation step in the eSOP.

[0227] For example, terminal device 100 also includes display 130. Assuming the first blocking rate threshold is 50%, Figure 8 As shown, when the failure blocking rate of the execution result corresponding to the current device failure event is greater than 50%, the terminal device 100 displays the target step 801 through the display 130. The content of the target step is "Execute xxx, then execute xxx". The target step is in the form of a flashing prompt and includes the corresponding operation video link 802.

[0228] like Figure 9 As shown, terminal device 100 reads the mapping relationship of the root cause database stored in memory 110. Memory 110 returns this mapping relationship, enabling controller 120 to determine the target step corresponding to the target fault root cause node in the electronic work instruction based on this mapping relationship, and update the target step according to the above step S702. To facilitate fault prevention and control, controller 120 also sends the updated target step to display on monitor 130 for display, thereby enhancing the target step.

[0229] If the execution result indicates that the failure prevention rate of the target step is less than the second prevention rate threshold, the prompt information for the target step is removed, where the second prevention rate threshold is less than the first prevention rate threshold. For example, after executing the fault diagnosis strategy, if the failure prevention rate of the target step is less than 15%, indicating that the target step is not effective in preventing the fault, the target step is removed or ignored, and this operation step is weakened in the eSOP.

[0230] S703. Update the electronic work instructions according to the updated target steps.

[0231] After the terminal device 100 completes the update of the above-mentioned target steps, it synchronously updates the control parameters of this operation step in the eSOP according to the updated target steps to complete the update of the eSOP. In some embodiments, the terminal device 100 also updates the model parameters of the risk calculation model according to the execution results to improve the accuracy of equipment fault diagnosis, such as updating the above-mentioned equipment parameter weights, environmental parameter weights, and risk thresholds.

[0232] The above embodiments are illustrated below with a specific example.

[0233] The root cause database stored in the memory 110 of the terminal device 100 contains mapping relationships between "screen display ghosting" fault events in the TV manufacturing scenario and the FMEA database, electronic control plan, and electronic work instructions. The terminal device 100 then generates a risk calculation model based on the database, integrating the TV's physical state, environmental disturbances, FMEA dynamic weights, and state drift trends. The physical state may include the cumulative panel illumination time and driver board voltage fluctuation rate; environmental disturbances cover workshop temperature and humidity and backlight module material batch quality scores; FMEA dynamic weights involve severity, occurrence, and basic detectability; and the state drift trend includes the degradation rate of pixel response speed. After collecting real-time status parameters, the terminal device performs a two-stage calculation to determine the risk level. The first stage calculates a first risk value based on the basic detectability. When the first risk value exceeds a trigger threshold, the basic detectability is superimposed with a preset adjustment value to obtain a temporary detectability. The second stage calculates a second risk value based on the temporary detectability. Assuming the risk threshold is 0.7, a tiered strategy is generated when the second risk value exceeds 0.7. Strengthen calibration prompts in electronic work instructions during medium-risk periods, and cut off qualified signals and send re-inspection instructions during high-risk periods. After execution, update the parameters of the control tools based on the results, shorten the backlight module calibration cycle, increase the FMEA base detectivity, realize the pre-emptive prevention of image retention faults, and improve the efficiency and accuracy of fault diagnosis.

[0234] In this way, after handling a single fault, the FMEA database, electronic control plan, and electronic work instructions are updated in a coordinated manner. Through a logically consistent update approach, a single fault is transformed into a global prevention and control capability, providing advance detection capabilities for subsequent equipment fault diagnosis. At the same time, because the parameters of all management and control tools are coordinated and adapted, missed detections and false diagnoses can be reduced, while enhancing the dynamic adaptability of the inspection system to scenarios such as equipment aging and environmental changes, and shortening the fault-to-zero cycle.

[0235] Based on the aforementioned terminal device 100, this application embodiment also provides a device fault diagnosis and control method, such as... Figure 3 As shown, the method may include the following steps:

[0236] S301. Generate a risk calculation model based on the root cause database.

[0237] The root cause database includes equipment failure events and the mapping relationship between equipment failure events and management tools. The management tools include a Failure Mode and Effects Analysis (FMEA) database, electronic control plans, and electronic work instructions. The FMEA database includes severity, occurrence, and basic detectability. The risk calculation model is used to integrate the state parameters of manufacturing equipment in different risk dimensions.

[0238] S302. Collect real-time status parameters of manufacturing equipment.

[0239] S303. Input the real-time status parameters into the risk calculation model.

[0240] S304. Based on the risk calculation model, calculate the first risk value according to the basic detectability.

[0241] S305. Determine the temporary detectivity based on the first risk value and the basic detectivity.

[0242] The temporary detection degree is greater than or equal to the basic detection degree, the temporary detection degree is effective only once, and the temporary detection degree is not used to update the basic detection degree of the FMEA database.

[0243] S306. Based on the risk calculation model, calculate the second risk value according to the temporary detectability.

[0244] S307. If the second risk value is greater than or equal to the risk threshold, generate a fault diagnosis strategy based on the risk level corresponding to the second risk value and execute the fault diagnosis strategy.

[0245] S308. Based on the mapping relationship between the execution results of the fault diagnosis strategy and the root cause database, update the control parameters of the management and control tools.

[0246] It is understood that the device fault diagnosis and control method in this application embodiment can refer to the embodiment of the terminal device 100 described above, and can adopt the same principle. Therefore, this application will not elaborate further.

[0247] Based on the above embodiments, the equipment fault diagnosis method can generate a risk calculation model integrating multiple risk dimensions based on a root cause database. After collecting real-time status parameters, it calculates and determines the risk value based on a two-stage temporary detectivity. When the risk value exceeds a threshold, a fault diagnosis strategy is generated and executed. Then, the control parameters of the FMEA database, electronic control plan, and electronic work instructions are updated according to the execution results and mapping relationships. The temporary detectivity does not change the basic detectivity value of the FMEA when it is activated only once. This application can respond to changes in the real-time operating status of equipment, achieve accurate diagnosis of manufacturing equipment faults, ensure the consistency of management tools, and improve the efficiency and accuracy of fault diagnosis.

[0248] For ease of explanation, the above description has been provided in conjunction with specific embodiments. However, the discussion in some embodiments is not intended to be exhaustive or to limit the embodiments to the specific forms disclosed above. Various modifications and variations can be obtained based on the above teachings. The selection and description of the above embodiments are for the purpose of better explaining the contents of this disclosure, thereby enabling those skilled in the art to better utilize the embodiments.

Claims

1. A terminal device, characterized in that, include: The memory is configured to store a root cause database, which includes equipment failure events and a mapping relationship between the equipment failure events and management tools. The management tools include a Failure Mode and Effects Analysis (FMEA) database, electronic control plans, and electronic work instructions. The FMEA database includes severity, occurrence, and basic detectability. The controller, connected to the memory, is configured to: A risk calculation model is generated based on the root cause database. The risk calculation model is used to integrate the state parameters of manufacturing equipment in different risk dimensions. Collect real-time status parameters of the manufacturing equipment; The real-time status parameters are input into the risk calculation model; Based on the risk calculation model, the first risk value is calculated according to the basic detectability. The temporary detection rate is determined based on the first risk value and the basic detection rate; The temporary detection degree is greater than or equal to the base detection degree, the temporary detection degree is effective only once, and the temporary detection degree is not used to update the base detection degree of the FMEA database; Based on the risk calculation model, a second risk value is calculated according to the temporary detectivity. If the second risk value is greater than or equal to the risk threshold, a fault diagnosis strategy is generated based on the risk level corresponding to the second risk value, and the fault diagnosis strategy is executed. Based on the mapping relationship between the execution result of the fault diagnosis strategy and the root cause database, the control parameters of the management tool are updated.

2. The terminal device according to claim 1, characterized in that, The controller executes the determination of a temporary detection rate based on the first risk value and the basic detection rate, specifically configured as follows: Read the trigger threshold of the temporary probeness; If the first risk value is greater than or equal to the trigger threshold, the sum of the basic detectivity and the preset adjustment value is set as the temporary detectivity; If the first risk value is less than the trigger threshold, the basic detectivity is set to the temporary detectivity.

3. The terminal device according to claim 1 or 2, characterized in that, The risk dimensions include the physical state of the manufacturing equipment, environmental disturbances, FMEA dynamic weights, and state drift trends. The controller executes a risk calculation model generated based on the root cause database, specifically configured as follows: Based on the historical fault root cause nodes corresponding to the manufacturing equipment in the root cause database, at least one of the cumulative number of detections, the runtime after the previous calibration, and the real-time torque fluctuation rate is read to obtain the first set of state parameters of the body state. Read at least one of the following: workshop temperature, humidity, and supplier quality score associated with material batches, to obtain the second set of state parameters for the environmental disturbance; The severity, occurrence, and basic detectability of the FMEA database are read, and a basic risk priority number is calculated based on the severity, occurrence, and basic detectability to obtain the third set of state parameters for the FMEA dynamic weights. The slope of the sliding window for the torque value and the sigma level of the control chart in the statistical process are read, and the degradation rate is calculated based on the slope of the sliding window for the torque value and the sigma level of the control chart to obtain the fourth set of state parameters for the state drift trend. The risk calculation model is constructed based on the first set of state parameters, the second set of state parameters, the third set of state parameters, and the fourth set of state parameters.

4. The terminal device according to claim 3, characterized in that, The controller performs the calculation of a first risk value based on the base detectivity, specifically configured as follows: Read the weighting coefficients, which include a first coefficient, a second coefficient, a third coefficient, and a fourth coefficient, and the sum of the first coefficient, the second coefficient, the third coefficient, and the fourth coefficient is 1; Calculate the first product of the first coefficient and the normalized value corresponding to the first state parameter set; Calculate the second product of the second coefficient and the normalized value corresponding to the second state parameter set; Calculate the third product of the third coefficient and the normalized value corresponding to the third state parameter set; Calculate the fourth product of the fourth coefficient and the normalized value corresponding to the fourth state parameter set; The sum of the first product, the second product, the third product, and the fourth product is determined as the first risk value.

5. The terminal device according to claim 4, characterized in that, The controller is configured to calculate a second risk value based on the temporary detectivity, specifically as follows: Read the severity and occurrence from the FMEA database; Calculate a dynamic risk priority number based on the severity, the occurrence, and the provisional detection rate; Calculate the fifth product of the third coefficient and the normalized value corresponding to the dynamic risk priority number; The sum of the first product, the second product, the fourth product, and the fifth product is determined as the second risk value.

6. The terminal device according to claim 1, characterized in that, The controller executes a fault diagnosis strategy based on the risk level corresponding to the second risk value, specifically configured as follows: Read the risk level threshold, which includes a first level threshold and a second level threshold, wherein the first level threshold is less than the second level threshold; If the second risk value is less than the first level threshold, a first fault diagnosis strategy is generated based on the FMEA database. The first fault diagnosis strategy is used to instruct the maintenance of the current operation of the manufacturing equipment. If the second risk value is greater than or equal to the first level threshold and the second risk value is less than the second level threshold, a second fault diagnosis strategy is generated according to the FMEA database. The second fault diagnosis strategy is used to prompt the corresponding operation steps in the electronic work instruction, generate preventive maintenance work orders, and increase the sampling inspection ratio of the manufacturing equipment. If the second risk value is greater than or equal to the second level threshold, a third fault diagnosis strategy is generated based on the FMEA database. The third fault diagnosis strategy is used to instruct the disconnection of the output signal of the manufacturing equipment, display the fault tree analysis guidance of the FMEA database, and send a re-inspection instruction.

7. The terminal device according to claim 1, characterized in that, The controller updates the control parameters of the management tool and is configured as follows: The target root cause node of the fault is determined based on the execution results; Based on the mapping relationship between the root cause database and the FMEA database, query the failure mode items in the FMEA database that have a mapping relationship with the target failure root cause node to obtain the target item; Update the target project based on the execution result; Update the FMEA database according to the updated target project; Specifically, the controller is configured to update the target project based on the execution result. If the execution result indicates an improving trend in the pass rate of the quality indicator, the occurrence rate of the target item will be lowered. If the number of times the temporary detection rate is triggered within the preset period is greater than or equal to the frequency threshold, the base detection rate of the target project is increased. If the execution result indicates a downward trend in the pass rate of the quality indicator, the severity of the target project is increased.

8. The terminal device according to claim 7, characterized in that, The controller updates the control parameters of the management tool and is configured as follows: Based on the mapping relationship between the root cause database and the electronic control plan, the control items in the electronic control plan that have a mapping relationship with the target fault root cause node are queried to obtain the target control items; the target control items include the equipment calibration cycle, parameter control limits and triggering conditions of the reaction plan of the manufacturing equipment. Update the target control item based on the execution result; The electronic control plan is updated according to the updated target control items; Specifically, the controller is configured to update the target control item based on the execution result. If the execution result indicates a decreasing trend in the failure rate, the calibration cycle should be shortened. If the correlation between the execution result characterizing the parameter control limit and the failure rate is greater than the correlation threshold, then the parameter control limit should be reduced. If the execution result indicates that the response time of the reaction plan is greater than a time threshold, the triggering condition of the reaction plan is updated.

9. The terminal device according to claim 7, characterized in that, The controller updates the control parameters of the management tool and is configured as follows: Based on the mapping relationship between the root cause database and the electronic work instruction, query the operation steps in the electronic work instruction that have a mapping relationship with the target fault root cause node to obtain the target steps; Update the target step based on the execution result; Update the electronic work instructions according to the updated target steps; Specifically, the controller is configured to perform the step of updating the target based on the execution result as follows: If the execution result indicates that the failure blocking rate of the target step is greater than the first blocking rate threshold, a flashing prompt, an operation video link, or an additional verification item is written into the target step. If the execution result indicates that the failure blocking rate of the target step is less than the second blocking rate threshold, the prompt information of the target step is removed; the second blocking rate threshold is less than the first blocking rate threshold.

10. A method for diagnosing and controlling equipment faults, characterized in that, include: A risk calculation model is generated based on a root cause database. The root cause database includes equipment failure events and the mapping relationship between the equipment failure events and management tools. The management tools include a Failure Mode and Effects Analysis (FMEA) database, electronic control plans, and electronic work instructions. The FMEA database includes severity, occurrence, and basic detectability. The risk calculation model is used to integrate the state parameters of manufacturing equipment in different risk dimensions. Collect real-time status parameters of the manufacturing equipment; The real-time status parameters are input into the risk calculation model; Based on the risk calculation model, the first risk value is calculated according to the basic detectability. The temporary detection rate is determined based on the first risk value and the basic detection rate; The temporary detection degree is greater than or equal to the base detection degree, the temporary detection degree is effective only once, and the temporary detection degree is not used to update the base detection degree of the FMEA database; Based on the risk calculation model, a second risk value is calculated according to the temporary detectivity. If the second risk value is greater than or equal to the risk threshold, a fault diagnosis strategy is generated based on the risk level corresponding to the second risk value, and the fault diagnosis strategy is executed. Based on the mapping relationship between the execution result of the fault diagnosis strategy and the root cause database, the control parameters of the management tool are updated.

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