GoB process quality evaluation system for LED display screen processing

Abstract

The GOB process quality evaluation system for LED display screen processing relates to the technical field of GOB process quality evaluation, acquires current GOB process flow information, sets an edge monitoring node according to the flow information, and acquires test data of a plurality of quality monitoring indexes of each process subsequence; the time sequence of the test data of the plurality of quality monitoring indexes of each process subsequence is monitored in real time to acquire quality test results of each process subsequence; the quality test content corresponding to each process subsequence is acquired according to the plurality of quality monitoring indexes of each process subsequence; stable analysis is performed on the process subsequences in which each quality monitoring index is marked as quality test qualified; a reliability decision model is constructed to analyze and decide the stable analysis coefficients of each stable index and unstable index of the received process subsequences; and thus the efficiency and accuracy of quality evaluation are significantly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of GOB process quality assessment, and in particular to a GOB process quality assessment system applied to LED display screen processing. Background Art

[0002] The existing GOB process quality assessment for LED display processing has many technical problems, including fixed test content, which cannot be dynamically adjusted according to actual conditions and is difficult to adapt to changes in the production process. It lacks flexibility and cannot flexibly adjust test standards according to different environments or product requirements. Data analysis is insufficient and relies on the experience of engineers for data analysis. There is a lack of systematic data support, which makes it easy to make misjudgments. Decision support is weak and there is a lack of a reliable decision support system. The decision-making process is highly subjective and lacks scientific basis. Summary of the Invention

[0003] In order to solve the above technical problems, the purpose of the present invention is to provide a GOB process quality assessment system for LED display screen processing, including a monitoring center, wherein the monitoring center is communicatively connected to a data acquisition module, a quality test monitoring module, a test content adaptation module, a data analysis module, a reliability decision model construction module and a threshold analysis module;

[0004] The data acquisition module is used to obtain the current GOB process information, divide the GOB process into several process sub-sequences, set edge monitoring nodes according to the process information, and obtain test data of several quality monitoring indicators of each process sub-sequence;

[0005] The quality test monitoring module is used to monitor the test data time series of several quality monitoring indicators in the quality test of each process subsequence in real time to obtain the quality test results of each process subsequence;

[0006] The test content adaptation module is used to obtain the quality test content corresponding to each process subsequence according to a number of quality monitoring indicators of each process subsequence;

[0007] The data analysis module is used to perform stability analysis on process subsequences whose quality monitoring indicators are all marked as qualified in quality tests;

[0008] The reliability decision model building module is used to build a reliability decision model and analyze and make decisions on the stability analysis coefficients of each stability index and instability index of the received process subsequence;

[0009] The threshold analysis module is used to obtain the reliability analysis coefficient threshold of each process subsequence based on the test data in several historical test cycles of each process subsequence.

[0010] Furthermore, the data acquisition module obtains the current GOB process information, divides the GOB process into several process subsequences, sets edge monitoring nodes according to the process information, and obtains test data of several quality monitoring indicators of each process subsequence. The process includes:

[0011] Obtain the process flow characteristics of each current GOB process processing equipment, divide the GOB process flow into several process sub-sequences according to the process flow characteristics, set edge monitoring nodes in each process sub-sequence, and use data retrieval to obtain several quality monitoring indicators of each process sub-sequence according to the process flow characteristics of each process sub-sequence;

[0012] The quality test content corresponding to each process subsequence is obtained, and the quality test content includes the intensity levels of different test environment intervals. The end timestamp of each process subsequence is used as the quality test time point. A test process sequence is constructed according to the quality test content and the quality test time point. The LED display screen of each process subsequence is quality tested according to the test process sequence, and test data of several quality monitoring indicators of each process subsequence is obtained. The edge monitoring node is used to obtain the test data of several quality monitoring indicators of the process subsequence and mark the test time, and set the test cycle.

[0013] Furthermore, the quality test monitoring module monitors the test data time series of several quality monitoring indicators in the quality test of each process subsequence in real time. The process of obtaining the quality test results of each process subsequence includes:

[0014] Setting threshold intervals for several quality monitoring indicators of each process subsequence according to the intensity level of the test environment interval corresponding to each process subsequence, obtaining a time series sequence of test data for several quality monitoring indicators of each process subsequence, comparing the time series sequence of test data for several quality monitoring indicators of each process subsequence with the corresponding quality monitoring indicator threshold intervals, obtaining the cumulative time during which the test data for each quality monitoring indicator of each process subsequence is not within the corresponding quality monitoring indicator threshold interval, and comparing the cumulative time for each quality monitoring indicator of each process subsequence with a preset cumulative time threshold;

[0015] If the cumulative time of the quality monitoring indicators of a process subsequence is greater than the cumulative time threshold, the quality monitoring indicators of the process subsequence will be marked as unqualified in the quality test, and the process subsequence will be marked as unqualified in the GOB process quality. If the cumulative time of the quality monitoring indicators of the process subsequence is less than or equal to the cumulative time threshold, the quality monitoring indicators of the process subsequence will be marked as qualified in the quality test.

[0016] Furthermore, the process of the test content adaptation module acquiring the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence includes:

[0017] Obtaining quality test results corresponding to different test environment interval intensity levels for each process subsequence within several historical test cycles, performing statistical analysis on the quality test results, and obtaining the probability of quality test failure for each quality monitoring indicator of each process subsequence at different test environment interval intensity levels;

[0018] According to the probability of quality test failure of each quality monitoring indicator of each process subsequence at different test environment interval intensity levels, each quality monitoring indicator of each process subsequence is divided into stable indicators and unstable indicators;

[0019] Determine whether each process subsequence has unstable indicators. If the process subsequence does not have unstable indicators, select the lowest test environment interval strength level as the quality test content of the process subsequence. If the process subsequence has unstable indicators, screen out the maximum quality test failure probability of the unstable indicators at different test environment interval strength levels, and obtain the test environment interval strength level corresponding to the maximum quality test failure probability as the quality test content of the process subsequence.

[0020] Furthermore, the process of dividing each quality monitoring indicator of the process subsequence into stable indicators and unstable indicators includes:

[0021] Obtain the maximum quality test failure probability and the minimum quality test failure probability of each quality monitoring indicator of the process subsequence in different test environment interval intensity levels, obtain the quality test failure probability difference between the maximum quality test failure probability and the minimum quality test failure probability of each quality monitoring indicator, compare the quality test failure probability difference of the quality monitoring indicator with a preset difference threshold, and if the quality test failure probability difference is less than or equal to the difference threshold, mark the quality monitoring indicator as a stable indicator;

[0022] If the quality test failure probability difference of the quality monitoring indicator is greater than the difference threshold, the quality monitoring indicator is marked as an unstable indicator.

[0023] Furthermore, the data analysis module performs a stable analysis on the process subsequences whose quality monitoring indicators are all marked as qualified by the quality test, including:

[0024] If all quality monitoring indicators of the process subsequence are marked as qualified, then the test data time series sequence of each stability indicator in the current test cycle is obtained, and the stability analysis coefficient of each stability indicator is obtained based on the test data time series sequence;

[0025] Similarly, a test data time series sequence of each instability indicator in the current test cycle is obtained, and a stability analysis coefficient of each instability indicator is obtained based on the test data time series sequence;

[0026] The stability analysis coefficients of each stability index and instability index of the process subsequence are sent to the reliability decision model construction module.

[0027] Furthermore, the reliability decision model building module builds a reliability decision model, and the process of analyzing and making decisions on the stability analysis coefficients of the received stability indicators and instability indicators of the process subsequence includes:

[0028] A reliability decision model is constructed based on the stability analysis coefficient of the stability index and the stability analysis coefficient of the instability index. The stability analysis coefficients of the stability index and the instability index of the process subsequence are input into the reliability decision model. The reliability analysis coefficient is output according to the reliability decision model. At the same time, the reliability analysis coefficient threshold of the process subsequence is obtained. The reliability analysis coefficient is compared with the reliability analysis coefficient threshold. If the reliability analysis coefficient is greater than or equal to the reliability analysis coefficient threshold, the process subsequence is marked as having qualified GOB process quality.

[0029] If the reliability analysis coefficient is less than the reliability analysis coefficient threshold, the highest test environment interval intensity level is selected as the secondary quality test content corresponding to the process subsequence, and the LED display screen of each process subsequence is subjected to secondary quality testing according to the secondary quality test content, and the test data of each quality monitoring indicator of the process subsequence is obtained, and the test data is sent to the quality test monitoring module for analysis, and the cumulative time during which the test data of each quality monitoring indicator of the process subsequence is not located in the corresponding quality monitoring indicator threshold interval is obtained. If the cumulative time of the quality monitoring indicator of a process subsequence is greater than the cumulative time threshold, the process subsequence is marked as GOB process quality unqualified. If the cumulative time of each quality monitoring indicator of the process subsequence is less than or equal to the cumulative time threshold, the process subsequence is marked as GOB process quality qualified.

[0030] Furthermore, the threshold analysis module obtains the reliability analysis coefficient threshold of each process subsequence based on the test data in several historical test cycles of each process subsequence, including:

[0031] Obtain test data time series of each stability indicator and instability indicator of each process subsequence within several historical test cycles, screen out historical test cycles in which each process subsequence is marked as having unqualified GOB process quality from the several historical test cycles, and mark the historical test cycles as key historical test cycles;

[0032] According to the test data time series sequence of each stability indicator of the process subsequence in a certain key historical test cycle, the stability analysis coefficient of the process subsequence in a certain key historical test cycle is obtained. Similarly, according to the test data time series sequence of each instability indicator of the process subsequence in a certain key historical test cycle, the instability analysis coefficient of the process subsequence in a certain key historical test cycle is obtained. The stability analysis coefficient and the instability analysis coefficient of the process subsequence in a certain key historical test cycle are sent to the reliability decision model construction module to obtain the reliability analysis coefficient of the process subsequence in a certain key historical test cycle. Similarly, the reliability analysis coefficient of each process subsequence in each key historical test cycle is obtained, and the reliability analysis coefficient of each process subsequence in each key historical test cycle is weighted averaged to obtain the reliability analysis coefficient threshold of each process subsequence.

[0033] Compared with the existing technology, the beneficial effects of the present invention are: through real-time monitoring and data analysis, the present invention can discover potential problems earlier, and improve the efficiency and accuracy of quality assessment by adaptively adjusting the test content. In addition, the construction of the reliability decision-making model makes the decision more scientific and reasonable, which helps to improve product quality and production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a schematic diagram of a GOB process quality assessment system for LED display screen processing according to an embodiment of the present application. DETAILED DESCRIPTION

[0035] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0036] like Figure 1 As shown, the GOB process quality assessment system for LED display screen processing includes a monitoring center, which is communicatively connected to a data acquisition module, a quality test monitoring module, a test content adaptation module, a data analysis module, a reliability decision model construction module, and a threshold analysis module;

[0037] The data acquisition module is used to obtain the current GOB process information, divide the GOB process into several process sub-sequences, set edge monitoring nodes according to the process information, and obtain test data of several quality monitoring indicators of each process sub-sequence;

[0038] The quality test monitoring module is used to monitor the test data time series of several quality monitoring indicators in the quality test of each process subsequence in real time to obtain the quality test results of each process subsequence;

[0039] The test content adaptation module is used to obtain the quality test content corresponding to each process subsequence according to a number of quality monitoring indicators of each process subsequence;

[0040] The data analysis module is used to perform stability analysis on process subsequences whose quality monitoring indicators are all marked as qualified in quality tests;

[0041] The reliability decision model building module is used to build a reliability decision model and analyze and make decisions on the stability analysis coefficients of each stability index and instability index of the received process subsequence;

[0042] The threshold analysis module is used to obtain the reliability analysis coefficient threshold of each process subsequence based on the test data in several historical test cycles of each process subsequence.

[0043] It should be further explained that, in a specific implementation process, the data acquisition module obtains the current GOB process information, divides the GOB process into several process subsequences, sets edge monitoring nodes according to the process information, and obtains test data of several quality monitoring indicators of each process subsequence. The process includes:

[0044] Obtain the process flow characteristics of each current GOB process processing equipment, divide the GOB process flow into several process sub-sequences according to the process flow characteristics, set edge monitoring nodes in each process sub-sequence, and use data retrieval to obtain several quality monitoring indicators of each process sub-sequence according to the process flow characteristics of each process sub-sequence;

[0045] The process flow characteristics of each GOB processing equipment include raw material preparation (PCB board, LED chip, solder, packaging material, etc.), tool preparation (preparation of required production equipment, such as placement machine, welding equipment, coating equipment, etc.), chip positioning (using placement machine to accurately place LED chip at the designated position on PCB board), pasting and fixing (using special adhesive to fix LED chip on PCB board), connecting LED chip to the circuit on PCB board through welding technology, electrical testing (ensuring that each LED chip is correctly connected to the circuit and functions normally), coating (using transparent epoxy resin or other protective materials to encapsulate the placed chip to protect the chip from the external environment), curing (the packaging material needs to undergo a certain curing process to ensure that the material is completely hardened), polishing, cleaning, etc.

[0046] Several quality monitoring indicators for each process sub-sequence include optical performance data (such as brightness, brightness uniformity, color temperature, color saturation, contrast, etc.) of the LED display screen under different test environment intensity levels, electrical performance data (such as operating voltage / current, power consumption, signal delay, driver IC stability, etc.), mechanical performance data (impact resistance, vibration resistance), display effect data (refresh rate, response time, etc.);

[0047] The quality test content corresponding to each process subsequence is obtained, and the quality test content includes the intensity levels of different test environment intervals. The end timestamp of each process subsequence is used as the quality test time point. A test process sequence is constructed according to the quality test content and the quality test time point. The LED display screen of each process subsequence is quality tested according to the test process sequence, and test data of several quality monitoring indicators of each process subsequence is obtained. The edge monitoring node is used to obtain the test data of several quality monitoring indicators of the process subsequence and mark the test time, and set the test cycle.

[0048] It should be further explained that the test environment interval intensity level represents a series of environmental condition value intervals for environmental testing of the product, and the series of environmental condition value intervals include:

[0049] Temperature range (for example, to simulate the product's operating conditions in a high-temperature environment, the test temperature range can be +50°C to +85°C; to simulate the product's operating conditions in a low-temperature environment, the test temperature range can be -20°C to -40°C; to simulate the product's performance in an environment with rapid temperature changes, the test range usually includes both high and low temperature extremes, such as from -40°C to +85°C), humidity range (for example, to simulate the product's operating conditions in a high-humidity environment, the test humidity range can be 85%RH to 95%RH), pressure range (for example, to simulate the product's performance in a high-altitude or vacuum environment, the test pressure range can be atmospheric pressure to 0.1 atmospheres), light intensity range, electrostatic discharge (ESD) intensity range, vibration intensity range, shock intensity range, etc.

[0050] It should be further explained that, in a specific implementation process, the quality test monitoring module monitors the test data time series of several quality monitoring indicators in the quality test of each process subsequence in real time. The process of obtaining the quality test results of each process subsequence includes:

[0051] Setting threshold intervals for several quality monitoring indicators of each process subsequence according to the intensity level of the test environment interval corresponding to each process subsequence, obtaining a time series sequence of test data for several quality monitoring indicators of each process subsequence, comparing the time series sequence of test data for several quality monitoring indicators of each process subsequence with the corresponding quality monitoring indicator threshold intervals, obtaining the cumulative time during which the test data for each quality monitoring indicator of each process subsequence is not within the corresponding quality monitoring indicator threshold interval, and comparing the cumulative time for each quality monitoring indicator of each process subsequence with a preset cumulative time threshold;

[0052] If the cumulative time of the quality monitoring indicators of a process subsequence is greater than the cumulative time threshold, the quality monitoring indicators of the process subsequence will be marked as unqualified in the quality test, and the process subsequence will be marked as unqualified in the GOB process quality. If the cumulative time of the quality monitoring indicators of the process subsequence is less than or equal to the cumulative time threshold, the quality monitoring indicators of the process subsequence will be marked as qualified in the quality test.

[0053] It should be further explained that, in a specific implementation process, the process in which the test content adaptation module obtains the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence includes:

[0054] Obtaining quality test results corresponding to different test environment interval intensity levels for each process subsequence within several historical test cycles, performing statistical analysis on the quality test results, and obtaining the probability of quality test failure for each quality monitoring indicator of each process subsequence at different test environment interval intensity levels;

[0055] According to the probability of quality test failure of each quality monitoring indicator of each process subsequence at different test environment interval intensity levels, each quality monitoring indicator of each process subsequence is divided into stable indicators and unstable indicators;

[0056] Determine whether each process subsequence has unstable indicators. If the process subsequence does not have unstable indicators, select the lowest test environment interval strength level as the quality test content of the process subsequence. If the process subsequence has unstable indicators, screen out the maximum quality test failure probability of the unstable indicators at different test environment interval strength levels, and obtain the test environment interval strength level corresponding to the maximum quality test failure probability as the quality test content of the process subsequence.

[0057] It should be further explained that, in the specific implementation process, the process of dividing each quality monitoring indicator of the process subsequence into stable indicators and unstable indicators includes:

[0058] Obtain the maximum quality test failure probability and the minimum quality test failure probability of each quality monitoring indicator of the process subsequence in different test environment interval intensity levels, obtain the quality test failure probability difference between the maximum quality test failure probability and the minimum quality test failure probability of each quality monitoring indicator, compare the quality test failure probability difference of the quality monitoring indicator with a preset difference threshold, and if the quality test failure probability difference is less than or equal to the difference threshold, mark the quality monitoring indicator as a stable indicator;

[0059] If the quality test failure probability difference of the quality monitoring indicator is greater than the difference threshold, the quality monitoring indicator is marked as an unstable indicator.

[0060] It should be further explained that, in a specific implementation process, the data analysis module performs a stable analysis on the process subsequences whose quality monitoring indicators are all marked as qualified by the quality test, including:

[0061] If the quality test result of the process subsequence is that all quality monitoring indicators are marked as qualified, then obtain the test data time series sequence of each stability indicator in the current test cycle, and obtain the stability analysis coefficient of each stability indicator based on the test data time series sequence;

[0062] Among them, the calculation formula of the stability analysis coefficient of each stability index is:

[0063] ;

[0064] in, represents the stability analysis coefficient of stability index i, It represents the value of the stability index i at the tth moment in the test data time series, N represents the total number of moments in the test cycle, Indicates the conversion factor;

[0065] Similarly, a test data time series sequence of each instability indicator in the current test cycle is obtained, and a stability analysis coefficient of each instability indicator is obtained based on the test data time series sequence;

[0066] The stability analysis coefficients of each stability index and instability index of the process subsequence are sent to the reliability decision model construction module.

[0067] It should be further explained that, in a specific implementation process, the reliability decision model building module builds a reliability decision model, and the process of analyzing and deciding the stability analysis coefficients of the received stability indicators and instability indicators of the process subsequence includes:

[0068] A reliability decision model is constructed based on the stability analysis coefficient of the stability index and the stability analysis coefficient of the instability index: ,in, represents the stability analysis coefficient of stability index i, represents the stability analysis coefficient of the instability index j, is the error correction factor, which is set to 0.9. The stability analysis coefficients of the various stability indicators and unstable indicators of the process subsequence are input into the reliability decision model. The reliability analysis coefficient dc is output according to the reliability decision model. At the same time, the reliability analysis coefficient threshold of the process subsequence is obtained. The reliability analysis coefficient is compared with the reliability analysis coefficient threshold. If the reliability analysis coefficient is greater than or equal to the reliability analysis coefficient threshold, the process subsequence is marked as GOB process quality qualified. If the reliability analysis coefficient is less than the reliability analysis coefficient threshold, the highest test environment interval intensity level is selected as the secondary quality test content corresponding to the process subsequence. According to the secondary quality The quantity test content performs a secondary quality test on the LED display screen of each process subsequence, obtains the test data of each quality monitoring indicator of the process subsequence, sends the test data to the quality test monitoring module for analysis, obtains the cumulative time during which the test data of each quality monitoring indicator of the process subsequence is not located in the corresponding quality monitoring indicator threshold interval, if the cumulative time of the quality monitoring indicator of a process subsequence is greater than the cumulative time threshold, the process subsequence is marked as GOB process quality unqualified, if the cumulative time of each quality monitoring indicator of the process subsequence is less than or equal to the cumulative time threshold, the process subsequence is marked as GOB process quality qualified.

[0069] It should be further explained that, in a specific implementation, the threshold analysis module obtains the reliability analysis coefficient threshold of each process subsequence based on the test data of several historical test cycles of each process subsequence, including:

[0070] Obtain test data time series of each stability indicator and instability indicator of each process subsequence within several historical test cycles, screen out historical test cycles of each process subsequence marked as unqualified GOB process quality from the several historical test cycles of each process subsequence, and mark the historical test cycles as key historical test cycles;

[0071] According to the test data time series sequence of each stability indicator of the process subsequence in a certain key historical test cycle, the stability analysis coefficient of the process subsequence in a certain key historical test cycle is obtained. Similarly, according to the test data time series sequence of each instability indicator of the process subsequence in a certain key historical test cycle, the instability analysis coefficient of the process subsequence in a certain key historical test cycle is obtained. The stability analysis coefficient and the instability analysis coefficient of the process subsequence in a certain key historical test cycle are sent to the reliability decision model construction module to obtain the reliability analysis coefficient of the process subsequence in a certain key historical test cycle. Similarly, the reliability analysis coefficient of each process subsequence in each key historical test cycle is obtained, and the reliability analysis coefficient of each process subsequence in each key historical test cycle is weighted averaged to obtain the reliability analysis coefficient threshold of each process subsequence.

[0072] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The GOB process quality evaluation system for LED display screen processing is characterized by: It includes a monitoring center, which is communicatively connected to a data acquisition module, a quality test monitoring module, a test content adaptation module, a data analysis module, a reliability decision model construction module and a threshold analysis module; The data acquisition module is used to obtain the current GOB process information, divide the GOB process into several process sub-sequences, set edge monitoring nodes according to the process information, and obtain test data of several quality monitoring indicators of each process sub-sequence according to the quality test content of each process sub-sequence; The quality test monitoring module is used to monitor the test data time series of several quality monitoring indicators in the quality test of each process subsequence in real time to obtain the quality test results of each process subsequence; The test content adaptation module is used to obtain the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence, including: Obtaining quality test results corresponding to different test environment interval intensity levels for each process subsequence within several historical test cycles, performing statistical analysis on the quality test results, and obtaining the probability of quality test failure for each quality monitoring indicator of each process subsequence at different test environment interval intensity levels; According to the probability of quality test failure of each quality monitoring indicator of each process subsequence at different test environment interval intensity levels, each quality monitoring indicator of each process subsequence is divided into stable indicators and unstable indicators; Determine whether each process subsequence has unstable indicators. If no unstable indicators exist in the process subsequence, select the lowest test environment interval strength level as the quality test content of the process subsequence. If unstable indicators exist in the process subsequence, screen out the maximum quality test failure probability of the unstable indicators at different test environment interval strength levels, and obtain the test environment interval strength level corresponding to the maximum quality test failure probability as the quality test content of the process subsequence; The data analysis module is used to perform stability analysis on process subsequences whose quality monitoring indicators are marked as qualified, including: If all quality monitoring indicators of the process subsequence are marked as qualified, then the test data time series sequence of each stability indicator in the current test cycle is obtained, and the stability analysis coefficient of each stability indicator is obtained based on the test data time series sequence; Similarly, a test data time series sequence of each instability indicator in the current test cycle is obtained, and a stability analysis coefficient of each instability indicator is obtained based on the test data time series sequence; Sending the stability analysis coefficients of each stability index and instability index of the process subsequence to the reliability decision model building module; The reliability decision model building module is used to build a reliability decision model and analyze and make decisions on the stability analysis coefficients of each stability index and instability index of the received process subsequence, including: A reliability decision model is constructed based on the stability analysis coefficient of the stability index and the stability analysis coefficient of the instability index. The stability analysis coefficients of the stability index and the instability index of the process subsequence are input into the reliability decision model. The reliability analysis coefficient is output according to the reliability decision model. At the same time, the reliability analysis coefficient threshold of the process subsequence is obtained. The reliability analysis coefficient is compared with the reliability analysis coefficient threshold. If the reliability analysis coefficient is greater than or equal to the reliability analysis coefficient threshold, the process subsequence is marked as having qualified GOB process quality. If the reliability analysis coefficient is less than the reliability analysis coefficient threshold, the highest test environment interval intensity level is selected as the secondary quality test content corresponding to the process subsequence, and the LED display screen of each process subsequence is subjected to secondary quality testing according to the secondary quality test content, and the test data of each quality monitoring indicator of the process subsequence is obtained, and the test data is sent to the quality test monitoring module for analysis, and the cumulative time during which the test data of each quality monitoring indicator of the process subsequence is not located in the corresponding quality monitoring indicator threshold interval is obtained. If the cumulative time of the quality monitoring indicator of a process subsequence is greater than the cumulative time threshold, the process subsequence is marked as GOB process quality unqualified. If the cumulative time of each quality monitoring indicator of the process subsequence is less than or equal to the cumulative time threshold, the process subsequence is marked as GOB process quality qualified. The threshold analysis module is used to obtain the reliability analysis coefficient threshold of each process subsequence based on the test data in several historical test cycles of each process subsequence.

2. The GOB process quality assessment system for LED display screen processing according to claim 1 is characterized in that: The data acquisition module obtains the current GOB process information, divides the GOB process into several process sub-sequences, sets edge monitoring nodes according to the process information, and obtains test data of several quality monitoring indicators of each process sub-sequence according to the quality test content of each process sub-sequence, including the following process: Obtain the process flow characteristics of each current GOB process processing equipment, divide the GOB process flow into several process sub-sequences according to the process flow characteristics, set edge monitoring nodes in each process sub-sequence, and use data retrieval to obtain several quality monitoring indicators of each process sub-sequence according to the process flow characteristics of each process sub-sequence; The quality test content corresponding to each process subsequence is obtained, and the quality test content includes the intensity levels of different test environment intervals. The end timestamp of each process subsequence is used as the quality test time point. A test process sequence is constructed according to the quality test content and the quality test time point. The LED display screen of each process subsequence is quality tested according to the test process sequence, and test data of several quality monitoring indicators of each process subsequence is obtained. The edge monitoring node is used to obtain the test data of several quality monitoring indicators of the process subsequence and mark the test time, and set the test cycle.

3. The GOB process quality assessment system for LED display screen processing according to claim 2 is characterized in that: The quality test monitoring module monitors the test data time series of several quality monitoring indicators in the quality test of each process subsequence in real time. The process of obtaining the quality test results of each process subsequence includes: Setting threshold intervals for several quality monitoring indicators of each process subsequence according to the intensity level of the test environment interval corresponding to each process subsequence, obtaining a time series sequence of test data for several quality monitoring indicators of each process subsequence, comparing the time series sequence of test data for several quality monitoring indicators of each process subsequence with the corresponding quality monitoring indicator threshold intervals, obtaining the cumulative time during which the test data for each quality monitoring indicator of each process subsequence is not within the corresponding quality monitoring indicator threshold interval, and comparing the cumulative time for each quality monitoring indicator of each process subsequence with a preset cumulative time threshold; If the cumulative time of the quality monitoring indicators of a process subsequence is greater than the cumulative time threshold, the quality monitoring indicators of the process subsequence will be marked as unqualified in the quality test, and the process subsequence will be marked as unqualified in the GOB process quality. If the cumulative time of the quality monitoring indicators of the process subsequence is less than or equal to the cumulative time threshold, the quality monitoring indicators of the process subsequence will be marked as qualified in the quality test.

4. The GOB process quality assessment system for LED display screen processing according to claim 3 is characterized in that: The process of dividing each quality monitoring indicator of a process subsequence into stable indicators and unstable indicators includes: Obtain the maximum quality test failure probability and the minimum quality test failure probability of each quality monitoring indicator of the process subsequence in different test environment interval intensity levels, obtain the quality test failure probability difference between the maximum quality test failure probability and the minimum quality test failure probability of each quality monitoring indicator, compare the quality test failure probability difference of the quality monitoring indicator with a preset difference threshold, and if the quality test failure probability difference is less than or equal to the difference threshold, mark the quality monitoring indicator as a stable indicator; If the quality test failure probability difference of the quality monitoring indicator is greater than the difference threshold, the quality monitoring indicator is marked as an unstable indicator.

5. The GOB process quality assessment system for LED display screen processing according to claim 4 is characterized in that: The threshold analysis module obtains the reliability analysis coefficient threshold of each process subsequence based on the test data of several historical test cycles of each process subsequence, including: Obtain test data time series of each stability indicator and instability indicator of each process subsequence within several historical test cycles, screen out historical test cycles in which each process subsequence is marked as having unqualified GOB process quality from the several historical test cycles, and mark the historical test cycles as key historical test cycles; According to the test data time series sequence of each stability indicator of the process subsequence in a certain key historical test cycle, the stability analysis coefficient of the process subsequence in a certain key historical test cycle is obtained. Similarly, according to the test data time series sequence of each instability indicator of the process subsequence in a certain key historical test cycle, the instability analysis coefficient of the process subsequence in a certain key historical test cycle is obtained. The stability analysis coefficient and the instability analysis coefficient of the process subsequence in a certain key historical test cycle are sent to the reliability decision model construction module to obtain the reliability analysis coefficient of the process subsequence in a certain key historical test cycle. Similarly, the reliability analysis coefficient of each process subsequence in each key historical test cycle is obtained, and the reliability analysis coefficient of each process subsequence in each key historical test cycle is weighted averaged to obtain the reliability analysis coefficient threshold of each process subsequence.

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