GOB process quality evaluation system applied to LED display screen processing

Abstract

A GOB process quality evaluation system applying LED display screen processing relates to the technical field of GOB process quality evaluation, and obtains current GOB process flow information, sets edge monitoring nodes according to the process flow information, and obtains test data of a plurality of quality monitoring indexes of each process flow sub-sequence; monitoring the test data time sequence of the plurality of quality monitoring indexes of each process sub-sequence in real time to obtain a quality test result of each process sub-sequence; obtaining quality test content corresponding to each process sub-sequence according to the plurality of quality monitoring indexes of each process sub-sequence; carrying out stability analysis on the process subsequences of which the quality monitoring indexes are marked as qualified in the quality test; constructing a reliability decision model, and carrying out analysis decision on the stability analysis coefficients of each stable index and each unstable index of the received process sub-sequence; therefore, the efficiency and the accuracy of quality evaluation are remarkably improved.

Description

Technical Field

[0001] The 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] There are many technical problems in the existing GOB process quality assessment for LED display processing, including fixed test content, which cannot be adjusted dynamically according to actual conditions, and is difficult to adapt to changes in the production process. It lacks flexibility and cannot flexibly adjust the 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 is prone to misjudgment, weak decision support, lack of a reliable decision support system, and 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 object 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 with 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 flow information, divide the GOB process flow 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; 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 adaptive module is used to obtain the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence; The data analysis module is used to perform stability analysis on the process subsequences whose quality monitoring indicators are all marked as qualified for quality testing; The reliability decision model building module is used to build a reliability decision model to analyze and make decisions on the stability analysis coefficients of each stability index and instability index of the received process subsequence; 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.

[0004] Furthermore, the data acquisition module obtains the current GOB process flow information, divides the GOB process flow into several process sub-sequences, sets edge monitoring nodes according to the process information, and obtains the test data of several quality monitoring indicators of each process sub-sequence, including: 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 level 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.

[0005] 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, and the process of obtaining the quality test results of each process subsequence includes: According to the intensity level of the test environment interval corresponding to each process subsequence, several quality monitoring indicator threshold intervals of each process subsequence are set, test data time series sequences of several quality monitoring indicators of each process subsequence are obtained, the test data time series sequences of several quality monitoring indicators of each process subsequence are compared with the corresponding quality monitoring indicator threshold intervals, the accumulated time during which the test data of each quality monitoring indicator of each process subsequence is not located in the corresponding quality monitoring indicator threshold interval is obtained, and the accumulated time of each quality monitoring indicator of each process subsequence is compared with a preset accumulated 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 failing the quality test, and the process subsequence will be marked as failing 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 passing the quality test.

[0006] 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: Obtain quality test results corresponding to different test environment interval intensity levels of each process subsequence in several historical test cycles, perform statistical analysis on the quality test results, and obtain the probability of quality test failure of 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 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.

[0007] Furthermore, the process of dividing each quality monitoring indicator of the 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 strength 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.

[0008] Furthermore, the process of the data analysis module performing stability analysis on the process subsequences whose quality monitoring indicators are all marked as qualified for quality testing includes: If all quality monitoring indicators of the process subsequence are marked as qualified for the quality test, 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 according to the test data time series sequence; Similarly, the test data time series sequence of each unstable indicator in the current test cycle is obtained, and the stability analysis coefficient of each unstable indicator is obtained according to the test data time series sequence; The stability analysis coefficients of each stability index and instability index of the process subsequence are sent to the reliability decision model building module.

[0009] 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 each stability index and instability index of the received process subsequence includes: A reliability decision model is constructed according to the stability analysis coefficient of the stability index and the stability analysis coefficient of the unstable index, and the stability analysis coefficients of each stability index and unstable index of the process subsequence are input into the reliability decision model. The reliability analysis coefficient is output according to the reliability decision model, and the reliability analysis coefficient threshold of the process subsequence is obtained at the same time. 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 test 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 there is a process subsequence whose quality monitoring indicator has a cumulative time 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.

[0010] Furthermore, the process of the threshold analysis module obtaining the reliability analysis coefficient threshold of each process subsequence according to the test data in several historical test cycles of each process subsequence includes: Obtain test data time series of each stable indicator and unstable indicator of each process subsequence in several historical test cycles, select the historical test cycle marked as GOB process quality failure for each process subsequence from the several historical test cycles, and mark the historical test cycle as a key historical test cycle; 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.

[0011] Compared with the prior art, the beneficial effects of the present invention are: the present invention can discover potential problems earlier through real-time monitoring and data analysis, and improve the efficiency and accuracy of quality assessment by adaptively adjusting the test content. In addition, the construction of a reliability decision model makes the decision more scientific and reasonable, which helps to improve product quality and production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] 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

[0013] 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 creative work are within the scope of protection of the present application.

[0014] like Figure 1 As shown, the GOB process quality evaluation system for LED display screen processing includes a monitoring center, which is communicatively connected with 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 flow information, divide the GOB process flow 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; 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 adaptive module is used to obtain the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence; The data analysis module is used to perform stability analysis on the process subsequences whose quality monitoring indicators are all marked as qualified for quality testing; The reliability decision model building module is used to build a reliability decision model to analyze and make decisions on the stability analysis coefficients of each stability index and instability index of the received process subsequence; 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.

[0015] It should be further explained that, in the specific implementation process, the data acquisition module obtains the current GOB process flow information, divides the GOB process flow into several process sub-sequences, sets the edge monitoring node according to the process information, and obtains the test data of several quality monitoring indicators of each process sub-sequence. The process includes: 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; Among them, the process flow characteristics of each GOB process processing equipment include raw material preparation (PCB board, LED chip, solder, packaging material, etc.), tool preparation (prepare the required production equipment, such as SMT machine, welding equipment, coating equipment, etc.), chip positioning (use SMT machine to accurately place LED chip at the specified position on PCB board), pasting and fixing (use special adhesive to fix LED chip on PCB board), connecting LED chip with circuit on PCB board through welding technology, electrical testing (ensure that each LED chip is correctly connected to the circuit and functions normally), coating (use transparent epoxy resin or other protective materials to encapsulate the placed chip to protect the chip from external environment), curing (the packaging material needs to go through a certain curing process to ensure that the material is completely hardened), polishing, cleaning, etc.; Several quality monitoring indicators of each process sub-sequence include optical performance data (such as brightness, brightness uniformity, color temperature, color saturation, contrast, etc.) of LED display screens 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.; The quality test content corresponding to each process subsequence is obtained, and the quality test content includes the intensity level 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.

[0016] 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: Temperature range (for example: to simulate the working condition of the product in a high temperature environment, the test temperature range can be +50°C to +85°C; to simulate the working condition of the product in a low temperature environment, the test temperature range can be -20°C to -40°C; to simulate the performance of the product in an environment with rapid temperature changes, the test range usually includes the two extremes of high and low temperatures, such as from -40°C to +85°C), humidity range (for example: to simulate the working condition of the product in a high humidity environment, the test humidity range can be 85%RH to 95%RH), pressure range (for example: to simulate the performance of the product in a high altitude or vacuum environment, the test pressure range can be normal pressure to 0.1 atmospheres), light intensity range, electrostatic discharge (ESD) intensity range, vibration intensity range, impact intensity range, etc.

[0017] It should be further explained that, in the 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, and the process of obtaining the quality test results of each process subsequence includes: According to the intensity level of the test environment interval corresponding to each process subsequence, several quality monitoring indicator threshold intervals of each process subsequence are set, test data time series sequences of several quality monitoring indicators of each process subsequence are obtained, the test data time series sequences of several quality monitoring indicators of each process subsequence are compared with the corresponding quality monitoring indicator threshold intervals, the accumulated time during which the test data of each quality monitoring indicator of each process subsequence is not located in the corresponding quality monitoring indicator threshold interval is obtained, and the accumulated time of each quality monitoring indicator of each process subsequence is compared with a preset accumulated 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 failing the quality test, and the process subsequence will be marked as failing 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 passing the quality test.

[0018] It should be further explained that, in the specific implementation process, the process of the test content adaptation module obtaining the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence includes: Obtain quality test results corresponding to different test environment interval intensity levels of each process subsequence in several historical test cycles, perform statistical analysis on the quality test results, and obtain the probability of quality test failure of 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 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.

[0019] 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: 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 strength 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.

[0020] It should be further explained that, in the specific implementation process, the process of the data analysis module performing stable analysis on the process subsequences whose quality monitoring indicators are all marked as qualified for quality testing includes: If the quality test result of the process subsequence is that each quality monitoring indicator is marked as qualified for the quality test, 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 according to the test data time series sequence; Among them, the calculation formula of the stability analysis coefficient of each stability index is: ; in, represents the stability analysis coefficient of stability index i, represents the value of the test data time series of stability index i at the tth moment, N represents the total number of moments in the test cycle, Indicates the conversion factor; Similarly, the test data time series sequence of each unstable indicator in the current test cycle is obtained, and the stability analysis coefficient of each unstable indicator is obtained according to the test data time series sequence; The stability analysis coefficients of each stability index and instability index of the process subsequence are sent to the reliability decision model building module.

[0021] It should be further explained that, in the specific implementation process, the reliability decision model construction module constructs a reliability decision model, and the process of analyzing and deciding the stability analysis coefficients of each stability index and instability index of the received process subsequence includes: The 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 takes a value of 0.9. The stability analysis coefficients of 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 qualified for GOB process quality. If the reliability analysis coefficient is less than the reliability analysis coefficient threshold, the highest test environment interval strength 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 that the test data of each quality monitoring indicator of the process subsequence is not located in the corresponding quality monitoring indicator threshold interval, if there is a process subsequence The cumulative time of the quality monitoring indicator 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.

[0022] It should be further explained that, in a specific implementation process, the threshold analysis module obtains the reliability analysis coefficient threshold of each process subsequence according to the test data in several historical test cycles of each process subsequence, including: Obtain test data time series of each stable indicator and unstable indicator of each process subsequence in several historical test cycles, select the historical test cycle of each process subsequence marked as GOB process quality failure from the several historical test cycles of each process subsequence, and mark the historical test cycle as a key historical test cycle; 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.

[0023] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. 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 with 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 flow information, divide the GOB process flow 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; 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 adaptive module is used to obtain the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence; The data analysis module is used to perform stability analysis on the process subsequences whose quality monitoring indicators are all marked as qualified for quality testing; The reliability decision model building module is used to build a reliability decision model to analyze and make decisions on the stability analysis coefficients of each stability index and instability index of the received process subsequence; 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 evaluation system for LED display screen processing according to claim 1 is characterized in that: The data acquisition module obtains the current GOB process flow information, divides the GOB process flow into several process sub-sequences, sets edge monitoring nodes according to the process information, and obtains the test data of several quality monitoring indicators of each process sub-sequence, including: 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 the process flow characteristics of each process sub-sequence. Several quality monitoring indicators of the program sequence; The quality test content corresponding to each process subsequence is obtained, and the quality test content includes the intensity level 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 evaluation 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, and the process of obtaining the quality test results of each process subsequence includes: According to the intensity level of the test environment interval corresponding to each process subsequence, several quality monitoring indicator threshold intervals of each process subsequence are set, test data time series sequences of several quality monitoring indicators of each process subsequence are obtained, the test data time series sequences of several quality monitoring indicators of each process subsequence are compared with the corresponding quality monitoring indicator threshold intervals, the accumulated time during which the test data of each quality monitoring indicator of each process subsequence is not located in the corresponding quality monitoring indicator threshold interval is obtained, and the accumulated time of each quality monitoring indicator of each process subsequence is compared with a preset accumulated 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 failing the quality test, and the process subsequence will be marked as failing 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 passing the quality test.

4. The GOB process quality evaluation system for LED display screen processing according to claim 3 is characterized in that: The process of the test content adaptation module obtaining the quality test content corresponding to each process subsequence according to several quality monitoring indicators of each process subsequence includes: Obtain quality test results corresponding to different test environment interval intensity levels of each process subsequence in several historical test cycles, perform statistical analysis on the quality test results, and obtain the probability of quality test failure of 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 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.

5. The GOB process quality evaluation system for LED display screen processing according to claim 4 is characterized in that: The process of dividing each quality monitoring indicator of the 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 strength 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.

6. The GOB process quality evaluation system for LED display screen processing according to claim 5 is characterized in that: The process of the data analysis module performing stable analysis on the process subsequences whose quality monitoring indicators are all marked as qualified for quality testing includes: If all quality monitoring indicators of the process subsequence are marked as qualified for the quality test, 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 according to the test data time series sequence; Similarly, the test data time series sequence of each unstable indicator in the current test cycle is obtained, and the stability analysis coefficient of each unstable indicator is obtained according to the test data time series sequence; The stability analysis coefficients of each stability index and instability index of the process subsequence are sent to the reliability decision model building module.

7. The GOB process quality evaluation system for LED display screen processing according to claim 6 is characterized in that: 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 each stability index and instability index of the received process subsequence includes: A reliability decision model is constructed according to the stability analysis coefficient of the stability index and the stability analysis coefficient of the unstable index, and the stability analysis coefficients of each stability index and unstable index of the process subsequence are input into the reliability decision model. The reliability analysis coefficient is output according to the reliability decision model, and the reliability analysis coefficient threshold of the process subsequence is obtained at the same time. 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 test 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 there is a process subsequence whose quality monitoring indicator has a cumulative time 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.

8. The GOB process quality evaluation system for LED display screen processing according to claim 7 is characterized in that: The process of obtaining the reliability analysis coefficient threshold of each process subsequence according to the test data in several historical test cycles of each process subsequence by the threshold analysis module includes: Obtain test data time series of each stable indicator and unstable indicator of each process subsequence in several historical test cycles, select the historical test cycle marked as GOB process quality failure for each process subsequence from the several historical test cycles, and mark the historical test cycle as a key historical test cycle; 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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