Liquid crystal display module assembly line process control system

Abstract

The invention relates to the technical field of assembly line management, in particular to a liquid crystal display module assembly line process control system which comprises an assembly line management and control center, an initial setting unit, a data acquisition unit, a collaborative beat unit, an auxiliary assembly unit, an assembly operation unit, a processing verification unit and an execution response unit. According to the invention, through precise cooperation and beat balance supervision and intelligent adjustment of each process of the assembly line, the cooperation effect and beat balance of each process of the assembly line are improved, and through an information feedback mode, comprehensive monitoring and intelligent analysis of a glue solution material and a screw torque are further carried out. Meanwhile, the overall assembly performance of the assembly line is judged along with assembly operation evaluation performance and assembly risk fusion processing, the reasonability and effectiveness of a parameter adjustment strategy are ensured by generating the reference adjustment strategy and combining digital twinning virtual verification, and the adverse effect of blind adjustment on production is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of assembly line management, and in particular to a liquid crystal display module assembly line process control system. BACKGROUND

[0002] As the core component of various electronic devices, the assembly quality of the liquid crystal display module directly determines the display effect and reliability of the terminal product. With the rapid iteration of display technology towards high resolution, flexibility and narrow frame, the assembly process involves backlight module bonding, precise glue coating, screw tightening, circuit connection and other key processes, which puts forward strict requirements on the collaborative precision, beat balance and process parameter control of each process.

[0003] The current process control system of the liquid crystal display module assembly line still has the following significant technical defects: the traditional assembly line adopts a fixed beat rigid production mode, each process runs independently according to the preset parameters, lacks a dynamic collaboration mechanism, the existing system cannot quantitatively evaluate the overall performance of the assembly operation, lacks the ability to analyze the multi-dimensional risks such as operator skill differences, equipment aging trend and environmental fluctuations, and lacks auxiliary assembly monitoring of glue materials and screw torque, and in the face of abnormal fluctuations in the assembly process, the traditional adjustment method relies on the experience of engineers, lacks data support and virtual verification link.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The purpose of the present application is to provide a liquid crystal display module assembly line process control system to solve the above technical defects. The present application improves the collaborative effect and beat balance of each process of the assembly line through precise collaboration and beat balance monitoring and intelligent adjustment of each process of the assembly line, further monitors and intelligently analyzes the glue materials and screw torque through information feedback, and judges the overall assembly performance of the assembly line through the evaluation performance of the assembly operation and the fusion processing of the assembly risk, generates a reference adjustment strategy and combines digital twin virtual verification to ensure the rationality and effectiveness of the parameter adjustment strategy.

[0006] The purpose of the present application can be achieved by the following technical solution: a liquid crystal display module assembly line process control system, comprising an assembly line management center, an initial setting unit, a data acquisition unit, a collaborative beat unit, an auxiliary assembly unit, an assembly operation unit, a processing verification unit and an execution response unit.

[0007] The initial setting unit is used for parameter initialization, and the data acquisition unit is used for acquiring the real-time process beat time S of each assembly process in the assembly line and sending it to the assembly line management center for storage.

[0008] The cooperative rhythm unit is used for assembling rhythm cooperative supervision analysis on the real-time process rhythm time S, and the obtained rhythm deviation value is subjected to discrimination processing to obtain a regulation signal or a normal signal. When the regulation signal is based, a bottleneck process or a rich process is analyzed and obtained;

[0009] The auxiliary assembly unit is used for auxiliary assembly condition feedback analysis on the collected assembly material data in the assembly line assembly process to obtain an assembly fitting signal or an assembly defect signal.

[0010] The assembly operation unit is used for assembly operation performance evaluation analysis on the collected assembly raw data in the assembly line assembly process to obtain a warning signal or a normal signal.

[0011] Based on the generated assembly fitting signal and normal signal, fusion intersection analysis is performed to obtain an assembly stability signal or an assembly risk signal.

[0012] The processing verification unit is used for abnormal type processing verification analysis to determine whether the preset adjustment decision fits or not, and to obtain a verification failure signal or a verification success signal.

[0013] Preferably, the analysis process of the cooperative rhythm unit is as follows:

[0014] The running period of the assembly line of the liquid crystal display module is collected, the set initial rhythm reference value L0 and the real-time process rhythm time S of each assembly process in the running period are obtained, and the average process rhythm time PS of each assembly process is obtained based on the real-time process rhythm time S.

[0015] The difference between the average process rhythm time PS and the set initial rhythm reference value L0 is set as the rhythm deviation value, and the rhythm deviation value is subjected to discrimination processing to obtain a regulation signal or a normal signal.

[0016] Preferably, when the regulation signal is generated, the assembly process corresponding to the regulation signal is set as the to-be-adjusted process, the average process rhythm time PS greater than the set initial rhythm reference value L0 corresponding to the to-be-adjusted process is obtained, and the corresponding to-be-adjusted process is set as the bottleneck process. The to-be-adjusted process corresponding to the set initial rhythm reference value L0 is set as the rich process;

[0017] The assembly route of the bottleneck process in the running period is obtained, the pre-set alternative route of the bottleneck process is obtained, the rhythm deviation value of the pre-set alternative route is obtained, and the alternative route corresponding to the rhythm deviation value less than the pre-set rhythm deviation value threshold is set as the alternative route.

[0018] Based on the rich process, the part with the average process rhythm time PS less than the set initial rhythm reference value L0 is set as the rich duration, and the running speed set in the preset rich duration interval to which the rich duration belongs is obtained.

[0019] Preferably, the analysis process of the auxiliary assembly unit is as follows: obtaining assembly material data in the assembly process of the assembly line in the running period, the assembly material data including glue viscosity, coating amount, coating track, and performing one-by-one discrimination processing on the assembly material data to obtain comparison results of each parameter of the assembly material data, the comparison results including normal and abnormal, and analyzing the comparison results to obtain a material normal signal or a material abnormal signal.

[0020] Preferably, the torque-angle characteristic curve in the screw tightening process of the assembly line is collected, the peak torque and the final torque are obtained based on the torque-angle characteristic curve, and the peak torque and the final torque are discriminated to obtain a torque normal signal or a torque abnormal signal.

[0021] The generated material normal signal and torque normal signal are fused and fed back for analysis to obtain an assembly fitting signal or an assembly defect signal.

[0022] Preferably, the analysis process of the assembly operation unit is as follows:

[0023] Obtaining assembly original data in the assembly process of the assembly line in the running period;

[0024] Preprocessing the assembly original data;

[0025] Inputting the preprocessed assembly original data into a pre-set deep learning anomaly detection model to monitor whether there is an anomaly in the assembly process in real time, obtaining a warning signal or a normal signal, and simultaneously obtaining an abnormal type of the assembly line;

[0026] Fusing and intersecting the generated assembly fitting signal and normal signal for analysis to obtain an assembly stable signal or an assembly risk signal.

[0027] Preferably, the analysis process of the processing verification unit is as follows:

[0028] Obtaining an abnormal type of the assembly line and a preset adjustment decision corresponding to the abnormal type of the assembly line;

[0029] Constructing a digital twin model of the assembly line, synchronizing a parameter adjustment scheme to the digital twin model, and obtaining assembly actions of each assembly process in the digital twin model based on the preset adjustment decision;

[0030] Obtaining a fitting coefficient, a device load rate, and a product virtual quality based on the assembly actions;

[0031] And discriminating the fitting coefficient, the device load rate, and the product virtual quality to obtain a verification pass signal or a verification fail signal.

[0032] Preferably, the fitting coefficient represents the proportion of the fitting gap below the preset fitting gap threshold value;

[0033] The analysis process of the product virtual quality is that the sum of the process collaborative quality and the product qualification rate multiplied by the corresponding preset weight coefficient, and the process collaborative quality represents the sum of the bottleneck process and the rich process divided by the total number of processes.

[0034] The beneficial effects of the present application are as follows:

[0035] (1) The present application improves the collaborative effect and beat balance of each process of the assembly line through precise collaboration and beat balance monitoring and intelligent adjustment of each process of the assembly line, and simultaneously realizes rational management of the rich process and the bottleneck process;

[0036] (2) The present application further comprehensively monitors and intelligently analyzes the glue solution material and screw torque through the information feedback mode, realizes fine control of the liquid crystal display module assembly process, effectively reduces the quality defects caused by glue solution problems and improper screw fastening, improves the production efficiency and product reliability, and simultaneously realizes the fusion processing of the evaluation performance of the assembly operation and the assembly risk to judge the overall assembly performance of the assembly line;

[0037] (3) The present application deeply adjusts and manages the abnormal type of the assembly line in a self-adaptive manner, that is, generates a reference adjustment strategy and combines digital twin virtual verification to ensure the rationality and effectiveness of the parameter adjustment strategy, and avoids the adverse effects of blind adjustment on production. BRIEF DESCRIPTION OF DRAWINGS

[0038] The present application will be further described below with reference to the accompanying drawings;

[0039] Fig. 1 is a system flow chart of the present application;

[0040] Fig. 2 is a partial reference drawing of the first embodiment of the present application. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0042] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase "in an embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily all directed to the same embodiment, or to a single alternative embodiment. It is explicitly contemplated that embodiments described herein can be combined with each other, in whole or in part;

[0043] Embodiment one:

[0044] Referring to Figs. 1-2 The application is a liquid crystal display module assembly line process control system, which comprises an assembly line management and control center, an initial setting unit, a data acquisition unit, a collaborative rhythm unit, an auxiliary assembly unit, an assembly operation unit, a processing verification unit and an execution response unit. The assembly line management and control center is in bidirectional communication connection with the initial setting unit and the data acquisition unit, and in unidirectional communication connection with the collaborative rhythm unit. The collaborative rhythm unit is in unidirectional communication connection with the auxiliary assembly unit and the assembly operation unit. The auxiliary assembly unit is in unidirectional communication connection with the assembly operation unit. The assembly operation unit is in unidirectional communication connection with the processing verification unit and the execution response unit. The processing verification unit is in unidirectional communication connection with the execution response unit.

[0045] The initial setting unit is used for parameter initialization. According to the model specification of the liquid crystal display module to be assembled, the process parameter threshold value of each assembly process in the assembly line, the equipment operation parameter benchmark value and the like are preset.

[0046] The data acquisition unit is used for acquiring the real-time process rhythm time S of each assembly process in the assembly line and sending it to the assembly line management and control center for storage.

[0047] The collaborative rhythm unit is used for assembly rhythm collaborative supervision analysis on the retrieved real-time process rhythm time S. The specific assembly rhythm collaborative supervision analysis process is as follows:

[0048] The running time period of the assembly line of the liquid crystal display module is acquired.

[0049] The set initial rhythm benchmark value L0 and the real-time process rhythm time S of each assembly process in the assembly line in the running time period are acquired. The average process rhythm time PS of each assembly process is acquired based on the real-time process rhythm time S.

[0050] The difference between the average process cycle time PS and the set initial cycle reference value L0 is obtained, and the difference between the average process cycle time PS and the set initial cycle reference value L0 is set as a cycle deviation value, and the cycle deviation value is discriminated, if the cycle deviation value is greater than a preset cycle deviation value threshold, a control signal is generated, if the cycle deviation value is less than or equal to the preset cycle deviation value threshold, a normal signal is generated;

[0051] When the control signal is generated, the assembly process corresponding to the control signal is set as the to-be-adjusted process, the average process cycle time PS greater than the to-be-adjusted process corresponding to the set initial cycle reference value L0 is obtained, and the corresponding to-be-adjusted process is set as the bottleneck process, and the to-be-adjusted process corresponding to the set initial cycle reference value L0 is set as the surplus process;

[0052] The assembly route of the bottleneck process in the running period is obtained, the pre-set alternative route of the bottleneck process is obtained, the cycle deviation value of the pre-set alternative route is obtained, and the alternative route corresponding to the cycle deviation value less than the preset cycle deviation value threshold is set as the alternative route;

[0053] Based on the surplus process, the part of the average process cycle time PS less than the set initial cycle reference value L0 is obtained, and the part of the average process cycle time PS less than the set initial cycle reference value L0 is set as the surplus time length, the running speed set in the preset surplus time length interval to which the surplus time length belongs is obtained, and the response unit is used to respond to the alternative route or the running speed and execute the corresponding preset warning operation, so as to reasonably adjust the surplus process or the bottleneck process, and improve the collaborative effect and cycle balance of each process of the assembly line;

[0054] Wherein, the preset surplus time length interval is set in ascending order, and the running speed set in each preset surplus time length interval is set in descending order;

[0055] The present application improves the collaborative effect and cycle balance of each process of the assembly line through precise cooperation, cycle balance monitoring and intelligent adjustment of each process of the assembly line.

[0056] Embodiment two:

[0057] When the normal signal is generated, the auxiliary assembly unit is used for auxiliary assembly condition feedback analysis on the collected assembly material data in the assembly process of the assembly line, and the specific auxiliary assembly condition feedback analysis process is as follows:

[0058] The assembly material data in the assembly line assembly process in the running period is acquired, the assembly material data includes glue liquid viscosity, coating amount, coating track, etc., and the assembly material data is processed one by one to obtain comparison results of parameters of the assembly material data, the comparison results include normal and abnormal, if the comparison results of parameters of the assembly material data are all normal, a material normal signal is generated, if the comparison results of parameters of the assembly material data are not all normal, a material abnormal signal is generated;

[0059] The comparison results are as follows: if the glue liquid viscosity deviates from the preset glue liquid viscosity range, it is determined to be abnormal, if the glue liquid viscosity does not deviate from the preset glue liquid viscosity range, it is determined to be normal; if the coating amount belongs to the preset coating amount range, it is determined to be normal, if the coating amount does not belong to the preset coating amount range, it is determined to be abnormal; if the coating track has deviation from the preset coating track, it is determined to be abnormal, if the coating track has no deviation from the preset coating track, it is determined to be normal, and so on, and the comparison is made one by one;

[0060] The torque-angle characteristic curve in the screw tightening process of the assembly line is collected, the peak torque and the final torque are obtained based on the torque-angle characteristic curve, and the peak torque and the final torque are processed, if the peak torque belongs to the preset peak torque range and the final torque belongs to the preset final torque range, a torque normal signal is generated, if the peak torque does not belong to the preset peak torque range or the final torque belongs to the preset final torque range, a torque abnormal signal is generated;

[0061] The generated material normal signal and torque normal signal are fused and fed back for analysis, if the material normal signal and the torque normal signal are generated at the same time, an assembly fitting signal is obtained, if the material normal signal and the torque normal signal are not generated at the same time, an assembly defect signal is obtained;

[0062] The present application realizes fine control of the liquid crystal display module assembly process through comprehensive monitoring and intelligent analysis of glue liquid material and screw torque, effectively reduces quality defects caused by glue liquid problems and improper screw tightening, and improves production efficiency and product reliability;

[0063] The assembly operation unit is used for assembly operation performance evaluation analysis of the collected assembly raw data in the assembly line assembly process, and the specific assembly operation performance evaluation analysis process is as follows:

[0064] The assembly raw data in the assembly line assembly process in the running period is acquired, the assembly raw data includes assembly fitting pressure, fitting feature image, assembly equipment running speed, etc.

[0065] The assembly raw data is preprocessed, and the preprocessing includes data cleaning, standardization, feature extraction, etc.

[0066] The preprocessed assembly raw data is input into the pre-set deep learning anomaly detection model to monitor whether there is an anomaly in the assembly process in real time. If the output result of the pre-set deep learning anomaly detection model is abnormal, an early warning signal is generated, and the type of anomaly of the assembly line is obtained, including abnormal fitting pressure, position deviation anomaly, etc. If the output result of the pre-set deep learning anomaly detection model is normal, a normal signal is generated.

[0067] The generated assembly fitting signal and normal signal are fused and analyzed. If the assembly fitting signal and the normal signal are generated at the same time, an assembly stability signal is obtained. If the assembly fitting signal and the normal signal are not generated at the same time, an assembly risk signal is obtained.

[0068] The execution response unit is used to respond to the assembly stability signal or the assembly risk signal, and immediately make the preset early warning operation corresponding to the assembly stability signal or the assembly risk signal, so as to intuitively understand the overall assembly stability of the assembly line, and make reasonable management according to the feedback information.

[0069] The training process of the pre-set deep learning anomaly detection model:

[0070] Data set construction: collect historical normal assembly data and various types of abnormal assembly data (such as excessive / inadequate pressure, position deviation exceeding standard, etc.) to construct a training data set.

[0071] Data enhancement: time stretching, noise injection and other data enhancement processing are performed on the training data set to improve the generalization ability of the model.

[0072] Mixed training: the model is trained in a combination of labeled supervised learning (using known abnormal data to train the model to identify specific abnormalities) and unlabeled contrast learning (training the model to learn normal patterns from normal data to identify unknown abnormalities), so that the model can accurately identify known and unknown abnormalities.

[0073] Embodiment three:

[0074] When the early warning signal is generated, the processing verification unit is used for abnormal processing verification analysis of the type of anomaly. The specific abnormal processing verification analysis process is as follows:

[0075] The type of anomaly of the assembly line is obtained.

[0076] The preset adjustment decision corresponding to the type of anomaly of the assembly line is obtained.

[0077] A digital twin model of the assembly line is constructed, and the parameter adjustment scheme is synchronized to the digital twin model. Based on the preset adjustment decision, the assembly actions of each assembly process in the digital twin model are obtained, such as the movement of the mechanical arm according to the new trajectory and the output of the pressure device according to the new parameters.

[0078] Based on the assembly action, the fitting coefficient (the proportion value corresponding to the fitting gap lower than the preset fitting gap threshold), the equipment load rate and the product virtual quality are obtained;

[0079] The analysis process of the product virtual quality is: the sum value of the process coordination quality (the sum of the bottleneck process and the rich process divided by the total number of processes) and the product qualification rate multiplied by the corresponding preset weight coefficient;

[0080] The fitting coefficient, the equipment load rate and the product virtual quality are discriminated, if the fitting coefficient is greater than the preset fitting coefficient threshold, the equipment load rate is lower than the preset equipment load rate threshold, and the product virtual quality is greater than the preset product virtual quality threshold, a verification pass signal is generated, and the preset adjustment decision is sent to the assembly line by the response unit to control the assembly line to run according to the preset adjustment decision;

[0081] If the fitting coefficient is not greater than the preset fitting coefficient threshold, the equipment load rate is lower than the preset equipment load rate threshold, and the product virtual quality is greater than the preset product virtual quality threshold, a verification fail signal is generated;

[0082] The response unit responds to the verification fail signal, and displays the corresponding text of the verification fail signal to remind the operation and management personnel to further manage the assembly line;

[0083] The adaptive adjustment strategy combined with the digital twin virtual verification ensures the rationality and effectiveness of the parameter adjustment strategy, and avoids the adverse effects of blind adjustment on production;

[0084] In summary, the present application realizes fine control of the liquid crystal display module assembly process by precise coordination and beat balance supervision and intelligent adjustment of each process of the assembly line, effectively reduces quality defects caused by glue problems and improper screw tightening, improves production efficiency and product reliability, and further monitors and intelligently analyzes the glue material and screw torque through information feedback, judges the overall assembly performance of the assembly line, and adaptively adjusts the abnormal type of the assembly line, that is, generates a reference adjustment strategy and combines digital twin virtual verification to ensure the rationality and effectiveness of the parameter adjustment strategy, and avoids the adverse effects of blind adjustment on production.

[0085] The threshold is set for result comparison and analysis to determine whether it is good or bad, and the size of the threshold is determined by combining large model analysis of sample data and artificial experience to set the input storage, and can be appropriately adjusted by seasonal or rational influence conditions.

[0086] The size of the coefficient is a specific value obtained by quantizing each parameter, which is convenient for subsequent comparison. The size of the coefficient depends on how many sample data and the corresponding running coefficient preliminarily set by the person skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0087] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art within the technical range disclosed by the present application, according to the technical scheme and the inventive concept of the present application, equivalent replacement or change, should be covered within the protection scope of the present application.

Claims

1. A liquid crystal display module assembly line process control system, characterized by, The assembly line management and control center, the initial setting unit, the data acquisition unit, the collaborative beat unit, the auxiliary assembly unit, the assembly operation unit, the processing verification unit and the execution response unit are included. The initial setting unit is used for parameter initialization, and the data acquisition unit is used for acquiring real-time process beat time S of each assembly process in the assembly line and sending the real-time process beat time S to the assembly line management and control center for storage. The collaborative beat unit is used for assembly beat collaborative supervision analysis on the acquired real-time process beat time S, discriminant processing on the obtained beat deviation value, obtaining a regulation signal or a normal signal, and analyzing a bottleneck process or a rich process based on the regulation signal. The auxiliary assembly unit is used for auxiliary assembly condition feedback analysis on the collected assembly material data in the assembly process of the assembly line, obtaining an assembly fitting signal or an assembly defect signal. The assembly operation unit is used for assembly operation performance evaluation analysis on the collected assembly raw data in the assembly process of the assembly line, obtaining a warning signal or a normal signal. Based on the generated assembly fitting signal and the normal signal, fusion intersection analysis is performed to obtain an assembly stability signal or an assembly risk signal. The processing verification unit is used for abnormal processing verification analysis on the abnormal type, judges whether the preset adjustment decision fits, and obtains a verification failure signal or a verification success signal.

2. The liquid crystal display module assembly line process control system according to claim 1, wherein, The analysis process of the collaborative beat unit is as follows: The running time period of the liquid crystal display module assembly line is collected, the set initial beat reference value L0 and the real-time process beat time S of each assembly process in the assembly line in the running time period are obtained, the average process beat time PS of each assembly process is obtained based on the real-time process beat time S; The difference between the average process beat time PS and the set initial beat reference value L0 is set as the beat deviation value, and the beat deviation value is discriminant processed to obtain a regulation signal or a normal signal.

3. The liquid crystal display module assembly line process control system according to claim 2, wherein, When the regulation signal is generated, the assembly process corresponding to the regulation signal is set as the process to be adjusted, the process to be adjusted corresponding to the average process beat time PS greater than the set initial beat reference value L0 is obtained, and the corresponding process to be adjusted is set as the bottleneck process, and the process to be adjusted corresponding to the average process beat time PS less than the set initial beat reference value L0 is set as the rich process; The assembly route of the bottleneck process in the running time period is obtained, the pre-set alternative route of the bottleneck process is obtained, the beat deviation value of the pre-set alternative route is obtained, and the alternative route corresponding to the beat deviation value less than the pre-set beat deviation value threshold is set as the alternative route; Based on the rich process, the part with the average process beat time PS less than the set initial beat reference value L0 is set as the rich time length, and the running speed set in the pre-set rich time length interval to which the rich time length belongs is obtained.

4. The liquid crystal display module assembly line process control system according to claim 1, wherein, The analysis process of the auxiliary assembly unit is as follows: the assembly material data in the assembly process of the assembly line in the running time period is obtained, the assembly material data includes glue viscosity, coating amount and coating track, and the assembly material data is discriminant processed one by one, the comparison result of each parameter of the assembly material data is obtained, the comparison result includes normal and abnormal, the comparison result is analyzed, and a material normal signal or a material abnormal signal is obtained.

5. The liquid crystal display module assembly line process control system according to claim 4, wherein, The torque-angle characteristic curve in the screw tightening process of the assembly line is collected, the peak torque and the final torque are obtained based on the torque-angle characteristic curve, the peak torque and the final torque are subjected to discrimination processing, and a torque normal signal or a torque abnormal signal is obtained; The generated material normal signal and the torque normal signal are subjected to fusion feedback analysis, and an assembly fitting signal or an assembly defect signal is obtained.

6. The liquid crystal display module assembly line process control system according to claim 1, wherein, The analysis process of the assembly operation unit is as follows: Obtain the assembly raw data in the assembly process of the assembly line in the running period; The assembly raw data is preprocessed; The preprocessed assembly raw data is input into the pre-set deep learning anomaly detection model, the assembly process is monitored in real time to determine whether there is an anomaly, a warning signal or a normal signal is obtained, and the type of anomaly of the assembly line is obtained; The generated assembly fitting signal and normal signal are subjected to fusion intersection analysis, and an assembly stable signal or an assembly risk signal is obtained.

7. The liquid crystal display module assembly line process control system according to claim 1, wherein, The analysis process of the processing verification unit is as follows: Obtain the type of anomaly of the assembly line, obtain the preset adjustment decision corresponding to the type of anomaly of the assembly line; A digital twin model of the assembly line is constructed, a parameter adjustment scheme is synchronized to the digital twin model, assembly actions of each assembly process in the digital twin model are obtained based on the preset adjustment decision; Based on the assembly actions, a fitting coefficient, a device load rate and a product virtual quality are obtained; The fitting coefficient, the device load rate and the product virtual quality are subjected to discrimination processing, and a verification pass signal or a verification fail signal is obtained.

8. The liquid crystal display module assembly line process control system according to claim 7, wherein, The fitting coefficient represents the proportion value corresponding to the fitting gap being lower than the preset fitting gap threshold value; The analysis process of the product virtual quality: the sum of the process coordination quality and the product qualification rate multiplied by the corresponding preset weight coefficient, the process coordination quality represents the sum of the bottleneck process and the surplus process divided by the total number of processes.

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