Manufacturing process for improving light-emitting display material

Abstract

The invention relates to the technical field of light-emitting display material manufacturing data processing, provides a light-emitting display material manufacturing process, and provides a brand-new solution for solving the problem that data in the manufacturing process cannot be effectively processed and analyzed to reduce errors in the prior art. A manufacturing process task is received, corresponding control parameters are generated, data generated when equipment executes the parameters are collected in real time, abnormal values and fluctuation data are processed through an optimization algorithm, the control parameters are adjusted, the effect is verified, if errors exceed a preset range, a digital twinborn model is constructed, and a simulation model is optimized through a genetic algorithm. According to the manufacturing method, the manufacturing error of the light-emitting display material is effectively reduced, the accuracy of the manufacturing process is remarkably improved, and the manufacturing method is suitable for manufacturing the light-emitting display material.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing for manufacturing luminescent display materials, and in particular to a method for improving the manufacturing process of luminescent display materials. Background Art

[0002] The manufacturing process of light-emitting display materials mainly includes the steps of substrate processing, thin film deposition and packaging. In the substrate processing stage, ITO glass is usually used as the substrate. Through strict cleaning and surface pretreatment processes, the cleanliness and flatness of the substrate are ensured to provide a good foundation for subsequent thin film deposition. Thin film deposition is the core of the manufacturing process of light-emitting display materials, which mainly includes two methods: vacuum evaporation and inkjet printing. Vacuum evaporation is to evaporate the organic material and deposit it on the substrate to form a thin film under a high vacuum environment, while inkjet printing is to accurately deposit the organic material solution on the substrate through an inkjet device. Finally, in the packaging stage, adhesives and covering materials are used to isolate the organic film and metal film from the outside water and air to protect the performance of the device and extend its service life. The entire production process needs to be carried out in a clean environment to ensure the quality and stability of the product.

[0003] In the process of reducing material errors through data processing in the production process of light-emitting display materials, there are the following technical pain points: Different luminescent materials have differences in properties such as luminous efficiency and service life, which directly affect the display quality of the image. The impact is particularly obvious during the production of large-size display screens. Existing technologies are unable to process and analyze the data generated during the production of luminescent display materials, thereby reducing the production errors of luminescent display materials. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a method for improving the production process of luminescent display materials, thereby solving the problem that the prior art cannot reduce the production error of the luminescent display materials by processing and analyzing the data generated during the production process of the luminescent display materials.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows: The present invention provides a process for improving the production of luminescent display materials, comprising: Step S101, receiving a light-emitting display material manufacturing process task, sending the light-emitting display material manufacturing process task to a preset light-emitting display material manufacturing process control model, outputting a light-emitting display material manufacturing process control parameter, sending the light-emitting display material manufacturing process control parameter to a light-emitting display material manufacturing device, collecting data generated by the light-emitting display material manufacturing device executing the light-emitting display material manufacturing process control parameter, and obtaining light-emitting display material manufacturing basic data; Step S102, performing data processing on the collected basic data for making luminescent display materials, identifying abnormal values ​​and fluctuations in the basic data for making luminescent display materials, obtaining abnormal value and fluctuation data in the basic data for making luminescent display materials, optimizing the abnormal value and fluctuation data in the basic data for making luminescent display materials using a preset optimization algorithm, and generating optimized basic data for making luminescent display materials; Step S103, adjusting the light-emitting display material production process control parameters according to the optimized data light-emitting display material production basic data to obtain adjusted light-emitting display material production process control parameters, sending the adjusted light-emitting display material production process control parameters to the light-emitting display material production equipment, collecting the light-emitting display material production operation data of the light-emitting display material production equipment executing the adjusted light-emitting display material production process control parameters, and obtaining the light-emitting display material production operation data; Step S104, substituting the adjusted light-emitting display material manufacturing process control parameters into a preset light-emitting display material manufacturing simulation model, outputting a light-emitting display material manufacturing simulation result, comparing the light-emitting display material manufacturing operation data with the light-emitting display material manufacturing simulation result, obtaining light-emitting display material manufacturing error data, and comparing the light-emitting display material manufacturing error data with a preset error range value; Step S105, if the error data of the production of the luminescent display material exceeds the preset error range value, the data generated when the data is processed in steps S101, S102, S103 and S104 is obtained to obtain a data set to be processed, and a digital twin model of the production process of the luminescent display material is constructed based on the data set to be processed, and a mirror model of the production process of the luminescent display material is established to obtain a mirror model group of the production process of the luminescent display material, and the error data of the production of the luminescent display material and the preset luminescent display material production simulation model are sequentially configured into the mirror model group of the production process of the luminescent display material, and a genetic algorithm is used to optimize the preset luminescent display material production simulation model in each mirror model group of the luminescent display material production process to obtain an optimized luminescent display material production simulation model, and the adjusted luminescent display material production process control parameters are processed using the optimized luminescent display material production simulation model to obtain optimized luminescent display material production process control parameters, and the optimized luminescent display material production process control parameters are sent to the luminescent display material production equipment.

[0006] Furthermore, in the process for improving the production of light-emitting display materials according to the present invention, step S101 comprises: The manufacturing process tasks of light-emitting display materials include the required material types, specifications, quantities and expected performance index information; The light-emitting display material manufacturing process control model is constructed based on historical data, empirical formulas and machine learning algorithms, and is used to generate corresponding manufacturing process control parameters according to task requirements. The light-emitting display material manufacturing process control model outputs the light-emitting display material manufacturing process control parameters according to the input light-emitting display material manufacturing process task. The light-emitting display material manufacturing process control parameters include temperature, pressure, time and material ratio; In the process of the luminescent display material manufacturing equipment executing the luminescent display material manufacturing process control parameters, the data generated by the real-time acquisition equipment includes temperature, pressure, time, current, voltage and material state change data to obtain the basic data of the luminescent display material manufacturing.

[0007] Furthermore, in the process for improving the production of light-emitting display materials according to the present invention, step S102 includes: Perform time series analysis on the data to identify fluctuation patterns in the data, and choose to delete, replace, or retain the identified outliers for marking; For fluctuating data, filtering, smoothing or prediction methods are used to reduce fluctuations and improve data stability. Preset optimization algorithms are selected, including genetic algorithms, particle swarm optimization and simulated annealing, to optimize the processed data. Through the processing of the optimization algorithm, the optimized basic data for the production of luminescent display materials is obtained.

[0008] Furthermore, in the process for improving the production of light-emitting display materials of the present invention, step S103 includes: According to the optimized data of light-emitting display material production basic data, determine the direction and amplitude of the light-emitting display material production process control parameters that need to be adjusted; In the light-emitting display material manufacturing process control model, according to the determined adjustment direction, the light-emitting display material manufacturing process control parameters are adjusted so that the adjusted parameter values ​​are within the acceptable range of the equipment and meet the requirements of the production process; The adjusted light-emitting display material manufacturing process control parameters are organized into a parameter set, and the adjusted light-emitting display material manufacturing process control parameters are sent to the light-emitting display material manufacturing device through the communication interface.

[0009] Furthermore, in the process for improving the production of light-emitting display materials of the present invention, step S104 comprises: Starting a preset simulation model for light-emitting display material production, performing simulation calculations according to the input adjusted light-emitting display material production process control parameters, and outputting simulation results of light-emitting display material production after the simulation model runs; The simulation results of the production of light-emitting display materials include product quality indicators, the influence of process parameters, and changes in the production process of light-emitting display materials; Comparing the simulation results of the production of the light-emitting display material with the production operation data of the light-emitting display material, the comparison content includes the difference between the actual value and the simulation value of the product quality index and the process parameter, and obtaining the comparison results of the simulation results of the production of the light-emitting display material and the production operation data of the light-emitting display material; According to the comparison result of the simulation result of the light-emitting display material production and the light-emitting display material production operation data, the error data of the light-emitting display material production is calculated, and the calculated production error data is compared with the preset error range value.

[0010] If the error data is within the preset error range, the adjustment of the light-emitting display material manufacturing process control parameters is effective, and the adjusted light-emitting display material manufacturing process control parameters are continued to be used for production.

[0011] Furthermore, in the process for improving the production of light-emitting display materials of the present invention, step S105 comprises: In the framework of the digital twin model, a mirror model of the manufacturing process of the luminescent display material is established based on the data set to be processed; according to different parts or stages of the manufacturing process, the mirror model is subdivided into multiple sub-models to form a mirror model group; The error data of luminescent display material production and the preset luminescent display material production simulation model are sequentially configured into each mirror model group, and the preset luminescent display material production simulation model in each luminescent display material production process mirror model group is optimized using a genetic algorithm, and the optimized simulation model is verified. If the verification result is satisfactory, the optimized luminescent display material production simulation model is used for subsequent data processing.

[0012] Furthermore, in the process for improving the production of light-emitting display materials according to the present invention, step S105 comprises: The specific steps of sequentially configuring the light-emitting display material manufacturing error data and the preset light-emitting display material manufacturing simulation model into the light-emitting display material manufacturing process mirror model group, and optimizing them using a genetic algorithm to finally obtain the optimized light-emitting display material manufacturing process control parameters are as follows: Importing the light-emitting display material manufacturing error data into the light-emitting display material manufacturing process mirror model group, and also loading the preset light-emitting display material manufacturing simulation model into the light-emitting display material manufacturing process mirror model group; Initializing the genetic algorithm and determining the objective function of the genetic algorithm, that is, the error between the simulation result of the light-emitting display material production and the operation data of the light-emitting display material production; Encoding the parameters in the preset simulation model for making luminescent display materials into a gene form that can be processed by a genetic algorithm, each gene represents a parameter in the simulation model for making luminescent display materials, and the combination of genes represents the parameter set of the entire simulation model for making luminescent display materials; Generate an initial population, use a random or specific method to generate an initial set of luminescent display material production simulation model parameter sets as the initial population of the genetic algorithm; each parameter set corresponds to a luminescent display material production simulation model for subsequent evaluation and optimization.

[0013] Evaluate population fitness: Each parameter set (i.e. each individual) in the initial population is evaluated and its fitness value is calculated.

[0014] The fitness value is based on the matching degree between the simulation result of the light-emitting display material production generated by the light-emitting display material production simulation model using the parameter set and the light-emitting display material production operation data; Performing the steps of evaluation, selection, crossover and mutation until a preset genetic generation is reached or an optimization result that meets the requirements is achieved. When the genetic algorithm iteration is completed, the individual with the highest fitness value is selected from the final population as the optimized light-emitting display material production simulation model, and the adjusted light-emitting display material production process control parameters are input into the optimized light-emitting display material production simulation model; The optimized light-emitting display material production simulation model performs simulation calculations based on the adjusted light-emitting display material production process control parameters to obtain prediction results of the optimized production process control parameters.

[0015] Beneficial effects of the present invention: The present invention can reduce the error in the production process of luminescent display materials through data processing and optimization algorithms, thereby improving production accuracy and enhancing the stability of product quality. By utilizing the optimization capabilities of simulation models and genetic algorithms, the present invention continuously adjusts and optimizes the production process control parameters, making the production process more sophisticated and efficient. By optimizing the production process, the present invention reduces material waste and defective product rate, thereby reducing production costs and improving economic benefits.

[0016] The present invention reduces manual intervention through automated and intelligent data processing and analysis, thereby improving production efficiency and shortening production cycles. The present invention provides a high-quality and efficient light-emitting display material manufacturing process, which helps enterprises gain an advantageous position in the fierce market competition and enhance market competitiveness.

[0017] The present invention applies advanced technologies such as data processing, optimization algorithms, simulation models and genetic algorithms to the production process of light-emitting display materials, promoting technological progress and innovative development in this field. By improving product quality and stability, the present invention meets customer expectations and needs, thereby enhancing customer satisfaction and trust in the product. The present invention reduces the impact on the environment by optimizing the production process and reducing material waste, conforming to the concept and requirements of sustainable development, and helping to promote the green and sustainable development of the industry.

[0018] In summary, the present invention has significant beneficial effects in improving the manufacturing process of light-emitting display materials, which not only improves product quality and production efficiency, but also promotes technological progress and sustainable development, bringing substantial benefits to enterprises and customers. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0020] Figure 1 A schematic diagram of a process for improving the manufacturing process of light-emitting display materials provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings. In order to better understand the purpose of the present invention, the present invention is further described in detail below.

[0022] The present invention provides a process for improving the production of luminescent display materials, comprising: Step S101, receiving a light-emitting display material manufacturing process task, sending the light-emitting display material manufacturing process task to a preset light-emitting display material manufacturing process control model, outputting a light-emitting display material manufacturing process control parameter, sending the light-emitting display material manufacturing process control parameter to a light-emitting display material manufacturing device, collecting data generated by the light-emitting display material manufacturing device executing the light-emitting display material manufacturing process control parameter, and obtaining light-emitting display material manufacturing basic data; Step S101: receiving a light-emitting display material manufacturing process task, and generating and executing corresponding manufacturing process control parameters.

[0023] Receiving task information: The system receives the luminescent display material production process task through the user interface or automation interface. These task information include the required material type (such as organic luminescent material, inorganic luminescent material, etc.), specifications (such as size, thickness, etc.), quantity and expected performance indicators (such as luminous efficiency, service life, color purity, etc.).

[0024] Task analysis: Detailed analysis of the received task information, extraction of key parameters and requirements, and provision of precise guidance for subsequent steps.

[0025] Construction and application of the process control model for light-emitting display materials; The light-emitting display material manufacturing process control model is built based on rich historical data, empirical formulas and advanced machine learning algorithms. This model can accurately generate corresponding manufacturing process control parameters based on the input task requirements. These parameters cover multiple aspects such as temperature, pressure, time and material ratio. Extensive data from historical production tasks are collected, including both successful cases and failed cases, to provide comprehensive samples for model training. The empirical formulas accumulated in the industry are effectively integrated into the model to further improve the practicality and accuracy of the model.

[0026] The model is trained and optimized using advanced machine learning algorithms such as neural networks and support vector machines, so that the model can automatically generate the optimal manufacturing process control parameters according to the task requirements. The parsed task information is accurately input into the light-emitting display material manufacturing process control model, and the model generates the corresponding manufacturing process control parameters based on this information.

[0027] The present invention sends the generated manufacturing process control parameters to the light-emitting display material manufacturing device through a communication interface (such as TCP / IP, serial communication, etc.). After receiving the control parameters, the light-emitting display material manufacturing device strictly performs the corresponding manufacturing process steps according to the parameter requirements, and these steps may include substrate processing, thin film deposition (such as vacuum evaporation and inkjet printing) and packaging.

[0028] In the process of executing the production process control parameters of the light-emitting display material production equipment, various data generated by the equipment are collected in real time. These data cover temperature, pressure, time, current, voltage, and material state change data (such as evaporation rate, deposition thickness, etc.). The collected data is properly stored in the database to facilitate subsequent data processing and analysis.

[0029] In order to continuously improve the accuracy and practicality of the model, the following lower-level technical solutions are used to train and optimize the model. The model is strictly trained using the cross-validation method to improve the generalization ability of the model. The model's hyperparameters are fine-tuned through grid search, random search and other methods to find the optimal combination of model parameters. New data is continuously collected during the production process, and the model is used for online learning so that the model can flexibly adapt to new production tasks and requirements.

[0030] In order to improve the accuracy and completeness of data, the following lower-level technical solutions are used to optimize data collection and monitoring: Effectively combine data from different sensors and devices to improve the overall accuracy of data. Use machine learning algorithms to detect anomalies in the collected data, and immediately trigger an alarm mechanism once abnormal data is found so that it can be processed in a timely manner.

[0031] Before data storage, the collected data is comprehensively cleaned and preprocessed, such as removing noise and filling missing values, to improve the accuracy of subsequent data analysis.

[0032] Step S102, performing data processing on the collected basic data for making luminescent display materials, identifying abnormal values ​​and fluctuations in the basic data for making luminescent display materials, obtaining abnormal value and fluctuation data in the basic data for making luminescent display materials, optimizing the abnormal value and fluctuation data in the basic data for making luminescent display materials using a preset optimization algorithm, and generating optimized basic data for making luminescent display materials; Identify outliers: Use statistical methods (such as Z-score, IQR, etc.) or machine learning algorithms (such as Isolation Forest) to effectively identify outliers in the data.

[0033] Handling outliers: Deletion: For obvious errors or outliers, delete them directly.

[0034] Replacement: Use the mean, median, or interpolation to make reasonable replacements.

[0035] Mark: Keep outliers marked for further analysis.

[0036] Data cleaning involves thorough removal of duplicate data. Missing values ​​can be filled using interpolation, mean filling, or prediction filling based on machine learning models.

[0037] Conduct in-depth time series analysis on data to accurately identify trends, seasonality, and cyclical components in the data. Use methods such as moving average and exponential smoothing to effectively remove random fluctuations in the data and improve the stability of the data.

[0038] Low-pass filtering: removes high-frequency noise and retains low-frequency signals.

[0039] Bandpass filtering: retains signals within a specific frequency range and removes noise at other frequencies.

[0040] Kalman filter: Especially suitable for data smoothing of dynamic systems, combining predicted and measured data to obtain the optimal estimate.

[0041] Fluctuation identification, accurately identifying fluctuation patterns in data through time series decomposition or statistical methods.

[0042] Reduced volatility; Smoothing: such as moving average and Savitzky-Golay filtering, which are used to effectively reduce short-term fluctuations in data.

[0043] Prediction method: Use time series prediction models (such as ARIMA, LSTM, etc.) to accurately predict future data and reduce the uncertainty caused by random fluctuations.

[0044] Carefully select appropriate optimization algorithms according to data characteristics and optimization goals, such as genetic algorithms, particle swarm optimization (PSO), simulated annealing (SA), etc.

[0045] Genetic Algorithm: Encoding: Encoding data or parameters into genetic form.

[0046] Initialize the population: Randomly generate a set of initial solutions as the population.

[0047] Fitness evaluation: Accurately calculate the fitness of each individual based on the optimization objective function.

[0048] Selection, crossover, and mutation: Generate a new generation of population through selection, crossover, and mutation operations.

[0049] Iteration: Repeat the above process until the preset genetic generation number is reached or the optimization goal is met.

[0050] Particle Swarm Optimization (PSO): Initialize the particle swarm: randomly generate a group of particles, each particle represents a solution.

[0051] Speed ​​update: timely update the particle speed according to the individual optimal solution and the global optimal solution.

[0052] Position Update: Update the particle's position based on its velocity.

[0053] Iteration: Repeat the velocity update and position update until the stop condition is met.

[0054] Simulated Annealing (SA): Initial solution: Randomly generate an initial solution.

[0055] Neighborhood search: Generate a new solution within the neighborhood of the current solution.

[0056] Acceptance criteria: Decide whether to accept the new solution based on the Metropolis criterion.

[0057] Cooling: Gradually reduce the temperature parameters.

[0058] Iteration: Repeat the neighborhood search, acceptance criteria, and cooling process until the stopping condition is met.

[0059] After being processed by the optimization algorithm, the optimized basic data for the production of luminescent display materials is finally obtained.

[0060] Step S103, adjusting the light-emitting display material production process control parameters according to the optimized data light-emitting display material production basic data to obtain adjusted light-emitting display material production process control parameters, sending the adjusted light-emitting display material production process control parameters to the light-emitting display material production equipment, collecting the light-emitting display material production operation data of the light-emitting display material production equipment executing the adjusted light-emitting display material production process control parameters, and obtaining the light-emitting display material production operation data; Based on the optimized basic data of light-emitting display material production, the effects of current production process control parameters can be accurately evaluated, and the direction and magnitude of adjustment can be determined.

[0061] Establish evaluation indicators: According to the characteristics of the production of luminescent display materials, establish a series of evaluation indicators, such as material deposition rate, film uniformity, luminous efficiency, etc. These indicators can comprehensively reflect the effect of the production process.

[0062] Comparative analysis: Conduct a detailed comparative analysis of the optimized basic data with the preset standard data. Through statistical methods and visualization tools, identify the differences between various evaluation indicators and the standard values, and provide a basis for subsequent parameter adjustments.

[0063] Based on the evaluation results, the specific adjustment strategy for the control parameters of the light-emitting display material manufacturing process is determined to improve the effect of the manufacturing process.

[0064] Rule library establishment: Based on historical data and expert experience, a library containing adjustment rules is established. Each rule should clearly describe how to adjust the corresponding manufacturing process control parameters when a certain evaluation indicator deviates from the standard value, such as the adjustment range and adjustment direction.

[0065] Rule matching and execution: According to the evaluation results, the corresponding adjustment rules are matched in the rule library, and the adjusted manufacturing process control parameters are generated. This step can be achieved through automated algorithms to improve adjustment efficiency and accuracy.

[0066] On the premise that the adjusted parameter values ​​are within the acceptable range of the equipment and meet the production process requirements, the production process control parameters are finely adjusted to further improve the production quality.

[0067] Before adjusting the parameters, first verify whether the adjusted parameter value is within the acceptable range of the device. If it is out of range, appropriate adjustments need to be made, such as linear interpolation or limiting the maximum / minimum value, to ensure that the device can operate normally.

[0068] For key parameters, multiple rounds of iterative optimization can be used. In each round of iteration, the parameter value is further fine-tuned according to the production effect under the current parameters, and steps S101 to S104 are repeated until the best production effect is achieved. In this process, machine learning algorithms or optimization algorithms can be used to assist parameter adjustment to improve optimization efficiency.

[0069] The adjusted production process control parameters are organized into a parameter set and sent to the light-emitting display material production equipment through a communication interface to achieve real-time updating and application of the parameters.

[0070] The adjusted manufacturing process control parameters are sorted in the format required by the equipment to form a parameter set. This step requires ensuring that the format of the parameter set matches the interface specification of the equipment to avoid communication errors.

[0071] The correct configuration of the communication interface, including communication protocol, transmission rate, etc., is required to ensure that the parameter set can be sent to the production equipment accurately and timely. At the same time, an error handling mechanism needs to be established to deal with abnormal situations that may occur during the communication process.

[0072] Step S104, substituting the adjusted light-emitting display material manufacturing process control parameters into a preset light-emitting display material manufacturing simulation model, outputting a light-emitting display material manufacturing simulation result, comparing the light-emitting display material manufacturing operation data with the light-emitting display material manufacturing simulation result, obtaining light-emitting display material manufacturing error data, and comparing the light-emitting display material manufacturing error data with a preset error range value; First, start the pre-built and rigorously verified simulation model for the production of luminescent display materials. This simulation model must be able to simulate various physical and chemical changes in the production process of luminescent display materials, and reflect the impact of different process parameters on the quality of the final product.

[0073] The simulation model for the production of luminescent display materials adopts a physics-based modeling method, which is closely integrated with the working principle of organic light-emitting diodes (OLEDs). The model needs to consider key factors such as material evaporation rate, deposition thickness, and current density distribution, so as to establish a high-precision mathematical model.

[0074] The light-emitting display material manufacturing process control parameters (including temperature, pressure, time, material ratio, etc.) adjusted in step S103 are accurately input into the simulation model. These parameters are transmitted in a structured data format (such as JSON, XML, etc.) through the standardized input interface of the model to ensure that the simulation model can correctly parse and use these parameters for subsequent simulation calculations.

[0075] The simulation model for the production of luminescent display materials performs a series of complex calculations and simulations based on the input process control parameters, and finally outputs the simulation results of the production of luminescent display materials. These results should fully reflect the product quality indicators (such as luminous efficiency, color purity, service life, etc.), the influence of process parameters, and various changes in the production process.

[0076] To improve the speed and accuracy of calculations, simulation calculations can use high-performance computing technologies, such as parallel computing, distributed computing, etc. The simulation results should be output in an intuitive form (such as charts, reports, etc.) to facilitate subsequent analysis and comparison.

[0077] When the light-emitting display material manufacturing equipment is running according to the adjusted process control parameters, the actual operation data of the equipment needs to be collected in real time. These data should cover key information such as temperature, pressure, time, current, voltage, and material state changes.

[0078] High-precision sensors and data acquisition systems should be used to ensure data accuracy. At the same time, a data cache and preprocessing mechanism should be established to perform preliminary processing (such as denoising, filtering, etc.) on the collected data to improve the reliability and effectiveness of the data.

[0079] The simulation results are compared with the actual operation data in a comprehensive and detailed manner, including the differences between the actual values ​​and the simulated values ​​of product quality indicators and process parameters. Data comparison and statistical analysis methods (such as mean square error (MSE) and root mean square error (RMSE)) are used to quantify the differences between the simulation results and the actual operation data. At the same time, a comparison chart is drawn to intuitively show the differences and change trends between the two, providing strong support for subsequent analysis.

[0080] According to the comparison results, calculate the error data of the light-emitting display material production. These error data should be able to accurately reflect the degree of deviation between the simulation results and the actual operation data. Clearly define the error calculation formula and indicators (such as absolute error, relative error, etc.). By calculating these indicators, get the specific error data value. At the same time, classify and count the error data (such as by process parameters, equipment status, etc.) for subsequent analysis and improvement.

[0081] The calculated error data is compared with the preset error range value to determine whether the error is within an acceptable range.

[0082] The preset error range value should be reasonably determined according to the actual application requirements and process standards. When comparing, set a clear threshold or tolerance range. If the error data exceeds this range, the error is considered unacceptable and further adjustment and optimization are required.

[0083] Step S105, if the error data of the production of the luminescent display material exceeds the preset error range value, the data generated when the data is processed in steps S101, S102, S103 and S104 is obtained to obtain a data set to be processed, and a digital twin model of the production process of the luminescent display material is constructed based on the data set to be processed, and a mirror model of the production process of the luminescent display material is established to obtain a mirror model group of the production process of the luminescent display material, and the error data of the production of the luminescent display material and the preset luminescent display material production simulation model are sequentially configured into the mirror model group of the production process of the luminescent display material, and a genetic algorithm is used to optimize the preset luminescent display material production simulation model in each mirror model group of the luminescent display material production process to obtain an optimized luminescent display material production simulation model, and the adjusted luminescent display material production process control parameters are processed using the optimized luminescent display material production simulation model to obtain optimized luminescent display material production process control parameters, and the optimized luminescent display material production process control parameters are sent to the luminescent display material production equipment.

[0084] Collect all relevant data generated in steps S101 to S104, including but not limited to basic data of light-emitting display material production, abnormal value and fluctuation data, optimized data, adjusted production process control parameters, light-emitting display material production operation data and production error data.

[0085] The collected data is strictly cleaned to remove duplicate, redundant or erroneous data points to ensure the accuracy, consistency and reliability of the data. The cleaned data is integrated into a unified data set to be processed, providing a solid data foundation for the subsequent construction of the digital twin model.

[0086] Under the concept of digital twin, a mirror model framework of the manufacturing process of luminescent display materials is designed based on the data set to be processed. This framework should be able to fully and accurately reflect all links and stages of the actual manufacturing process.

[0087] Sub-model segmentation: The mirror model is further subdivided into multiple sub-models according to different parts or stages of the manufacturing process, such as substrate processing, thin film deposition, packaging, etc. Each sub-model is responsible for simulating the process and data changes of the corresponding stage, improving the precision and accuracy of the model.

[0088] The sub-models are organically combined to form a complete mirror model group. This model group should be able to comprehensively and systematically reflect the process and data flow of the entire light-emitting display material manufacturing process, providing strong support for subsequent optimization.

[0089] In the genetic algorithm, the error between the simulation results of the light-emitting display material production and the operation data of the light-emitting display material production is clearly taken as the objective function. The goal of optimization is to minimize this error and improve the accuracy and reliability of the simulation results.

[0090] Parameter encoding: Encode the parameters in the preset simulation model of light-emitting display materials into a gene form that can be processed by the genetic algorithm. Each gene represents a parameter in the simulation model, and the combination of genes represents the parameter set of the entire simulation model, providing a basis for the operation of the genetic algorithm.

[0091] Initial population generation: Use random or specific methods to generate a set of initial parameters of the simulation model for the production of luminescent display materials as the initial population of the genetic algorithm. Each parameter set corresponds to a possible simulation model for the production of luminescent display materials, providing a variety of starting points for subsequent optimization.

[0092] Fitness evaluation: Perform fitness evaluation on each parameter set (i.e. each individual) in the initial population and calculate its fitness value. The fitness value is based on the degree of match between the simulation results generated by the simulation model using the parameter set and the production and operation data of the luminescent display material, reflecting the quality of the individual.

[0093] Genetic operations: Perform genetic operations of selection, crossover, and mutation to gradually optimize individuals in the population. The selection operation retains individuals with high fitness, the crossover operation generates new individual combinations, and the mutation operation introduces new gene mutations to increase the diversity and optimization potential of the population.

[0094] Iterative optimization: Repeat the genetic operation until the preset genetic generation is reached or the optimization requirements are met (such as the error is less than the preset threshold). In each iteration, the population is updated according to the new fitness value to promote the evolution of the population in a better direction.

[0095] Verification of optimization results: After the genetic algorithm iteration is completed, the individual with the highest fitness value is selected from the final population as the optimized simulation model for the production of luminescent display materials. The optimized model is strictly verified to ensure that it can accurately simulate the actual production process and significantly reduce production errors.

[0096] Application of optimized manufacturing process control parameters Parameter input and simulation: Input the adjusted light-emitting display material manufacturing process control parameters into the optimized light-emitting display material manufacturing simulation model for simulation calculation. This step is the key link to verify the optimization effect.

[0097] Result output and analysis: The simulation model outputs the predicted results of the optimized manufacturing process control parameters, including product quality indicators, the impact of process parameters, etc. The predicted results are analyzed in depth to ensure that they meet the actual application requirements and process standards.

[0098] Parameter sending and execution: If the prediction results are satisfactory, the optimized production process control parameters will be sent to the light-emitting display material production equipment to execute the new production process.

[0099] Specifically, the process for improving the production of light-emitting display materials according to the present invention, step S101, comprises: The manufacturing process tasks of light-emitting display materials include the required material types, specifications, quantities and expected performance index information; The light-emitting display material manufacturing process control model is constructed based on historical data, empirical formulas and machine learning algorithms, and is used to generate corresponding manufacturing process control parameters according to task requirements. The light-emitting display material manufacturing process control model outputs the light-emitting display material manufacturing process control parameters according to the input light-emitting display material manufacturing process task. The light-emitting display material manufacturing process control parameters include temperature, pressure, time and material ratio; In the process of the luminescent display material manufacturing equipment executing the luminescent display material manufacturing process control parameters, the data generated by the real-time acquisition equipment includes temperature, pressure, time, current, voltage and material state change data to obtain the basic data of the luminescent display material manufacturing.

[0100] Task reception: The system receives light-emitting display material production process tasks from users or upstream systems. These tasks are sent in a structured data format (such as JSON, XML, etc.), which contains the required material type, specifications, quantity, and expected performance indicator information. The extracted key information is fed into the light-emitting display material manufacturing process control model. The light-emitting display material manufacturing process control model is built based on historical data, empirical formulas and machine learning algorithms (such as neural networks, decision trees, etc.), and can generate corresponding manufacturing process control parameters according to task requirements. The light-emitting display material manufacturing process control parameters include temperature, pressure, time and material ratio, which are crucial to the manufacturing quality and efficiency of light-emitting display materials.

[0101] During the process of executing the control parameters of the light-emitting display material manufacturing equipment, the system collects the data generated by the equipment in real time. The data generated by the real-time acquisition equipment includes temperature, pressure, time, current, voltage, and material state change data, which are used for subsequent data processing and analysis. During the data collection process, the system ensures the integrity and accuracy of the data to avoid manufacturing process deviations caused by data errors.

[0102] Specifically, the process for improving the production of light-emitting display materials according to the present invention, step S102, comprises: Perform time series analysis on the data to identify fluctuation patterns in the data, and choose to delete, replace, or retain the identified outliers for marking; For fluctuating data, filtering, smoothing or prediction methods are used to reduce fluctuations and improve data stability. Preset optimization algorithms are selected, including genetic algorithms, particle swarm optimization and simulated annealing, to optimize the processed data. Through the processing of the optimization algorithm, the optimized basic data for the production of luminescent display materials is obtained.

[0103] Time series analysis: Time series analysis is performed on the collected basic data of light-emitting display material production to identify fluctuation patterns and outliers in the data. Time series analysis uses methods such as sliding windows or autoregressive models to capture the changing trends and periodic fluctuations of data over time.

[0104] Outlier processing: For the identified outliers, select appropriate processing methods based on their impact on the overall data and the requirements of the manufacturing process. If the outlier is caused by equipment failure or operating error and has a significant impact on subsequent analysis, choose to delete the data point; if the outlier is representative or reflects a special process state, choose to replace it with the average or median of the adjacent data, or retain it but mark it for consideration in subsequent analysis.

[0105] Fluctuating data processing: For fluctuating data, filtering, smoothing or prediction methods are used to reduce fluctuations and improve data stability. Filtering methods include mean filtering, median filtering or Kalman filtering to smooth data and remove noise; smoothing methods use moving average or exponential smoothing to smooth data trends; prediction methods use time series prediction models, such as ARIMA models or LSTM neural networks, to predict and correct fluctuating data.

[0106] Application of optimization algorithm: Select a preset optimization algorithm, such as genetic algorithm, particle swarm optimization or simulated annealing, to optimize the processed data. The optimization algorithm uses the key indicators (such as luminous efficiency, uniformity, stability, etc.) in the production process of luminescent display materials as the objective function and finds the optimal solution through iterative calculation. During the optimization process, adjust the algorithm parameters (such as the crossover probability and mutation probability of the genetic algorithm) according to the data characteristics and algorithm performance to ensure the optimization effect.

[0107] Specifically, the process for improving the production of light-emitting display materials according to the present invention, step S103, comprises: According to the optimized data of light-emitting display material production basic data, determine the direction and amplitude of the light-emitting display material production process control parameters that need to be adjusted; In the light-emitting display material manufacturing process control model, according to the determined adjustment direction, the light-emitting display material manufacturing process control parameters are adjusted so that the adjusted parameter values ​​are within the acceptable range of the equipment and meet the requirements of the production process; The adjusted light-emitting display material manufacturing process control parameters are organized into a parameter set, and the adjusted light-emitting display material manufacturing process control parameters are sent to the light-emitting display material manufacturing device through the communication interface.

[0108] Control parameter adjustment strategy: Based on the optimized basic data of light-emitting display material production, determine the direction and magnitude of control parameter adjustment. This involves fine adjustment of key parameters such as temperature, pressure, time, and material ratio. The adjustment strategy is based on data analysis and process requirements to ensure that the adjusted parameters can improve the production quality and efficiency of light-emitting display materials.

[0109] Equipment compatibility considerations: When adjusting parameters in the control model, the acceptance range of the manufacturing equipment and the production process requirements must be fully considered. Ensure that the adjusted parameter values ​​not only meet the process standards, but also achieve optimal performance under the premise of stable operation of the equipment. This requires a deep understanding of the equipment performance and parameter adjustments based on the equipment specifications and limitations.

[0110] Parameter set organization and transmission: The adjusted light-emitting display material manufacturing process control parameters are organized into parameter sets to ensure the integrity and accuracy of the parameters. The parameter sets are sent to the light-emitting display material manufacturing equipment through the communication interface. The communication interface needs to support efficient and stable data transmission to ensure that the parameters can be accurately and timely communicated to the equipment.

[0111] Operation data collection and monitoring: After the equipment implements the new parameters, the operation data is collected in real time, including temperature, pressure, time, current, voltage, and material state changes. These data are used for subsequent data analysis, simulation comparison, and error calculation to verify whether the adjusted parameters achieve the expected results. At the same time, the operation data is monitored to detect and handle any abnormalities in a timely manner.

[0112] Specifically, the process for improving the production of light-emitting display materials according to the present invention, step S104, comprises: Starting a preset simulation model for light-emitting display material production, performing simulation calculations according to the input adjusted light-emitting display material production process control parameters, and outputting simulation results of light-emitting display material production after the simulation model runs; The simulation results of the production of light-emitting display materials include product quality indicators, the influence of process parameters, and changes in the production process of light-emitting display materials; Comparing the simulation results of the production of the light-emitting display material with the production operation data of the light-emitting display material, the comparison content includes the difference between the actual value and the simulation value of the product quality index and the process parameter, and obtaining the comparison results of the simulation results of the production of the light-emitting display material and the production operation data of the light-emitting display material; According to the comparison result of the simulation result of the light-emitting display material production and the light-emitting display material production operation data, the error data of the light-emitting display material production is calculated, and the calculated production error data is compared with the preset error range value.

[0113] If the error data is within the preset error range, the adjustment of the light-emitting display material manufacturing process control parameters is effective, and the adjusted light-emitting display material manufacturing process control parameters are continued to be used for production.

[0114] Start the preset simulation model for the production of luminescent display materials. This model is built based on advanced simulation technology and can accurately reflect the physical and chemical changes in the production process of luminescent display materials. Input the adjusted process control parameters of the luminescent display material production into the simulation model for simulation calculation. After the simulation model is completed, the simulation results of the luminescent display material production are output, including product quality indicators, the influence of process parameters, and changes in the production process.

[0115] The simulation results of the production of luminescent display materials are compared with the production operation data of luminescent display materials. The comparison covers the differences between the actual values ​​and simulation values ​​of product quality indicators (such as luminous efficiency, uniformity, stability, etc.) and process parameters. Through comparative analysis, we can intuitively understand the impact of the adjusted parameters on the production effect of luminescent display materials, providing a basis for subsequent error analysis.

[0116] According to the comparison results, the error data of the light-emitting display material production is calculated. The error data reflects the degree of deviation between the simulation results and the operating data. The calculated production error data is compared with the preset error range value to determine whether the error is within the acceptable range. If the error data is within the preset error range, it means that the adjustment of the control parameters of the light-emitting display material production process is effective, and the adjusted parameters can continue to be used for production; if the error exceeds the range, it is necessary to further adjust the parameters or optimize the simulation model to reduce the error.

[0117] Make optimization decisions based on the error analysis results. If the error is within an acceptable range, keep the current parameters unchanged and continue production; if the error is large, adjust the light-emitting display material manufacturing process control parameters or improve the simulation model according to the specific situation of the error data to improve the accuracy of the simulation and the precision of the production. At the same time, the results of the optimization decision are fed back to the relevant links so that the production plan and process flow can be adjusted in a timely manner.

[0118] Specifically, the process for improving the production of light-emitting display materials according to the present invention, step S105, comprises: In the framework of the digital twin model, a mirror model of the manufacturing process of the luminescent display material is established based on the data set to be processed; according to different parts or stages of the manufacturing process, the mirror model is subdivided into multiple sub-models to form a mirror model group; The error data of luminescent display material production and the preset luminescent display material production simulation model are sequentially configured into each mirror model group, and the preset luminescent display material production simulation model in each luminescent display material production process mirror model group is optimized using a genetic algorithm, and the optimized simulation model is verified. If the verification result is satisfactory, the optimized luminescent display material production simulation model is used for subsequent data processing.

[0119] Within the framework of the digital twin model, a digital twin model of the manufacturing process of the light-emitting display material is constructed based on the data set to be processed (including all the data generated in steps S101 to S104). The model is a virtual representation of the manufacturing process and can reflect the status and changes of the manufacturing process in real time. According to different parts or stages of the manufacturing process, the digital twin model is subdivided into multiple sub-models to form a mirror model group. Each sub-model corresponds to a specific part or stage of the manufacturing process for more detailed analysis and optimization.

[0120] The error data of light-emitting display material production and the preset simulation model of light-emitting display material production are sequentially configured into each mirror model group. The preset simulation model in each light-emitting display material production process mirror model group is optimized using a genetic algorithm. Genetic algorithm is an optimization algorithm based on the principle of biological evolution. Through operations such as selection, crossover and mutation, the model parameters are continuously iterated to minimize the error between the simulation results and the operating data. The optimization process includes initializing the genetic algorithm, determining the objective function (i.e., the error between the simulation results and the operating data), parameter encoding, generating the initial population, evaluating the fitness of the population, and performing operations such as selection, crossover and mutation until the preset genetic generation is reached or the optimization requirements are met.

[0121] The optimized simulation model performs simulation calculations based on the adjusted manufacturing process control parameters to obtain more accurate prediction results. The prediction results are compared with the actual operation data to verify the accuracy and reliability of the model. If the verification results are satisfactory, the optimized light-emitting display material production simulation model is used for subsequent data processing and production guidance. This includes sending the optimized production process control parameters to the light-emitting display material production equipment for a new round of production and verification to ensure the stability of the production process and product quality.

[0122] In the process of building and optimizing the digital twin model, full use is made of the error data of the light-emitting display material. These data reflect the actual deviations and fluctuations in the manufacturing process and provide an important basis for model optimization. By configuring the error data into the mirror model group and optimizing it using a genetic algorithm, the model parameters can be continuously adjusted to make the simulation results closer to the actual operation. At the same time, the error data can also be used to evaluate the accuracy and reliability of the model, providing a reference for subsequent model improvement and optimization.

[0123] Specifically, the process for improving the production of light-emitting display materials according to the present invention, step S105, comprises: The specific steps of sequentially configuring the light-emitting display material manufacturing error data and the preset light-emitting display material manufacturing simulation model into the light-emitting display material manufacturing process mirror model group, and optimizing them using a genetic algorithm to finally obtain the optimized light-emitting display material manufacturing process control parameters are as follows: Importing the light-emitting display material manufacturing error data into the light-emitting display material manufacturing process mirror model group, and also loading the preset light-emitting display material manufacturing simulation model into the light-emitting display material manufacturing process mirror model group; Initializing the genetic algorithm and determining the objective function of the genetic algorithm, that is, the error between the simulation result of the light-emitting display material production and the operation data of the light-emitting display material production; Encoding the parameters in the preset simulation model for making luminescent display materials into a gene form that can be processed by a genetic algorithm, each gene represents a parameter in the simulation model for making luminescent display materials, and the combination of genes represents the parameter set of the entire simulation model for making luminescent display materials; Generate an initial population, use a random or specific method to generate an initial set of luminescent display material production simulation model parameter sets as the initial population of the genetic algorithm; each parameter set corresponds to a luminescent display material production simulation model for subsequent evaluation and optimization.

[0124] Evaluate population fitness: Each parameter set (i.e. each individual) in the initial population is evaluated and its fitness value is calculated.

[0125] The fitness value is based on the matching degree between the simulation result of the light-emitting display material production generated by the light-emitting display material production simulation model using the parameter set and the light-emitting display material production operation data; Performing the steps of evaluation, selection, crossover and mutation until a preset genetic generation is reached or an optimization result that meets the requirements is achieved. When the genetic algorithm iteration is completed, the individual with the highest fitness value is selected from the final population as the optimized light-emitting display material production simulation model, and the adjusted light-emitting display material production process control parameters are input into the optimized light-emitting display material production simulation model; The optimized light-emitting display material production simulation model performs simulation calculations based on the adjusted light-emitting display material production process control parameters to obtain prediction results of the optimized production process control parameters.

[0126] The error data of the light-emitting display material manufacturing is imported into the mirror model group of the light-emitting display material manufacturing process. These data reflect the actual deviation and fluctuation in the manufacturing process, providing an important basis for model optimization. At the same time, the preset light-emitting display material manufacturing simulation model is also loaded into the mirror model group of the light-emitting display material manufacturing process for subsequent optimization work.

[0127] Genetic algorithm initialization: Initialize the genetic algorithm and determine the objective function of the genetic algorithm. The objective function is the error between the simulation results of the light-emitting display material production and the light-emitting display material production operation data. The optimization goal is to minimize this error.

[0128] Set the parameters of the genetic algorithm, such as population size, genetic generations, crossover probability, mutation probability, etc., to ensure the effectiveness and stability of the algorithm.

[0129] The parameters in the preset light-emitting display material production simulation model are encoded into a gene form that can be processed by the genetic algorithm. Each gene represents a parameter in the light-emitting display material production simulation model, and the combination of genes represents the parameter set of the entire light-emitting display material production simulation model.

[0130] A set of initial parameters of the simulation model for the production of luminescent display materials is generated by random or specific methods as the initial population of the genetic algorithm. Each parameter set corresponds to a simulation model for the production of luminescent display materials for subsequent evaluation and optimization.

[0131] Fitness evaluation: Each parameter set (i.e., each individual) in the initial population is evaluated and its fitness value is calculated. The fitness value is based on the degree of match between the simulation results generated by the luminescent display material production simulation model using the parameter set and the luminescent display material production operation data. The higher the degree of match, the greater the fitness value.

[0132] Selection, crossover and mutation operations: According to the fitness value, individuals with higher fitness are selected as parents, and crossover and mutation operations are performed to generate new offspring individuals.

[0133] The crossover operation generates offspring individuals with new characteristics by exchanging some genes of parent individuals.

[0134] The mutation operation increases the diversity of the population and prevents the algorithm from falling into local lag by randomly changing certain genes of the offspring individuals.

[0135] The selection, crossover, and mutation steps are repeated until a preset number of genetic generations is reached or the optimization requirements are met.

[0136] Optimization result selection: After the genetic algorithm iteration is completed, the individual with the highest fitness value is selected from the final population as the optimized simulation model for the production of luminescent display materials. This model has the optimal parameter set and can produce simulation results that best match the operation data of the production of luminescent display materials.

[0137] Simulation calculation and prediction results: The adjusted light-emitting display material production process control parameters are input into the optimized light-emitting display material production simulation model.

[0138] The optimized simulation model performs simulation calculations based on the adjusted parameters to obtain the prediction results of the optimized manufacturing process control parameters. This prediction result can be used to guide subsequent production practices, reduce manufacturing errors, and improve product quality.

[0139] The present invention provides a technical solution for improving the manufacturing process of a luminescent display material, aiming to solve the problem that the prior art cannot reduce the manufacturing error of the luminescent display material by processing and analyzing the data generated in the manufacturing process of the luminescent display material.

[0140] Receive the luminescent display material production process task including material type, specification, quantity and expected performance indicators. Send the luminescent display material production process task information to the preset luminescent display material production process control model. The luminescent display material production process control model generates luminescent display material production process control parameters such as temperature, pressure, time, material ratio, etc. based on historical data, empirical formulas and machine learning algorithms.

[0141] The control parameters of the light-emitting display material production process are sent to the production equipment, and the data generated during the execution process, such as temperature, pressure, time, current, voltage and material state change data, are collected as basic production data.

[0142] Perform time series analysis on the collected basic production data to identify outliers and fluctuations. Use preset optimization algorithms, such as genetic algorithms, particle swarm optimization, simulated annealing, etc., to optimize these outliers and fluctuation data to generate optimized data. This step aims to improve the accuracy and reliability of the data and provide a basis for subsequent control parameter adjustments.

[0143] According to the optimized data, adjust the manufacturing process control parameters to ensure that these parameter values ​​are within the acceptable range of the equipment and meet the production process requirements. Send the adjusted control parameters to the manufacturing equipment again, and collect the number of runs after execution. Compare these run data with the simulation results of the preset light-emitting display material production simulation model to calculate the production error data. This step is used to verify whether the adjusted control parameters have effectively reduced the production error.

[0144] If the error data exceeds the preset range, it means that the current manufacturing process and control parameters still need to be further optimized. At this time, a digital twin model of the manufacturing process of the light-emitting display material is constructed, and a mirror model group is established. The error data and the simulation model are configured into the mirror model group, and the simulation model is optimized using a genetic algorithm. The genetic algorithm searches and finds the optimal or approximately optimal solution by simulating natural selection and genetic mechanisms, thereby optimizing the accuracy and predictive ability of the simulation model. The adjusted control parameters are processed using the optimized simulation model to obtain new optimized control parameters. These parameters can more accurately reflect the actual needs of the manufacturing process and reduce manufacturing errors. Finally, the new optimized control parameters are sent to the production equipment to guide the actual production process of the light-emitting display material.

[0145] Through the above steps, the present invention can realize comprehensive and in-depth processing and analysis of data generated in the process of manufacturing light-emitting display materials, thereby effectively reducing manufacturing errors and improving the accuracy of the manufacturing process.

Claims

1. A process for improving the production of luminescent display materials, characterized in that: include: Step S101, receiving a light-emitting display material manufacturing process task, sending the light-emitting display material manufacturing process task to a preset light-emitting display material manufacturing process control model, outputting a light-emitting display material manufacturing process control parameter, sending the light-emitting display material manufacturing process control parameter to a light-emitting display material manufacturing device, collecting data generated by the light-emitting display material manufacturing device executing the light-emitting display material manufacturing process control parameter, and obtaining light-emitting display material manufacturing basic data; Step S102, performing data processing on the collected basic data for making luminescent display materials, identifying abnormal values ​​and fluctuations in the basic data for making luminescent display materials, obtaining abnormal value and fluctuation data in the basic data for making luminescent display materials, optimizing the abnormal value and fluctuation data in the basic data for making luminescent display materials using a preset optimization algorithm, and generating optimized basic data for making luminescent display materials; Step S103, adjusting the light-emitting display material production process control parameters according to the optimized data light-emitting display material production basic data to obtain adjusted light-emitting display material production process control parameters, sending the adjusted light-emitting display material production process control parameters to the light-emitting display material production equipment, collecting the light-emitting display material production operation data of the light-emitting display material production equipment executing the adjusted light-emitting display material production process control parameters, and obtaining the light-emitting display material production operation data; Step S104, substituting the adjusted light-emitting display material manufacturing process control parameters into a preset light-emitting display material manufacturing simulation model, outputting a light-emitting display material manufacturing simulation result, comparing the light-emitting display material manufacturing operation data with the light-emitting display material manufacturing simulation result, obtaining light-emitting display material manufacturing error data, and comparing the light-emitting display material manufacturing error data with a preset error range value; Step S105, if the error data of the production of the luminescent display material exceeds the preset error range value, the data generated when the data is processed in steps S101, S102, S103 and S104 is obtained to obtain a data set to be processed, and a digital twin model of the production process of the luminescent display material is constructed based on the data set to be processed, and a mirror model of the production process of the luminescent display material is established to obtain a mirror model group of the production process of the luminescent display material, and the error data of the production of the luminescent display material and the preset luminescent display material production simulation model are sequentially configured into the mirror model group of the production process of the luminescent display material, and a genetic algorithm is used to optimize the preset luminescent display material production simulation model in each mirror model group of the luminescent display material production process to obtain an optimized luminescent display material production simulation model, and the adjusted luminescent display material production process control parameters are processed using the optimized luminescent display material production simulation model to obtain optimized luminescent display material production process control parameters, and the optimized luminescent display material production process control parameters are sent to the luminescent display material production equipment.

2. The process for improving the production of luminescent display materials according to claim 1, characterized in that: The step S101 includes: The manufacturing process tasks of light-emitting display materials include the required material types, specifications, quantities and expected performance index information; The light-emitting display material manufacturing process control model is constructed based on historical data, empirical formulas and machine learning algorithms, and is used to generate corresponding manufacturing process control parameters according to task requirements. The light-emitting display material manufacturing process control model outputs the light-emitting display material manufacturing process control parameters according to the input light-emitting display material manufacturing process task. The light-emitting display material manufacturing process control parameters include temperature, pressure, time and material ratio; In the process of the luminescent display material manufacturing equipment executing the luminescent display material manufacturing process control parameters, the data generated by the real-time acquisition equipment includes temperature, pressure, time, current, voltage and material state change data to obtain the basic data of the luminescent display material manufacturing.

3. The process for improving the production of luminescent display materials according to claim 1, characterized in that: The step S102 includes: Perform time series analysis on the data to identify fluctuation patterns in the data, and choose to delete, replace, or retain the identified outliers for marking; For fluctuating data, filtering, smoothing or prediction methods are used to reduce fluctuations and improve data stability. Preset optimization algorithms are selected, including genetic algorithms, particle swarm optimization and simulated annealing, to optimize the processed data. Through the processing of the optimization algorithm, the optimized basic data for the production of luminescent display materials is obtained.

4. The process for improving the production of luminescent display materials according to claim 1, characterized in that: The step S103 includes: According to the optimized data of light-emitting display material production basic data, determine the direction and amplitude of the light-emitting display material production process control parameters that need to be adjusted; In the light-emitting display material manufacturing process control model, according to the determined adjustment direction, the light-emitting display material manufacturing process control parameters are adjusted so that the adjusted parameter values ​​are within the acceptable range of the equipment and meet the requirements of the production process; The adjusted light-emitting display material manufacturing process control parameters are organized into a parameter set, and the adjusted light-emitting display material manufacturing process control parameters are sent to the light-emitting display material manufacturing device through the communication interface.

5. The process for improving the production of luminescent display materials according to claim 1, characterized in that: The step S104 includes: Starting a preset simulation model for light-emitting display material production, performing simulation calculations according to the input adjusted light-emitting display material production process control parameters, and outputting simulation results of light-emitting display material production after the simulation model runs; The simulation results of the production of light-emitting display materials include product quality indicators, the influence of process parameters, and changes in the production process of light-emitting display materials; Comparing the simulation results of the production of the light-emitting display material with the production operation data of the light-emitting display material, the comparison content includes the difference between the actual value and the simulation value of the product quality index and the process parameter, and obtaining the comparison results of the simulation results of the production of the light-emitting display material and the production operation data of the light-emitting display material; According to the comparison result of the simulation result of the light-emitting display material production and the light-emitting display material production operation data, the error data of the light-emitting display material production is calculated, and the calculated production error data is compared with the preset error range value. If the error data is within the preset error range, the adjustment of the light-emitting display material manufacturing process control parameters is effective, and the adjusted light-emitting display material manufacturing process control parameters are continued to be used for production.

6. The process for producing a light-emitting display material according to claim 1, characterized in that: The step S105 includes: In the framework of the digital twin model, a mirror model of the manufacturing process of the luminescent display material is established based on the data set to be processed; according to different parts or stages of the manufacturing process, the mirror model is subdivided into multiple sub-models to form a mirror model group; The error data of luminescent display material production and the preset luminescent display material production simulation model are sequentially configured into each mirror model group, and the preset luminescent display material production simulation model in each luminescent display material production process mirror model group is optimized using a genetic algorithm, and the optimized simulation model is verified. If the verification result is satisfactory, the optimized luminescent display material production simulation model is used for subsequent data processing.

7. The process for improving the production of luminescent display materials according to claim 6, characterized in that: The step S105 includes: The specific steps of sequentially configuring the light-emitting display material manufacturing error data and the preset light-emitting display material manufacturing simulation model into the light-emitting display material manufacturing process mirror model group, and optimizing them using a genetic algorithm to finally obtain the optimized light-emitting display material manufacturing process control parameters are as follows: Importing the light-emitting display material manufacturing error data into the light-emitting display material manufacturing process mirror model group, and also loading the preset light-emitting display material manufacturing simulation model into the light-emitting display material manufacturing process mirror model group; Initializing the genetic algorithm and determining the objective function of the genetic algorithm, that is, the error between the simulation result of the light-emitting display material production and the operation data of the light-emitting display material production; Encoding the parameters in the preset simulation model for making luminescent display materials into a gene form that can be processed by a genetic algorithm, each gene represents a parameter in the simulation model for making luminescent display materials, and the combination of genes represents the parameter set of the entire simulation model for making luminescent display materials; Generate an initial population, use a random or specific method to generate an initial set of luminescent display material production simulation model parameter sets as the initial population of the genetic algorithm; each parameter set corresponds to a luminescent display material production simulation model for subsequent evaluation and optimization. Evaluate population fitness: Each parameter set (i.e. each individual) in the initial population is evaluated and its fitness value is calculated. The fitness value is based on the matching degree between the simulation result of the light-emitting display material production generated by the light-emitting display material production simulation model using the parameter set and the light-emitting display material production operation data; Performing the steps of evaluation, selection, crossover and mutation until a preset genetic generation is reached or an optimization result that meets the requirements is achieved. When the genetic algorithm iteration is completed, the individual with the highest fitness value is selected from the final population as the optimized light-emitting display material production simulation model, and the adjusted light-emitting display material production process control parameters are input into the optimized light-emitting display material production simulation model; The optimized light-emitting display material production simulation model performs simulation calculations based on the adjusted light-emitting display material production process control parameters to obtain prediction results of the optimized production process control parameters.

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