A control method for waterproof furniture production equipment

Abstract

The present invention relates to the technical field of intelligent furniture production. The present invention provides a control method for waterproof furniture production equipment. The present invention obtains production and customer demand data, encodes production parameters, and uses genetic algorithms and simulated production models for intelligent optimization. The present invention realizes automation and high efficiency of the production process. The present invention not only ensures the waterproof performance of furniture, but also significantly reduces production costs and time costs, so that when enterprises produce new styles of waterproof furniture, the present invention can quickly adjust parameters and reduce testing links, thereby improving production efficiency and quality. The control method of the present invention has the characteristics of automation, high efficiency, low cost, etc., which brings significant economic benefits and market competitiveness to enterprises.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent furniture production, and in particular to a control method for waterproof furniture production equipment. Background Art

[0002] With the continuous advancement of science and technology, the automation of furniture production equipment has become an important trend in the development of the industry. Especially in the field of waterproof furniture production, the application of automation technology is particularly important. At present, the existing furniture automation production line has realized the full automation operation from raw material processing to finished product assembly through integrated robotic arms, sensors and control systems. The furniture automation production line can not only greatly improve production efficiency, but also ensure the stability and consistency of product quality to a certain extent, meeting the market's growing demand for refined furniture.

[0003] In the production process of waterproof furniture, the application of automation technology runs through the whole process. First, in the raw material processing stage, the automation equipment can accurately cut and polish the wood to ensure that each piece of material meets the production standards. Then, in the assembly process, the robot arm can accurately complete the splicing of each component. At the same time, the sensor monitors the various parameters of the production process in real time to ensure that each step of the operation is accurate. Finally, in the coating and waterproofing process, the automation equipment can evenly apply the waterproof material, thereby improving the waterproof performance and durability of the furniture. The whole process is not only efficient, but also greatly reduces the errors caused by human factors.

[0004] Although automation technology plays an important role in the production of waterproof furniture, there are still the following technical pain points that need to be solved: consumers' demand for waterproof furniture is dynamically changing. When new styles of waterproof furniture need to be produced, it is necessary to adjust parameters and test the automated production equipment for waterproof furniture, which increases production costs and time costs. For some complex furniture designs and special process requirements, it takes longer to adjust parameters and test the automated production equipment for waterproof furniture. Therefore, a control method for waterproof furniture production equipment is developed to improve the efficiency of parameter adjustment and testing of automated production equipment for waterproof furniture and reduce the maintenance cost of automated production equipment for waterproof furniture. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a control method for waterproof furniture production equipment to solve the problem that when new styles of waterproof furniture need to be produced, parameters of the waterproof furniture automated production equipment need to be adjusted and tested, which increases production costs and time costs.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0007] The present invention provides a control method for waterproof furniture production equipment, comprising:

[0008] Step S101, obtaining waterproof furniture production data, the waterproof furniture production data including waterproof furniture production quality standard data and waterproof furniture production customer demand data, the waterproof furniture production customer demand data including furniture size, furniture waterproof position, furniture outer wall contour shape, furniture structure design and furniture weight;

[0009] Step S102, collecting the real-time furniture production customer demand data of the waterproof furniture production equipment and the actual quality data of the furniture produced by the waterproof furniture production equipment in real time, performing error analysis on the real-time furniture production customer demand data and the quality data of the furniture produced in real time, and obtaining the real-time error of the waterproof furniture production equipment;

[0010] Step S103, substitute the real-time error of the waterproof furniture production equipment and the customer demand data of the waterproof furniture production into the preset simulation production model of the waterproof furniture production equipment to obtain the simulation result of the waterproof furniture production, substitute the customer demand data of the waterproof furniture production into the waterproof furniture production equipment for production to obtain the actual data of the produced waterproof furniture production equipment, perform error analysis on the simulation result of the waterproof furniture production and the actual data of the waterproof furniture production equipment to obtain the actual production error;

[0011] Step S104, adjusting the customer demand data for waterproof furniture production according to the actual production error to obtain actual parameter data for waterproof furniture production, substituting the actual parameter data for waterproof furniture production into the waterproof furniture production equipment to produce waterproof furniture, and obtaining the finished waterproof furniture;

[0012] Step S105, perform quality inspection on the finished waterproof furniture to obtain waterproof furniture quality inspection data. If the waterproof furniture quality inspection data is lower than the waterproof furniture production quality standard data, use a genetic algorithm to optimize the actual parameter data of the waterproof furniture production until the waterproof furniture quality inspection data meets the waterproof furniture production quality standard data.

[0013] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which comprises, in step S101:

[0014] The obtained waterproof furniture production quality standard data is stored in a database, and the waterproof furniture production quality standard data includes physical performance standards, chemical performance standards, density and thickness standards, durability standards, surface treatment standards, and coating thickness standards;

[0015] Acquire new furniture production quality standard data according to a preset time period, and replace the waterproof furniture production quality standard data stored in the database to obtain updated furniture production quality standard data;

[0016] The updated furniture production quality standard data is converted into a format to obtain the updated furniture production quality standard data in a standard format.

[0017] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which comprises, in step S102:

[0018] Pre-process the real-time furniture production customer demand data and the actual quality data of the waterproof furniture production equipment to obtain the real-time furniture pre-processed data;

[0019] Compare the customer demand data in the real-time furniture pre-processed data with the quality data of the produced furniture to obtain the difference data between the customer demand data in the real-time furniture pre-processed data and the quality data of the produced furniture;

[0020] Calculate the error between the customer demand data in the real-time furniture pre-processed data and the quality data of the produced furniture, obtain the real-time furniture error calculation result, and output the real-time furniture error calculation result;

[0021] Real-time furniture error calculation results include error value, size deviation, material error, and weight deviation.

[0022] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which comprises, in step S103:

[0023] Obtain historical production data of waterproof furniture production, including historical production demand, historical equipment parameters, various indicators in the historical production process, and historical product quality data;

[0024] Use the multivariate regression model to process and analyze historical production data to obtain the relationship data between independent variables and dependent variables. The independent variables include material properties, processing parameters, and equipment performance indicators, and the dependent variables include product quality and production time. Based on the relationship data between the independent variables and the dependent variables, the influence of each factor of the independent variable on the production results is obtained;

[0025] Based on historical production data and information on the degree of influence of various factors of independent variables on production results, the neural network model is trained. The production process of waterproof furniture is determined in the neural network model, including material preparation, processing, and quality inspection, to obtain a trained simulation production model of waterproof furniture production equipment.

[0026] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which in step S103 further includes:

[0027] Determine the error analysis indicators, which include comparison indicators, including the product's waterproof performance, size, weight, and furniture structure position;

[0028] Match each index in the waterproof furniture production simulation result with the corresponding index in the actual data of the waterproof furniture production equipment produced to obtain an error matching result;

[0029] Compare and analyze each pair of indicators in the error pairing results, and calculate the difference between the simulated value and the actual value. The error is calculated by calculating the absolute value of the difference between the simulated value and the actual value;

[0030] The calculated error values ​​are statistically analyzed, including the calculation of the average error, maximum error, and error distribution, to obtain the causes of the errors, which include model inaccuracy, random fluctuations in the production process, and differences in equipment performance.

[0031] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which comprises, in step S104:

[0032] Extract data features of actual production errors to obtain error feature information, and determine features to be adjusted based on the error feature information;

[0033] Perform data adjustment on the features to be adjusted to obtain a parameter combination data set after the data to be adjusted is adjusted;

[0034] The parameter combination data set after adjustment is substituted into the simulated production model of waterproof furniture production equipment for prediction, and compared with the actual production results to obtain the adjusted waterproof furniture product data. Among the adjusted waterproof furniture product data, the data features with the lowest error value compared with the actual production error are selected as the actual parameter data for waterproof furniture production.

[0035] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which comprises, in step S105:

[0036] Receive the quality inspection process and quality inspection index, and compare the received quality inspection index with the waterproof furniture production quality standard data. If the quality inspection index is higher than the waterproof furniture production quality standard data, the received quality inspection process and quality inspection index will take effect;

[0037] If the quality inspection index is lower than the waterproof furniture production quality standard data, the received quality inspection process and quality inspection index will be invalid;

[0038] Five pieces of waterproof furniture are randomly selected as test samples from the finished products. The test samples are tested according to the receiving quality inspection process and quality inspection indicators to obtain the quality inspection data of the waterproof furniture.

[0039] Furthermore, the present invention provides a control method for waterproof furniture production equipment, which in step S105 further includes:

[0040] Encode the actual parameters of waterproof furniture production to form individuals in the genetic algorithm;

[0041] A set of initial parameter data is randomly generated as the initial population, and each individual represents a set of optimized parameter combinations;

[0042] The waterproof furniture production equipment is used to simulate the production model for prediction, and the quality inspection data of the produced furniture is used to evaluate the fitness of each individual;

[0043] According to the fitness evaluation results, individuals with high fitness are selected as parents to generate the next generation population. Crossover operations are performed between the selected parent individuals to generate new offspring individuals. Genes in the offspring individuals are randomly mutated to introduce more genetic diversity.

[0044] The selection, crossover and mutation operations are performed repeatedly to generate a new population, and the fitness of the new population is evaluated, gradually approaching the optimal solution. When the termination condition is met, the algorithm stops iterating and outputs the optimal waterproof furniture production quality standard data.

[0045] Beneficial effects of the present invention;

[0046] Improvement of production efficiency: The present invention realizes intelligent control of waterproof furniture production equipment through data-driven parameter adjustment, real-time error analysis and simulation prediction, intelligent optimization algorithm and other means, and significantly improves production efficiency. This means that more products can be produced in the same amount of time to meet market demand.

[0047] Cost reduction: The present invention effectively reduces production costs by reducing trial and error costs, improving production efficiency, automating quality inspection, etc. At the same time, dynamically updating production standards also helps enterprises to continuously optimize the production process and further control costs.

[0048] Quality improvement: Through intelligent optimization algorithms and automated quality inspection processes, the present invention can ensure that the quality of waterproof furniture produced is stable and meets the latest market requirements and industry standards. This not only improves customer satisfaction, but also enhances the market competitiveness of enterprises.

[0049] Enhanced flexibility: The present invention uses historical data learning and model training to enable the production process to quickly adapt to the production needs of new styles. In addition, dynamically updating production standards also allows companies to flexibly respond to market changes and adjust production strategies in a timely manner.

[0050] In summary, the beneficial effects of the present invention include improving production efficiency, reducing costs, improving quality and enhancing flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 A schematic diagram of a method flow is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0053] 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.

[0054] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0055] The present invention provides a control method for waterproof furniture production equipment, comprising:

[0056] Step S101, obtaining waterproof furniture production data, the waterproof furniture production data including waterproof furniture production quality standard data and waterproof furniture production customer demand data, the waterproof furniture production customer demand data including furniture size, furniture waterproof position, furniture outer wall contour shape, furniture structure design and furniture weight;

[0057] In the process of waterproof furniture production, the first thing to do is to obtain comprehensive production data, which mainly includes two categories: waterproof furniture production quality standard data and waterproof furniture production customer demand data.

[0058] The waterproof furniture production quality standard data stipulates the standards that the waterproof performance of furniture should meet. It is a quality requirement that must be followed during the production process. It is usually stipulated by industry standards, internal corporate standards or relevant laws and regulations, and serves as an important basis for product quality control.

[0059] Waterproof furniture production customer demand data reflects customers' specific needs and preferences for furniture. They are key inputs for customized production and directly affect the design and manufacturing process of products. Customer demand data specifically includes the following:

[0060] Furniture size: The overall size of the furniture expected by the customer, including length, width, height, etc.

[0061] Furniture waterproofing positions: specific parts that require special strengthening of waterproofing treatment, such as the bottom, joints, etc.

[0062] Furniture outer wall contour shape: design requirements for furniture appearance, such as straight line, curve or other special shapes.

[0063] Furniture structural design: layout and design requirements of internal structures, such as storage space, supporting structure, etc.

[0064] Furniture weight: The customer's specific requirements for furniture weight may be subject to considerations of usage scenarios or handling restrictions.

[0065] Step S102, collecting the real-time furniture production customer demand data of the waterproof furniture production equipment and the actual quality data of the furniture produced by the waterproof furniture production equipment in real time, performing error analysis on the real-time furniture production customer demand data and the quality data of the furniture produced in real time, and obtaining the real-time error of the waterproof furniture production equipment;

[0066] Real-time furniture production customer demand data, during the production process, continuously collect customer demand data for furniture, including furniture size, waterproof position, outer wall contour shape, structural design and weight and other specific requirements. These data may be updated and obtained in real time through the production management system, customer order system or other information means.

[0067] By installing quality inspection equipment and sensors on the production line, various quality indicators of the furniture produced can be obtained in real time, such as waterproof performance, dimensional accuracy, structural stability, etc.

[0068] Compare the real-time collected furniture production customer demand data with the real-time produced furniture quality data to analyze the errors between the two. The errors may include size deviation, substandard waterproof performance, inconsistent structural design, etc.

[0069] Through error analysis software or algorithms, various errors are quantitatively evaluated to obtain the real-time error of waterproof furniture production equipment. The error value can be a comprehensive indicator or a collection of multiple single indicators, depending on the quality control requirements in the production process.

[0070] Step S103, substitute the real-time error of the waterproof furniture production equipment and the customer demand data of the waterproof furniture production into the preset simulation production model of the waterproof furniture production equipment to obtain the simulation result of the waterproof furniture production, substitute the customer demand data of the waterproof furniture production into the waterproof furniture production equipment for production to obtain the actual data of the produced waterproof furniture production equipment, perform error analysis on the simulation result of the waterproof furniture production and the actual data of the waterproof furniture production equipment to obtain the actual production error;

[0071] Use the preset waterproof furniture production equipment to simulate the production model. The model is built based on historical production data, equipment parameters, production process and other factors, and can predict the production results under given inputs.

[0072] The real-time error of waterproof furniture production equipment and customer demand data for waterproof furniture production are used as input and substituted into the simulation production model to obtain the simulation results of waterproof furniture production. This result predicts the possible production output under the current equipment status and customer demand.

[0073] Directly substitute the customer demand data of waterproof furniture production into the actual waterproof furniture production equipment for production. Record and collect the actual data generated during the production process, including various indicators and parameters of the produced furniture, which reflect the real production situation.

[0074] Compare the results of simulated production with the actual production data and analyze the difference between the two. By calculating the deviation between the two, the actual production error is obtained. The error reflects the degree of conformity between the simulated prediction and the actual production, and also reveals the possible problems or links that need to be improved in the production process.

[0075] Step S104, adjusting the customer demand data for waterproof furniture production according to the actual production error to obtain actual parameter data for waterproof furniture production, substituting the actual parameter data for waterproof furniture production into the waterproof furniture production equipment to produce waterproof furniture, and obtaining the finished waterproof furniture;

[0076] Adjust customer demand data: Based on the actual production error obtained in step S103, adjust the original waterproof furniture production customer demand data. The purpose of the adjustment is to reduce or eliminate the error in actual production so that the produced furniture better meets the actual needs of customers. The adjustment may involve fine-tuning of furniture size, waterproof position, outer wall contour shape, structural design or weight. These adjustments should be based on the results of error analysis and improve the deficiencies in the production process in a targeted manner.

[0077] Determine the actual parameter data for waterproof furniture production: After adjustment, new customer demand data for waterproof furniture production is obtained, which will be regarded as the actual parameter data for waterproof furniture production. The actual parameter data will be used as input for the next actual production.

[0078] Carry out waterproof furniture production: Substitute the adjusted actual parameter data of waterproof furniture production into the waterproof furniture production equipment. Start the production equipment and carry out actual waterproof furniture production according to these parameters.

[0079] Obtain finished waterproof furniture: After the production equipment completes the processing, the finished waterproof furniture will be obtained according to the adjusted customer demand data (ie, actual production parameter data).

[0080] Step S105, perform quality inspection on the finished waterproof furniture to obtain waterproof furniture quality inspection data. If the waterproof furniture quality inspection data is lower than the waterproof furniture production quality standard data, use a genetic algorithm to optimize the actual parameter data of the waterproof furniture production until the waterproof furniture quality inspection data meets the waterproof furniture production quality standard data.

[0081] Quality inspection: Conduct comprehensive quality inspection on the finished waterproof furniture, including but not limited to the waterproof performance, structural stability, appearance quality, etc. Through professional testing equipment and methods, collect and record the data of various quality indicators to form the quality inspection data of waterproof furniture.

[0082] Quality comparison and judgment: Compare the collected waterproof furniture quality test data with the preset waterproof furniture production quality standard data. If the waterproof furniture quality test data is lower than (i.e. does not reach or exceeds the allowable error range) the waterproof furniture production quality standard data, it means that the product quality is unqualified and needs to be optimized.

[0083] Parameter optimization: When product quality is unqualified, the genetic algorithm is used to optimize the actual parameter data of waterproof furniture production. Genetic algorithm is an optimization algorithm that simulates the principles of natural selection and genetics. It continuously iterates and selects excellent parameter combinations to find the optimal solution that can improve product quality.

[0084] During the optimization process, the actual parameter data of waterproof furniture production are encoded to form individuals in the genetic algorithm, and new parameter combinations are generated through operations such as selection, crossover, and mutation.

[0085] Iterative optimization and stop conditions: Use the optimized parameter data to produce waterproof furniture again and conduct quality inspection on the newly produced products. If the quality inspection data of the new product is still lower than the production quality standard, continue to optimize using the genetic algorithm. The iterative optimization process will continue until the quality inspection data of the waterproof furniture meets (i.e. reaches or exceeds) the production quality standard data of the waterproof furniture.

[0086] Stop optimization: When the quality inspection data of waterproof furniture meets the production quality standards, stop using the genetic algorithm for optimization, and save the current optimized production parameter data as a reference for subsequent production.

[0087] Specifically, the present invention provides a control method for waterproof furniture production equipment, which includes, in step S101:

[0088] The obtained waterproof furniture production quality standard data is stored in a database, and the waterproof furniture production quality standard data includes physical performance standards, chemical performance standards, density and thickness standards, durability standards, surface treatment standards, and coating thickness standards;

[0089] Acquire new furniture production quality standard data according to a preset time period, and replace the waterproof furniture production quality standard data stored in the database to obtain updated furniture production quality standard data;

[0090] The updated furniture production quality standard data is converted into a format to obtain the updated furniture production quality standard data in a standard format.

[0091] Specifically, the present invention provides a control method for waterproof furniture production equipment, which includes, in step S102:

[0092] Pre-process the real-time furniture production customer demand data and the actual quality data of the waterproof furniture production equipment to obtain the real-time furniture pre-processed data;

[0093] Compare the customer demand data in the real-time furniture pre-processed data with the quality data of the produced furniture to obtain the difference data between the customer demand data in the real-time furniture pre-processed data and the quality data of the produced furniture;

[0094] Calculate the error between the customer demand data in the real-time furniture pre-processed data and the quality data of the produced furniture, obtain the real-time furniture error calculation result, and output the real-time furniture error calculation result;

[0095] Real-time furniture error calculation results include error value, size deviation, material error, and weight deviation.

[0096] Specifically, the present invention provides a control method for waterproof furniture production equipment, which includes, in step S103:

[0097] Obtain historical production data of waterproof furniture production, including historical production demand, historical equipment parameters, various indicators in the historical production process, and historical product quality data;

[0098] Use the multivariate regression model to process and analyze historical production data to obtain the relationship data between independent variables and dependent variables. The independent variables include material properties, processing parameters, and equipment performance indicators, and the dependent variables include product quality and production time. Based on the relationship data between the independent variables and the dependent variables, the influence of each factor of the independent variable on the production results is obtained;

[0099] Based on historical production data and information on the degree of influence of various factors of independent variables on production results, the neural network model is trained. The production process of waterproof furniture is determined in the neural network model, including material preparation, processing, and quality inspection, to obtain a trained simulation production model of waterproof furniture production equipment.

[0100] Specifically, the present invention provides a control method for waterproof furniture production equipment, which, in step S103, also includes:

[0101] Determine the error analysis indicators, which include comparison indicators, including the product's waterproof performance, size, weight, and furniture structure position;

[0102] Match each index in the waterproof furniture production simulation result with the corresponding index in the actual data of the waterproof furniture production equipment produced to obtain an error matching result;

[0103] Compare and analyze each pair of indicators in the error pairing results, and calculate the difference between the simulated value and the actual value. The error is calculated by calculating the absolute value of the difference between the simulated value and the actual value;

[0104] The calculated error values ​​are statistically analyzed, including the calculation of the average error, maximum error, and error distribution, to obtain the causes of the errors, which include model inaccuracy, random fluctuations in the production process, and differences in equipment performance.

[0105] Specifically, the present invention provides a control method for waterproof furniture production equipment, which includes, in step S104:

[0106] Extract data features of actual production errors to obtain error feature information, and determine features to be adjusted based on the error feature information;

[0107] Perform data adjustment on the features to be adjusted to obtain a parameter combination data set after the data to be adjusted is adjusted;

[0108] The parameter combination data set after adjustment is substituted into the simulated production model of waterproof furniture production equipment for prediction, and compared with the actual production results to obtain the adjusted waterproof furniture product data. Among the adjusted waterproof furniture product data, the data features with the lowest error value compared with the actual production error are selected as the actual parameter data for waterproof furniture production.

[0109] Specifically, the present invention provides a control method for waterproof furniture production equipment, which includes, in step S105:

[0110] Receive the quality inspection process and quality inspection index, and compare the received quality inspection index with the waterproof furniture production quality standard data. If the quality inspection index is higher than the waterproof furniture production quality standard data, the received quality inspection process and quality inspection index will take effect;

[0111] If the quality inspection index is lower than the waterproof furniture production quality standard data, the received quality inspection process and quality inspection index will be invalid;

[0112] Five pieces of waterproof furniture are randomly selected as test samples from the finished products. The test samples are tested according to the receiving quality inspection process and quality inspection indicators to obtain the quality inspection data of the waterproof furniture.

[0113] Specifically, the present invention provides a control method for waterproof furniture production equipment, which, in step S105, further includes:

[0114] The optimization problem of actual parameter data of waterproof furniture production is defined as an optimization problem. The goal is to find a set of parameter values ​​so that the quality of the produced waterproof furniture meets or exceeds the production quality standards.

[0115] Encode the actual parameters of waterproof furniture production to form individuals in the genetic algorithm;

[0116] A set of initial parameter data is randomly generated as the initial population, and each individual represents a set of optimized parameter combinations;

[0117] The waterproof furniture production equipment is used to simulate the production model for prediction, and the quality inspection data of the produced furniture is used to evaluate the fitness of each individual;

[0118] According to the fitness evaluation results, individuals with high fitness are selected as parents to generate the next generation population. Crossover operations are performed between the selected parent individuals to generate new offspring individuals. Genes in the offspring individuals are randomly mutated to introduce more genetic diversity.

[0119] The selection, crossover and mutation operations are performed repeatedly to generate a new population, and the fitness of the new population is evaluated, gradually approaching the optimal solution. When the termination condition is met, the algorithm stops iterating and outputs the optimal waterproof furniture production quality standard data.

[0120] The present invention effectively solves the production cost and time cost problems faced in producing new styles of waterproof furniture. Specifically:

[0121] Data-driven parameter adjustment: The present invention first obtains the production data and customer demand data of waterproof furniture, thereby providing a solid foundation for subsequent parameter adjustment. The adjustment of production parameters of the present invention is no longer blind, but is based on actual data and customer demand, thereby improving the accuracy and efficiency of the adjustment.

[0122] Real-time error analysis and simulation prediction: By collecting production data and customer demand data in real time and performing error analysis, the present invention can quickly identify the difference between the current production status and the target status. At the same time, by using a preset simulation production model combined with real-time error data for simulation prediction, potential errors can be discovered in advance, thereby reducing the trial and error costs in actual production.

[0123] Intelligent optimization algorithm: The present invention uses genetic algorithm to intelligently optimize production parameters. By continuously iteratively adjusting production parameters, the quality of the produced furniture can gradually approach and reach the quality standard, reducing the time required for repeated testing and adjustment in the prior art.

[0124] Historical data learning and model training: Use historical production data to train the neural network model so that it can more accurately predict production results under different parameter combinations. This method enables the model to quickly adapt to the production needs of new styles, further improving production efficiency and quality.

[0125] Automated quality inspection process: Through the automated quality inspection process, the present invention reduces human intervention, improves inspection efficiency and accuracy, and thus ensures the stability of product quality. This not only reduces the cost of quality inspection, but also shortens the time to market for products.

[0126] Dynamically update production standards: The present invention also mentions updating production quality standard data at a preset time period to ensure that production always meets the latest market requirements and industry standards. This dynamic update mechanism makes the production process more flexible and adaptable to market changes.

[0127] In summary, the present invention effectively solves the production cost and time cost problems in the production of new styles of waterproof furniture through these specific methods, realizes intelligent control of waterproof furniture production equipment, improves production efficiency and reduces costs.

[0128] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-described embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A control method for waterproof furniture production equipment, characterized in that: include: Step S101, obtaining waterproof furniture production data, the waterproof furniture production data including waterproof furniture production quality standard data and waterproof furniture production customer demand data, the waterproof furniture production customer demand data including furniture size, furniture waterproof position, furniture outer wall contour shape, furniture structure design and furniture weight; Step S102, collecting the real-time furniture production customer demand data of the waterproof furniture production equipment and the actual quality data of the furniture produced by the waterproof furniture production equipment in real time, performing error analysis on the real-time furniture production customer demand data and the quality data of the furniture produced in real time, and obtaining the real-time error of the waterproof furniture production equipment; Step S103, substitute the real-time error of the waterproof furniture production equipment and the customer demand data of the waterproof furniture production into the preset simulation production model of the waterproof furniture production equipment to obtain the simulation result of the waterproof furniture production, substitute the customer demand data of the waterproof furniture production into the waterproof furniture production equipment for production to obtain the actual data of the produced waterproof furniture production equipment, perform error analysis on the simulation result of the waterproof furniture production and the actual data of the waterproof furniture production equipment to obtain the actual production error; Step S104, adjusting the customer demand data for waterproof furniture production according to the actual production error to obtain actual parameter data for waterproof furniture production, substituting the actual parameter data for waterproof furniture production into the waterproof furniture production equipment to produce waterproof furniture, and obtaining the finished waterproof furniture; Step S105, performing quality inspection on the waterproof furniture after production to obtain quality inspection data of the waterproof furniture. If the quality inspection data of the waterproof furniture is lower than the quality standard data of the waterproof furniture production, the genetic algorithm is used to optimize the actual parameter data of the waterproof furniture production until the quality inspection data of the waterproof furniture meets the quality standard data of the waterproof furniture production; In step S101, it includes: The obtained waterproof furniture production quality standard data is stored in a database, and the waterproof furniture production quality standard data includes physical performance standards, chemical performance standards, density and thickness standards, durability standards, surface treatment standards, and coating thickness standards; Acquire new furniture production quality standard data according to a preset time period, and replace the waterproof furniture production quality standard data stored in the database to obtain updated furniture production quality standard data; Convert the updated furniture production quality standard data into a format to obtain the updated furniture production quality standard data in a standard format; In step S102, it includes: Preprocessing the real-time furniture production customer demand data and the actual quality data of the waterproof furniture production equipment produced in real time to obtain the real-time furniture preprocessed data; Compare the customer demand data in the real-time furniture pre-processed data with the quality data of the produced furniture to obtain the difference data between the customer demand data in the real-time furniture pre-processed data and the quality data of the produced furniture; Calculate the error between the customer demand data in the real-time furniture pre-processed data and the quality data of the produced furniture, obtain the real-time furniture error calculation result, and output the real-time furniture error calculation result; Real-time furniture error calculation results include error value, size deviation, material error, and weight deviation; In step S103, it includes: Obtain historical production data of waterproof furniture production, including historical production demand, historical equipment parameters, various indicators in the historical production process, and historical product quality data; Use the multivariate regression model to process and analyze historical production data to obtain the relationship data between independent variables and dependent variables. The independent variables include material properties, processing parameters, and equipment performance indicators, and the dependent variables include product quality and production time. Based on the relationship data between the independent variables and the dependent variables, the influence of each factor of the independent variable on the production results is obtained; Based on historical production data and the information on the degree of influence of various factors of independent variables on production results, the neural network model is trained, and the production process of waterproof furniture, including material preparation, processing, and quality inspection, is determined in the neural network model to obtain a simulated production model of waterproof furniture production equipment after training; In step S103, it also includes: Determine the error analysis indicators, which include comparison indicators, including the product's waterproof performance, size, weight, and furniture structure position; Match each index in the waterproof furniture production simulation result with the corresponding index in the actual data of the waterproof furniture production equipment produced to obtain an error matching result; Compare and analyze each pair of indicators in the error pairing results, and calculate the difference between the simulated value and the actual value. The error is calculated by calculating the absolute value of the difference between the simulated value and the actual value; Perform statistical analysis on the calculated error values, including calculating the average error, maximum error, and error distribution, and obtaining the causes of the errors, which include model inaccuracy, random fluctuations in the production process, and differences in equipment performance; In step S104, it includes: Extract data features of actual production errors to obtain error feature information, and determine features to be adjusted based on the error feature information; Perform data adjustment on the features to be adjusted to obtain a parameter combination data set after the data to be adjusted is adjusted; Substitute the adjusted parameter combination data set of the data to be adjusted into the simulated production model of the waterproof furniture production equipment for prediction, and compare it with the actual production results to obtain the adjusted waterproof furniture product data, and select the data feature with the lowest error value compared with the actual production error from the adjusted waterproof furniture product data as the actual parameter data of waterproof furniture production; In step S105, it includes: Receive the quality inspection process and quality inspection index, and compare the received quality inspection index with the waterproof furniture production quality standard data. If the quality inspection index is higher than the waterproof furniture production quality standard data, the received quality inspection process and quality inspection index will take effect; If the quality inspection index is lower than the waterproof furniture production quality standard data, the received quality inspection process and quality inspection index will be invalid; Randomly select 5 pieces of waterproof furniture from the finished products as test samples, and test the test samples according to the receiving quality inspection process and quality inspection indicators to obtain the quality inspection data of waterproof furniture; In step S105, it also includes: Encode the actual parameters of waterproof furniture production to form individuals in the genetic algorithm; A set of initial parameter data is randomly generated as the initial population, and each individual represents a set of optimized parameter combinations; The waterproof furniture production equipment is used to simulate the production model for prediction, and the quality inspection data of the produced furniture is used to evaluate the fitness of each individual; According to the fitness evaluation results, individuals with high fitness are selected as parents to generate the next generation population. Crossover operations are performed between the selected parent individuals to generate new offspring individuals. Genes in the offspring individuals are randomly mutated to introduce more genetic diversity. The selection, crossover and mutation operations are performed repeatedly to generate a new population, and the fitness of the new population is evaluated, gradually approaching the optimal solution. When the termination condition is met, the algorithm stops iterating and outputs the optimal waterproof furniture production quality standard data.

Images