Precision Secondary Molding Method for Plastic Products Based on 3D Printing Technology

Abstract

The present application provides a precise secondary forming method for plastic products based on 3D printing technology, which relates to the field of plastic forming technology. The method includes: collecting substrate specification information; performing index matching to obtain multiple secondary forming regions and multiple regional forming specification information, and collecting multiple thickness information and composition information; performing forming compensation difficulty analysis; allocating weights for secondary forming optimization and optimizing thermoforming parameters; performing secondary thermoforming, collecting multiple actual forming specification information, combining multiple regional forming specification information, and calculating multiple forming error specification information; performing forming compensation printing to obtain plastic products with secondary forming. Through the present application, the technical problem in the prior art that the accuracy of extracting the deviation to be repaired is relatively low, further affecting the quality of secondary forming, can be solved, the technical goal of improving the acquisition accuracy of repair deviation can be achieved, and the technical effect of improving the quality of secondary forming can be achieved.

Description

Technical Field

[0001] This application relates to the technical field of plastic molding, and particularly to a precise secondary molding method for plastic products based on 3D printing technology. Background Art

[0002] Secondary thermoforming of plastic substrates is an important part of the plastic product production process. The preformed plastic substrates are further heated and shaped to achieve the required shape and size.

[0003] Currently, during the secondary molding of existing plastic products, the shrinkage and deformation degrees of different thickness regions during thermoforming may vary, and different components may result in different shrinkage rates, thermal expansion coefficients and other characteristics, thus affecting the accuracy of secondary molding. At the same time, the lack of analysis of the difficulty of forming compensation may lead to the need to find the best repair solution through repeated tests and adjustments, which not only reduces the repair efficiency but also may reduce the success rate of repair. Therefore, a method is needed to solve the above problems.

[0004] In summary, in the prior art, there are technical problems that since most do not perform analysis on the difficulty of forming compensation based on the thickness information and component information of the secondary molding area, the accuracy of extracting the deviation to be repaired is relatively low, further affecting the quality of secondary molding. Summary of the Invention

[0005] The purpose of this application is to provide a precise secondary molding method for plastic products based on 3D printing technology to solve the technical problems in the prior art that since most do not perform analysis on the difficulty of forming compensation based on the thickness information and component information of the secondary molding area, the accuracy of extracting the deviation to be repaired is relatively low, further affecting the quality of secondary molding.

[0006] In view of the above problems, this application provides a precise secondary molding method for plastic products based on 3D printing technology.

[0007] The present application provides a precise secondary forming method for plastic products based on 3D printing technology. The method includes: collecting the substrate specification information of the plastic substrate to be secondarily formed, where the substrate specification information includes the size specification information of the plastic substrate; indexing and matching the substrate specification information according to the forming specification information of the secondary forming to obtain multiple secondary forming regions and multiple regional forming specification information, and collecting the thickness information and composition information of the multiple secondary forming regions on the plastic substrate; analyzing the forming compensation difficulty of the multiple regional forming specification information to obtain multiple forming compensation difficulty information; according to the multiple forming compensation difficulty information, allocating the weights for optimizing the secondary forming of the multiple secondary forming regions, and combining the multiple thickness information, multiple composition information and multiple regional forming specification information to optimize the thermoforming parameters of the multiple secondary forming regions to obtain the optimal thermoforming parameters, where the thermoforming parameters include forming temperature, forming speed and setting temperature; using the optimal thermoforming parameters to perform secondary thermoforming on the multiple secondary forming regions, and collecting multiple actual forming specification information after completion, and combining the multiple regional forming specification information to calculate multiple forming error specification information; according to the multiple forming error specification information, based on 3D printing, performing forming compensation printing to obtain the plastic products of the secondary forming.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] By collecting the substrate specification information of the plastic substrate to be secondary formed, where the substrate specification information includes the size specification information of the plastic substrate; indexing and matching the substrate specification information according to the forming specification information of the secondary forming to obtain multiple secondary forming areas and multiple area forming specification information, and collecting the thickness information and composition information of the multiple secondary forming areas on the plastic substrate; analyzing the forming compensation difficulty of the multiple area forming specification information to obtain multiple forming compensation difficulty information; according to the multiple forming compensation difficulty information, allocating the weights for optimizing the secondary forming of the multiple secondary forming areas, and combining the multiple thickness information, multiple composition information and multiple area forming specification information to optimize the thermoforming parameters of the multiple secondary forming areas to obtain the optimal thermoforming parameters, where the thermoforming parameters include forming temperature, forming speed and setting temperature; using the optimal thermoforming parameters to perform secondary thermoforming on the multiple secondary forming areas, and collecting multiple actual forming specification information after completion, and combining the multiple area forming specification information to calculate multiple forming error specification information; according to the multiple forming error specification information, performing forming compensation printing based on 3D printing to obtain the plastic products of the secondary forming, realizing the technical goal of improving the acquisition accuracy of the repair deviation and achieving the technical effect of improving the quality of the secondary forming.

[0010] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are given below. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. Brief Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0012] Figure 1 It is a schematic flow chart of the method for precise secondary forming of plastic products based on 3D printing technology of the present application;

[0013] Figure 2 It is a schematic flow chart of obtaining multiple secondary forming areas and multiple area forming specification information in the method for precise secondary forming of plastic products based on 3D printing technology of the present application. Detailed Description of the Embodiments

[0014] By providing a precise secondary forming method for plastic products based on 3D printing technology, this application solves the technical problem in the prior art that due to the lack of difficulty analysis of forming compensation based on the thickness information and composition information of the secondary forming area, the accuracy of the deviation to be repaired is relatively low, further affecting the quality of secondary forming. The technical goal of improving the acquisition accuracy of repair deviation is achieved, and the technical effect of improving the quality of secondary forming is achieved.

[0015] Next, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited by the example embodiments described here. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application. In addition, it should be noted that for the sake of description, only the parts related to this application are shown in the drawings, rather than all of them.

[0016] Embodiment 1

[0017] Please refer to the attached Figure 1 , this application provides a precise secondary forming method for plastic products based on 3D printing technology. Among them, the method specifically includes the following steps:

[0018] Step 1: Collect the substrate specification information of the plastic substrate to be subjected to secondary forming. Among them, the substrate specification information includes the dimensional specification information of the plastic substrate;

[0019] Specifically, the plastic substrate to be subjected to secondary forming refers to a plastic product formed by secondary thermoforming of the plastic substrate. For example, a plastic sheet is subjected to thermoforming and pressing using a mold to obtain a plastic with a preset shape, such as a basin and other products. Due to the forming size deviation, 3D printing is used to repair the error areas to complete secondary forming. Further, the substrate specification information of the plastic substrate is the dimensional specification of the plastic substrate. For example, it can be a three-dimensional model of the plastic substrate.

[0020] Step 2: According to the forming specification information of the secondary forming, perform index matching on the substrate specification information to obtain multiple secondary forming areas and multiple area forming specification information, and collect the thickness information and composition information of the multiple secondary forming areas on the plastic substrate;

[0021] Specifically, the coordinates are unified according to the substrate specification information and the forming specification information, and then indexing and matching are performed to obtain areas with different specifications, which are multiple areas that need secondary forming. Obtain the information on the specifications, thicknesses, and compositions of the multiple secondary forming areas for subsequent secondary forming. Among them, since the plastic on some plastic products may be unevenly formed, affecting the forming quality, the composition information includes the density of the plastic composition.

[0022] Step Three: Analyze the forming compensation difficulty of the forming specification information of the multiple areas to obtain multiple forming compensation difficulty information;

[0023] Specifically, according to the specification information of the multiple areas, analyze the difficulty of compensation after forming, and then obtain multiple forming compensation difficulty information. Among them, the more complex the forming area, the greater the forming compensation difficulty, and vice versa, the smaller it is.

[0024] Step Four: According to the multiple forming compensation difficulty information, allocate weights for optimizing the secondary forming of the multiple secondary forming areas, and combine multiple thickness information, multiple composition information, and multiple area forming specification information to optimize the thermoforming parameters of the multiple secondary forming areas to obtain the optimal thermoforming parameters, where the thermoforming parameters include forming temperature, forming speed, and setting temperature;

[0025] Specifically, allocate weights according to the multiple forming compensation difficulty information to reflect the difficulty of different areas in achieving the target specifications during thermoforming. Among them, the lower the difficulty, the greater the allocated weight, indicating that the deviation between the actual specifications of the multiple areas and the preset area specifications is easier to repair, and vice versa, the smaller it is. Then, optimize the parameters of the secondary thermoforming of the plastic substrate to reduce the deviation between the actual specifications of the multiple areas and the preset area specifications after forming. Among them, obtaining the optimal parameters of the thermoforming parameters includes forming temperature, forming speed, and setting temperature.

[0026] Step Five: Use the optimal thermoforming parameters to perform secondary thermoforming on the multiple secondary forming areas, and after completion, collect and obtain multiple actual forming specification information, and combine the multiple area forming specification information to calculate and obtain multiple forming error specification information;

[0027] Specifically, perform secondary thermoforming on the multiple secondary forming areas based on the optimal thermoforming parameters, and collect the dimensional errors between the actual specifications and the preset area specifications of the multiple areas after actual thermoforming for compensating the plastic products according to the errors.

[0028] Step Six: According to the multiple forming error specification information, perform forming compensation printing based on 3D printing to obtain the plastic products after secondary forming.

[0029] Specifically, according to multiple molding error specification information, compensation printing is performed based on 3D printing to meet the preset specification requirements. The 3D printing is performed using materials that are the same or similar to the plastic substrate, and after printing, curing is performed to obtain a secondary molded plastic product.

[0030] The precise secondary molding method for plastic products based on 3D printing technology can achieve the technical goal of improving the accuracy of obtaining repair deviations and achieve the technical effect of improving the quality of secondary molding.

[0031] Furthermore, the present application also includes the following steps:

[0032] Unifying coordinates and establishing a position index relationship according to the molding specification information and the substrate specification information;

[0033] According to the position index relationship and the substrate specification information, index matching is performed in the molding specification information to obtain regions with different specifications as multiple secondary molding regions, and molding specification information of multiple regions of the secondary molding regions is obtained;

[0034] The plurality of thickness information and the plurality of composition information of the plurality of secondary molding areas on the plastic substrate are detected and collected.

[0035] Specifically, if Figure 2 As shown, determine the coordinate system of the molding specification information and the substrate specification information. If the coordinate systems of the two are not unified, coordinate conversion is required to ensure that the two are in the same coordinate system. For example, by operations such as translation, rotation, or scaling, the coordinate origin, coordinate axis direction, and unit length of the two are consistent. Establish a position index relationship. Among them, this is achieved by associating each position point in the substrate specification information with the corresponding position point in the molding specification information. For example, the corresponding relationship can be stored by creating an index table or using a data structure such as a database for subsequent quick query and matching.

[0036] Then, according to the position index relationship and the substrate specification information, the index matching in the molding specification information is used to obtain the areas with different specifications. For example, this can be achieved by comparing the size, shape and other parameters of the corresponding position points in the substrate specification information and the molding specification information. Find the area with large differences, that is, the area that needs to be secondary molded. For each secondary molding area, obtain the regional molding specification information. Among them, the size, shape, position and other information of the area are included as the basis for secondary molding.

[0037] Next, the thickness information and composition information are detected and collected. Among them, non-destructive testing techniques such as ultrasonic testing and X-ray testing can be used to measure the thickness of each secondary molding area. At the same time, chemical analysis or spectral analysis can be used to detect composition information.

[0038] By determining the areas that require secondary forming, detailed specification information and physical and chemical properties are obtained, providing strong support for subsequent secondary forming processes.

[0039] Furthermore, this application also includes the following steps:

[0040] According to the historical data of the secondary forming of plastic products, obtain the set of forming specification information for sample areas;

[0041] Mark according to the difficulty of compensation adjustment after forming for the forming specification information of different sample areas, and obtain the set of sample forming compensation difficulty information;

[0042] Use the set of forming specification information for sample areas and the set of sample forming compensation difficulty information to construct an area forming compensation difficulty analyzer, analyze the forming compensation difficulty of the multiple area forming specification information, and obtain the multiple forming compensation difficulty information.

[0043] Specifically, extract the forming specification information of different sample areas from the historical data of the secondary forming of plastic products. For example, it may include the size, shape, material type, forming process parameters, etc. of the area. Organize the multiple forming specification information into a set to obtain the set of forming specification information for sample areas as the input data for subsequent analysis.

[0044] Then, for each sample area, mark the difficulty according to the difficulty of compensation adjustment after forming recorded in the historical data. Among them, the compensation difficulty can be quantitatively evaluated according to indicators such as the number of adjustments, adjustment time, and adjustment cost in actual production. For example, the higher the number of adjustments, adjustment time, and adjustment cost, the higher the compensation difficulty, and vice versa. Organize the compensation difficulty information into a set to obtain the set of sample forming compensation difficulty information, corresponding to the set of forming specification information for sample areas.

[0045] Next, select the features that have a significant impact on the forming compensation difficulty from the set of forming specification information for the sample areas. For example, the features may include the complexity of the area, the plasticity of the material, the stability of the forming process, etc. Based on the set of forming specification information for the sample areas and the set of sample forming compensation difficulty information as input data, construct an area forming compensation difficulty analyzer. Among them, according to the characteristics of the data, a suitable machine learning model, such as a decision tree, a random forest, a neural network, etc., can be selected as the area forming compensation difficulty analyzer. Use the set of forming specification information for the sample areas and the set of sample forming compensation difficulty information to divide and obtain training data and validation data, and train the area forming compensation difficulty analyzer with the training data. Among them, the division ratio is custom-set by those skilled in the art according to the actual situation. When the output of the area forming compensation difficulty analyzer tends to be stable, verify the area forming compensation difficulty analyzer with the validation data, extract the output accuracy rate of the area forming compensation difficulty analyzer, and if it is determined that the output accuracy rate threshold of the area forming compensation difficulty analyzer is met, the training of the area forming compensation difficulty analyzer is completed. Among them, the output accuracy rate threshold of the area forming compensation difficulty analyzer is custom-set by those skilled in the art according to the actual situation. Furthermore, analyze the area forming specification information through the area forming compensation difficulty analyzer to obtain the forming compensation difficulty information.

[0046] By constructing an area forming compensation difficulty analyzer, it helps to improve the production efficiency of the secondary forming of plastic products and optimize the product quality.

[0047] Furthermore, this application also includes the following steps:

[0048] According to the multiple forming compensation difficulty information, allocate multiple area weights for optimizing the secondary forming of the multiple secondary forming areas;

[0049] Obtain the thermoforming parameter space for the secondary forming of plastic products, where the thermoforming parameter space is constructed according to the forming temperature range, the forming speed range, and the qualitative temperature range;

[0050] Within the thermoforming parameter space, adopt the multiple area weights, and optimize the thermoforming parameters according to the multiple thickness information, the multiple composition information, and the multiple area forming specification information to obtain the optimal thermoforming parameters.

[0051] Specifically, for the area with smaller forming compensation difficulty, the allocated weight is smaller, and vice versa, and then allocate multiple area weights for optimizing the secondary forming of the multiple secondary forming areas, so as to give different attentions during the optimization process.

[0052] Then, the thermoforming parameter space includes multiple dimensions such as the forming temperature range, the forming speed range, and the setting temperature range, etc. Among them, it is determined according to the thermal properties of the material, the performance range of the equipment, and the actual production requirements. Furthermore, according to the material characteristics, equipment capabilities, and process requirements, the upper and lower limits of each parameter range are determined. A multi-dimensional parameter space is constructed for subsequent parameter optimization search.

[0053] Next, according to multiple thickness information, multiple composition information, and multiple regional forming specification information, the goal of thermoforming parameter optimization is determined. For example, the optimization goal can be to improve the forming accuracy, etc. The search and optimization of thermoforming parameters are carried out by calculating parameter fitness, etc. During the optimization process, the allocated regional weights are used to adjust the influence of different regions on the optimization goal. The optimal thermoforming parameter combination that meets the optimization goal is found by searching within the thermoforming parameter space through an optimization algorithm. The optimal parameters are output for production optimization.

[0054] Weights are assigned to multiple regions according to the forming compensation difficulty information, and parameter optimization is carried out within the thermoforming parameter space to obtain the optimal thermoforming parameters for specific plastic products, which helps to improve the accuracy and efficiency of secondary forming.

[0055] Furthermore, this application also includes the following steps:

[0056] Within the thermoforming parameter space, multiple initial thermoforming parameters and multiple target thermoforming parameters are randomly generated, and the mapping relationship between the multiple initial thermoforming parameters and the multiple target thermoforming parameters is randomly constructed;

[0057] Taking the multiple target thermoforming parameters as the adjustment direction, according to the mapping relationship, the multiple initial thermoforming parameters are adjusted to obtain multiple adjusted thermoforming parameters;

[0058] Random cross-updating is performed on the parameter data within the multiple adjusted thermoforming parameters and the multiple target thermoforming parameters to obtain multiple trial thermoforming parameters, where at least one of the forming temperature, the forming speed, and the setting temperature is cross-updated;

[0059] According to the multiple trial thermoforming parameters, multiple thickness information, and multiple composition information, secondary thermoforming simulation is carried out, and multiple trial fitnesses are calculated in combination with the multiple regional weights. It is judged whether they are greater than the target fitnesses of the corresponding target thermoforming parameters. If so, the target thermoforming parameters are replaced. If not, no replacement is made to obtain multiple target thermoforming parameters with replacement updates;

[0060] Continue to randomly generate initial thermoforming parameters, and perform iterative optimization in combination with the multiple target thermoforming parameters with replacement updates until the convergence times are reached, and output the thermoforming parameters with the maximum fitness to obtain the optimal thermoforming parameters.

[0061] Specifically, within the thermoforming parameter space, multiple initial thermoforming parameters are randomly generated. Each initial thermoforming parameter includes parameters such as forming temperature, forming speed, and setting temperature. At the same time, multiple target thermoforming parameters are randomly generated as the target references during the optimization process. A mapping relationship between the initial thermoforming parameters and the target thermoforming parameters is randomly constructed for subsequent adjustment of the initial parameters according to the target parameters.

[0062] Then, taking the target thermoforming parameters as the adjustment direction, the initial thermoforming parameters are adjusted according to the mapping relationship. During the adjustment process, more attention can be given to the regions with larger weights according to the regional weights, making the adjustment more in line with the actual production requirements. Multiple adjusted thermoforming parameters are obtained as the candidate parameters for the next round of optimization.

[0063] Then, the parameter data within the adjusted thermoforming parameters and the target thermoforming parameters are randomly cross-updated. The cross-update can be at least one of the forming temperature, forming speed, and setting temperature to increase the diversity of the parameters. Through the cross-update, multiple trial thermoforming parameters are obtained.

[0064] Next, secondary thermoforming simulation is performed using multiple trial thermoforming parameters, combining multiple thickness information and multiple composition information to simulate the forming process. According to the simulation results and the regional weights, the fitness of each trial thermoforming parameter is calculated. It is judged whether the fitness of the trial thermoforming parameter is greater than the target fitness of the corresponding target thermoforming parameter. If it is greater, the target thermoforming parameter is replaced with the trial thermoforming parameter. If it is not greater, the target thermoforming parameter remains unchanged. After replacement and update, a new set of target thermoforming parameters is obtained.

[0065] Next, new initial thermoforming parameters are continuously randomly generated, and the next round of iterative optimization is carried out in combination with the replaced and updated target thermoforming parameters. The steps of adjustment, cross-update, simulation, and evaluation are repeated until the preset convergence times are reached or other stop conditions are met. During the iteration process, the fitness changes of each iteration are recorded for subsequent analysis. When the convergence condition is reached, the thermoforming parameter with the maximum fitness is output, which is the optimal thermoforming parameter sought.

[0066] Through iterative optimization, the optimal thermoforming parameters can be searched within the thermoforming parameter space, thereby improving the accuracy and efficiency of the secondary forming.

[0067] Furthermore, the present application further includes the following steps:

[0068] According to the secondary thermoforming data records of plastic products, obtain a set of sample thermoforming parameters, a set of sample thickness information for multiple secondary forming areas, and a set of sample composition information, and obtain a set of actual specification information for multiple sample areas after secondary thermoforming;

[0069] Use the set of sample thermoforming parameters, the set of sample thickness information, the set of sample composition information, and the set of actual specification information for multiple sample areas to construct a thermoforming simulator;

[0070] According to the thermoforming simulator, perform secondary thermoforming simulation on the multiple test thermoforming parameters, multiple thickness information, and multiple composition information to obtain a set of actual specification information for multiple areas;

[0071] Construct a thermoforming function, and calculate multiple test fitness values according to the set of actual specification information for multiple areas and the set of forming specification information for multiple areas.

[0072] Specifically, extract the parameters in the forming records within the historical time from the secondary thermoforming data records as the set of sample thermoforming parameters, including forming temperature, forming speed, setting temperature, etc. For each secondary forming area, obtain the corresponding set of sample thickness information and set of sample composition information to reflect the material properties and initial states of different areas. Collect the set of actual specification information for each area after secondary thermoforming, including dimensions, shapes, etc., for evaluating the actual effects of thermoforming parameters.

[0073] Then, use machine learning or physical simulation methods, and use the set of sample thermoforming parameters, the set of sample thickness information, the set of sample composition information, and the set of actual specification information for sample areas as input data to construct a thermoforming simulator. Among them, the input data is divided into sample training data and sample verification data. The division ratio is custom-set by those skilled in the art according to the actual situation. Train the thermoforming simulator with the sample training data. When the output of the thermoforming simulator tends to be stable, verify the output of the thermoforming simulator with the sample verification data. If the output accuracy rate of the thermoforming simulator meets the output accuracy rate threshold of the thermoforming simulator, the training of the thermoforming simulator is completed. Among them, the output accuracy rate threshold of the thermoforming simulator is custom-set by those skilled in the art according to the actual situation. Through the thermoforming simulator, the secondary thermoforming process of plastic products under different thermoforming parameters can be simulated.

[0074] Next, use the constructed thermoforming simulator to perform secondary thermoforming simulation on multiple test thermoforming parameters, multiple thickness information, and multiple composition information. Through the secondary thermoforming simulation, obtain the set of actual specification information for each area under each test thermoforming parameter, which is used to reflect the influence of thermoforming parameters on the forming effect of plastic products.

[0075] Next, construct a thermoforming function that can quantify the difference between the actual specification information of the simulated region and the forming specification information of the target region. Use this function to calculate the fitness of multiple trials and evaluate the advantages and disadvantages of each trial's thermoforming parameters.

[0076] Constructing a thermoforming simulator through the secondary thermoforming data record of plastic products and simulating and evaluating the fitness of trial thermoforming parameters helps predict and optimize thermoforming parameters before actual production, improving the forming quality and efficiency of plastic products.

[0077] Furthermore, the present application further includes the following steps:

[0078] Construct a thermoforming function as follows: ;

[0079] where THF is the fitness, M is the number of multiple secondary forming regions, is the regional weight of the i-th secondary forming region, is the deviation degree between the actual specification information and the forming specification information of the i-th secondary forming region;

[0080] According to the multiple sets of actual specification information of the regions and the multiple sets of forming specification information of the regions, calculate multiple sets of deviation degrees, and in combination with the thermoforming function, calculate multiple trial fitnesses.

[0081] Specifically, THF is the fitness, representing the comprehensive effect of the thermoforming parameters. M is the number of multiple secondary forming regions, is the regional weight of the i-th secondary forming region, is the deviation degree between the actual specification information and the forming specification information of the i-th secondary forming region. Among them, the deviation degree between the actual specification information and the forming specification information of the i-th secondary forming region The lower it is, the better the fitness THF, and vice versa, the worse it is. The higher the fitness, the better the value of the forming parameters, and vice versa, the worse it is.

[0082] Then, for each secondary forming region, calculate the deviation degree between its actual specification information and the forming specification information. Among them, the calculation of the deviation degree can be based on various methods, such as Euclidean distance, absolute error, etc., specifically depending on the type and measurement method of the specification information. For example, if the specification information includes dimensions and shapes, a comprehensive error index can be used to calculate the deviation degree. Use the thermoforming function, in combination with the set of deviation degrees of each trial thermoforming parameter and the corresponding regional weight, to calculate the fitness. The calculation of the fitness takes into account the weights of different regions and the deviation degree of each region, so as to comprehensively evaluate the advantages and disadvantages of the thermoforming parameters.

[0083] Quantify and evaluate the fitness of different trial thermoforming parameters through a thermoforming function, thereby providing a basis for subsequent parameter optimization. The calculation of fitness comprehensively considers the weights of multiple regions and the deviation degree of specification information, making the evaluation results more accurate and comprehensive.

[0084] Furthermore, the present application further includes the following steps:

[0085] Adopt the optimal thermoforming parameters to perform secondary thermoforming on the multiple secondary forming regions, and collect multiple actual forming specification information of the multiple secondary forming regions after completion;

[0086] Combine the forming specification information of the multiple regions to calculate multiple forming error specification information of the multiple actual forming specification information.

[0087] Specifically, input the obtained optimal thermoforming parameters, including forming temperature, forming speed, and setting temperature, into the thermoforming equipment. Ensure that the equipment is correctly set up and ready for secondary thermoforming. Prepare the corresponding plastic products according to the material thickness and composition information of the required multiple secondary forming regions. Place the prepared plastic products into the thermoforming equipment and perform thermoforming operations according to the optimal thermoforming parameters. After the secondary thermoforming is completed, use appropriate measuring tools or equipment to collect multiple actual forming specification information of the multiple secondary forming regions. Record the collected actual forming specification information in detail to ensure the accuracy and integrity of the data.

[0088] Then, compare the multiple actual forming specification information collected with the preset multiple region forming specification information. By comparing the differences between the two, the quality of the thermoforming effect can be evaluated. For example, by calculating the difference, deviation rate, or other relevant indicators between the actual specification and the target specification, the forming error specification information can be obtained.

[0089] Performing secondary thermoforming operations with the optimal thermoforming parameters and collecting actual forming specification information to calculate forming error specification information helps to evaluate the thermoforming effect, optimize the production process, and improve product quality.

[0090] To sum up, the precise secondary forming method for plastic products based on 3D printing technology provided by the present application has the following technical effects:

[0091] By collecting the substrate specification information of the plastic substrate to be secondarily formed, where the substrate specification information includes the size specification information of the plastic substrate; indexing and matching the substrate specification information according to the forming specification information of the secondary forming to obtain a plurality of secondary forming areas and a plurality of area forming specification information, and collecting the thickness information and composition information of the plurality of secondary forming areas on the plastic substrate; analyzing the forming compensation difficulty of the plurality of area forming specification information to obtain a plurality of forming compensation difficulty information; according to the plurality of forming compensation difficulty information, allocating the weights for optimizing the secondary forming of the plurality of secondary forming areas, and combining the plurality of thickness information, the plurality of composition information and the plurality of area forming specification information to optimize the thermoforming parameters of the plurality of secondary forming areas to obtain the optimal thermoforming parameters, where the thermoforming parameters include the forming temperature, the forming speed and the setting temperature; using the optimal thermoforming parameters to perform secondary thermoforming on the plurality of secondary forming areas, and collecting a plurality of actual forming specification information after completion, and combining the plurality of area forming specification information to calculate and obtain a plurality of forming error specification information; according to the plurality of forming error specification information, based on 3D printing, performing forming compensation printing to obtain the plastic product of the secondary forming, achieving the technical goal of improving the acquisition accuracy of the repair deviation and reaching the technical effect of improving the quality of the secondary forming.

[0092] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0093] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A precise secondary forming method for plastic products based on 3D printing technology, characterized in that, The method includes: Collecting the substrate specification information of the plastic substrate to be secondarily formed, where the substrate specification information includes the dimensional specification information of the plastic substrate; Indexing and matching the substrate specification information according to the forming specification information of the secondary forming to obtain a plurality of secondary forming areas and a plurality of area forming specification information, and collecting the thickness information and composition information of the plurality of secondary forming areas on the plastic substrate; Performing a forming compensation difficulty analysis on the plurality of area forming specification information to obtain a plurality of forming compensation difficulty information; According to the plurality of forming compensation difficulty information, allocating weights for optimizing the secondary forming of the plurality of secondary forming areas, and combining a plurality of thickness information, a plurality of composition information, and a plurality of area forming specification information to optimize the thermoforming parameters of the plurality of secondary forming areas to obtain optimal thermoforming parameters, where the thermoforming parameters include forming temperature, forming speed, and setting temperature; Performing secondary thermoforming on the plurality of secondary forming areas using the optimal thermoforming parameters, and collecting a plurality of actual forming specification information after completion, and combining the plurality of area forming specification information to calculate and obtain a plurality of forming error specification information; Performing forming compensation printing based on 3D printing according to the plurality of forming error specification information to obtain the secondarily formed plastic product; Indexing and matching the substrate specification information according to the forming specification information of the secondary forming to obtain a plurality of secondary forming areas and a plurality of area forming specification information, including: Unifying coordinates according to the forming specification information and the substrate specification information to establish a position index relationship; Indexing and matching within the forming specification information according to the position index relationship and the substrate specification information to obtain areas with different specifications as the plurality of secondary forming areas, and obtaining the plurality of area forming specification information of the secondary forming areas; Detecting and collecting the plurality of thickness information and the plurality of composition information of the plurality of secondary forming areas on the plastic substrate; Performing a forming compensation difficulty analysis on the plurality of area forming specification information to obtain a plurality of forming compensation difficulty information, including: Obtaining a set of sample area forming specification information according to the historical data of the secondary forming of the plastic product; Marking according to the difficulty of compensation adjustment after forming with different sample area forming specification information to obtain a set of sample forming compensation difficulty information; Using the set of sample area forming specification information and the set of sample forming compensation difficulty information to construct an area forming compensation difficulty analyzer, and performing a forming compensation difficulty analysis on the plurality of area forming specification information to obtain the plurality of forming compensation difficulty information; According to the plurality of forming compensation difficulty information, allocating weights for optimizing the secondary forming of the plurality of secondary forming areas, and combining a plurality of thickness information, a plurality of composition information, and a plurality of area forming specification information to optimize the thermoforming parameters of the plurality of secondary forming areas, including: According to the plurality of forming compensation difficulty information, allocating a plurality of area weights for optimizing the secondary forming of the plurality of secondary forming areas; Obtain the thermoforming parameter space for the secondary forming of plastic products, wherein the thermoforming parameter space is constructed according to the forming temperature range, the forming speed range, and the qualitative temperature range; Within the thermoforming parameter space, using the multiple regional weights, optimize the thermoforming parameters according to the multiple thickness information, the multiple composition information, and the multiple regional forming specification information to obtain the optimal thermoforming parameters; Within the thermoforming parameter space, using the multiple regional weights, optimize the thermoforming parameters according to the multiple thickness information, the multiple composition information, and the multiple regional forming specification information, including: Within the thermoforming parameter space, randomly generate multiple initial thermoforming parameters and multiple target thermoforming parameters, and randomly construct the mapping relationship between the multiple initial thermoforming parameters and the multiple target thermoforming parameters; Taking the multiple target thermoforming parameters as the adjustment direction, adjust the multiple initial thermoforming parameters according to the mapping relationship to obtain multiple adjusted thermoforming parameters; Randomly cross-update the parameter data within the multiple adjusted thermoforming parameters and the multiple target thermoforming parameters to obtain multiple trial thermoforming parameters, wherein at least one of the forming temperature, the forming speed, and the setting temperature is cross-updated; Conduct secondary thermoforming simulation according to the multiple trial thermoforming parameters, the multiple thickness information, and the multiple composition information, and calculate multiple trial fitness values in combination with the multiple regional weights, and judge whether they are greater than the target fitness values of the corresponding target thermoforming parameters. If so, replace the target thermoforming parameters. If not, do not replace them to obtain multiple target thermoforming parameters after replacement update; Continue to randomly generate initial thermoforming parameters, and perform iterative optimization in combination with the multiple target thermoforming parameters after replacement update until the convergence number is reached, output the thermoforming parameters with the maximum fitness value, and obtain the optimal thermoforming parameters.

2. The method according to claim 1, wherein Conduct secondary thermoforming simulation according to the multiple trial thermoforming parameters, the multiple thickness information, and the multiple composition information, and calculate multiple trial fitness values in combination with the multiple regional weights, including: According to the secondary thermoforming data record of the plastic product, obtain the sample thermoforming parameter set, the multiple sample thickness information sets of multiple secondary forming regions and the multiple sample composition information sets, and obtain the multiple sample region actual specification information sets after secondary thermoforming; Construct a thermoforming simulator using the sample thermoforming parameter set, the multiple sample thickness information sets, the multiple sample composition information sets, and the multiple sample region actual specification information sets; According to the thermoforming simulator, conduct secondary thermoforming simulation on the multiple trial thermoforming parameters, the multiple thickness information, and the multiple composition information to obtain the multiple region actual specification information sets; Construct a thermoforming function, and calculate multiple trial fitness values according to the multiple region actual specification information sets and the multiple region forming specification information.

3. The method according to claim 2, characterized in that Construct a thermoforming function, and calculate multiple trial fitness values according to the multiple region actual specification information sets and the multiple region forming specification information, including: Construct a thermoforming function as follows: ； Among them, THF is the fitness, M is the number of multiple secondary forming regions, is the regional weight of the i-th secondary forming region, is the deviation degree between the actual regional specification information and the regional forming specification information of the i-th secondary forming region; Based on the actual specification information set of the multiple regions and the forming specification information of the multiple regions, a plurality of deviation degree sets are calculated, and in combination with the thermoforming function, a plurality of test fitnesses are calculated.

4. The method according to claim 1, wherein Using the optimal thermoforming parameters, secondary thermoforming is performed on the multiple secondary forming regions, and after completion, a plurality of actual forming specification information is collected. In combination with the forming specification information of the multiple regions, a plurality of forming error specification information is calculated, including: Using the optimal thermoforming parameters, secondary thermoforming is performed on the multiple secondary forming regions, and after completion, a plurality of actual forming specification information of the multiple secondary forming regions is collected; In combination with the forming specification information of the multiple regions, a plurality of forming error specification information of the plurality of actual forming specification information is calculated.

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