A foam product production system based on artificial intelligence

Abstract

The present invention discloses a foam product production system based on artificial intelligence, which specifically relates to the field of plastic manufacturing, including a sub-region division module, a sub-region production information collection module, a sub-region production efficiency analysis module, a target region production efficiency analysis module, a factory production efficiency judgment module, and an interactive feedback module. The present invention realizes comprehensive monitoring of the target area through precise regional division. Through the information collection module, detailed data including product quality and production efficiency are collected. Based on these data, we have established a comprehensive model that can measure product quality and production efficiency at the same time, achieving dual optimization of the two. This method enables the factory to have a more comprehensive understanding of the production process, discover problems in a timely manner and take improvement measures, thereby improving the overall production efficiency and market competitiveness.

Description

Technical Field

[0001] The present invention relates to the technical field of plastic manufacturing, and more specifically, to a foam product production system based on artificial intelligence. Background Art

[0002] The artificial intelligence-based foam product production system is a modern production solution that integrates advanced technology and intelligent management. The system has achieved automation and intelligent control of the production process by introducing cutting-edge technologies such as automated production lines, intelligent robots, sensors and cameras, greatly improving production efficiency. In this process, artificial intelligence algorithms continuously optimize the production process and ensure efficient operation of equipment, thereby significantly reducing production time and costs.

[0003] At the same time, the system also has strong quality control and testing capabilities. By real-time monitoring of production links, using sensors and cameras to capture key data, and combining advanced machine learning algorithms, the system can accurately assess product quality and automatically adjust production parameters when necessary to ensure that every foam product meets strict quality standards.

[0004] However, there are still some shortcomings in its actual use. For example, the data collected by the existing technology is too single, which makes it difficult for the system to accurately judge the real-time status of the factory's production of foam products. Due to the incomplete data collection, the system cannot fully capture the various subtle changes and key parameters in the production process, so it is impossible to monitor the production process more accurately. In addition, the current monitoring of foam product production mainly focuses on two aspects: product quality and production efficiency, and these two are usually paid attention to separately. This single monitoring method makes the system often ignore the impact of product production quality on overall performance when evaluating product quality. In fact, the production quality of a product is not only related to its appearance and physical properties, but also involves multiple aspects such as product durability and safety. If monitoring is only carried out from a single dimension, the understanding and grasp of the production process may not be comprehensive enough, which in turn affects the final quality of the product and the benefits of the enterprise. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a foam product production system based on artificial intelligence, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a foam product production system based on artificial intelligence, comprising a sub-area division module, a sub-area production information collection module, a sub-area production efficiency analysis module, a target area production efficiency analysis module, a factory production efficiency judgment module and an interactive feedback module.

[0007] Preferably, the sub-area division module is used to record the factory to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to each production line, and mark them as 1, 2, 3...n in sequence;

[0008] The sub-region production information collection module includes a foam product quality information collection unit and a production data collection unit, which is used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region production efficiency analysis module;

[0009] The sub-region production efficiency analysis module is used to import and calculate the data collected in the sub-region production information collection module to obtain the sub-region product quality coefficient, sub-region production efficiency coefficient and sub-region production efficiency index;

[0010] The target area production efficiency analysis module is used to calculate the target area production efficiency index based on the data imported by the sub-area production efficiency analysis module;

[0011] The judgment module is used to compare the target area production efficiency index with the preset value, and input the comparison result into the interactive feedback module;

[0012] The interactive feedback module is used to import the comparison results into the administrator terminal, and when the comparison result of the production efficiency index of the target area is lower than the preset value, an alarm will be issued to the administrator's equipment.

[0013] Preferably, the comprehensive parameters refer to the temperature stability parameters of sub-region product size, the humidity stability parameters of sub-region product size, the tension stability parameters of sub-region product structure, the pressure stability parameters of sub-region product structure, the density parameters of sub-region product, the time utilization rate parameters of sub-region product, the performance utilization rate parameters of sub-region product, the scrap rate parameters of sub-region product, and the production cycle parameters of sub-region product;

[0014] The sub-area product size temperature stability parameter refers to the stability of the size of the product in the i sub-area when the temperature changes. ;

[0015] The sub-area product size humidity stability parameter refers to the stability of the size of the product in the i sub-area when the humidity changes. ;

[0016] The tensile stability parameter of the sub-region product structure refers to the tensile strength of the product in the sub-region ;

[0017] The sub-region product structure pressure stability parameter refers to the compressive strength of the product in the i sub-region ;

[0018] The sub-region product density parameter refers to the average density of products in sub-region i ;

[0019] The sub-area product time utilization rate parameter refers to the time utilization rate of the product in the i sub-area ;

[0020] The sub-region product performance utilization rate parameter refers to the performance utilization rate of the product in the i sub-region ;

[0021] The sub-region product scrap rate parameter refers to the product scrap rate of the i sub-region ;

[0022] The sub-region product production cycle parameter refers to the product production cycle of the i sub-region .

[0023] Preferably, the specific method for collecting the sub-region product size temperature stability parameters is as follows:

[0024] Take some samples by random sampling and record them as 1, 2, 3, ... n in sequence. Place the samples in a slowly heating environment and record the starting temperature. and the initial sample volume Observe the deformation of the sample until the sample is significantly deformed and record the temperature at this time. And the sample volume Finally, the sub-area product size temperature stability parameter is obtained = .

[0025] Preferably, the specific method for collecting the sub-region product size humidity stability parameters is as follows:

[0026] Take some samples by random sampling and record them as 1, 2, 3...n in sequence. Place the samples in a slowly humidified environment and record the initial humidity. and the initial sample volume Observe the deformation of the sample until the sample is significantly deformed and record the temperature at this time. And the sample volume , and finally obtain the sub-area product size humidity stability parameter = .

[0027] Preferably, the specific method of collecting the tensile stability parameters of the sub-region product structure is as follows:

[0028] Randomly sample the products in the sub-area to obtain several samples. Use professional tensile equipment to apply a continuously increasing tensile force to the samples from different angles until the product is irreversibly deformed. The irreversible deformation means that the product cannot be restored to its original state after the tensile force is stopped after the deformation occurs. Different angles are marked as 1, 2, 3...n in sequence to obtain the tensile force at different angles. , … , and the type variables at different angles , … , the type variable = ,in Refers to the deformation of sample j under tension at the nth angle. Refers to the volume of sample j after being subjected to tension at the nth angle. refers to the volume before the tension, and we get = , and finally get .

[0029] Preferably, the specific method of collecting the sub-region product structure pressure stability parameters is as follows:

[0030] Randomly sample the products in the sub-area to obtain several samples. Use professional pressure equipment to apply a continuously increasing pressure to the samples from different angles until the product is irreversibly deformed. The irreversible deformation means that the product cannot be restored to its original state after the tensile force is stopped after the deformation. Different angles are marked as 1, 2, 3...n in sequence to obtain the pressure at different angles. , … , and the type variables at different angles , … , the type variable = ,in Refers to the type variable of sample j under pressure at the nth angle, Refers to the volume of sample j after being subjected to pressure at the nth angle, refers to the volume before the tension, and we get = , and finally get = .

[0031] Preferably, the specific method of collecting the sub-region product time utilization rate parameter is as follows:

[0032] Record the time required for a sub-area production line to produce a set of products and downtime ,get = - , and finally get = .

[0033] Preferably, the specific method of collecting the sub-region product performance utilization rate parameters is as follows: = × / .in, Refers to the theoretical production time of a single product. refers to the input quantity, Refers to the working time.

[0034] Preferably, the mathematical model of the sub-region product quality coefficient is as follows: = ,in Refers to the sub-region product quality coefficient, refers to the average density of products in sub-region i, Refers to the stability of the size of the product in the i-sub-area when the temperature changes. Refers to the stability of the size of the product in the i-zone when the humidity changes. Refers to the tensile strength of the product in sub-area i, Refers to the compressive strength of the product in the i sub-area, Refers to the historical average density of products produced by the factory. , , Refers to the fitting parameters.

[0035] Preferably, the mathematical model of the sub-region production efficiency coefficient is as follows: = ,in refers to the sub-region production efficiency coefficient, Refers to the time utilization rate of products in sub-area i, Refers to the performance utilization rate of products in the i sub-area, Refers to the product scrap rate of sub-area i, Refers to the product production cycle of sub-region i, , , , , , Refers to the fitting parameters.

[0036] Preferably, the mathematical model of the sub-region production efficiency index is as follows: = + ,in Refers to the sub-region production efficiency index, Refers to the sub-region product quality coefficient, refers to the sub-region production efficiency coefficient, , Refers to the weight coefficient.

[0037] Preferably, the mathematical model of the target area production efficiency index is as follows: ,in Refers to the production efficiency index of the target area, Refers to the sub-region production efficiency index.

[0038] Preferably, the preset value is a comprehensive warning value for evaluating the quality and efficiency of foam products produced by a factory based on industry practical experience. When the production efficiency index of the target area of ​​the target factory is lower than the preset value, it indicates that the foam product production efficiency is low, and corresponding measures need to be taken to optimize and improve production efficiency and quality.

[0039] Preferably, when the comparison result of the interactive feedback module is lower than a preset value, the system will trigger an alarm function on the terminal, send a warning signal to the management personnel through sound, vibration and pop-up window, and provide relevant parameters, to help the management personnel analyze the reasons affecting the production quality and efficiency in the process of foam product production in the factory, and further track down the specific production line colleagues to provide methods to improve the production efficiency index.

[0040] Technical effects and advantages of the present invention:

[0041] 1. The present invention realizes comprehensive monitoring of the target area through precise regional division. The target area is divided into several sub-areas through the sub-area division module, and basic information is collected in each sub-area. The basic information includes product size temperature stability information, product size humidity stability information, product structure tension stability information, product structure pressure stability information, product density information, product time utilization rate information, product performance utilization rate information, product scrap rate information, product production cycle information, covering the two aspects of product quality information and production efficiency information produced by the factory, thereby providing a more comprehensive and detailed monitoring means for product performance detection;

[0042] 2. By conducting an in-depth analysis of the collected production data, the present invention establishes a mathematical model that can comprehensively measure the product quality and production efficiency of the foam products produced by the factory. By establishing such a comprehensive model, the present invention helps the factory to measure product quality while also taking into account the improvement of production efficiency. This means that while the factory pursues high-quality products, it will not ignore the improvement of production efficiency, thereby achieving dual optimization of product quality and production efficiency. This comprehensive evaluation method enables the factory to have a more comprehensive understanding of the actual situation of the production process, identify problems in a timely manner and take corresponding improvement measures, thereby improving the overall production efficiency and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0045] As attached Figure 1 An artificial intelligence-based foam product production system is shown, comprising a sub-area division module, a sub-area production information collection module, a sub-area production efficiency analysis module, a target area production efficiency analysis module, a factory production efficiency judgment module and an interactive feedback module.

[0046] The output end of the sub-region division module is connected to the input end of the sub-region production information collection module by telecommunication, the output end of the sub-region production information collection module is connected to the input end of the sub-region production efficiency analysis module by telecommunication, the output end of the sub-region production efficiency analysis module is connected to the input end of the target region production efficiency analysis module by telecommunication, the output end of the target region production efficiency analysis module is connected to the input end of the factory production efficiency judgment module by telecommunication, and the output end of the factory production efficiency judgment module is connected to the input end of the interactive feedback module by telecommunication.

[0047] The sub-area division module is used to record the factory to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to each production line, and mark them as 1, 2, 3...n in sequence;

[0048] The sub-region production information collection module includes a foam product quality information collection unit and a production data collection unit, which is used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region production efficiency analysis module;

[0049] In a preferred technical solution of the present application, the specific method for obtaining the comprehensive parameters of each sub-region in the sub-region information acquisition module is as follows:

[0050] In this embodiment, it should be specifically explained that the comprehensive parameters refer to the temperature stability parameters of the sub-region product size, the humidity stability parameters of the sub-region product size, the tension stability parameters of the sub-region product structure, the pressure stability parameters of the sub-region product structure, the density parameters of the sub-region product, the time utilization rate parameters of the sub-region product, the performance utilization rate parameters of the sub-region product, the scrap rate parameters of the sub-region product, and the production cycle parameters of the sub-region product;

[0051] The sub-area product size temperature stability parameter refers to the stability of the size of the product in the i sub-area when the temperature changes. ;

[0052] The sub-area product size humidity stability parameter refers to the stability of the size of the product in the i sub-area when the humidity changes. ;

[0053] The tensile stability parameter of the sub-region product structure refers to the tensile strength of the product in the sub-region ;

[0054] The sub-region product structure pressure stability parameter refers to the compressive strength of the product in the i sub-region ;

[0055] The sub-region product density parameter refers to the average density of products in sub-region i ;

[0056] The sub-area product time utilization rate parameter refers to the time utilization rate of the product in the i sub-area ;

[0057] The sub-region product performance utilization rate parameter refers to the performance utilization rate of the product in the i sub-region ;

[0058] The sub-region product scrap rate parameter refers to the product scrap rate of the i sub-region ;

[0059] The sub-region product production cycle parameter refers to the product production cycle of the i sub-region ;

[0060] It should be specifically noted in this embodiment that the parameters of the sub-region product scrap rate, sub-region product density, and sub-region product production cycle are all obtained by conventional equipment and methods, such as collecting product density through sensors and collecting sub-region product scrap rate, regional product production cycle, and sub-region equipment operation time information through production logs, so this embodiment does not make specific limitations;

[0061] The specific collection method of the sub-area product size temperature stability parameters is as follows:

[0062] Take some samples by random sampling and record them as 1, 2, 3, ... n in sequence. Place the samples in a slowly heating environment and record the starting temperature. and the initial sample volume Observe the deformation of the sample until the sample is significantly deformed and record the temperature at this time. And the sample volume Finally, the sub-area product size temperature stability parameter is obtained = ;

[0063] The specific method for collecting the sub-area product size and humidity stability parameters is as follows:

[0064] Take some samples by random sampling and record them as 1, 2, 3...n in sequence. Place the samples in a slowly humidified environment and record the initial humidity. and the initial sample volume Observe the deformation of the sample until the sample is significantly deformed and record the temperature at this time. And the sample volume , and finally obtain the sub-area product size humidity stability parameter = ;

[0065] It should be specifically explained in this embodiment that the obvious deformation means that the sample cannot maintain its original shape and structure, and has obvious bending, twisting, or expansion and contraction deformation;

[0066] The specific method for collecting the tensile stability parameters of the product structure in the sub-region is as follows:

[0067] Randomly sample the products in the sub-area to obtain several samples. Use professional tensile equipment to apply a continuously increasing tensile force to the samples from different angles until the product is irreversibly deformed. The irreversible deformation means that the product cannot be restored to its original state after the tensile force is stopped after the deformation occurs. Different angles are marked as 1, 2, 3...n in sequence to obtain the tensile force at different angles. , … , and the type variables at different angles , … , the type variable = ,in Refers to the deformation of sample j under tension at the nth angle. Refers to the volume of sample j after being subjected to tension at the nth angle. refers to the volume before the tension, and we get = , and finally get ;

[0068] The specific collection method of the sub-region product structure pressure stability parameters is as follows:

[0069] Randomly sample the products in the sub-area to obtain several samples. Use professional pressure equipment to apply a continuously increasing pressure to the samples from different angles until the product is irreversibly deformed. The irreversible deformation means that the product cannot be restored to its original state after the tensile force is stopped after the deformation. Different angles are marked as 1, 2, 3...n in sequence to obtain the pressure at different angles. , … , and the type variables at different angles , … , the type variable = ,in Refers to the type variable of sample j under pressure at the nth angle, Refers to the volume of sample j after being subjected to pressure at the nth angle, refers to the volume before the tension, and we get = , and finally get = ;

[0070] The specific method of collecting the sub-area product time utilization rate parameters is as follows:

[0071] Record the time required for a sub-area production line to produce a set of products and downtime ,get = - , and finally get = ;

[0072] The specific method of collecting the sub-region product performance utilization rate parameters is as follows:

[0073] = × / .in, Refers to the theoretical production time of a single product. refers to the input quantity, Refers to the working time;

[0074] What needs to be specifically explained in this embodiment is that The time required to produce a single product is determined based on the parameters set by the design department or based on the matching of demand and personnel. Refers to the number of products that produce a group of products:

[0075] The sub-region production efficiency analysis module is used to import and calculate the data collected in the sub-region production information collection module to obtain the sub-region product quality coefficient, the sub-region production efficiency coefficient and the sub-region production efficiency index;

[0076] It should be specifically explained in this embodiment that the mathematical model of the sub-region product quality coefficient is as follows: = ,in Refers to the sub-region product quality coefficient, refers to the average density of products in sub-region i, Refers to the stability of the size of the product in the i-sub-area when the temperature changes. Refers to the stability of the size of the product in the i-zone when the humidity changes. Refers to the tensile strength of the product in sub-area i, Refers to the compressive strength of the product in the i sub-area, Refers to the historical average density of products produced by the factory. , , refers to the fitting parameters;

[0077] It should be specifically explained in this embodiment that the fitting parameter specifically refers to a constant that enables the model to best describe or predict the data, that is, the model has the best fitting degree.

[0078] It should be specifically explained in this embodiment that the mathematical model of the sub-region production efficiency coefficient is as follows: = ,in Refers to the sub-region production efficiency coefficient, Refers to the time utilization rate of products in sub-area i, Refers to the performance utilization rate of products in the i sub-area, Refers to the product scrap rate of sub-area i, Refers to the product production cycle of sub-region i, , , , , , refers to the fitting parameters;

[0079] It should be specifically explained in this embodiment that the mathematical model of the sub-region production efficiency index is as follows: = + ,in Refers to the sub-region production efficiency index, Refers to the sub-region product quality coefficient, refers to the sub-region production efficiency coefficient, , Refers to the weight coefficient;

[0080] The target area production efficiency analysis module is used to calculate the data imported by the sub-area production efficiency analysis module to obtain the target area production efficiency index;

[0081] It should be specifically explained in this embodiment that the mathematical model of the target area production efficiency index is as follows: ,in Refers to the production efficiency index of the target area, Refers to the sub-region production efficiency index;

[0082] The judgment module is used to compare the target area production efficiency index with a preset value, and input the comparison result into the interactive feedback module;

[0083] What needs to be specifically explained in this embodiment is that the preset value is a comprehensive warning value for evaluating the quality and efficiency of foam products produced by a factory based on industry practical experience. When the production efficiency index of the target area of ​​the target factory is lower than the preset value, it means that the production efficiency of the foam products is low, and corresponding measures need to be taken to optimize and improve production efficiency and quality.

[0084] The interactive feedback module is used to import the comparison result into the administrator terminal, and when the comparison result of the production efficiency index of the target area is lower than the preset value, an alarm will be issued to the administrator's equipment.

[0085] What needs to be specifically explained in this embodiment is that when the comparison result of the interactive feedback module is lower than the preset value, the system will trigger an alarm function on the terminal, and send a warning signal to the management personnel through sound, vibration and pop-up window and provide relevant parameters, so as to help the management personnel analyze the reasons affecting the production quality and efficiency in the process of foam product production in the factory, and further track down the specific production line colleagues to provide methods to improve the production efficiency index.

[0086] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0087] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A foam product production system based on artificial intelligence, characterized in that: include: Sub-region division module, sub-region production information collection module, sub-region production efficiency analysis module, target region production efficiency analysis module, factory production efficiency judgment module and interactive feedback module; The sub-area division module is used to record the factory to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to each production line, and mark them as 1, 2, 3...n in sequence; The sub-region production information collection module includes a foam product quality information collection unit and a production data collection unit, which is used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region production efficiency analysis module; The sub-region production efficiency analysis module is used to import and calculate the data collected in the sub-region production information collection module to obtain the sub-region product quality coefficient, sub-region production efficiency coefficient and sub-region production efficiency index; The mathematical model of the sub-region product quality coefficient is as follows: Among them, HM i Refers to the sub-region product quality coefficient, m i refers to the average density of the product in sub-area i, Te i Refers to the stability of the size of the product in the i sub-area when the temperature changes. i Refers to the stability of the size of the product in the i sub-area when the humidity changes, l i Refers to the tensile strength of the product in sub-area i, f i Refers to the compressive strength of the product in the i sub-area, It refers to the historical average density of the products produced by the factory, and α1, α2, and α3 refer to the fitting parameters; Among them KM i Refers to the sub-region production efficiency coefficient, TL i Refers to the time utilization rate of the product in the i sub-area, PL i Refers to the performance utilization rate of products in sub-area i, c i refers to the product scrap rate of sub-area i, t i refers to the production cycle of products in sub-region i, q1, q2, β1, β2, β3, and β4 refer to fitting parameters; The mathematical model of the sub-region production efficiency index is as follows: DM i =γ1HM i +γ2KM i , where DM i Refers to the sub-region production efficiency index, HM i Refers to the sub-region product quality coefficient, KM i refers to the sub-region production efficiency coefficient, γ1 and γ2 refer to weight coefficients; The target area production efficiency analysis module is used to calculate the target area production efficiency index based on the data imported by the sub-area production efficiency analysis module; The judgment module is used to compare the target area production efficiency index with the preset value, and input the comparison result into the interactive feedback module; The interactive feedback module is used to import the comparison results into the administrator terminal, and when the comparison result of the production efficiency index of the target area is lower than the preset value, an alarm will be issued to the administrator's equipment.

2. The artificial intelligence-based foam product production system according to claim 1, characterized in that: The comprehensive parameters refer to the temperature stability parameters of sub-regional product dimensions, the humidity stability parameters of sub-regional product dimensions, the tension stability parameters of sub-regional product structures, the pressure stability parameters of sub-regional product structures, the density parameters of sub-regional products, the time utilization rate parameters of sub-regional products, the performance utilization rate parameters of sub-regional products, the scrap rate parameters of sub-regional products, and the production cycle parameters of sub-regional products; The sub-area product size temperature stability parameter refers to the stability of the size of the product in the i sub-area when the temperature changes. i ; The sub-area product size humidity stability parameter refers to the stability of the size of the product in the i sub-area when the humidity changes. i ; The tensile stability parameter of the sub-region product structure refers to the tensile strength l of the product in the sub-region i i ; The sub-region product structure pressure stability parameter refers to the pressure resistance strength f of the product in sub-region i i ; The sub-region product density parameter refers to the average density m of the products in sub-region i. i ; The sub-area product time utilization rate parameter refers to the time utilization rate TL of the product in the i sub-area i ; The sub-region product performance utilization rate parameter refers to the performance utilization rate PL of the product in the i sub-region i ; The sub-region product scrap rate parameter refers to the product scrap rate c of sub-region i. i ; The sub-region product production cycle parameter refers to the product production cycle t of the i sub-region i .

3. The artificial intelligence-based foam product production system according to claim 1, characterized in that: The specific collection method of the sub-area product size temperature stability parameters is as follows: Take some samples by random sampling and record them as 1, 2, 3, ... n in sequence. Place the samples in a slowly heated environment and record the starting temperature T n0 and the initial sample volume V n0 Observe the deformation of the sample until the sample is significantly deformed and record the temperature T at this time. n形 and the sample volume V n形 , and finally obtain the sub-area product size temperature stability 4. The artificial intelligence-based foam product production system according to claim 1, characterized in that: The specific method for collecting the tensile stability parameters of the product structure in the sub-region is as follows: Randomly sample the products in the sub-area to obtain several samples. Use professional tensile equipment to apply a continuously increasing tensile force to the samples from different angles until the product is deformed beyond recovery. The irreversible deformation means that the product cannot be restored to its original state after the tensile force is stopped after deformation. Different angles are marked as 1, 2, 3...n in sequence to obtain the tensile force F at different angles. j1 、F j2 ……F jn , and the type variable T at different angles j1 , T j2 ……T jn , the type variable T jn =|V jn后 -V jn前 |, where T jn V refers to the deformation of sample j under tension at the nth angle. jn后 Refers to the volume of sample j after being pulled at the nth angle, V jn前 refers to the volume before the tension, and we get Finally get 5. The artificial intelligence-based foam product production system according to claim 1, characterized in that: The mathematical model of the target area production efficiency index is as follows: DM refers to the target area production efficiency index, DM i Refers to the sub-region production efficiency index.

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