Automatic production system and method of squeeze-squeeze lid for sauce packaging

Abstract

The application provides an automatic production system and method of squeeze squeeze caps for sauce packaging, obtains squeeze squeeze cap production characteristics according to original parameters of raw materials, factory environment parameters and customer demand parameters, constructs a squeeze squeeze cap production machine control model according to the squeeze squeeze cap production characteristics and a corresponding squeeze squeeze cap machine control method, inputs current squeeze squeeze cap production characteristics of the squeeze squeeze cap to be produced obtained through order processing to obtain a real-time squeeze squeeze cap machine control method, and adjusts squeeze squeeze cap machine facility parameters with the help of the squeeze squeeze cap machine control method and relevant management personnel of a squeeze squeeze cap production line, so as to manage the automatic production quality of the squeeze squeeze cap. Through specific processing of customer and production end data parameters that affect the production effect of the squeeze squeeze cap, and through an improved machine automatic parameter adjustment model, the production control precision of the squeeze squeeze cap is improved, the production quality of the squeeze squeeze cap is improved, and the satisfaction of customers with the squeeze squeeze cap product is improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent manufacturing technology, and in particular relates to an automated production system and method for extrusion caps for sauce packaging. Background Technology

[0002] In the extrusion cap manufacturing industry, to achieve high-quality development, save energy, and improve product delivery quality, tailoring extrusion cap production to the production environment and customer needs is crucial for improving production quality, saving electricity, and extending machine lifespan. Traditional methods of adjusting equipment production parameters rely primarily on operator experience and do not consider the specific parameters of raw materials, customer needs, and airflow parameters during extrusion cap connection for proper machine control during the extrusion cap production process. This is essential to ensure that the produced extrusion caps are delivered to customers in a green, efficient, and high-quality manner.

[0003] Manually adjusting the parameters of modular extrusion cap production equipment is not only time-consuming and labor-intensive, but also often fails to accurately control the equipment, making it impossible to produce extrusion cap products that maximize satisfaction for both manufacturers and consumers. Furthermore, while recent advancements in information and automation technologies have provided new means for equipment monitoring and control—such as installing various sensors to collect real-time equipment operating data and using computer systems for data monitoring and analysis—these technologies often focus on collecting and monitoring data to accurately and quickly obtain relevant equipment settings. However, the models lack strong application scenarios, failing to consider the processing and analysis of data from the production, client, and consumer ends, and are difficult to adapt to specific demand scenarios.

[0004] Based on the above analysis, the existing technologies have the following problems that need to be addressed:

[0005] This paper proposes an automated production system and method for extruded caps for sauce packaging. This system addresses how to consider the impact of three-party data on extruded cap production, and how to apply this data to specific scenarios. Specifically, it explores how to construct a simple and practical machine learning model tailored to the control scenarios of actual extruded cap production machines, based on the three-party data. This model would automatically generate control methods for each module of the extruded cap production machine, assisting managers in adjusting operating parameters and managing production quality. Furthermore, it addresses how to effectively set parameters for various data affecting extruded cap production, improve the accuracy of control through simple and practical machine learning models, and select the most suitable model after training. This would assist in quality management, reduce labor costs, improve production quality, and increase customer satisfaction with the high quality of extruded caps for both B-end and C-end consumers. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention proposes an automated production system and method for extrusion caps used in sauce packaging.

[0007] In a first aspect of the invention, an automated production method for squeeze caps for sauce packaging is provided, the method comprising:

[0008] Obtain the original parameters of raw materials, factory environmental parameters, and customer requirements that affect the production of extrusion caps for sauce packaging; and obtain the corresponding extrusion cap machine control methods.

[0009] The original parameters of the raw materials, the factory environment parameters, and the customer demand parameters are used to obtain the extrusion cap production characteristics.

[0010] Based on the characteristics of extrusion cap production and the corresponding extrusion cap machine control method, a control model for extrusion cap production machine is constructed.

[0011] The accuracy of the control method generated by the control model of the extruded cap production machine was tested by using relevant parameters from historical production of extruded caps.

[0012] Based on the extrusion cap production machine control model with an accuracy greater than a threshold, a control method for the extrusion cap machine to be produced is generated. Relevant management personnel of the extrusion cap production line perform automated production quality management of extrusion caps according to the control method for the extrusion cap machine to be produced.

[0013] Furthermore, the original parameters are obtained by processing material type, density, melt flow index, and stamping index.

[0014] Furthermore, the factory environmental parameters refer to the feed track environmental parameters, which are specifically obtained by processing the air temperature, relative humidity, and average wind speed of the feed track.

[0015] Furthermore, the customer demand parameters include the customer packaged sauce category value and the applicable population parameter, wherein the customer packaged sauce category value S is obtained based on liquid and semi-solid.

[0016] Furthermore, the applicable population parameters are calculated based on the consumer's grip strength level, age, and gender correction factor.

[0017] Furthermore, the process of obtaining extrusion cap production characteristics from the original parameters of raw materials, the factory environment parameters, and the customer demand parameters is performed using a vector splicing method, which includes both horizontal and vertical vector splicing.

[0018] Furthermore, the method of testing the control accuracy of the extrusion cap production machine control model by using historical production extrusion cap related parameters includes historical original parameters used outside the training model, historical factory environment parameters, historical customer demand parameters, and historical actual extrusion cap machine control methods.

[0019] The accuracy rate is calculated based on the error value of the machine equipment operating parameters between the historical extrusion cap machine control method obtained by inputting the historical original parameters, the historical factory environment parameters, and the historical customer demand parameters into the extrusion cap production machine control model, and the historical actual extrusion cap machine control method.

[0020] Furthermore, the extrusion cap production machine control model utilizes a Fisher criterion-based classifier modified based on factory environment parameters and customer demand parameters.

[0021] An automated production system for extrusion caps for sauce packaging is also disclosed, including a raw material parameter acquisition module, a factory environment parameter acquisition module, an order receiving module, an extrusion cap production feature processing module, an extrusion cap production machine control model construction module, and an extrusion cap terminal control module, characterized in that:

[0022] The raw material parameter acquisition module acquires the original parameters of the raw materials that affect the production of extrusion caps for sauce packaging.

[0023] The factory environment parameter acquisition module acquires factory environment parameters that affect the production of squeeze caps for sauce packaging.

[0024] The order receiving module uploads and retrieves customer demand parameters that affect the production of extrusion caps for sauce packaging.

[0025] The extrusion cap production feature processing module: obtains extrusion cap production features from the original parameters of the raw materials, the factory environment parameters, and the customer demand parameters;

[0026] The extrusion cap production machine control model construction module: constructs an extrusion cap production machine control model using the characteristics of extrusion cap production and the corresponding extrusion cap machine control method.

[0027] The extrusion cap terminal control module is connected to the extrusion cap production machine control model construction module. It uses historical extrusion cap production parameters to test the accuracy of the control method generation of the extrusion cap production machine control model. Based on the extrusion cap production machine control model with an accuracy greater than a threshold, it generates the control method for the extrusion cap machine to be produced. The relevant management personnel of the extrusion cap production line perform automated production quality management of the extrusion caps according to the control method for the extrusion cap machine to be produced.

[0028] This invention considers and objectively calculates relevant data on the production of extruded caps from three parties, processes the data for application scenarios, and constructs a specific machine learning model based on the control scenarios required for actual extruded cap production machines. This automatically generates control methods for each module of the extruded cap production machine, assisting extruded cap production machine managers in adjusting the machine's operating parameters and managing the quality of extruded cap production.

[0029] Specifically, this invention addresses the issue by setting targeted and effective parameters for various data factors affecting the extrusion cap production process. Based on the experience of technical personnel and guided by historical results, it employs a simple and practical Fisher model to improve the control accuracy of parameters in each module of the extrusion cap production machine through scenario-specific parameter settings and improvements. Furthermore, it sets relevant accuracy thresholds to select the most suitable model after training, thereby assisting in the quality management of extrusion cap production, reducing labor costs, improving the quality of extrusion cap production, and increasing the satisfaction of B-end customers and C-end consumers with the high quality of extrusion cap products.

[0030] Further embodiments and improvements of the present invention will be described in conjunction with the accompanying drawings and specific examples. Attached Figure Description

[0031] Figure 1 This is a training diagram of an automated production method for squeeze caps for sauce packaging according to the present invention.

[0032] Figure 2 This is a schematic diagram of an automated production system for extrusion caps for sauce packaging according to the present invention;

[0033] Figure 3 This is a schematic diagram of the feeding track module in this invention;

[0034] Figure 4 This is an example diagram of the squeeze cap for packaging in this invention;

[0035] Figure 5 This is a schematic diagram of the improved Fisher criterion-based classifier in this invention. Detailed Implementation

[0036] The invention will now be further described in conjunction with the accompanying drawings and specific embodiments.

[0037] In a first aspect of the invention, an automated production method for squeeze caps for sauce packaging is provided, the method comprising:

[0038] Obtain the original parameters of raw materials, factory environmental parameters, and customer requirements that affect the production of extrusion caps for sauce packaging; and obtain the corresponding extrusion cap machine control methods.

[0039] The original parameters of the raw materials, the factory environment parameters, and the customer demand parameters are used to obtain the extrusion cap production characteristics.

[0040] Based on the characteristics of extrusion cap production and the corresponding extrusion cap machine control method, a control model for extrusion cap production machine is constructed.

[0041] The accuracy of the control method generated by the control model of the extruded cap production machine was tested by using relevant parameters from historical production of extruded caps.

[0042] Based on the extrusion cap production machine control model with an accuracy greater than a threshold, a control method for the extrusion cap machine to be produced is generated. Relevant management personnel of the extrusion cap production line perform automated production quality management of extrusion caps according to the control method for the extrusion cap machine to be produced.

[0043] In this embodiment Figure 1 It shows a flowchart of the specific model training and usage.

[0044] Furthermore, the original parameters are obtained by processing material type, density, melt flow index, and stamping index, and the calculation formula is as follows:

[0045]

[0046] In the formula, The original parameters, This represents the compensation value for raw material type K. If the raw material is polyethylene, then... The value is 0.05. If the raw material is polypropylene, then... The value is 0.072, which is the optimal raw material type compensation value set by the present invention based on the input and output features during model training. Let K be the density of the raw material. This represents the density of the dimensionless raw material K. Melt index is the mass of molten plastic passing through a specific aperture in 10 minutes under standard conditions. The unit is grams per 10 minutes (g / 10min). The ratio of tensile strength to impact strength of raw materials has a significant impact on the control methods of extrusion cap production machines. Targeted processing of the original parameters of the raw materials can enhance the precision of subsequent model generation for extrusion cap machine control methods.

[0047] Furthermore, the factory environmental parameters refer to the feed track environmental parameters, specifically obtained by processing the airflow temperature, relative humidity, and average wind speed of the feed track. The processing formula is as follows:

[0048]

[0049] In the formula, The factory environmental parameters, The average wind speed is typically between 0.5 and 1.5 m / s. The purpose of blowing air is to maintain a certain temperature at the joint of the outer cover, preventing excessive hardness due to rapid cooling and potential breakage during subsequent cap closure. Given its relatively low variation range and minimal impact on extrusion cap production, similarly, this invention utilizes a logarithmic function for constraint control to manipulate minute changes affecting the accuracy of the subsequent model. This invention considers the subtle variations in the extrusion cap production process, resulting in a more refined model control method. The humidity of the feed track. The optimal humidity is achieved when the lid is closed.

[0050] Furthermore, the customer demand parameters include the customer packaged sauce category value and the applicable population parameter. The customer packaged sauce category value S is obtained based on liquid and semi-solid, with liquid taking a value of 1 and semi-solid taking a value of 0.9. It is set according to the ease of extruding the packaged sauce. Liquid is easy to extrude, so its value is greater than that of semi-solid, in order to facilitate the subsequent classification processing of the model.

[0051] Furthermore, the applicable population parameters are calculated based on the consumer's grip strength level, age, and gender correction factor:

[0052]

[0053] In the formula, For the parameters of the applicable population, This is a gender correction factor; generally, women's grip strength is 80% of men's. The ratio of men to women is assumed to be equal for the target population. The value is 0.9, P is the consumer's grip strength level. Generally, the grip strength level of males is 50kg and that of females is 40kg. The consumer's grip strength level is calculated based on the average grip strength ratio. If the ratio of males and females is the same, then P is 45kg. N is the age of the group of consumers who use the product the most, which is 30 years old here.

[0054] Furthermore, the process of obtaining extrusion cap production characteristics from the original parameters of raw materials, the factory environment parameters, and the customer demand parameters is performed using a vector splicing method, which includes both horizontal and vertical vector splicing.

[0055] Furthermore, the method of testing the control accuracy of the extrusion cap production machine control model by using historical production extrusion cap related parameters includes historical original parameters used outside the training model, historical factory environment parameters, historical customer demand parameters, and historical actual extrusion cap machine control methods.

[0056] The accuracy rate is calculated based on the error value of machine equipment operating parameters between the historical extrusion cap machine control method obtained by inputting the historical original parameters, the historical factory environment parameters, and the historical customer demand parameters into the extrusion cap production machine control model, and the historical actual extrusion cap machine control method. The threshold is 90%.

[0057] Furthermore, the extrusion cap production machine control model utilizes a Fisher criterion-based classifier modified based on factory environment parameters and customer demand parameters.

[0058] Furthermore, the calculation formula for the Fisher criterion-based classifier, which is modified based on factory environment parameters and customer demand parameters, is as follows:

[0059]

[0060] In the formula, The output of the squeeze cap machine control method is given, where WT is the normal vector perpendicular to the hyperplane, obtained through model training. The extrusion cap production characteristics are as described above. The factory environmental parameters, For the customer's packaged sauce category value, For the parameters of the applicable population, the present invention is based on The output of the extrusion cap machine control method is selected based on the value, and there are four types of extrusion cap machine control methods, each targeting... The value is less than -1. The value is greater than or equal to -1 and less than 0. The value is 0. The values ​​are divided into four categories, each with a value greater than 0.

[0061] The extrusion capping process specifically includes the following steps:

[0062] 1. Outer cover injection molding.

[0063] The outer cover is formed by injection molding using a horizontal injection molding machine, which is a technology already in use.

[0064] 2. The contents are transferred to three vibrating discs for processing.

[0065] After injection molding, the outer cover is transported via a conveyor track to three vibratory feeders for cap finishing. The vibratory feeders are located inside the white cylindrical shell.

[0066] The material is transmitted from the vibratory feeder to the feeding track. Multiple air vents are inclined above and below the feeding track (the lower air vent is not shown; it is symmetrically positioned on both sides of the feeding track with the upper air vent). The upper air vent blows hot air to ensure the outer cover's connection point has a certain temperature, preventing it from becoming too hard due to rapid cooling and breaking during subsequent closing. The air from the upper and lower air vents together propels the outer cover forward. There are also three feeding tracks, with a moving feeding channel in the middle. Each feeding track is equipped with a sensor. When the outer covers on the feeding track reach the sensor's position, the number of outer covers on that track has reached a predetermined quantity. The moving feeding channel then moves to the corresponding feeding track, allowing the predetermined number of outer covers to move forward until they reach the closing mechanism.

[0067] The lid closing mechanism includes a turntable, with multiple fixed grippers on the outer periphery of the turntable to fix the outer lid. The outer periphery of the turntable also has a lid closing block. The outer lid passes through the lid closing block under the drive of the turntable to close the outer lid. The closed outer lid is then transported to the inner and outer lid assembly mechanism.

[0068] Meanwhile, in the inner and outer cover assembly mechanism, the soft cover and the soft cover bracket are first assembled together. The inner and outer cover assembly mechanism includes a turntable, and several positioning pins are set on the outer periphery of the turntable. One vibrating plate feeds the soft cover onto the positioning pin, and a cross mark is set in the middle of the soft cover. Another vibrating plate feeds the soft cover bracket onto the positioning pin and it is located above the soft cover. The pressure bar above the turntable presses down to combine the soft cover bracket and the soft cover together. The two combined parts are then removed from the positioning pin and moved upward. The pressure bar presses down again to press the soft cover bracket and the soft cover into the closed outer cover, completing the assembly of the inner and outer covers. The assembled cover is then conveyed to the soft aluminum film assembly mechanism.

[0069] The soft aluminum film assembly mechanism includes an unwinding machine and a rewinding machine. The cover is conveyed to the stamping platform, and the punch above stamps the soft aluminum film into the inner cavity of the cover, completing the assembly of the cover and the soft aluminum film. After that, the material is unloaded to complete the production of the extruded cover.

[0070] In this embodiment, the specific control method for the extrusion cap machine includes the corresponding operating parameters of each module of the extrusion cap production machine equipment, such as the horizontal injection molding machine, vibratory feeder, feed channel transmission speed, cap closing mechanism turntable speed, inner and outer cap assembly mechanism, and soft aluminum film assembly mechanism. The specific value ranges for the corresponding working parameters of each module are set here, which are the settings made by those skilled in the art as needed, and will not be elaborated here.

[0071] An automated production system for extrusion caps for sauce packaging is also provided, including a raw material parameter acquisition module, a factory environment parameter acquisition module, an order receiving module, an extrusion cap production feature processing module, an extrusion cap production machine control model construction module, and an extrusion cap terminal control module, characterized in that:

[0072] The raw material parameter acquisition module acquires the original parameters of the raw materials that affect the production of extrusion caps for sauce packaging.

[0073] The factory environment parameter acquisition module acquires factory environment parameters that affect the production of squeeze caps for sauce packaging.

[0074] The order receiving module uploads and retrieves customer demand parameters that affect the production of extrusion caps for sauce packaging.

[0075] The extrusion cap production feature processing module: obtains extrusion cap production features from the original parameters of the raw materials, the factory environment parameters, and the customer demand parameters;

[0076] The extrusion cap production machine control model construction module: constructs an extrusion cap production machine control model using the characteristics of extrusion cap production and the corresponding extrusion cap machine control method.

[0077] The extrusion cap terminal control module is connected to the extrusion cap production machine control model construction module. It uses historical extrusion cap production parameters to test the accuracy of the control method generation of the extrusion cap production machine control model. Based on the extrusion cap production machine control model with an accuracy greater than a threshold, it generates the control method for the extrusion cap machine to be produced. The relevant management personnel of the extrusion cap production line perform automated production quality management of the extrusion caps according to the control method for the extrusion cap machine to be produced.

[0078] This invention considers and objectively calculates relevant data on the production of extruded caps from three parties, processes the data for application scenarios, and constructs a specific machine learning model based on the control scenarios required for actual extruded cap production machines. This automatically generates control methods for each module of the extruded cap production machine, assisting extruded cap production machine managers in adjusting the machine's operating parameters and managing the quality of extruded cap production.

[0079] like Figure 4 As shown, the extrusion cap includes an outer cap, an inner cap, and a soft aluminum film. The inner cap includes a soft cap (with a cross-shaped scratch in the middle as an opening) and a soft cap bracket. The soft cap is assembled in the soft cap bracket, and the soft cap bracket is then connected to the outer cap.

[0080] Specifically, this invention addresses the issue by setting targeted and effective parameters for various data factors affecting the extrusion cap production process. Based on the experience of technical personnel and guided by historical results, it employs a simple and practical Fisher model to improve the control accuracy of parameters in each module of the extrusion cap production machine through scenario-specific parameter settings and improvements. Furthermore, it sets relevant accuracy thresholds to select the most suitable model after training, thereby assisting in the quality management of extrusion cap production, reducing labor costs, improving the quality of extrusion cap production, and increasing the satisfaction of B-end customers and C-end consumers with the high quality of extrusion cap products.

[0081] Of course, it is understood that each embodiment of the present invention can achieve one of the effects on its own, and the combination of multiple embodiments of the present invention can achieve all the above effects. However, it is not required that each embodiment of the present invention achieve all the above advantages and effects, because each embodiment of the present invention can constitute a separate technical solution and make one or more contributions to the prior art.

[0082] For any module structures not specifically defined in this invention, the existing technical specifications shall prevail. The existing technical specifications mentioned in the foregoing background and specific embodiments sections are considered part of this invention and are used to understand the meaning of certain technical features or parameters. The scope of protection of this invention is determined by the actual contents of the claims.

Claims

1. An automated production method of an extrusion-extrusion lid for sauce packaging, characterized by, The method includes: Obtain the original parameters of raw materials, factory environmental parameters, and customer requirements that affect the production of extrusion caps for sauce packaging; and obtain the corresponding extrusion cap machine control methods. The original parameters of the raw materials, the factory environment parameters, and the customer demand parameters are used to obtain the extrusion cap production characteristics. Based on the characteristics of extrusion cap production and the corresponding extrusion cap machine control method, a control model for extrusion cap production machine is constructed. The accuracy of the control method generated by the control model of the extruded cap production machine was tested by using relevant parameters from historical production of extruded caps. Based on the extrusion cap production machine control model with an accuracy greater than the threshold, the control method for the extrusion cap machine to be produced is generated, and the relevant management personnel of the extrusion cap production line perform automated production quality management of extrusion caps according to the control method for the extrusion cap machine to be produced. The original parameters are obtained by processing material type, density, melt flow index, and stamping index, and the calculation formula is as follows: wherein, is the original parameter, represents a compensation value for the raw material kind K, is the density of the raw material K, represents the density of the raw material K which is non-dimensionalized, is the melt index of the raw material, is the ratio of the tensile strength to the impact strength of the raw material; The factory environmental parameters refer to the feed track environmental parameters, specifically obtained by processing the feed track's blowing temperature, relative humidity, and average wind speed. The processing formula is as follows: wherein is the factory environment parameter, is the average wind speed, is the humidity of the feed track, is the optimal humidity for capping; The extrusion cap production machine control model utilizes a Fisher criterion-based classifier modified based on factory environmental parameters and customer demand parameters. The calculation formula for the Fisher criterion-based classifier modified based on factory environmental parameters and customer demand parameters is as follows: In the formula, The output is the control method for the extrusion cap machine. The normal vector perpendicular to the hyperplane is obtained through model training. The extrusion cap production characteristics are as described above. The factory environmental parameters, For the customer's packaged sauce category value, Parameters for the applicable population.

2. The automated production method for extrusion caps for sauce packaging as described in claim 1, characterized in that: The customer demand parameters include the customer packaged sauce category value and the applicable population parameter. The customer packaged sauce category value S is obtained based on liquid and semi-solid.

3. The automated production method for extrusion caps for sauce packaging as described in claim 2, characterized in that: The applicable population parameters are calculated based on consumers' grip strength level, age, and gender correction factors: In the formula, For the parameters of the applicable population, This is a gender correction factor. The value is 0.9, where P is the consumer's grip strength level and N is the age of the group of consumers who use the product the most.

4. An automated production method for extrusion caps for sauce packaging as described in claim 1, characterized in that: The process of obtaining extrusion cap production characteristics from the original parameters of raw materials, the factory environment parameters, and the customer demand parameters is performed using a vector splicing method, which includes horizontal vector splicing and vertical vector splicing.

5. An automated production method for extrusion caps for sauce packaging as described in claim 1, characterized in that: The method of testing the control accuracy of the extrusion cap production machine control model by using historical production extrusion cap related parameters includes historical original parameters used outside the training model, historical factory environment parameters, historical customer demand parameters, and historical actual extrusion cap machine control methods. The accuracy rate is calculated based on the error value of the machine equipment operating parameters between the historical extrusion cap machine control method obtained by inputting the historical original parameters, the historical factory environment parameters, and the historical customer demand parameters into the extrusion cap production machine control model, and the historical actual extrusion cap machine control method.

6. An automated production system for extrusion caps for sauce packaging, comprising a raw material parameter acquisition module, a factory environment parameter acquisition module, an order receiving module, an extrusion cap production feature processing module, an extrusion cap production machine control model construction module, and an extrusion cap terminal control module, characterized in that: The raw material parameter acquisition module acquires the original parameters of the raw materials that affect the production of extrusion caps for sauce packaging. The factory environment parameter acquisition module acquires factory environment parameters that affect the production of squeeze caps for sauce packaging. The original parameters are obtained by processing material type, density, melt flow index, and stamping index, and the calculation formula is as follows: In the formula, The original parameters, This represents the compensation value for raw material type K. Let K be the density of the raw material. This represents the density of the dimensionless raw material K. The melt flow index of the raw material. This is the ratio of the tensile strength to the impact strength of the raw material. The factory environmental parameters refer to the feed track environmental parameters, specifically obtained by processing the feed track's blowing temperature, relative humidity, and average wind speed. The processing formula is as follows: In the formula, The factory environmental parameters, The average wind speed is... The humidity of the feed track. For optimal humidity when the lid is closed; The order receiving module uploads and retrieves customer demand parameters that affect the production of extrusion caps for sauce packaging. The extrusion cap production feature processing module: obtains extrusion cap production features from the original parameters of the raw materials, the factory environment parameters, and the customer demand parameters; The extrusion cap production machine control model construction module: This module constructs a control model for the extrusion cap production machine using the characteristics of extrusion cap production and the corresponding extrusion cap machine control method. The control model utilizes a Fisher criterion-based classifier modified based on factory environment parameters and customer demand parameters. The calculation formula for this Fisher criterion-based classifier is shown below: In the formula, The output is the control method for the extrusion cap machine. The normal vector perpendicular to the hyperplane is obtained through model training. The extrusion cap production characteristics are as described above. The factory environmental parameters, For the customer's packaged sauce category value, Parameters for the applicable population; The extrusion cap terminal control module is connected to the extrusion cap production machine control model construction module. It uses historical extrusion cap production parameters to test the accuracy of the control method generation of the extrusion cap production machine control model. Based on the extrusion cap production machine control model with an accuracy greater than a threshold, it generates the control method for the extrusion cap machine to be produced. The relevant management personnel of the extrusion cap production line perform automated production quality management of the extrusion caps according to the control method for the extrusion cap machine to be produced.

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