Product manufacturing methods, apparatus, equipment, storage media, and products

Abstract

This application discloses a product manufacturing method, apparatus, equipment, storage medium, and product, relating to the field of product manufacturing technology. The product manufacturing method includes: acquiring product information of a product to be manufactured; performing parameter analysis on the product information using a preset parameter model to obtain analyzed production parameters; sending the production parameters to an edge controller, so that the edge controller can set parameters for functional areas based on the production parameters, and process the product to be manufactured based on the parameter-set functional areas. This application avoids the problem of reduced product manufacturing efficiency caused by manually adjusting various production parameters after changing molds.

Description

Technical Field

[0001] This application relates to the field of product manufacturing technology, and in particular to a product manufacturing method, apparatus, equipment, storage medium, and product. Background Technology

[0002] Pultrusion is a continuous production process for composite materials, primarily used to manufacture long, straight profiles such as rods, tubes, plates, and angle steel. This process is commonly used to produce fiber-reinforced plastics (FRPs), where glass fiber is the most frequently used reinforcing material, and thermosetting resins (such as unsaturated polyesters, epoxy resins, or vinyl esters) serve as the matrix material.

[0003] In related technologies, when producing products through composite material pultrusion molding, after changing the product mold, it is necessary to manually adjust various production parameters after the mold change, which reduces the production efficiency of the product. Summary of the Invention

[0004] The main purpose of this application is to provide a product manufacturing method, apparatus, equipment, storage medium, and product, aiming to solve the technical problem that after changing the product mold, it is necessary to manually adjust various production parameters after the mold change, which reduces the production efficiency of the product.

[0005] To achieve the above objectives, this application proposes a product manufacturing method applied to a host computer, wherein the host computer is communicatively connected to at least one edge controller, and one edge controller corresponds to multiple functional areas;

[0006] The product manufacturing method includes:

[0007] Obtain product information for products to be manufactured;

[0008] The product information is analyzed using a preset parameter model to obtain the analyzed production parameters.

[0009] The production parameters are sent to the edge controller, which then sets the parameters of the functional area based on the production parameters and processes the product to be produced based on the parameter-set functional area.

[0010] In one embodiment, the edge controller includes at least one monitoring device, and prior to the step of acquiring product information of the product to be manufactured, the following steps are included:

[0011] Receive historical parameter data of the functional area collected by the monitoring device from the edge controller, and obtain the initial parameter model;

[0012] The historical parameter data is input into the initial parameter model, and the initial parameter model is iteratively trained to obtain the preset parameter model.

[0013] In one embodiment, the step of inputting the historical parameter data into the initial parameter model and iteratively training the initial parameter model to obtain a preset parameter model includes:

[0014] The historical product parameters of the historical parameter data are input into the initial parameter model to obtain the initial production parameters predicted by the initial parameter model;

[0015] Based on the historical production parameters and the initial production parameters from the historical parameter data, the initial parameter model is iteratively trained to obtain a preset parameter model that meets the accuracy requirements.

[0016] In one embodiment, after the step of sending the production parameters to the edge controller so that the edge controller can set parameters for the functional area based on the production parameters, and processing the product to be produced based on the parameter-set functional area, the process includes:

[0017] The system receives production information from the monitoring of each functional area after parameter settings by the monitoring device, wherein the production information includes yarn information from the yarn feeding area and quality information from the traction area;

[0018] Based on the production parameters, anomaly analysis is performed on the functional area corresponding to the production information to obtain the anomaly analysis results.

[0019] In one embodiment, the edge controller includes an alarm device. After the step of performing anomaly analysis on the functional area corresponding to the production information based on the production parameters and obtaining the anomaly analysis result, the method includes:

[0020] If the yarn information and / or the quality information are abnormal, an alarm signal is sent to the edge controller so that the alarm device of the edge controller can issue an early warning based on the alarm signal.

[0021] In one embodiment, after the step of sending the production parameters to the edge controller so that the edge controller can set parameters for the functional area based on the production parameters, and processing the product to be produced based on the parameter-set functional area, the method further includes:

[0022] Based on the production parameters, information tags are generated so that users can obtain the production parameters of the processed product to be produced based on the information tags.

[0023] Furthermore, to achieve the above objectives, this application also proposes a product manufacturing apparatus, which includes:

[0024] The acquisition module is used to acquire product information of the products to be manufactured.

[0025] The analysis module is used to perform parameter analysis on the product information using a preset parameter model to obtain the analyzed production parameters;

[0026] The production module is used to send the production parameters to the edge controller, so that the edge controller can set the parameters of the functional area based on the production parameters, and process the product to be produced based on the functional area after the parameter setting.

[0027] In addition, to achieve the above objectives, this application also proposes a product manufacturing apparatus, the apparatus comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the product manufacturing method as described above.

[0028] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and which, when executed by a processor, implements the steps of the product manufacturing method described above.

[0029] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the product manufacturing method described above.

[0030] One or more technical solutions proposed in this application have at least the following technical effects:

[0031] Compared to related technologies where manual adjustments to production parameters are required after mold replacement, reducing production efficiency, this application obtains product information of the product to be produced; analyzes the product information using a preset parameter model to obtain analyzed production parameters; and sends these production parameters to an edge controller. The edge controller then sets parameters for functional areas based on these production parameters and processes the product to be produced based on the parameter-set functional areas. In essence, this application automatically analyzes the product information using a preset parameter model after obtaining the product information and automatically sends the analyzed production parameters to the edge controller. The edge controller then automatically sets parameters for functional areas based on the obtained production parameters, eliminating the need for manual adjustments to production parameters after mold replacement. This avoids the problem of reduced production efficiency caused by manual adjustments to production parameters after mold replacement. Attached Figure Description

[0032] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0033] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a flowchart illustrating the first embodiment of the product manufacturing method of this application.

[0035] Figure 2 This is an overall architecture diagram of the product manufacturing method of this application;

[0036] Figure 3 A simplified flowchart illustrating the product manufacturing method provided in Embodiment 2 of this application;

[0037] Figure 4 This is a schematic diagram of the modular structure of the product manufacturing apparatus according to an embodiment of this application;

[0038] Figure 5 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the product manufacturing method in this application embodiment.

[0039] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0040] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0041] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0042] The main solution of this application embodiment is: to obtain product information of the product to be produced; to perform parameter analysis on the product information through a preset parameter model to obtain the analyzed production parameters; to send the production parameters to the edge controller so that the edge controller can set the parameters of the functional area based on the production parameters, and process the product to be produced based on the parameter-set functional area.

[0043] In related technologies, when producing products through composite material pultrusion molding, after changing the product mold, it is necessary to manually adjust various production parameters after the mold change, which reduces the production efficiency of the product.

[0044] After obtaining the product information of the product to be manufactured, this application automatically performs parameter analysis on the product information through a preset parameter model, and automatically sends the analyzed production parameters to the edge controller. The edge controller then automatically sets the parameters of the functional area based on the obtained production parameters, eliminating the need for manual adjustment of various production parameters after mold change. After parameter setting, the product to be manufactured is processed, thus avoiding the problem of reduced production efficiency caused by manual adjustment of various production parameters after mold change.

[0045] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions. The following description uses product manufacturing equipment as an example to illustrate this embodiment and the subsequent embodiments.

[0046] Based on this, the embodiments of this application provide a product manufacturing method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the product manufacturing method of this application.

[0047] In this embodiment, refer to Figure 2 , Figure 2 As shown in the overall architecture diagram, the product manufacturing method includes steps S100 to S300:

[0048] Step S100: Obtain product information of the product to be manufactured;

[0049] It should be noted that the execution entity in this embodiment is the product manufacturing equipment, which is equipped with a host computer. The product information includes the product cross-sectional shape, the product height-to-height ratio, and the minimum feature size. After changing the product model, the product manufacturing equipment uploads the product information corresponding to the new model to the host computer, whereby the product information includes the product cross-sectional shape, the product height-to-height ratio, and the minimum feature size.

[0050] In one feasible implementation, the following steps are included before step S100:

[0051] Receive historical parameter data of the functional area collected by the monitoring device from the edge controller, and obtain the initial parameter model;

[0052] Understandably, the product manufacturing equipment also includes an edge controller and a functional area. The edge controller is equipped with monitoring devices, and the functional area houses the production equipment. The edge controller controls the production equipment in the functional area and sets its production parameters. Historical parameter data includes yarn count, traction speed, traction force, injection pressure, injection volume, mixing ratio, extruder cross-section to die cross-section ratio, yarn inlet cone angle, and curing temperature of each zone. The initial parameter model is a mathematical model that can preliminarily predict production parameters. The product manufacturing equipment collects production parameter data in the functional area through the edge controller's monitoring devices, obtaining historical parameter data, and uploads this data to the host computer. The host computer also stores the initial parameter model, where historical parameter data includes yarn count, traction speed, traction force, injection pressure, injection volume, mixing ratio, extruder cross-section to die cross-section ratio, yarn inlet cone angle, and curing temperature of each zone.

[0053] The historical parameter data is input into the initial parameter model, and the initial parameter model is iteratively trained to obtain the preset parameter model.

[0054] It should be noted that the preset parameter model is used to analyze new product information and generate optimized production parameters. The product production equipment uses historical parameter data as input and iteratively trains the initial parameter model through machine learning algorithms to obtain the trained preset parameter model.

[0055] In one feasible implementation, the step of inputting the historical parameter data into the initial parameter model and iteratively training the initial parameter model to obtain a preset parameter model includes the following steps:

[0056] The historical product parameters of the historical parameter data are input into the initial parameter model to obtain the initial production parameters predicted by the initial parameter model;

[0057] Understandably, the product manufacturing equipment uses historical product parameters from historical parameter data as input features (X), inputs X into the initial parameter model, and obtains the initial production parameters predicted by the initial parameter model.

[0058] Based on the historical production parameters and the initial production parameters from the historical parameter data, the initial parameter model is iteratively trained to obtain a preset parameter model that meets the accuracy requirements.

[0059] It should be noted that historical production parameters refer to the production parameters used during the production of the product corresponding to historical product parameters. The product production equipment uses historical production parameters as a label (Y) and minimizes the distance between Y and the initial production parameters by adjusting the internal parameters of the initial parameter model, thereby obtaining a preset parameter model that meets the accuracy requirements.

[0060] Step S200: Analyze the product information using a preset parameter model to obtain the analyzed production parameters;

[0061] Understandably, production parameters are parameters used to set up production equipment. The host computer of the product production equipment analyzes the parameters corresponding to the acquired product information through a preset parameter model to obtain the analyzed production parameters used to set up the production equipment.

[0062] Step S300: The production parameters are sent to the edge controller so that the edge controller can set the parameters of the functional area based on the production parameters, and process the product to be produced based on the functional area after the parameter setting.

[0063] It should be noted that the product manufacturing equipment sends the obtained production parameters to the edge controller. After receiving the production parameters, the edge controller can set the parameters of the production equipment corresponding to the functional area. After the parameters are set, the functional area can carry out product manufacturing. The functional area includes the yarn feeding area, glue injection area, pultrusion area and cutting area.

[0064] In this embodiment, after obtaining product information, the product manufacturing equipment automatically analyzes the product information using a preset parameter model trained on the initial parameter model. Based on the production parameters obtained after the analysis, the equipment is automatically set by the edge controller, thereby machining the product to be manufactured and improving the production efficiency.

[0065] This application provides a product manufacturing method, referring to... Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the product manufacturing method of this application.

[0066] In one feasible implementation, step S300 is followed by the following steps A10 to A20:

[0067] Step A10: Receive production information obtained by the monitoring device after parameter settings for each of the functional areas, wherein the production information includes yarn information of the yarn feeding area and quality information of the traction area;

[0068] Understandably, the monitoring equipment includes scanning devices and visual monitoring. The traction area is equipped with scanning devices for product quality inspection of the products exiting the traction area, while the yarn feeding area is equipped with visual monitoring for inspecting the yarn condition. The production equipment acquires video images of the yarn through visual monitoring and preprocesses these images to better identify the yarn and extract its position and condition features from the processed images. The production equipment also captures images of the products through scanning devices and extracts key product features, such as size and appearance defects, from the preprocessed images. The monitoring equipment of the production equipment acquires production information from each functional area.

[0069] Specifically, the product manufacturing equipment can also analyze yarn and quality information through preset detection models. These preset detection models include a yarn detection sub-model and a quality detection sub-model. Specifically, the product manufacturing equipment acquires video images of the yarn through visual monitoring and uses the yarn detection sub-model to analyze the pre-processed images to determine the specific location of the yarn in the image and analyze its appearance characteristics, such as diameter consistency, surface defects (e.g., knots, burrs), and color uniformity. The product manufacturing equipment acquires product images through scanning equipment and identifies product appearance defects, such as wrinkles and stains, through the quality detection sub-model. Real-time quality control can be achieved through these preset detection models, ensuring that the quality of the yarn and the final product meets the prescribed standards, thereby improving production efficiency and product quality.

[0070] The functions of the ribbon are as follows:

[0071] 1. Yarn delivery area

[0072] Automatic temperature control device: Maintains the glass fiber yarn on the yarn rack at a suitable temperature to ensure the stability and consistency of the yarn during the feeding process.

[0073] Automatic humidity control device: controls the humidity around the yarn rack to prevent the yarn from being affected by humidity changes in subsequent processing.

[0074] Yarn feeding stage:

[0075] Motion mechanism: Controlling the movement of the yarn guide plate to ensure that the yarn is evenly fed into the mold.

[0076] Conical angle adjustment: Adjusting the conical angle of the yarn feed inlet helps the yarn to be better distributed and spread.

[0077] Visual monitoring system: Monitors the condition of yarn and promptly detects and addresses yarn abnormalities.

[0078] 2. Glue injection area

[0079] Mold:

[0080] Zoned heating: The mold is divided into multiple heating zones, and the temperature of each zone can be controlled independently to meet the curing requirements of different locations.

[0081] Temperature sensor: Used to monitor the temperature inside the mold and ensure that the temperature is controlled within the ideal range.

[0082] Temperature and pressure sensors: monitor temperature and pressure to further ensure process stability.

[0083] Glue dispensing device:

[0084] Metering pump: Precisely controls the amount of resin injected, ensuring consistent formulation for each section of composite material.

[0085] Formula data recording: Records formula data for each use, facilitating traceability and optimization.

[0086] 3. Pulling Zone

[0087] Curing area:

[0088] Thermal imaging camera: Monitors the temperature distribution of the product to ensure the uniformity of the curing process.

[0089] Multi-stage curing: The product passes through multiple curing zones, gradually completing the curing process.

[0090] Traction Zone:

[0091] Pressure sensor: Monitors the magnitude of traction force to ensure a smooth pultrusion process.

[0092] Scanning equipment: Used for quality inspection and dimensional measurement of products to ensure that product quality meets standards.

[0093] 4. Cutting area

[0094] Cutting:

[0095] Product retesting: A final quality check of the product.

[0096] Cutting: Cut the composite material to the required length according to the product specifications.

[0097] Picking: Collecting and organizing the cut products.

[0098] Step A20: Based on the production parameters, perform anomaly analysis on the functional area corresponding to the production information to obtain the anomaly analysis results.

[0099] It should be noted that the anomaly analysis results are used to characterize the working status of the functional area. The product manufacturing equipment compares the production parameters corresponding to the production information. Based on the distance between the production parameters corresponding to the production information and the production parameters output by the model, anomaly analysis is performed on the equipment in the functional area corresponding to the production information. Thus, anomaly analysis results are obtained to characterize the working status of the functional area. If the distance is greater than a preset threshold, an anomaly is identified.

[0100] In one feasible implementation, after performing anomaly analysis on the functional area corresponding to the production information based on the production parameters and obtaining the anomaly analysis results, the following steps are included:

[0101] If the yarn information and / or the quality information are abnormal, an alarm signal is sent to the edge controller so that the alarm device of the edge controller can issue an early warning based on the alarm signal.

[0102] Understandably, yarn information includes information such as the yarn's state and position. Quality information includes information such as the product's dimensions and appearance defects. The production equipment extracts key features from both yarn and quality information using a pre-set algorithm, resulting in yarn features and quality features. For each feature, the production equipment defines a scoring function, mapping the feature to a score. This score is typically between 0 and 1, where 1 represents perfect and 0 represents completely non-compliant. For example:

[0103] Size rating: A function can be defined that takes the deviation between the measured size and the target size as input and outputs a score. For example, assuming the target size is 100mm and the tolerance range is ±2mm, the size rating function can be defined as follows:

[0104]

[0105] Appearance defect scoring: A function can be defined based on the number or severity of defects. For example, a maximum allowed number of defects can be set, and then a score can be given based on the actual number of defects detected. An appearance defect scoring function can be defined as follows:

[0106]

[0107] Finally, the scores of all features are combined to obtain a comprehensive score. This can be achieved by simply calculating a weighted average, or by using other methods (such as machine learning models). For example, if all features are equally important, it can be calculated as follows:

[0108]

[0109] After the product manufacturing equipment obtains a comparable score, it compares the converted score with a preset threshold. If the score is lower than the preset threshold, an anomaly is identified. When an anomaly is detected, the product manufacturing equipment sends an alarm signal to the edge controller. When the edge controller receives the alarm signal, it triggers the corresponding device to issue a warning.

[0110] In one possible implementation, the following steps are included after step S300:

[0111] Based on the production parameters, an information tag is generated. If the quality of the target product obtained after processing is unqualified, the user can obtain the production parameters of the target product based on the information tag.

[0112] It should be noted that the information label can be a barcode, QR code, or other form. The product manufacturing equipment uses production parameters set for the functional areas and associates these parameters with specific product batches or individual items. This generates an information label containing the production parameters for each batch or product; this label can be a barcode, QR code, or other form. The resulting information label is printed and affixed to the surface of each batch of products. After production is complete, the products can be inspected for quality. If a quality problem is found, the user can retrieve the production parameters for that batch of products by reading the information label, thus tracing the product's production process.

[0113] In this embodiment, after the device parameters of the functional area are set, the product manufacturing equipment monitors each functional area during the production process to obtain production information. The production information is used to check the product quality during the production process. If the quality is abnormal, an early warning is issued. After the product is produced, information tags are generated based on the production parameters so that users can trace the production process based on the information tags, thereby improving the production efficiency of the product.

[0114] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the production method of the product of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0115] This application also provides a product manufacturing apparatus; please refer to... Figure 4 The product manufacturing apparatus includes:

[0116] Module 10 is used to acquire product information of the product to be manufactured;

[0117] The analysis module 20 is used to perform parameter analysis on the product information using a preset parameter model to obtain the analyzed production parameters;

[0118] The production module 30 is used to send the production parameters to the edge controller, so that the edge controller can set the parameters of the functional area based on the production parameters, and process the product to be produced based on the functional area after the parameter setting.

[0119] Optionally, the acquisition module includes:

[0120] The input module is used to receive historical parameter data of the functional area collected by the monitoring device sent by the edge controller, and to obtain an initial parameter model; input the historical parameter data into the initial parameter model, and iteratively train the initial parameter model to obtain a preset parameter model.

[0121] Optionally, the input module includes:

[0122] The training module is used to input the historical product parameters of the historical parameter data into the initial parameter model to obtain the initial production parameters predicted by the initial parameter model; based on the historical production parameters of the historical parameter data and the initial production parameters, the initial parameter model is iteratively trained to obtain a preset parameter model that meets the accuracy conditions.

[0123] Optionally, the production module includes:

[0124] The analysis module receives production information from the monitoring device after parameter settings for each of the functional areas, including yarn information from the yarn feeding area and quality information from the traction area; based on the production parameters, it performs anomaly analysis on the functional areas corresponding to the production information to obtain anomaly analysis results.

[0125] The tag module is used to generate information tags based on the production parameters. If the quality of the target product obtained after processing is unqualified, the user can obtain the production parameters of the target product based on the information tags.

[0126] Optionally, the analysis module includes:

[0127] The early warning module is used to send an alarm signal to the edge controller if the yarn information and / or the quality information is abnormal, so that the alarm device of the edge controller can issue an early warning based on the alarm signal.

[0128] The product manufacturing apparatus provided in this application, employing the product manufacturing method described in the above embodiments, can solve the technical problems in product manufacturing. Compared with the prior art, the beneficial effects of the product manufacturing apparatus provided in this application are the same as those of the product manufacturing method described in the above embodiments, and other technical features in the product manufacturing apparatus are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0129] This application provides a product manufacturing apparatus, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the product manufacturing method in Embodiment 1 above.

[0130] The following is for reference. Figure 5 The diagram illustrates a structural schematic of a product manufacturing apparatus suitable for implementing embodiments of this application. The product manufacturing apparatus in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, tablets, digital broadcast receivers, PDAs (Personal Digital Assistants), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The product manufacturing equipment shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0131] like Figure 5 As shown, the product manufacturing equipment may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the product manufacturing equipment. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the product manufacturing equipment to communicate wirelessly or wiredly with other equipment to exchange data. Although the figure shows product manufacturing equipment with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0132] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0133] The product manufacturing equipment provided in this application, employing the product manufacturing method described in the above embodiments, can solve the technical problems in product manufacturing. Compared with the prior art, the beneficial effects of the product manufacturing equipment provided in this application are the same as those of the product manufacturing method described in the above embodiments, and other technical features of the product manufacturing equipment are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0134] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0135] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0136] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the product manufacturing method described in the above embodiments.

[0137] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0138] The aforementioned computer-readable storage medium may be included in the product manufacturing equipment; or it may exist independently and not assembled into the product manufacturing equipment.

[0139] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the product manufacturing equipment, the product manufacturing equipment: acquires product information of the product to be manufactured; performs parameter analysis on the product information through a preset parameter model to obtain the analyzed production parameters; and sends the production parameters to an edge controller so that the edge controller can set parameters for the functional area based on the production parameters, and process the product to be manufactured based on the parameter-set functional area.

[0140] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0141] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0142] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0143] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described product manufacturing method, thereby solving the technical problems in product manufacturing. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the product manufacturing method provided in the above embodiments, and will not be repeated here.

[0144] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the product manufacturing method described above.

[0145] The computer program product provided in this application can solve the technical problems in product manufacturing. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the product manufacturing method provided in the above embodiments, and will not be repeated here.

[0146] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for producing pultruded products, characterized in that, The application is to a host computer, which is communicatively connected to at least one edge controller. One edge controller corresponds to multiple functional areas, and the edge controller includes at least one monitoring device. The product manufacturing method includes: The system receives historical parameter data of the functional area collected by the monitoring device and sends it to the edge controller, and obtains an initial parameter model. The functional area includes a yarn feeding area and a traction area. The historical parameter data is input into the initial parameter model, and the initial parameter model is iteratively trained to obtain the preset parameter model; Obtain product information for products to be manufactured; The product information is analyzed using a preset parameter model to obtain the analyzed production parameters. The production parameters are sent to the edge controller, which then sets the parameters of the functional area based on the production parameters, and processes the product to be produced based on the functional area after the parameter settings. The system receives production information from the monitoring of each functional area after parameter settings by the monitoring device, wherein the production information includes yarn information from the yarn feeding area and quality information from the traction area; Based on the production parameters, anomaly analysis is performed on the functional area corresponding to the production information to obtain the anomaly analysis results.

2. The method for producing pultruded products as described in claim 1, characterized in that, The step of inputting the historical parameter data into the initial parameter model and iteratively training the initial parameter model to obtain the preset parameter model includes: The historical product parameters of the historical parameter data are input into the initial parameter model to obtain the initial production parameters predicted by the initial parameter model; Based on the historical production parameters and the initial production parameters from the historical parameter data, the initial parameter model is iteratively trained to obtain a preset parameter model that meets the accuracy requirements.

3. The method for producing pultruded products as described in claim 1, characterized in that, The edge controller includes an alarm device. Following the step of performing anomaly analysis on the functional area corresponding to the production information based on the production parameters and obtaining the anomaly analysis results, the following steps are included: If the yarn information and / or the quality information are abnormal, an alarm signal is sent to the edge controller so that the alarm device of the edge controller can issue an early warning based on the alarm signal.

4. The method for producing pultruded products as described in claim 1, characterized in that, The step of sending the production parameters to the edge controller, so that the edge controller can set the parameters of the functional area based on the production parameters, and processing the product to be produced based on the parameter-set functional area, further includes: Based on the production parameters, information tags are generated so that users can obtain the production parameters of the processed product to be produced based on the information tags.

5. A pultrusion molding product manufacturing apparatus, characterized in that, Applied to a host computer, the host computer is communicatively connected to at least one edge controller, one edge controller corresponds to multiple functional areas, the edge controller includes at least one monitoring device, and the device includes: The acquisition module includes: The input module is used to receive historical parameter data of the functional area collected by the monitoring device sent by the edge controller, and to obtain an initial parameter model. The functional area includes a yarn feeding area and a traction area. The historical parameter data is input into the initial parameter model, and the initial parameter model is iteratively trained to obtain a preset parameter model. The acquisition module is used to acquire product information of the product to be manufactured; The analysis module is used to perform parameter analysis on the product information using a preset parameter model to obtain the analyzed production parameters; The production module is used to send the production parameters to the edge controller, so that the edge controller can set the parameters of the functional area based on the production parameters, and realize product production based on the functional area after parameter setting; The production module includes: The analysis module receives production information from the monitoring device after parameter settings for each of the functional areas, including yarn information from the yarn feeding area and quality information from the traction area; based on the production parameters, it performs anomaly analysis on the functional areas corresponding to the production information to obtain anomaly analysis results.

6. A pultrusion molding product manufacturing equipment, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the pultrusion product manufacturing method as described in any one of claims 1 to 4.

7. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the pultrusion molding product manufacturing method as described in any one of claims 1 to 4.

8. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the pultrusion product manufacturing method as described in any one of claims 1 to 4.

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