Environment control system and method for capacitor production and processing

Abstract

The invention provides an environment control system and method for capacitor production and processing, relates to the field of capacitor production, and solves the technical problems that a conventional environment control system mostly adopts fixed threshold alarm or simple PID adjustment, so that the adjustment strategy is'one-time ', and response lag, adjustment overshoot or low energy efficiency easily occur. The method comprises the following steps: determining core production equipment of the capacitor, and collecting working environment parameters of the core production equipment; the working environment quality index of the core production equipment is analyzed, and whether the working environment quality index is larger than a preset index threshold value or not is judged; if yes, the working environment is abnormal, and the compensation value of the environment parameter is analyzed; if not, the working environment is normal, and whether the process quality of the capacitor is qualified is evaluated; if so, continuing production; and if not, analyzing the compensation value of the environmental parameter. The method is used in the environment control process of capacitor production and processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of capacitor production, and in particular to an environment control system and method for capacitor production and processing. BACKGROUND

[0002] In the production process of capacitors, especially high-performance thin-film capacitors and multilayer ceramic capacitors (MLCC), key processes such as coating, winding, drying, and lamination are extremely sensitive to environmental conditions. Small fluctuations in temperature, humidity, cleanliness, or static electricity can lead to quality problems such as uneven coating, dielectric defects, breakdown voltage reduction, or capacitance drift, which can further cause batch defects.

[0003] Traditional environment control systems often use fixed threshold alarms or simple PID regulation, resulting in a "one-size-fits-all" adjustment strategy that can lead to response lags, over-adjustment, or low energy efficiency. Therefore, the present application provides an environment control system and method for capacitor production and processing. SUMMARY

[0004] The present application provides an environment control system and method for capacitor production and processing, which solves the technical problem of traditional environment control systems using fixed threshold alarms or simple PID regulation, resulting in a "one-size-fits-all" adjustment strategy that can lead to response lags, over-adjustment, or low energy efficiency.

[0005] To achieve the above-mentioned purposes, the present application adopts the following technical solutions: In a first aspect, an environment control method for capacitor production and processing is provided, comprising: analyzing the environmental sensitivity index and quality index of each production equipment of the capacitor to determine the core production equipment of the capacitor and collect the environmental parameters of the core production equipment; the environmental sensitivity index is the sensitivity of the production equipment to changes in the working environment; the quality index is a statistical indicator of defective products produced by the production equipment during the production cycle; analyzing the working environmental quality index of the core production equipment based on the collected environmental parameters; the environmental quality index is a comprehensive evaluation indicator of the working environment of the core production equipment; determining whether the working environmental quality index is greater than a preset index threshold; if yes, the working environment is abnormal, and the compensation value of the environmental parameters is analyzed; if no, the working environment is normal, and the process quality of the capacitor is evaluated; if yes, the production continues; if no, the compensation value of the environmental parameters is analyzed.

[0006] Based on the above technical solution, this application provides an environmental control method for capacitor production and processing. By deeply integrating environmental monitoring and quality assessment, a two-tiered, progressive intelligent judgment mechanism is constructed. First, focusing on the core equipment in capacitor production, its operating environment parameters are collected specifically, and a working environment quality index is calculated to achieve a quantitative assessment of the environmental state. When the index exceeds the standard, it is immediately identified as an environmental anomaly, and compensation adjustments are initiated. If the environmental index is normal, the process quality is further assessed to determine the potential quality risks of the product under the current environmental conditions. This avoids overreacting to minor fluctuations and prevents the omission of hidden quality hazards. Only when both environmental and process indicators meet the standards is production deemed safe. This strategy achieves a shift from "passive response" to "proactive prevention," significantly improving the accuracy of environmental control and the reliability of the production process, providing strong support for the manufacturing of highly consistent capacitors.

[0007] In conjunction with the first aspect above, in one possible implementation, the core production equipment for determining the capacitor includes: Environmental parameters and corresponding quality index values ​​for each production equipment are obtained from historical production data. A regression model between environmental parameters and quality index values ​​is established using the least squares method. Based on the regression model, the environmental sensitivity index of each production equipment is calculated. In addition, the number of defective products produced by production equipment is obtained from historical data, and the quality index of each production equipment is calculated. Based on the fitted regression model and quality index between environmental parameters and quality index values, the formula is used... The core index CEi of production equipment i is calculated; where i is the production equipment number, SZi is the environmental sensitivity index of production equipment i, and CZi is the quality index of production equipment i. These are the weighting coefficients; Determine if the core index is greater than the preset core threshold; if yes, then production equipment i is marked as a core production equipment; otherwise, it is not marked.

[0008] In conjunction with the first aspect above, in one possible implementation, the calculation of the environmental sensitivity index of each production device includes: Based on the fitted regression model between environmental parameters and quality index values, the formula is used... The environmental sensitivity index SZi of production equipment i is calculated; where k is the type of environmental parameter. Let be the partial derivative with respect to the environmental parameter k; Q is the fitted regression model between the environmental parameter and the quality index value. The value of the environmental parameter k. The weighting coefficients for environmental parameter k.

[0009] In conjunction with the first aspect above, in one possible implementation, the calculation of the quality index of each production device includes: Obtain production records for several production cycles of the production line; extract the number of defective products produced by each production equipment in each production cycle from the production records, and then use a formula... The quality index CZi of production equipment i is calculated. in, The defect coefficient, [0, 1], BLi is the average number of defective products produced per production cycle of production equipment i, j is the production cycle number, j=0, 1, ..., N, N is a positive integer, The number of defective products produced by production equipment i during production cycle j; To sum over i, To sum over i and j.

[0010] In conjunction with the first aspect above, in one possible implementation, the analysis of the working environment quality index of the core production equipment includes: Calculate the difference between the average environmental parameter k of the core production equipment i and the target environmental parameter k during the analysis period. ; Through formula The working environment quality index of core production equipment i was calculated. ;in, The allowable deviation of environmental parameter k for core production equipment i.

[0011] In conjunction with the first aspect above, in one possible implementation, the compensation value for the analytical environment parameter includes: Analyze the adjustment ratio coefficient of current environmental control equipment and response time coefficient Wherein, the adjustment ratio coefficient is the adjustment ratio required by the environmental control equipment under the current environmental parameters; the response time coefficient is the response time ratio required by the environmental control equipment under the current environmental parameters; wherein, each environmental control equipment corresponds to one environmental parameter; Through formula The compensation values ​​of the environmental parameters were calculated. Where dt is the time interval.

[0012] In conjunction with the first aspect above, in one possible implementation, the analysis of the adjustment ratio coefficient and response time coefficient of the current environmental control equipment includes: Information on core production equipment, abnormal environmental parameter sequences, adjustment ratio coefficients and response time coefficients of environmental control equipment, and the quality index of core production equipment after environmental adjustment are obtained from historical data, and feature vectors of environmental control equipment are constructed. The feature vectors are trained using a machine learning model. The feature vectors are divided into input feature vectors and output feature vectors, and a mapping relationship is established between the input feature vectors and the output feature vectors. The input feature vectors include core production equipment information and abnormal environmental parameter sequences, and the output feature vectors include the adjustment ratio coefficient and response time coefficient of the environmental control equipment. By inputting the feature vector of the current environmental control equipment into the machine learning model, the adjustment ratio coefficient and response time coefficient of the current environmental control equipment are obtained.

[0013] In conjunction with the first aspect above, in one possible implementation, the abnormal environment parameter sequence is a set of environmental parameters that exceed the corresponding preset threshold.

[0014] In conjunction with the first aspect above, in one possible implementation, the evaluation of whether the capacitor's manufacturing quality is up to standard includes: The environmental parameter sequence of the core production equipment i is input into the process quality assessment model, and the process quality label of the core production equipment i is output. The process quality label is 1 and 0, which represent qualified and unqualified, respectively. The process quality assessment model is obtained by training an artificial intelligence model.

[0015] Secondly, an environmental control device for capacitor production and processing is provided, comprising: a communication unit and a processing unit; the communication unit is used to determine the core production equipment of the capacitor and collect environmental parameters of the core production equipment; the processing unit is used to analyze the working environment quality index of the core production equipment based on the collected environmental parameters; determine whether the working environment quality index is greater than a preset index threshold; if yes, the working environment is abnormal, and the compensation value of the environmental parameters is analyzed; if no, the working environment is normal, and the process quality of the capacitor is evaluated; if yes, production continues; if no, the compensation value of the environmental parameters is analyzed.

[0016] Thirdly, this application provides an environmental control device for capacitor manufacturing, comprising: a processor and a storage medium; the storage medium includes instructions, and the processor is configured to execute the instructions to implement the method described in the first aspect and any possible implementation thereof. This environmental control device for capacitor manufacturing can be an electronic device or a chip within an electronic device.

[0017] Fourthly, this application provides an environmental control system for capacitor production and processing, comprising: an analysis module and an environmental control module; wherein, the analysis module is used to analyze the environmental sensitivity index and quality index of each capacitor production equipment, determine the core production equipment of the capacitor, and collect the environmental parameters of the core production equipment; the environmental control module is used to analyze the working environment quality index of the core production equipment based on the collected environmental parameters; determine whether the working environment quality index is greater than a preset index threshold; if yes, the working environment is abnormal, and the compensation value of the environmental parameters is analyzed; if no, the working environment is normal, and the process quality of the capacitor is evaluated; if yes, production continues; if no, the compensation value of the environmental parameters is analyzed.

[0018] Fifthly, this application provides a computer-readable storage medium storing instructions that, when executed on an environmental control device for capacitor manufacturing, cause the environmental control device for capacitor manufacturing to perform the methods described in the first aspect and any possible implementation thereof.

[0019] In a sixth aspect, this application provides a computer program product containing instructions that, when run on an environmental control device for capacitor manufacturing, causes the environmental control device for capacitor manufacturing to perform the methods described in the first aspect and any possible implementation thereof.

[0020] This application provides an environmental control system and method for capacitor manufacturing. The method constructs a closed-loop control system of "environmental monitoring—quality prediction—intelligent response," significantly improving the stability and intelligence level of the capacitor production process. By accurately identifying core production equipment such as coating machines, it focuses on environmental control of key processes, avoiding resource waste. Real-time calculation of the working environment quality index enables comprehensive evaluation of multiple parameters such as temperature, humidity, and cleanliness, overcoming the limitations of single-indicator judgment. Furthermore, it not only determines whether the environment is abnormal but also assesses its impact on process quality. Combined with an AI-based process quality assessment model, it predicts process quality from environmental parameter sequences, improving prediction accuracy and response speed. When any environmental or process quality indicator fails to meet standards, timely compensation adjustments are triggered, achieving proactive intervention and effectively preventing batch defects. The entire process is logically rigorous, responds rapidly, and balances real-time performance with foresight, providing a highly reliable and adaptive environmental protection mechanism for high-end capacitor manufacturing, demonstrating significant engineering application value.

[0021] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description

[0022] Figure 1 A system architecture diagram of an environmental control system for capacitor production and processing is provided in this application embodiment; Figure 2 A schematic flowchart illustrating an environmental control method for capacitor manufacturing provided in this application embodiment; Figure 3 A schematic flowchart illustrating the method for determining the core production equipment for capacitors provided in this application embodiment; Figure 4 This is a schematic diagram of the structure of an environmental control device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the hardware structure of an environmental control device provided in an embodiment of this application. Detailed Implementation

[0023] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] The environmental control method for capacitor manufacturing provided in this application embodiment can be applied to an environmental control system for capacitor manufacturing, such as... Figure 1 As shown, the system includes: an analysis module and an environmental control module; The analysis module is used to analyze the environmental sensitivity index and quality index of each capacitor production equipment, identify the core production equipment of the capacitor, and collect the environmental parameters of the core production equipment. The environmental control module is used to analyze the working environment quality index of core production equipment based on the collected environmental parameters; Determine if the working environment quality index is greater than the preset index threshold; if yes, the working environment is abnormal, and the compensation value of the environmental parameters is analyzed; if no, the working environment is normal, and the process quality of the capacitor is assessed; if yes, production continues; if no, the compensation value of the environmental parameters is analyzed.

[0025] To address the technical problems of traditional environmental control systems that often employ fixed threshold alarms or simple PID control, resulting in a "one-size-fits-all" approach and prone to response lag, overshoot, or low energy efficiency, this application provides an environmental control method for capacitor production. This method includes: analyzing the environmental sensitivity index and quality index of each capacitor production equipment to identify the core production equipment and collecting environmental parameters of the core equipment; the environmental sensitivity index represents the sensitivity of the production equipment to changes in the working environment; the quality index is a statistical indicator of the production equipment's production of defective products during the production cycle; analyzing the working environment quality index of the core production equipment based on the collected environmental parameters; the environmental quality index is a comprehensive evaluation index of the core production equipment's working environment; determining whether the working environment quality index exceeds a preset threshold; if yes, the working environment is abnormal, and the compensation value of the environmental parameters is analyzed; if no, the working environment is normal, and the process quality of the capacitor is evaluated; if yes, production continues; if no, the compensation value of the environmental parameters is analyzed. Based on this, through the linkage between environmental parameter monitoring and quality index judgment, hierarchical evaluation and intelligent decision-making of the capacitor production process are achieved. Its advantages lie in its ability to not only assess the working environment quality index in real time to identify environmental anomalies, but also to further incorporate process quality assessment, verifying environmental impacts from a product quality perspective and avoiding misjudgments or delays caused by relying solely on environmental thresholds. An environmental compensation mechanism is triggered whenever any standard is not met, enabling timely intervention in the early stages of environmental deterioration and proactive adjustments when potential quality risks emerge, thus enhancing the foresight and robustness of control. The overall process structure is clear and logically closed-loop, closely linking environmental control with process quality, improving the system's adaptability to complex disturbances, and effectively ensuring the stability of the production process and product consistency.

[0026] like Figure 2 As shown in the embodiment of this application, an environmental control method for capacitor manufacturing and processing is provided, comprising: S201. Identify the core production equipment for capacitors and collect environmental parameters of the core production equipment.

[0027] Among them, core production equipment refers to the key process equipment that has the greatest impact on the final performance and quality of capacitors, is most susceptible to environmental interference, and can lead to batch defects if problems occur. For example, the coating machine uniformly coats electrode paste or dielectric material onto the base film. If the coating thickness is uneven, the capacitance value will deviate greatly; if dust falls in, it will cause breakdown and short circuit; or if the humidity is high, the solvent will evaporate slowly, resulting in pinhole defects.

[0028] S202. Analyze the working environment quality index of core production equipment based on the collected environmental parameters.

[0029] This involves real-time monitoring of the working environment of core production equipment to comprehensively assess whether the working environment of the core production equipment is suitable.

[0030] S203. If the working environment quality index is greater than the preset index threshold, the working environment is abnormal, and the compensation value of the environmental parameters is analyzed.

[0031] S204. If the working environment quality index is less than or equal to the preset index threshold, the working environment is normal, and the process quality of the capacitor is evaluated to determine if it is qualified. If yes, production continues; otherwise, the compensation value of the environmental parameters is analyzed.

[0032] The evaluation of the capacitor's manufacturing quality includes the following specific steps: The environmental parameter sequence of the core production equipment i is input into the process quality assessment model, and the process quality label of the core production equipment i is output. The process quality label is 1 and 0, which represent qualified and unqualified, respectively. The process quality assessment model is obtained by training an artificial intelligence model.

[0033] Based on the above technical solution, this application provides an environmental control method for capacitor production and processing. By constructing a closed-loop control logic of "environmental monitoring—quality assessment—intelligent decision-making," it achieves refined management of the capacitor production process. First, it dynamically calculates the working environment quality index based on environmental parameters to accurately identify environmental anomalies. Combined with process quality, it not only focuses on the current environmental state but also predicts its impact on product quality, avoiding false alarms and missed alarms caused by single threshold judgments. When any environmental or process quality indicator fails to meet the standard, the system automatically triggers compensation value analysis to achieve proactive intervention and ensure production stability. The entire process has a clear logic and timely response, balancing the real-time nature of environmental control with the reliability of process quality. It effectively improves the intelligence level of the production process and product consistency, providing a scientific and quantifiable basis for environmental management in high-end capacitor manufacturing.

[0034] In one possible implementation of the embodiments of this application, combined with Figure 2 ,like Figure 3 As shown, the above S201 can be specifically implemented through the following S301, S302, S303 and S304, which are explained in detail below: S301. Obtain the environmental parameters of each production equipment and the corresponding quality index values ​​under each environmental parameter from historical production data, and establish a fitting regression model between the environmental parameters and the quality index values ​​using the least squares method. S302. Based on the fitting regression model between environmental parameters and quality index values, using the formula... The environmental sensitivity index SZi of production equipment i is calculated; where k is the type of environmental parameter. Let be the partial derivative with respect to the environmental parameter k; Q is the fitted regression model between the environmental parameter and the quality index value. The value of the environmental parameter k. The weighting coefficients for environmental parameter k.

[0035] For example, a factory produces capacitor components, including a coating machine 1, a winding machine 2, and a packaging machine 3. Taking the coating machine 1 as an example, its relevant historical production data is collected, namely the environmental parameters of a certain production batch of the coating machine and the corresponding quality index values ​​under each environmental parameter. Environmental parameters include temperature T, humidity H, cleanliness C, and static electricity E. Assuming that the historical environmental parameters and corresponding quality index values ​​are used to fit the regression model Q=6-2.5T-1.32H-1.18CE using the least squares method, the model is obtained. The partial derivatives with respect to each environmental parameter are calculated based on the fitted regression model. =-2.5, -1.32, =-1.18, =-1; Sets the weighting coefficient for each environmental parameter. =0.4, =0.3, =0.2, =0.1; Therefore, the environmental sensitivity index of coating machine 1 is 1.22.

[0036] S303. Obtain production records for several production cycles of the production line; extract the number of defective products produced by each production equipment in each production cycle from the production records, and use the formula... The quality index CZi of production equipment i is calculated. in, The defect coefficient, [0, 1], BLi is the average number of defective products produced per production cycle of production equipment i, j is the production cycle number, j=0, 1, ..., N, N is a positive integer, The number of defective products produced by production equipment i during production cycle j; To sum over i, To sum over i and j.

[0037] It should be noted that the formula for the quality index represents the average number of defective products produced by production equipment i per production cycle. The average number of defective products produced per production cycle across all production equipment Multiply by the defect coefficient , It can be set by those skilled in the art, and after simplification, it is shown in the above formula.

[0038] For example, suppose we obtain the production records for three production cycles of a capacitor manufacturer, and obtain the number of defective products of coating machine 1 in each production cycle, such as j=1, BL1=12; j=2, BL1=10; j=3, BL1=11; suppose the total number of defective products produced by all production equipment in these three production cycles is 50. =1, CZ1=1 33 / 50=0.66, therefore the quality index of coating machine 1 is 0.66.

[0039] S304. Based on the fitted regression model and quality index between environmental parameters and quality index values, the formula is used... The core index CEi of production equipment i is calculated; where i is the production equipment number, SZi is the environmental sensitivity index of production equipment i, and CZi is the quality index of production equipment i. These are the weighting coefficients; Determine if the core index is greater than the preset core threshold; if yes, then production equipment i is marked as a core production equipment; otherwise, it is not marked.

[0040] For example, based on the calculation results of the above embodiments, let... ; Calculate the core index of coating machine 1 Assuming the preset core threshold is 0.8, coating machine 1 is the core production equipment for capacitors.

[0041] Based on the above technical solution, the scientific identification of core production equipment was achieved by integrating data-driven modeling and multi-dimensional quantitative evaluation. A regression model of environmental parameters and quality indicators was established based on historical production data, accurately reflecting the equipment's sensitivity to environmental fluctuations. A quality index was calculated by combining defective product statistics to comprehensively measure the equipment's actual output stability. Then, a core index was obtained by weighted fusion of the environmental sensitivity index and the quality index, considering both the environmental dependence of the process and the final product quality performance, avoiding the one-sidedness of judging by a single indicator. The entire method is quantifiable, interpretable, and scalable, automatically identifying key equipment without relying on human experience. This provides a reliable basis for subsequent precise environmental control and resource optimization, improving the automation and intelligence level of the intelligent manufacturing system.

[0042] In one possible implementation of this application embodiment, the above-mentioned S202 can be specifically described as follows: Calculate the difference between the average environmental parameter k of the core production equipment i and the target environmental parameter k during the analysis period. ; Through formula The working environment quality index of core production equipment i was calculated. ;in, The allowable deviation of environmental parameter k for core production equipment i.

[0043] It should be noted that the overall stability and suitability of the current microenvironment are quantified by comprehensively evaluating the actual deviations of various key parameters in the environment in which the equipment is located, such as temperature, humidity, and cleanliness. The degree of deviation for each environmental parameter in the formula is reflected by the ratio of its actual deviation value to the allowable deviation; the smaller the ratio, the closer the parameter is to the ideal range, and the smaller the deviation. Then, based on weighting coefficients reflecting the importance of different parameters to the production process, a comprehensive index, namely the working environment quality index, is finally obtained through weighted summation. A higher working environment quality index indicates a more stable environmental state, which is more conducive to high-quality production; conversely, a lower index indicates that the environment deviates from control standards and timely intervention is required. Therefore, the working environment quality index not only reflects the compliance level of environmental parameters but also reflects their potential impact on production quality, providing a scientific basis for environmental monitoring and intelligent control.

[0044] In one possible implementation of the embodiments of this application, the above-mentioned S203 and S204 can be specifically implemented by the following S401 and S402, which are described in detail below: S401. Obtain information on core production equipment, abnormal environmental parameter sequences, adjustment ratio coefficients and response time coefficients of environmental control equipment from historical data, as well as the quality index of core production equipment after environmental adjustment, and construct the feature vector of environmental control equipment. Among them, the abnormal environmental parameter sequence is the set of environmental parameters that exceed the corresponding preset threshold. For example, if the humidity suddenly rises from 40% to 50%, exceeding the preset threshold of 45%, then the humidity data is abnormal at this time. The collection of abnormal humidity data at several time points is the abnormal humidity data sequence.

[0045] The feature vectors are trained using a machine learning model. The feature vectors are divided into input feature vectors and output feature vectors, and a mapping relationship is established between the input feature vectors and the output feature vectors. The input feature vectors include core production equipment information and abnormal environmental parameter sequences, and the output feature vectors include the adjustment ratio coefficient and response time coefficient of the environmental control equipment. The input feature vector of the current environmental control equipment is input into the machine learning model to obtain the adjustment ratio coefficient and response time coefficient of the current environmental control equipment.

[0046] It should be noted that the proportional gain refers to the "responsiveness" of the environmental controller to environmental deviations, such as in PID control. The percentage increase in FFU wind speed; the response time coefficient refers to the time from issuing a command to the environment returning to stability, reflecting the dynamic response capability of environmental control equipment.

[0047] Feature vectors are created by packaging all the above information into a structured data vector, which can then be used as input for machine learning. .

[0048] For example, if a certain environmental parameter exceeds the standard, such as a sudden increase in humidity, the information of the current core production equipment and the corresponding abnormal environmental parameter sequence are extracted and input into the trained model; the output is: the recommended adjustment ratio coefficient (e.g., wind speed increase of 30%), and the predicted response time (e.g., expected to recover within 2 minutes).

[0049] Based on the above technical solution, intelligent prediction and personalized optimization of adjustment parameters are achieved by constructing feature vectors for environmental control equipment and combining them with machine learning models. By fully mining the abnormal events and control response patterns in historical data, and using core production equipment information and abnormal environmental parameter sequences as input, the contextual features of the control scenario are accurately characterized. By establishing a nonlinear mapping relationship from input feature vectors to output feature vectors, the system can adaptively output optimal control parameters based on the actual performance, operating condition changes, and historical performance of different equipment, avoiding the lag and overshoot problems of traditional fixed-parameter control. Simultaneously, this method explicitly considers the dynamic characteristics of environmental disturbances and equipment response capabilities, improving the foresight and robustness of control, and significantly enhancing the accuracy, stability, and energy efficiency of environmental regulation. This provides data-driven closed-loop optimization capabilities for intelligent environmental control in high-precision manufacturing scenarios.

[0050] S402. Analyze the adjustment ratio coefficient of the current environmental control equipment. and response time coefficient Wherein, the adjustment ratio coefficient is the adjustment ratio required by the environmental control equipment under the current environmental parameters; the response time coefficient is the response time ratio required by the environmental control equipment under the current environmental parameters; wherein, each environmental control equipment corresponds to one environmental parameter; Through formula The compensation values ​​of the environmental parameters were calculated. Where dt is the time interval.

[0051] It should be noted that this formula is a dynamic environmental compensation model based on equipment characteristics. This means that the compensation value of environmental parameters is determined by two parts: the current deviation and the environmental parameters. The required "static adjustment amount" is determined by adjusting the proportional coefficient. Amplification; secondly, the rate of change of deviation. The reflected "trend response quantity" is expressed through the response duration coefficient. Weighted adjustment. The former ensures the system corrects existing deviations, while the latter anticipates environmental changes and proactively intervenes to prevent overshoot or lag. This formula combines the individual characteristics of environmental control equipment with real-time environmental dynamics, such as response speed and adjustment capabilities, achieving intelligent compensation from "passive following" to "active prediction." This significantly improves the accuracy and stability of environmental control, and is particularly suitable for precise control of parameters such as temperature, humidity, and cleanliness in highly sensitive production processes.

[0052] The above primarily describes the solutions of the embodiments of this application from the perspective of device implementation. It is understood that each device, for example, an environmental control device for capacitor production and processing, includes at least one of the hardware structures and software modules corresponding to the execution of each function in order to achieve the above-mentioned functions. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in a hardware-driven or software-driven manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0053] This application embodiment can divide an environmental control device for capacitor production and processing into functional units based on the above method example. For example, each function can be divided into separate functional units, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents a logical functional division; other division methods may be used in actual implementation.

[0054] When using integrated units, Figure 4 A possible structural schematic diagram of an environmental control device (referred to as environmental control device 50) for capacitor production and processing, as described in the above embodiments, is shown. The environmental control device 50 includes a processing unit 501 and a communication unit 502, and may also include a storage unit 503. Figure 4 The schematic diagram shown can be used to illustrate the structure of an environmental control device for capacitor production and processing involved in the above embodiments.

[0055] when Figure 4The schematic diagram shown illustrates the structure of an environmental control device for capacitor production and processing involved in the above embodiments. The processing unit 501 is used to control and manage the operation of the environmental control device for capacitor production and processing. The communication unit 502 is used for the environmental control device for capacitor production and processing to communicate with other devices. The storage unit 503 is used to store the program code and data of the environmental control device for capacitor production and processing.

[0056] For example, communication unit 502 is used to determine the core production equipment of the capacitor and collect environmental parameters of the core production equipment. The processing unit 501 is used to analyze the working environment quality index of the core production equipment based on the collected environmental parameters; determine whether the working environment quality index is greater than the preset index threshold; if yes, the working environment is abnormal and the compensation value of the environmental parameters is analyzed; if no, the working environment is normal and the process quality of the capacitor is evaluated; if yes, production continues; if no, the compensation value of the environmental parameters is analyzed.

[0057] The processing unit 501 can be a processor or a controller, and the communication unit 502 can be a communication interface, transceiver, transceiver circuit, transceiver device, etc. The term "communication interface" is a general term and may include one or more interfaces. The storage unit 503 can be a memory. When the environmental control device 50 is a chip, the processing unit 501 can be a processor or a controller, and the communication unit 502 can be an input interface and / or an output interface, pins, or circuits, etc. The storage unit 503 can be a storage unit within the chip (e.g., a register, cache, etc.) or a storage unit located outside the chip (e.g., read-only memory (ROM), random access memory (RAM, etc.).

[0058] The communication unit can also be called a transceiver unit. The antenna and control circuit with transceiver functions in the environmental control device 50 can be considered as the communication unit 502 of the environmental control device 50, and the processor with processing functions can be considered as the processing unit 501 of the environmental control device 50. Optionally, the device in the communication unit 502 that implements the receiving function can be considered as a communication unit, which is used to execute the receiving steps in the embodiments of this application. The communication unit can be a receiver, a receiver circuit, etc. The device in the communication unit 502 that implements the transmitting function can be considered as a transmitting unit, which is used to execute the transmitting steps in the embodiments of this application. The transmitting unit can be a transmitter, a transmitter, a transmitting circuit, etc.

[0059] Figure 4If the integrated units in the process are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. Storage media for storing computer software products include various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0060] Figure 4 The units in the process can also be called modules; for example, a processing unit can be called a processing module.

[0061] This application also provides a hardware structure diagram of an environmental control device (denoted as environmental control device 60) for capacitor production and processing, see [link to diagram]. Figure 5 The environmental control device 60 includes a processor 601, and optionally, a memory 602 connected to the processor 601.

[0062] In the first possible implementation, see Figure 5 The environmental control device 60 also includes a transceiver 603. The processor 601, memory 602, and transceiver 603 are connected via a bus. The transceiver 603 is used to communicate with other devices or communication networks. Optionally, the transceiver 603 may include a transmitter and a receiver. The device in the transceiver 603 that implements the receiving function can be considered as a receiver, which is used to perform the receiving steps in the embodiments of this application. The device in the transceiver 603 that implements the transmitting function can be considered as a transmitter, which is used to perform the transmitting steps in the embodiments of this application.

[0063] Based on the first possible implementation method Figure 5 The schematic diagram shown can be used to illustrate the structure of an environmental control device for capacitor production and processing involved in the above embodiments.

[0064] in, Figure 5 This can also be illustrated as a system chip in an environmental control device used in capacitor manufacturing. In this case, the actions performed by the aforementioned environmental control device for capacitor manufacturing can be implemented by this system chip; the specific actions performed are described above and will not be repeated here.

[0065] Some of the data in the above formula are calculated by removing dimensions and taking their numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

Claims

1. An environmental control method for capacitor manufacturing and processing, characterized in that, include: Analyze the environmental sensitivity index and quality index of each capacitor production equipment to identify the core capacitor production equipment and collect the environmental parameters of the core production equipment. The environmental sensitivity index refers to the degree to which production equipment is sensitive to changes in the working environment; The quality index is a statistical indicator of the production equipment's production of defective products during the production cycle. The working environment quality index of the core production equipment is analyzed based on the collected environmental parameters; the environmental quality index is a comprehensive evaluation index of the working environment of the core production equipment. Determine if the working environment quality index is greater than the preset index threshold; if so, the working environment is abnormal, and analyze the compensation value of the environmental parameters. If no, the working environment is normal, and the quality of the capacitor's manufacturing process is assessed; if yes, production continues; if no, the compensation values ​​of the environmental parameters are analyzed.

2. The environmental control method for capacitor manufacturing and processing according to claim 1, characterized in that, The core production equipment for the capacitors includes: Environmental parameters and corresponding quality index values ​​for each production equipment are obtained from historical production data. A regression model between environmental parameters and quality index values ​​is established using the least squares method. Based on the regression model, the environmental sensitivity index of each production equipment is calculated. In addition, the number of defective products produced by production equipment is obtained from historical data, and the quality index of each production equipment is calculated. Based on the fitted regression model and quality index between environmental parameters and quality index values, the formula is used... The core index CEi of production equipment i is calculated; where i is the production equipment number, SZi is the environmental sensitivity index of production equipment i, and CZi is the quality index of production equipment i. These are the weighting coefficients; Determine if the core index is greater than the preset core threshold; if yes, then production equipment i is marked as a core production equipment; otherwise, it is not marked.

3. The environmental control method for capacitor manufacturing and processing according to claim 2, characterized in that, The calculation of the environmental sensitivity index of each production equipment includes: Based on the fitted regression model between environmental parameters and quality index values, the formula is used... The environmental sensitivity index SZi of production equipment i is calculated; where k is the type of environmental parameter. Let be the partial derivative with respect to the environmental parameter k; Q is the fitted regression model between the environmental parameter and the quality index value. The value of the environmental parameter k. The weighting coefficients for environmental parameter k.

4. The environmental control method for capacitor manufacturing and processing according to claim 2, characterized in that, The calculation of the quality index of each production equipment includes: Obtain production records for several production cycles of the production line; extract the number of defective products produced by each production equipment in each production cycle from the production records, and then use a formula... The quality index CZi of production equipment i is calculated. in, The defect coefficient, [0, 1], BLi is the average number of defective products produced per production cycle of production equipment i, j is the production cycle number, j=0, 1, ..., N, N is a positive integer, The number of defective products produced by production equipment i during production cycle j; To sum over i, To sum over i and j.

5. The environmental control method for capacitor manufacturing and processing according to claim 3, characterized in that, The analysis of the working environment quality index of the core production equipment includes: Calculate the difference between the average environmental parameter k of the core production equipment i and the target environmental parameter k during the analysis period. ; Through formula The working environment quality index of core production equipment i was calculated. ;in, The allowable deviation of environmental parameter k for core production equipment i.

6. The environmental control method for capacitor manufacturing and processing according to claim 5, characterized in that, The compensation values ​​for the analytical environment parameters include: Analyze the adjustment ratio coefficient of current environmental control equipment and response time coefficient Wherein, the adjustment ratio coefficient is the adjustment ratio required by the environmental control equipment under the current environmental parameters; the response time coefficient is the response time ratio required by the environmental control equipment under the current environmental parameters; wherein, each environmental control equipment corresponds to one environmental parameter; Through formula The compensation values ​​of the environmental parameters were calculated. Where dt is the time interval.

7. The environmental control method for capacitor manufacturing and processing according to claim 6, characterized in that, The analysis of the adjustment ratio coefficient and response time coefficient of the current environmental control equipment includes: Information on core production equipment, abnormal environmental parameter sequences, adjustment ratio coefficients and response time coefficients of environmental control equipment, and the quality index of core production equipment after environmental adjustment are obtained from historical data, and feature vectors of environmental control equipment are constructed. The feature vectors are trained using a machine learning model. The feature vectors are divided into input feature vectors and output feature vectors, and a mapping relationship is established between the input feature vectors and the output feature vectors. The input feature vectors include core production equipment information and abnormal environmental parameter sequences, and the output feature vectors include the adjustment ratio coefficient and response time coefficient of the environmental control equipment. By inputting the feature vector of the current environmental control equipment into the machine learning model, the adjustment ratio coefficient and response time coefficient of the current environmental control equipment are obtained.

8. The environmental control method for capacitor manufacturing and processing according to claim 7, characterized in that, The abnormal environment parameter sequence is a set of environmental parameters that exceed the corresponding preset threshold.

9. The environmental control method for capacitor manufacturing and processing according to claim 1, characterized in that, The evaluation of whether the capacitor's manufacturing process quality is up to standard includes: The environmental parameter sequence of the core production equipment i is input into the process quality assessment model, and the process quality label of the core production equipment i is output. The process quality label is 1 and 0, which represent qualified and unqualified, respectively. The process quality assessment model is obtained by training an artificial intelligence model.

10. An environmental control system for capacitor manufacturing, operating based on the environmental control method for capacitor manufacturing according to any one of claims 1-9, characterized in that, Includes an analysis module and an environmental control module; The analysis module is used to analyze the environmental sensitivity index and quality index of each capacitor production equipment, identify the core production equipment of the capacitor, and collect the environmental parameters of the core production equipment. The environmental control module is used to analyze the working environment quality index of the core production equipment based on the collected environmental parameters. Determine if the working environment quality index is greater than the preset index threshold; if so, the working environment is abnormal, and analyze the compensation value of the environmental parameters. If no, the working environment is normal, and the quality of the capacitor's manufacturing process is assessed; if yes, production continues. If not, then analyze the compensation values ​​of the environmental parameters.

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