Film production quality tracing system, method and device and storage medium

Abstract

The invention provides a thin film production quality traceability system, method and device and a storage medium, and relates to the technical field of quality traceability. Production data of each process section in the production process of a thin film product is collected in real time; acquiring historical production data, determining index association degrees among the process indexes in different process sections according to the historical production data, and screening out all key quality control indexes based on all the index association degrees; determining a quality control index domain corresponding to each key quality control index according to the historical production data; extracting a plurality of pieces of quality control production data, and determining all quality loss segment points through each piece of quality control production data and the corresponding quality control index domain; and determining a mass loss root cause by using all the mass loss segment points, and regulating and controlling the production process of the thin film product through the mass loss root cause, thereby realizing quality tracing in the production process of the thin film product. According to the method, the root cause of the quality problem can be evaluated in combination with historical data and production environment characteristics, so that the accuracy and reliability of thin film production quality tracing are improved.

Description

Technical Field

[0001] The present application relates to the technical field of quality traceability, and more specifically, to a film production quality traceability system, method, device and storage medium. Background Art

[0002] Film production quality traceability uses advanced data acquisition and analysis technologies to monitor and process process parameters and quality indicators in real time during the production process to improve the efficiency and accuracy of quality control. Intelligent traceability systems usually integrate multiple functions such as multi-source data acquisition, process parameter analysis, anomaly detection and quality prediction, which can automatically identify potential quality problems and issue early warnings in time, thereby reducing defective rates and production costs. In practical applications, intelligent traceability systems use machine learning and deep learning algorithms to analyze process patterns in production data, identify abnormal parameters and defective behaviors, and even perform full-process quality traceability and root cause analysis. In addition, the combination of multimodal sensors enables the system to monitor real-time changes in the production environment, such as temperature fluctuations, abnormal pressure or uneven thickness, thereby further enhancing quality control capabilities. The combination of these technologies not only improves the level of intelligence in film production, but also provides companies with more comprehensive and in-depth quality assurance.

[0003] However, in existing technologies, in complex and changing production environments, intelligent traceability systems still have misjudgments and missed judgments. For example, the system may mistakenly identify normal process fluctuations as quality issues, resulting in unnecessary production interruptions, or miss real quality risks. Therefore, how to accurately identify the change pattern of key quality control indicators and combine historical data and production environment characteristics to evaluate the root cause of quality problems is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a film production quality traceability system, method, device and storage medium, which can accurately identify the change pattern of key quality control indicators, and combine historical data and production environment characteristics to evaluate the root cause of quality problems, so as to improve the accuracy and reliability of film production quality traceability.

[0005] In a first aspect, the present application provides a film production quality tracing method, the tracing method comprising the following steps: Divide the film product production process into different process sections, and collect the production data of each process section in real time; Acquire historical production data of the thin film product production process, determine the indicator correlation between process indicators in different process sections according to the historical production data, screen out all key quality control indicators in the thin film product production process based on all indicator correlations, and determine the quality control indicator domain corresponding to each key quality control indicator in the thin film product production process according to the historical production data; Extract the quality control production data corresponding to each key quality control indicator from the production data of each process section, and determine all quality loss points in the production process of the film product through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; All quality loss points are used to determine the root causes of quality loss in the film product production process, and the film product production process is regulated by the root causes of quality loss, thereby achieving quality traceability in the film product production process.

[0006] In this embodiment, the thin film product production process is divided into different process sections according to changes in the chemical state and physical state of the thin film product during the thin film product production process.

[0007] In this embodiment, the quality control index domain is used to determine the normal range interval of the corresponding key quality control index in the production process of the thin film product.

[0008] In this embodiment, determining the index correlation between process indexes in different process sections according to the historical production data specifically includes: Determine the weights of the process indicators in different process sections affecting the film quality according to the historical production data, and obtain an indicator weight sequence; The indicator correlation between the process indicators in different process sections is determined by the indicator weight sequence.

[0009] In this embodiment, the quality loss section is a process section that affects the film production quality during the film product production process.

[0010] In this embodiment, all quality loss points in the film product production process are determined by using the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain, specifically including: Determine multiple potential quality loss points in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; Determine the process section where each potential quality loss point is located, and then screen each potential quality loss point through the semi-finished product quality data of the corresponding process section to obtain all quality loss points in the film product production process.

[0011] In this embodiment, all quality-destroying sections are used to determine the root causes of quality-destroying in the film product production process. The root causes of quality-destroying are determined by searching the film quality knowledge base according to the abnormal types of process parameters at each quality-destroying section.

[0012] In a second aspect, the present application provides a film production quality tracing system for executing a film production quality tracing method, the tracing system comprising: A data acquisition module is used to divide the thin film product production process into different process sections and collect the production data of each process section in the thin film product production process in real time; A data processing module, used to obtain historical production data of the thin film product production process, determine the indicator correlation between process indicators in different process sections according to the historical production data, screen out all key quality control indicators in the thin film product production process based on all indicator correlations, and determine the quality control indicator domain corresponding to each key quality control indicator in the thin film product production process according to the historical production data; The quality loss section determination module is used to extract the quality control production data corresponding to each key quality control indicator from the production data of each process section, and determine all the quality loss sections in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; The production control module is used to use all the quality loss points to determine the root causes of quality loss in the film product production process, and to control the film product production process based on the root causes of quality loss, thereby achieving quality traceability in the film product production process.

[0013] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned film production quality tracing method.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions or codes, and when the instructions or codes are run on a computer, the computer implements the above-mentioned film production quality tracing method when executing.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: The thin film product production process is divided into different process sections, and the production data of each process section in the thin film product production process is collected in real time; the historical production data of the thin film product production process is obtained, and the indicator correlation between the process indicators in different process sections is determined according to the historical production data, and all key quality control indicators in the thin film product production process are screened out based on all indicator correlations, and the quality control indicator domain corresponding to each key quality control indicator in the thin film product production process is determined according to the historical production data; the quality control production data corresponding to each key quality control indicator is extracted from the production data of each process section, and all quality control points in the thin film product production process are determined through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; all quality control points are used to determine the root cause of quality control in the thin film product production process, and the thin film product production process is regulated and controlled through the root cause of quality control, thereby realizing quality traceability in the thin film product production process.

[0016] It can be seen that in the present application, the change pattern of key quality control indicators can be accurately identified, and the root cause of quality problems can be evaluated in combination with historical data and production environment characteristics; wherein, by dividing the film production process into different process sections and collecting production data of each process section in real time, the process parameter changes in the production process can be systematically analyzed, and its normal and abnormal states can be identified, and then by extracting abnormal process sections, process fluctuations that are significantly different from normal production can be timely identified, thereby achieving real-time monitoring and response, and the dynamic adjustment of the quality control indicator domain can provide a quantified normal range interval for each key quality control indicator; then, by obtaining historical production data and determining the indicator correlation between process indicators, a more comprehensive process feature can be obtained, which is helpful to identify potential quality problems and quality loss points, thereby enhancing the quality control capability of the traceability system, and combined with multi-source data collection and analysis, multi-dimensional process optimization can be achieved, and constructing a quality control indicator weight sequence can help identify the impact weights of key quality control indicators; finally, based on the quality loss points and the film quality knowledge base, the root cause of the quality problem can be more accurately determined, so that the production process parameters can be adjusted in time to take quality control measures, and the quality consistency and production efficiency of film production can be significantly improved.

[0017] In summary, the technical solution adopted in this application can accurately identify the change patterns of key quality control indicators, and combine historical data and production environment characteristics to evaluate the root causes of quality problems, so as to improve the accuracy and reliability of film production quality traceability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0019] Figure 1 is an exemplary flow chart of a film production quality tracing method provided by the present application; Figure 2 It is a module structure diagram of the film production quality traceability system provided by the present application; Figure 3 It is a structural schematic diagram of a computer device for implementing a film production quality tracing method provided by the present application.

[0020] In the figure, 100, data acquisition module; 200, data processing module; 300, quality loss section point determination module; 301, processor; 302, memory; 303, instruction; 304, program; 305, communication unit; 400, production control module; DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0022] The embodiment of the present application provides a film production quality tracing method, system, device and storage medium, the core of which is to divide the film product production process into different process sections, collect the production data of each process section in the film product production process in real time; obtain the historical production data of the film product production process, determine the indicator correlation between the process indicators in different process sections according to the historical production data, screen out all the key quality control indicators in the film product production process based on all the indicator correlations, and determine the quality control indicator domain corresponding to each key quality control indicator in the film product production process according to the historical production data; extract the quality control production data corresponding to each key quality control indicator from the production data of each process section, and determine all the quality loss points in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; use all the quality loss points to determine the root cause of quality loss in the film product production process, and regulate the film product production process through the root cause of quality loss, so as to realize the quality traceability in the film product production process. The above scheme can accurately identify the change pattern of key quality control indicators, and combine historical data and production environment characteristics to evaluate the root cause of quality problems, so as to improve the accuracy and reliability of film production quality traceability.

[0023] Embodiment 1: In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in FIG. 1 , this figure is an exemplary flow chart of a film production quality tracing method according to this embodiment of the present application, and the tracing method includes the following steps: In step S1, the thin film product production process is divided into different process sections, and the production data of each process section in the thin film product production process is collected in real time.

[0024] In this embodiment, the thin film product production process is divided into different process sections according to changes in the chemical state and physical state of the thin film product during the thin film product production process.

[0025] In the specific implementation, first, the film product production process is divided into different process sections according to the changes in the chemical and physical states of the film products during the film product production process, for example, it can be divided into raw material pretreatment, extrusion molding, cooling and shaping, stretching orientation, surface treatment, slitting and winding, quality inspection and packaging sections; secondly, multiple types of sensors are deployed in each process section, such as temperature sensors, pressure sensors, ultrasonic thickness gauges, infrared thermal imagers, etc., to collect production data in real time, such as temperature, pressure, thickness, tension, surface roughness, coating thickness, etc.; then, a distributed database (such as Hadoop) is used to store real-time data.

[0026] In step S2, historical production data of the thin film product production process is obtained, and the indicator correlation between process indicators in different process sections is determined based on the historical production data. All key quality control indicators in the thin film product production process are screened out based on all indicator correlations, and the quality control indicator domain corresponding to each key quality control indicator in the thin film product production process is determined based on the historical production data.

[0027] In specific implementation, the historical production data of the thin film product production process can be obtained by traversing the database. The historical production data includes the process indicators and quality indicators of each process section. It should be noted that in this application, the quality indicator is an indicator range for standardizing the quality of thin film products determined based on historical production data and expert knowledge.

[0028] In this embodiment, the index correlation between the process indexes in different process sections can be determined according to the historical production data in the following manner, namely: Determine the weights of the process indicators in different process sections affecting the film quality according to the historical production data, and obtain an indicator weight sequence; The indicator correlation between the process indicators in different process sections is determined by the indicator weight sequence.

[0029] In the specific implementation, first, based on the historical production data, a machine learning algorithm (such as random forest, XGBoost) is used to analyze the influence weights of process indicators (such as temperature, pressure, thickness, tension, etc.) in different process sections on film quality (such as mechanical properties, optical properties, surface defects, etc.) to generate an indicator weight sequence; secondly, through the indicator weight sequence, it should be noted that in this application, the indicator weight sequence is a sequence coefficient used to describe the degree of influence of process indicators in different process sections on film quality during the production of film products, and the indicator correlation between process indicators in different process sections is determined by correlation analysis (such as Pearson correlation coefficient) or causal inference model (such as Bayesian network). For example, in the extrusion molding section, the influence weights of temperature and pressure on film thickness uniformity are 0.6 and 0.4 respectively. Through correlation analysis, it is found that there is a strong correlation between temperature and pressure, and the indicator correlation is 0.8, indicating that the two need to be controlled in a coordinated manner to optimize film quality. It should be noted that in this application, the indicator correlation is a coefficient to measure the correlation between indicators. In this application, by quantifying the influence weights and correlations of process indicators, data support is provided for process parameter optimization and root cause analysis of quality problems, thereby improving the quality control efficiency of film production.

[0030] In this embodiment, all key quality control indicators in the production process of thin film products are screened out based on the correlation of all indicators; in specific implementation, first, all indicator correlations and indicator weight sequences are obtained, and process indicators in the indicator weight sequence whose influence weights are greater than the weight threshold (such as 0.6), such as temperature, are screened out, and then process indicators with a high correlation with temperature indicators (indicator correlation>0.8) are excluded. For example, the correlation between temperature and pressure indicators is greater than 0.8, and temperature is retained as a key quality control indicator. All key quality control indicators can be obtained according to the above method. It should be noted that in this application, the weight threshold is a value used to determine the weight of the influence of process indicators on the quality of thin film products, and its value is adjusted according to the specific implementation of the scheme.

[0031] In this embodiment, the quality control indicator domain corresponding to each key quality control indicator in the production process of the film product is determined according to the historical production data. It should be noted that in this application, the quality control indicator domain is used to determine the normal range interval of the corresponding key quality control indicators in the production process of the film product. In specific implementation, first, according to the historical production data, the statistical process control (SPC) method is used to calculate the mean and standard deviation of each key quality control indicator (such as the temperature of the extrusion molding section, the cooling rate of the cooling and shaping section, the stretching ratio of the stretching orientation section, etc.), and determine its normal fluctuation range (such as μ±3σ); for example, the temperature mean of the extrusion molding section is 180°C, and the standard deviation is 2°C, then its quality control indicator domain is 180±6°C. Secondly, the data distribution of key quality control indicators is modeled through Gaussian mixture model (GMM) or kernel density estimation (KDE), its probability density function is determined, and the upper and lower limits of the quality control indicator domain (such as 95% confidence interval) are set; for example, the cooling rate data distribution of the cooling and shaping section shows that 95% of the data is concentrated in the range of 10-50℃ / s, so its quality control indicator domain is 10-50℃ / s. Finally, the quality control indicator domain is dynamically adjusted in combination with changes in the production environment (such as seasonal temperature fluctuations) and equipment status (such as equipment aging); for example, in the high temperature environment in summer, the temperature quality control indicator domain of the extrusion molding section is adjusted to 185±5℃.

[0032] In step S3, the quality control production data corresponding to each key quality control indicator is extracted from the production data of each process section, and all quality loss points in the film product production process are determined through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain.

[0033] In this embodiment, quality control production data corresponding to each key quality control indicator is extracted from the production data of each process section; in specific implementation, in the production data of each process section (such as raw material pretreatment, extrusion molding, cooling and shaping, stretching orientation, etc.), the corresponding quality control production data is extracted according to predetermined key quality control indicators (such as the temperature of the extrusion molding section, the cooling rate of the cooling and shaping section, the stretching ratio of the stretching orientation section, etc.).

[0034] In this embodiment, all quality loss points in the film product production process can be determined by using the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain in the following manner, namely: Determine multiple potential quality loss points in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; Determine the process section where each potential quality loss point is located, and then screen each potential quality loss point through the semi-finished product quality data of the corresponding process section to obtain all quality loss points in the film product production process.

[0035] In specific implementation, first, through the quality control production data corresponding to each key quality control indicator and the preset quality control indicator domain (such as the temperature range of 180±5℃ and the thickness range of 50±2 μm), multiple potential quality loss points in the film product production process are determined. For example, when the temperature data of the extrusion molding section exceeds the quality control indicator domain, the section is marked as a potential quality loss point. Through the above method, multiple potential quality loss points in the film product production process can be obtained. Secondly, the process section (such as the extrusion molding section, the cooling and shaping section, etc.) where each potential quality loss point is located is determined, and each potential quality loss point is screened through the semi-finished product quality data of the corresponding process section. For example, the semi-finished product quality data of the cooling and shaping section can be detected through an abnormal detection model. If the detection result is abnormal, the cooling and shaping section is marked as a quality loss point. Through the above, all quality loss points in the film product production process can be obtained. It should be noted that the quality loss point is a process section that affects the film production quality during the film product production process. It should be noted that in this application, by combining the quality control index domain and semi-finished product quality data, the quality loss section is accurately located, which provides a reliable basis for subsequent root cause analysis and process optimization, and significantly improves the quality control efficiency of film production.

[0036] In step S4, all the quality loss points are used to determine the root causes of quality loss in the film product production process, and the film product production process is regulated by the root causes of quality loss, thereby achieving quality traceability in the film product production process.

[0037] In this embodiment, all quality loss sections are used to determine the root cause of quality loss in the film product production process. The root cause of quality loss is determined by searching the film quality knowledge base based on the abnormal type of process parameters of each quality loss section. In specific implementation, the root cause of quality loss in the film product production process is determined by using the abnormal indicators detected by all quality loss sections, combined with the film quality knowledge base and historical production data, and using a causal inference model. It should be noted that in this application, the root cause of quality loss refers to the reason that causes the abnormal value of the abnormal indicator of the quality loss section. For example, if the temperature abnormality in the extrusion molding section causes uneven film thickness, wherein the uneven film thickness is the abnormal value of the thickness indicator of the extrusion molding section, and the temperature abnormality causes the abnormal value, the film quality knowledge base is searched, and the failure of the extruder heating system is one of the reasons for the temperature abnormality. The system automatically detects its extruder heating system, and then determines that the root cause of quality loss is the failure of the extruder heating system.

[0038] In this embodiment, the film product production process is regulated by the root cause of quality loss; in specific implementation, for example, when the root cause of quality loss is determined to be a failure of the extruder heating system, the extruder heating power can be adjusted or the heating element can be replaced to ensure that the temperature is stable within the corresponding quality control index range (such as 180±5°C). The above method can achieve quality traceability in the film product production process.

[0039] It can be seen that in the present application, the change pattern of key quality control indicators can be accurately identified, and the root cause of quality problems can be evaluated in combination with historical data and production environment characteristics; wherein, by dividing the film production process into different process sections and collecting production data of each process section in real time, the process parameter changes in the production process can be systematically analyzed, and its normal and abnormal states can be identified, and then by extracting abnormal process sections, process fluctuations that are significantly different from normal production can be timely identified, thereby achieving real-time monitoring and response, and the dynamic adjustment of the quality control indicator domain can provide a quantified normal range interval for each key quality control indicator; then, by obtaining historical production data and determining the indicator correlation between process indicators, a more comprehensive process feature can be obtained, which is helpful to identify potential quality problems and quality loss points, thereby enhancing the quality control capability of the traceability system, and combined with multi-source data collection and analysis, multi-dimensional process optimization can be achieved, and constructing a quality control indicator weight sequence can help identify the impact weights of key quality control indicators; finally, based on the quality loss points and the film quality knowledge base, the root cause of the quality problem can be more accurately determined, so that the production process parameters can be adjusted in time to take quality control measures, and the quality consistency and production efficiency of film production can be significantly improved.

[0040] In summary, the technical solution adopted in this application can accurately identify the change patterns of key quality control indicators, and combine historical data and production environment characteristics to evaluate the root causes of quality problems, so as to improve the accuracy and reliability of film production quality traceability.

[0041] Embodiment 2: This application provides a film production quality tracing system, referring to Figure 2 As shown, this figure is a module structure diagram of the traceability system shown in this embodiment of the present application, and the traceability system includes: The data acquisition module 100 is used to divide the thin film product production process into different process sections and collect the production data of each process section in the thin film product production process in real time; The data processing module 200 is used to obtain historical production data of the thin film product production process, determine the index correlation between process indicators in different process sections according to the historical production data, screen out all key quality control indicators in the thin film product production process based on all the index correlations, and determine the quality control index domain corresponding to each key quality control indicator in the thin film product production process according to the historical production data; The quality failure section determination module 300 is used to extract the quality control production data corresponding to each key quality control indicator from the production data of each process section, and determine all the quality failure sections in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; The production control module 400 is used to determine the root causes of quality loss in the film product production process using all quality loss points, and to control the film product production process based on the root causes of quality loss, thereby achieving quality traceability in the film product production process.

[0042] The above describes in detail the examples of the film production quality tracing method and system provided in the embodiments of the present application. It can be understood that in order to realize the above functions, the corresponding device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0043] In a third embodiment, the present application further provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned film production quality traceability method.

[0044] In this embodiment, reference Figure 3 , the dotted line in the figure indicates that the unit or the module is optional, and the figure is a structural schematic diagram of a computer device for a film production quality tracing method provided in an embodiment of the present application. The film production quality tracing method in the above embodiment can be Figure 3 The computer device shown in the figure is implemented, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device can be a terminal device, a server or a chip.

[0045] The processor 301 may be a general-purpose processor or a special-purpose processor. For example, the processor 301 may be a central processing unit (CPU), which may be used to control the computer device, execute software programs, and process data of the software programs. The computer device may also include a communication unit 305 to implement signal input (reception) and output (transmission).

[0046] For example, the computer device may be a chip, the communication unit 305 may be an input and / or output circuit of the chip, or the communication unit 305 may be a communication interface of the chip, and the chip may be a component of a terminal device, a network device, or other devices.

[0047] For another example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0048] The computer device may include one or more memories 302, on which a program 304 is stored. The program 304 can be executed by the processor 301 to generate instructions 303, so that the processor 301 performs the method described in the above method embodiment according to the instructions 303. Optionally, data (such as a target audit model) may also be stored in the memory 302. Optionally, the processor 301 may also read the data stored in the memory 302, and the data may be stored at the same storage address as the program 304, or the data may be stored at a different storage address from the program 304.

[0049] The processor 301 and the memory 302 may be provided separately or integrated together, for example, integrated on a system on chip (SOC) of the terminal device.

[0050] It should be understood that each step of the above method embodiment can be completed by a hardware-based logic circuit or a software-based instruction in the processor 301. The processor 301 can be a central processing unit, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, such as discrete gates, transistor logic devices or discrete hardware components.

[0051] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0052] In a fourth embodiment, the present application further provides a computer-readable storage medium, wherein instructions or codes are stored in the computer-readable storage medium. When the instructions or codes are executed on a computer, the above-mentioned film production quality tracing method is implemented when the computer executes the instructions or codes.

[0053] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

Claims

1. A film production quality tracing method, characterized in that: The tracing method comprises the following steps: Divide the film product production process into different process sections, and collect the production data of each process section in real time; Acquire historical production data of the thin film product production process, determine the indicator correlation between process indicators in different process sections according to the historical production data, screen out all key quality control indicators in the thin film product production process based on all indicator correlations, and determine the quality control indicator domain corresponding to each key quality control indicator in the thin film product production process according to the historical production data; Extract the quality control production data corresponding to each key quality control indicator from the production data of each process section, and determine all quality loss points in the production process of the film product through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; All quality loss points are used to determine the root causes of quality loss in the film product production process, and the film product production process is regulated by the root causes of quality loss, thereby achieving quality traceability in the film product production process.

2. A film production quality tracing method according to claim 1, characterized in that: The film product production process is divided into different process sections according to the changes in the chemical and physical states of the film products during the film product production process.

3. A film production quality tracing method according to claim 1, characterized in that: The quality control index domain is used to determine the normal range of the corresponding key quality control indicators in the production process of the film product.

4. A film production quality tracing method according to claim 1, characterized in that: Determining the index correlation between process indicators in different process sections according to the historical production data specifically includes: Determine the weights of the process indicators in different process sections affecting the film quality according to the historical production data, and obtain an indicator weight sequence; The indicator correlation between the process indicators in different process sections is determined by the indicator weight sequence.

5. A film production quality tracing method according to claim 1, characterized in that: The quality loss section is a process section that affects the film production quality during the film product production process.

6. A film production quality tracing method according to claim 1, characterized in that: Through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain, all quality loss points in the film product production process are determined, including: Determine multiple potential quality loss points in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; Determine the process section where each potential quality loss point is located, and then screen each potential quality loss point through the semi-finished product quality data of the corresponding process section to obtain all quality loss points in the film product production process.

7. A film production quality tracing method according to claim 1, characterized in that: Using all the quality-destroying sections to determine the root causes of quality loss in the film product production process is to search the film quality knowledge base based on the abnormal types of process parameters at each quality-destroying section, and then determine the root causes of quality loss.

8. A film production quality tracing system, used to execute a film production quality tracing method according to any one of claims 1 to 7, characterized in that: The traceability system includes: A data acquisition module is used to divide the thin film product production process into different process sections and collect the production data of each process section in the thin film product production process in real time; A data processing module, used to obtain historical production data of the thin film product production process, determine the indicator correlation between process indicators in different process sections according to the historical production data, screen out all key quality control indicators in the thin film product production process based on all indicator correlations, and determine the quality control indicator domain corresponding to each key quality control indicator in the thin film product production process according to the historical production data; The quality loss section determination module is used to extract the quality control production data corresponding to each key quality control indicator from the production data of each process section, and determine all the quality loss sections in the film product production process through the quality control production data corresponding to each key quality control indicator and the corresponding quality control indicator domain; The production control module is used to use all the quality loss points to determine the root causes of quality loss in the film product production process, and to control the film product production process based on the root causes of quality loss, thereby achieving quality traceability in the film product production process.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes a film production quality tracing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements a film production quality tracing method as described in any one of claims 1 to 7.

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