A system and method for coordinated production and quality control of cover films for new energy substrates
By collecting and binding production parameters in real time, generating collaborative early warning information and adjusting production parameters, the problem of batch defective products caused by independent processes in traditional production is solved, and efficient production and quality traceability are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 江西锦荣新材料有限公司
- Filing Date
- 2026-04-15
- Publication Date
- 2026-07-10
AI Technical Summary
In traditional production processes, each process completes its assigned task independently without interfering with the others. If a parameter in the previous process becomes abnormal, the subsequent processes will still proceed according to the previously set parameters, which can easily lead to a batch of defective products.
By setting up data acquisition devices to collect production control parameters in real time, assigning identification codes to production materials, dynamically binding production control parameters with identification codes, determining quality status in real time, generating collaborative early warning information, pushing it to the current and downstream processes, calling adaptive adjustment strategies to adjust parameters, and integrating to generate a full lifecycle quality archive.
It enables rapid identification of processing errors, reduces the generation of batch defective products, improves production efficiency and reduces costs, ensures product quality consistency and production robustness, and supports traceability analysis of production data.
Smart Images
Figure CN122363101A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of production quality control technology, and in particular relates to a collaborative control system and method for the production and quality of cover films for new energy substrates. Background Technology
[0002] Collaborative quality control is a multi-party collaboration mechanism based on cross-departmental, cross-organizational, and even cross-supply chain collaboration. It achieves quality planning, monitoring, analysis, and improvement throughout the entire lifecycle of a product or service through unified quality standards, information sharing platforms, and collaborative workflows.
[0003] In traditional production processes, each process independently completes the work set for that process, without interfering with each other. If a parameter abnormality occurs in the previous process, the subsequent processes will still process according to the previously set parameters, which can easily lead to a batch of defective products and have a significant impact on subsequent production. Summary of the Invention
[0004] The purpose of this invention is to provide a method for coordinated production and quality control of cover films for new energy substrates. This method aims to solve the problem that in traditional production processes, each process independently completes the work set for the current process without interfering with each other. However, if the parameters of the previous process are abnormal, the subsequent processes will still process according to the previously set parameters, which can easily lead to a batch of defective products.
[0005] This invention is implemented as follows: a method for coordinated production and quality control of a cover film for new energy substrates, the method comprising: The production control parameters are collected in real time by the set data acquisition equipment, and an identification code is assigned to the production materials. The production control parameters are dynamically bound to the identification code. The production control parameters include production equipment parameters, environmental parameters, and material status parameters. The production materials include raw materials, semi-finished rolls, and finished rolls. The production control parameters are compared with the predetermined quality rules to determine the quality status of the output of the process in real time, generate collaborative early warning information, and push the early warning information and the associated identification code to the current process and all downstream processes simultaneously. Based on the category and level of the collaborative early warning information, the pre-stored adaptive adjustment strategy is invoked for the production equipment of the current process and downstream processes to adjust the production parameters of this process; By integrating production process data, a full lifecycle quality archive for the covering film is generated from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back. The production process data includes data bound to the production process, quality judgment results, and warning and adjustment records.
[0006] Preferably, the step of comparing production control parameters with predetermined quality rules, determining the quality status of the output of the process in real time, generating collaborative early warning information, and simultaneously pushing the early warning information and associated identification code to the current process and all downstream processes includes: Retrieve production control parameters, retrieve different predetermined quality rules based on different production control parameters, compare the parameters, and extract abnormal parameters that deviate from the normal range; The current warning is divided into different levels based on the value of the abnormal parameters. A structured warning information package is generated based on the warning level, abnormal parameters and corresponding identification code. The warning level is divided into three levels: severe, moderate and mild. The structured early warning information package is pushed to the human-machine interface of the production equipment in the downstream process, and the early warning workstation and identification code are displayed on the corresponding production equipment.
[0007] Preferably, the step of invoking a pre-stored adaptive adjustment strategy for the production equipment of the current process and downstream processes to adjust the production parameters of the current process based on the category and level of the collaborative early warning information specifically includes: Based on the warning level and abnormal parameter type of the collaborative early warning information, the corresponding compensation scheme is matched from the pre-stored adaptive strategy library, and specific equipment control instructions are generated. Based on equipment control commands, control the production equipment of the corresponding process and execute the corresponding adjustment strategies; After the strategy adjustment is implemented, the quality data of the output of this process is monitored in real time, and the adjusted production data is used as effect feedback. The effect feedback is then linked to the identification code of the batch of materials.
[0008] Preferably, the steps of integrating production process data to generate a full lifecycle quality file for the covering film from raw materials to finished products, and tracing back the process parameters from raw materials to finished products by scanning the identification code on the finished product, include: Upon obtaining the finished product, the production data, quality judgment records, early warning logs, and parameter adjustment records of all processes that the finished product has undergone are stored and archived according to the identification code to obtain a full life cycle quality file; Construct a product traceability chain, record bidirectional data in the product traceability chain, and determine the bidirectional traceability relationship between the data; When tracing the source, the identification code is scanned to retrieve the corresponding full life cycle quality file, and the process parameters are traced back by querying the full life cycle quality file.
[0009] Preferably, the quality record of each finished product has a preset retention period, and it is deleted when the retention period is exceeded.
[0010] Another objective of this invention is a collaborative production and quality control system for cover films used in new energy substrates, the system comprising: The parameter binding module is used to collect production control parameters in real time through the set data acquisition equipment, assign identification codes to production materials, and dynamically bind production control parameters with identification codes. Production control parameters include production equipment parameters, environmental parameters, and material status parameters. Production materials include raw materials, semi-finished rolls, and finished rolls. The process control module is used to compare production control parameters with predetermined quality rules, determine the quality status of the output of the process in real time, generate collaborative early warning information, and push the early warning information and associated identification code to the current process and all downstream processes simultaneously. The process adjustment module is used to call pre-stored adaptive adjustment strategies for the production equipment of the current process and downstream processes based on the category and level of collaborative early warning information, and adjust the production parameters of the current process. The production materials management module is used to integrate production process data and generate a full life cycle quality file for the covering film from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back. The production process data includes data bound to the production process, quality judgment results, and warning and adjustment records.
[0011] Preferably, the process control module includes: The abnormal parameter identification unit is used to retrieve production control parameters, retrieve different predetermined quality rules according to different production control parameters, compare the parameters, and extract abnormal parameters that deviate from the normal range. The early warning classification unit is used to classify the current early warning into different levels according to the value of the abnormal parameter, and to generate a structured early warning information package based on the early warning level, abnormal parameter and corresponding identification code. The early warning level is divided into three levels: severe, moderate and mild. The early warning information push unit is used to push structured early warning information packages to the human-machine interface of the production equipment in the downstream process, and display the early warning workstation and identification code on the corresponding production equipment.
[0012] Preferably, the process adjustment module includes: The control command generation unit is used to match the corresponding compensation scheme from the pre-stored adaptive strategy library according to the warning level and abnormal parameter type of the collaborative early warning information, and generate specific equipment control commands. The strategy adjustment unit is used to control the production equipment of the corresponding process based on the equipment control commands and execute the corresponding adjustment strategies. The adjustment feedback unit is used to monitor the quality data of the output of this process in real time after the adjustment strategy is implemented, and to use the adjusted production data as effect feedback, and to bind the effect feedback with the identification code of the batch of materials.
[0013] Preferably, the production materials management module includes: The data recording unit is used to store production data, quality judgment records, early warning logs and parameter adjustment records of all processes that the finished product has undergone when the finished product is obtained, and archive them according to the identification code to obtain a full life cycle quality file; The data association unit is used to build a product traceability chain, record bidirectional data in the product traceability chain, and determine the bidirectional traceability relationship between data. The data backtracking unit is used to scan the identification code to retrieve the corresponding full lifecycle quality file during the traceability process, and to backtrack the process parameters by querying the full lifecycle quality file.
[0014] Preferably, the quality record of each finished product has a preset retention period, and it is deleted when the retention period is exceeded.
[0015] This invention, through real-time quality assessment, can quickly determine whether there are processing errors in the current process. When a processing error is detected, it issues an early warning to the next process. Thus, when the current material enters the next process, the error in the current process can be compensated by the next process to achieve the purpose of linkage, which can ensure product quality. Furthermore, the data generated throughout the entire processing process is archived and bound to an identification code, enabling traceability of production data through scanning during subsequent use. This reduces the waste of materials and time caused by batch defects, improves production efficiency, and reduces production costs. Attached Figure Description
[0016] Figure 1 A flowchart illustrating a method for coordinated production and quality control of a cover film for a new energy substrate, provided in an embodiment of the present invention; Figure 2 A flowchart illustrating the steps of generating collaborative early warning information and pushing it to downstream processes, as provided in an embodiment of the present invention; Figure 3 A flowchart illustrating the steps of invoking a pre-stored adaptive adjustment strategy for production equipment in the current and downstream processes based on the category and level of collaborative early warning information, as provided in this embodiment of the invention. Figure 4 The integrated production process data provided in this embodiment of the invention generates a full life cycle quality file for the covering film from raw materials to finished products, and traces back the process parameters of the process from raw materials to finished products by scanning the identification code on the finished product. Figure 5 This invention provides an architecture diagram of a collaborative production and quality control system for a cover film used in new energy substrates, as provided in an embodiment of the invention. Figure 6 An architecture diagram of a process control module provided in an embodiment of the present invention; Figure 7 An architecture diagram of a process adjustment module provided in an embodiment of the present invention; Figure 8 This is an architecture diagram of a production materials management module provided in an embodiment of the present invention. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0018] like Figure 1 The diagram shows a flowchart of a method for coordinated production and quality control of a cover film for a new energy substrate, provided by an embodiment of the present invention. The method includes: S100 collects production control parameters in real time through set data acquisition devices, assigns identification codes to production materials, and dynamically binds production control parameters with identification codes. Production control parameters include production equipment parameters, environmental parameters, and material status parameters. Production materials include raw materials, semi-finished rolls, and finished rolls.
[0019] In this step, production control parameters are collected in real time using data acquisition devices. When building the production line, data acquisition devices are set up at each key process node of the cover film production to collect specific parameters of the production equipment. For example, for the coating process, the coating speed, tension, and wet film thickness are collected; for the baking process, the temperature, wind speed, and exhaust concentration at various locations in the baking area are collected; for the slitting process, the slitting speed, cutting pressure, and cutting accuracy are obtained; and for the die-cutting process, the punching pressure and product appearance are collected. Parameters are recorded by deploying data acquisition devices such as temperature sensors and tension sensors to reflect the equipment status in real time. Each batch of substrate input and each roll of semi-finished and finished product produced during the production process are assigned a unique identification code, such as a QR code.
[0020] S200 compares the production control parameters with the predetermined quality rules, determines the quality status of the output of the process in real time, generates collaborative early warning information, and pushes the early warning information and the associated identification code to the current process and all downstream processes simultaneously.
[0021] In this step, a predetermined quality rule library is constructed. This library records the parameter ranges corresponding to various process parameters. The production control parameters collected in real time are compared with this predetermined quality rule library to determine the quality of parameters in each production process. When any parameter at any node exceeds a preset threshold, a structured collaborative early warning message is generated. For example, if the coating thickness is insufficient, a set of collaborative early warning messages is generated to record the anomaly type, level, location, and related identification code. The collaborative early warning message is then synchronously pushed to the operation interface of the current process and the production equipment of all subsequent processes.
[0022] S300, based on the category and level of the collaborative early warning information, invokes pre-stored adaptive adjustment strategies for the production equipment of the current process and downstream processes to adjust the production parameters of this process.
[0023] In this step, collaborative early warning information is received. The production equipment in the downstream process calls the corresponding compensation scheme from the pre-stored adaptive adjustment strategy library according to the category and level of the early warning. For example, when the slitting machine receives an early warning from the upstream that the coating thickness of the material in this roll is too thin, it automatically executes the preset strategy, reduces the cutting depth of the slitting blade and the winding tension, so as to avoid breakage or burrs during slitting due to insufficient tensile strength of the material. The error of the previous process is compensated by the subsequent process, which effectively curbs the amplification and transmission of quality defects and significantly improves the robustness of the production process and the consistency of the product.
[0024] S400 integrates production process data to generate a full lifecycle quality archive for the cover film from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back. The production process data includes data bound to the production process, quality judgment results, and warning and adjustment records.
[0025] In this step, production process data is integrated. Based on a unique identification code, all data generated by the product is automatically integrated and archived, including original production parameters, real-time quality judgment results, collaborative early warning logs, and equipment adaptive adjustment records. This generates a full lifecycle quality profile for each product. Based on this full lifecycle quality profile, the trajectory of any finished product can be tracked. Furthermore, when quality problems occur, the original production batch, production line, and every process parameter and abnormal event can be traced back through the battery batch number or the cover film QR code, greatly improving the efficiency and accuracy of root cause analysis.
[0026] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of comparing production control parameters with predetermined quality rules, determining the quality status of the output of the process in real time, generating collaborative early warning information, and synchronously pushing the early warning information and associated identification code to the current process and all downstream processes includes: S201, retrieve production control parameters, retrieve different predetermined quality rules according to different production control parameters, compare the parameters, and extract abnormal parameters that deviate from the normal range.
[0027] In this step, production control parameters are retrieved and compared in real time with the parameter ranges set in the predetermined quality rules. For example, in the coating process, the real-time collected wet film thickness is continuously compared with the set target thickness and its tolerance zone; in the baking process, the actual temperature of each temperature zone is compared with the standard baking temperature. If any parameter is detected to be continuously deviating from the normal range, such as the thickness showing a unidirectional drift trend, or the instantaneous temperature fluctuation exceeding the standard, then the parameter is identified as an abnormal parameter and its degree of deviation is determined.
[0028] S202, the current warning is divided into different levels according to the value of the abnormal parameter, and a structured warning information package is generated based on the warning level, abnormal parameter and corresponding identification code. The warning level is divided into three levels: severe, moderate and mild.
[0029] In this step, the current warning is classified into different levels according to the value of the abnormal parameter. The level classification is based on preset rules. For example, if the parameter deviates slightly but is still within the controllable range, a mild warning is triggered, which is only recorded and prompted. If the deviation affects the key performance of the product, such as insulation, a moderate warning is triggered, requiring operator confirmation. If the parameter has seriously exceeded the standard and may generate a batch of scrap, a severe warning is immediately triggered, and the equipment may be automatically slowed down or stopped. The warning level, the specific abnormal parameter value, the time of occurrence, the workstation, and the identification code are packaged into a standardized structured warning information package.
[0030] S203 pushes the structured early warning information package to the human-machine interface of the production equipment in the downstream process and displays the early warning station and identification code on the corresponding production equipment.
[0031] In this step, the structured early warning information package is pushed to the human-machine interface of the production equipment in the downstream process. At the same time, the structured early warning information is also transmitted to the control center. The control center is used to comprehensively control the entire production line and to warn the production equipment of the process where the abnormality occurs through audible and visual warnings.
[0032] like Figure 3 As shown, in a preferred embodiment of the present invention, the step of invoking a pre-stored adaptive adjustment strategy for the production equipment of the current process and downstream processes according to the category and level of the collaborative early warning information to adjust the production parameters of the current process specifically includes: S301, based on the warning level and abnormal parameter type of the collaborative warning information, matches the corresponding compensation scheme from the pre-stored adaptive strategy library and generates specific equipment control instructions.
[0033] In this step, when the downstream production equipment receives the collaborative early warning information from the upstream, it searches and matches the information in the collaborative early warning information, such as the warning level being moderate and the anomaly type being thin coating thickness, in the adaptive strategy library to obtain a compensation scheme to deal with the current scenario. For example, thin thickness → reduce blade pressure and tension. After a successful match, this compensation scheme is converted into equipment control commands, such as adjusting the slitting blade pressure from 50N to 45N, and is prepared to be sent to the equipment's actuator.
[0034] S302 controls the production equipment of the corresponding process based on equipment control commands and executes the corresponding adjustment strategies.
[0035] In this step, the production equipment of the corresponding process is controlled based on the equipment control instructions. The control instructions are sent to the equipment actuator to realize the automatic adjustment of parameters. After receiving the instructions, the slitting machine automatically adjusts the cutting depth of the slitting knife and the winding tension before the material that is warned of being too thin reaches the slitting station. By actively adapting to the abnormal state of the material, the smooth processing of the product is ensured.
[0036] S303 After the adjustment strategy is implemented, the quality data of the output of this process is monitored in real time, and the adjusted production data is used as effect feedback. The effect feedback is then bound to the identification code of the batch of materials.
[0037] Specifically, based on the warning level and abnormal parameter type of the collaborative early warning information, the corresponding compensation scheme is matched from the pre-stored adaptive strategy library, and specific equipment control commands are generated. The specific steps are as follows: The abnormal parameter type is obtained from the production control parameters; The warning level is used to perform a preliminary screening in a pre-stored adaptive strategy library to determine the scope of the preliminary strategy screening. Specifically, the preliminary screening is as follows: severe warning corresponds to the strategy scope of all processes, moderate warning corresponds to the strategy scope of the current and downstream processes, and mild warning corresponds to the strategy scope of the current process, so as to determine the scope of the preliminary strategy screening. Within the initial strategy screening range, the abnormal parameter types are matched with historical data in the pre-stored adaptive strategy library. By comparing parameter features, compensation schemes with the same abnormal features are selected, and candidate compensation schemes with matching abnormal features are obtained. Retrieve historical compensation schemes from the pre-stored adaptive strategy library, compare and verify the candidate compensation schemes matching abnormal features with the historical compensation schemes, and select the effective compensation schemes after verification. Using production control parameters, the verified effective compensation scheme is numerically adjusted and adapted to the operating conditions to obtain the adapted compensation scheme. The parameters in the adapted compensation scheme are adjusted to an instruction format that the device can recognize in order to generate specific device control instructions.
[0038] Furthermore, based on the warning level and abnormal parameter type, this invention automatically generates equipment control commands by intelligently matching, verifying and optimizing historical compensation schemes, achieving precise adaptive adjustment, effectively improving product quality consistency, reducing defective products and waste, and improving production efficiency and system robustness.
[0039] Specifically, the abnormal parameter types are matched with historical data in the pre-stored adaptive strategy library. By comparing parameter features, compensation schemes with the same abnormal characteristics are selected to obtain candidate compensation schemes that match the abnormal features. The specific steps are as follows: Extract the abnormal parameter type identifiers and corresponding warning levels from the production control parameters that deviate from the predetermined quality rules; Using the abnormal parameter type identifiers that deviate from the predetermined quality rules and their corresponding warning levels as query conditions, historical abnormal records are searched in the pre-stored adaptive strategy library to obtain a set of historical abnormal records. Based on the parameter tolerance band set in the predetermined quality rules, the measured values in the abnormal feature set are compared with the parameter values in the historical abnormal record set to obtain a similarity score. Using a preset similarity threshold, historical abnormal records with similarity scores higher than the preset similarity threshold are filtered from the historical abnormal record set to obtain a matching historical record subset; Extract the corresponding device adjustment schemes from the matched historical record subsets to obtain an initial candidate compensation scheme set; merge the duplicate adjustment items of the same device parameter in the initial candidate compensation scheme set to obtain a deduplicated and optimized candidate compensation scheme set. The set of candidate compensation schemes after deduplication and optimization is used as the matching result of abnormal features to obtain candidate compensation schemes for abnormal feature matching.
[0040] Furthermore, this invention accurately matches current abnormal features with historical data, quickly filters out highly compatible candidate compensation schemes based on similarity scores, and significantly improves the accuracy and efficiency of strategy matching through deduplication optimization, ensuring that the equipment adjustment scheme is both reliable and targeted.
[0041] Specifically, the candidate compensation schemes matching abnormal features are compared and verified with historical compensation schemes to select the effective compensation schemes after verification. The specific steps are as follows: Using the parameter type identifier and warning level of the candidate compensation scheme that matches the abnormal features as query conditions, the system retrieves historical records with the same abnormal features from the pre-stored adaptive strategy library, and obtains the equipment adjustment parameters and corresponding historical production control parameters from the retrieved historical records, so as to obtain the parameter values of the candidate compensation scheme that matches the abnormal features and the parameter values in the historical compensation scheme. The numerical difference between the parameter values of the candidate compensation schemes matching the abnormal features and the parameter values in the historical compensation schemes is calculated to obtain the parameter deviation value. The tolerance zone range is preset by pre-defined quality rules; based on the tolerance zone range, historical compensation schemes whose absolute values of parameter deviations fall within the tolerance zone range are selected to obtain a preliminary subset of matching schemes. Using the identification code corresponding to each historical compensation scheme in the preliminary matching scheme subset, the corresponding quality judgment records and early warning logs are retrieved to obtain effect verification data; Based on the effect verification data, the first indicator is obtained by statistically analyzing whether the production control parameters of the same identification code in subsequent processes return to the predetermined quality rule range after the equipment adjustment parameters in the candidate compensation scheme with anomaly feature matching are applied. Using the effectiveness verification data, we statistically analyze the records of collaborative early warning information associated with identity codes that are terminated in the subsequent push process to obtain the second indicator; by combining the first and second indicators and quantifying them, we obtain the effectiveness score of the solution. A validity threshold is preset using historical production data; candidate compensation schemes with abnormal features matching the scheme validity score that is higher than the validity threshold are selected to obtain a list of valid candidate schemes; each scheme in the valid candidate schemes is selected as a valid compensation scheme after verification.
[0042] Furthermore, this invention uses historical data comparison and dual effect index quantitative verification to screen out effective compensation schemes that have been verified in actual production, ensuring that the adopted adjustment strategies have high reliability and excellent historical performance, thereby significantly improving the accuracy and success rate of quality intervention.
[0043] In this step, after the strategy is adjusted, the quality data produced by this process is continuously monitored, such as the width accuracy and edge quality image recognition results after slitting. The above data is used as quality data, and is re-bound with the identification code of the batch of materials, and updated as a historical record to the full life cycle quality file of the material.
[0044] like Figure 4 As shown, in a preferred embodiment of the present invention, the step of integrating production process data to generate a full lifecycle quality file for the covering film from raw materials to finished products, and tracing back the process parameters from raw materials to finished products by scanning the identification code on the finished product, includes: S401: Upon obtaining the finished product, the production data, quality judgment records, early warning logs, and parameter adjustment records of all processes that the finished product has undergone are stored and archived according to the identification code to obtain a full life cycle quality file.
[0045] In this step, when a set of finished products has completed all production processes and is ready to be unloaded, the identification code of the finished product is used as the core. All production data from the raw material warehousing to coating, baking, slitting, die cutting and other processes, the results of each quality judgment, all received or triggered early warning logs, and any parameter adjustment records are collected together to obtain a full life cycle quality file.
[0046] S402, Construct a product traceability chain, record bidirectional data in the product traceability chain, and determine the bidirectional traceability relationship between the data.
[0047] S403, when performing traceability, scan the identification code to retrieve the corresponding full life cycle quality file, and trace back the process parameters by querying the full life cycle quality file.
[0048] Specifically, upon obtaining the finished product, all production data, quality judgment records, early warning logs, and parameter adjustment records from all processes the finished product has undergone are stored and archived according to the identification code to obtain a full lifecycle quality file. The specific steps are as follows: When the production process ends, the data acquisition equipment generates a finished product completion signal; based on the finished product completion signal, using the identification code as the retrieval condition, combined with the production control parameters and quality judgment records, all process data corresponding to the target identification code are retrieved to obtain a preliminary data set; Based on the preliminary dataset, the production control parameters and corresponding quality judgment records are sorted according to the actual execution time sequence of each process in order to establish the time relationship between the data and obtain the time series data sequence. Based on time-series data sequences, coating speed, baking temperature, and wet film thickness are extracted from production data, environmental parameters, and material state parameters, respectively. Combining quality judgment results, early warning levels, and equipment control instructions, coating speed, baking temperature, and wet film thickness are classified and organized into six categories: production equipment parameters, environmental parameters and material state parameters, quality judgment results, early warning information, and adjustment records, to obtain a structured parameter dataset. Based on the structured parameter dataset, the categorized parameters are bound to the identification codes to establish a parameter-identification code correspondence and obtain the bound data packet. By using bound data packets, production data, quality judgment records, early warning logs, and parameter adjustment records are stored in the database, and an identification code index is established to obtain archived data; By using archived data, all bound data packets are aggregated to obtain a full lifecycle quality profile.
[0049] Furthermore, by integrating production data across the entire process and establishing structured quality archives, this invention enables complete data traceability from raw materials to finished products, significantly improving the efficiency and accuracy of source analysis for quality issues.
[0050] In this step, a product traceability chain is constructed, which has bidirectional traceability capabilities, including forward and reverse traceability. For example, by entering the identification code of any finished product into the system interface, the buyer of the finished product and the product to which it is applied can be found. In the reverse traceability process, if a battery manufacturer reports a problem with a certain batch of batteries, the batch number of the cover film used can be found by reverse querying the batch number of the battery. Then, by using the identification code of the cover film, the batch of the original materials used to produce the cover film, the production line number, the production time, and any abnormal events and adjustments during the production process can be traced. When tracing, the entire life cycle quality record can be traced back simply by scanning the code.
[0051] like Figure 5 As shown in the figure, a collaborative production and quality control system for a cover film of a new energy substrate is provided in an embodiment of the present invention. The system includes: The parameter binding module 100 is used to collect production control parameters in real time through the set data acquisition device, assign identification codes to production materials, and dynamically bind production control parameters with identification codes. Production control parameters include production equipment parameters, environmental parameters, and material status parameters. Production materials include raw materials, semi-finished rolls, and finished rolls.
[0052] In this system, the parameter binding module 100 collects production control parameters in real time through set data acquisition devices. When constructing the production line, data acquisition devices are set at each key process node of the cover film production to collect specific parameters of the production equipment. For example, for the coating process, the coating speed, tension, and wet film thickness are collected; for the baking process, the temperature, wind speed, and exhaust concentration at various locations in the baking area are collected; for the slitting process, the slitting speed, cutting pressure, and cutting accuracy are obtained; and for the die-cutting process, the punching pressure and product appearance are collected. By deploying data acquisition devices such as temperature sensors and tension sensors, parameters are recorded to reflect the equipment status in real time. Each batch of substrate input and each roll of semi-finished and finished product produced during the production process are assigned a unique identification code, such as a QR code.
[0053] The process control module 200 is used to compare production control parameters with predetermined quality rules, determine the quality status of the output of the process in real time, generate collaborative early warning information, and push the early warning information and associated identification code to the current process and all downstream processes simultaneously.
[0054] In this system, the process control module 200 constructs a predetermined quality rule library. This library records the parameter ranges corresponding to various process parameters. The production control parameters collected in real time are compared with this predetermined quality rule library to determine the quality of parameters in each process. When any parameter exceeds a preset threshold, a structured collaborative early warning message is generated. For example, if the coating thickness is insufficient, a set of collaborative early warning messages is generated to record the anomaly type, level, location, and related identification code. The collaborative early warning message is then synchronously pushed to the operation interface of the current process and the production equipment of all subsequent processes.
[0055] The process adjustment module 300 is used to call pre-stored adaptive adjustment strategies for the production equipment of the current process and downstream processes according to the category and level of the collaborative early warning information, and adjust the production parameters of the current process.
[0056] In this system, the process adjustment module 300 receives collaborative early warning information. The production equipment in the downstream process calls the corresponding compensation scheme from the pre-stored adaptive adjustment strategy library according to the category and level of the early warning. For example, when the slitting machine receives an early warning from the upstream that the coating thickness of the material in this roll is too thin, it automatically executes the preset strategy, reduces the cutting depth of the slitting blade and the winding tension, so as to avoid breakage or burrs during slitting due to insufficient tensile strength of the material. The error of the previous process is compensated by the subsequent process, which effectively curbs the amplification and transmission of quality defects and significantly improves the robustness of the production process and the consistency of the products.
[0057] The production materials management module 400 is used to integrate production process data and generate a full life cycle quality file for the covering film from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back. The production process data includes data bound to the production process, quality judgment results, and warning and adjustment records.
[0058] In this system, the production data management module 400 integrates production process data. Based on a unique identification code, it automatically integrates and archives all data generated by the product, including original production parameters, real-time quality judgment results, collaborative early warning logs, and equipment adaptive adjustment records. This generates a full lifecycle quality file for each product. Based on this full lifecycle quality file, the trajectory of any finished product can be queried. Furthermore, when quality problems occur, the system can trace back to the original batch, production line, and every process parameter and abnormal event through the battery batch number or the cover film QR code, greatly improving the efficiency and accuracy of root cause analysis.
[0059] like Figure 6 As shown, in a preferred embodiment of the present invention, the process control module 200 includes: The abnormal parameter identification unit 201 is used to retrieve production control parameters, retrieve different predetermined quality rules according to different production control parameters, compare the parameters, and extract abnormal parameters that deviate from the normal range.
[0060] In this module, the abnormal parameter identification unit 201 retrieves production control parameters and compares them in real time with the parameter ranges set in the predetermined quality rules. For example, in the coating process, it continuously compares the real-time collected wet film thickness with the set target thickness and its tolerance zone; in the baking process, it compares the actual temperature of each temperature zone with the standard baking temperature. If any parameter is detected to be continuously deviating from the normal range, such as the thickness showing a unidirectional drift trend, or the instantaneous temperature fluctuation exceeding the standard, then the parameter is identified as an abnormal parameter and its degree of deviation is determined.
[0061] The early warning classification unit 202 is used to classify the current early warning into different levels according to the value of the abnormal parameter, and generate a structured early warning information package based on the early warning level, abnormal parameter and corresponding identification code. The early warning level is divided into three levels: severe, moderate and mild.
[0062] In this module, the early warning classification unit 202 classifies the current early warning into different levels based on the value of the abnormal parameter. The classification is based on preset rules. For example, if the parameter deviates slightly but is still within a controllable range, a mild early warning is triggered, which is only recorded and prompted. If the deviation affects the key performance of the product, such as insulation, a moderate early warning is triggered, requiring operator confirmation. If the parameter has seriously exceeded the standard and may generate a batch of defective products, a severe early warning is triggered immediately, and the equipment may be automatically slowed down or stopped. The early warning level, the specific abnormal parameter value, the time of occurrence, the workstation, and the identification code are encapsulated into a standardized structured early warning information package.
[0063] The early warning information push unit 203 is used to push the structured early warning information package to the human-machine interface of the production equipment in the downstream process, and display the early warning workstation and identification code on the corresponding production equipment.
[0064] In this module, the early warning information push unit 203 pushes the structured early warning information package to the human-machine interface of the production equipment in the downstream process. At the same time, it also transmits the structured early warning information to the control center. The control center is used to comprehensively control the entire production line and to warn the production equipment of the process where the abnormality occurs through audible and visual warnings.
[0065] like Figure 7 As shown, in a preferred embodiment of the present invention, the process adjustment module 300 includes: The control command generation unit 301 is used to match the corresponding compensation scheme from the pre-stored adaptive strategy library according to the warning level and abnormal parameter type of the collaborative warning information, and generate specific equipment control commands.
[0066] In this module, when the downstream production equipment of the control command generation unit 301 receives the collaborative early warning information from the upstream, it searches and matches the information in the collaborative early warning information, such as the early warning level being moderate and the anomaly type being thin coating thickness, in the adaptive strategy library to obtain a compensation scheme to deal with the current scenario. For example, thin thickness → reduce blade pressure and tension. After successful matching, this compensation scheme is converted into equipment control commands, such as adjusting the slitting blade pressure from 50N to 45N, and is prepared to be sent to the equipment's actuator.
[0067] The strategy adjustment unit 302 is used to control the production equipment of the corresponding process based on the equipment control instructions and execute the corresponding adjustment strategy.
[0068] In this module, the strategy adjustment unit 302 controls the production equipment of the corresponding process based on the equipment control instructions. The control instructions are sent to the equipment execution mechanism to realize the automatic adjustment of parameters. After receiving the instructions, the slitting machine automatically adjusts the cutting depth of the slitting knife and the winding tension before the material that is warned of being too thin reaches the slitting station. By actively adapting to the abnormal state of the material, the smooth processing of the product is ensured.
[0069] The adjustment feedback unit 303 is used to monitor the quality data of the current process in real time after the adjustment strategy is executed, and to use the adjusted production data as effect feedback, and to bind the effect feedback with the identification code of the batch of materials.
[0070] In this module, after the adjustment strategy is executed, the adjustment feedback unit 303 continuously monitors the quality data produced in this process, such as the width accuracy and edge quality image recognition results after slitting. The above data is used as quality data, and is re-bound with the identification code of the batch of materials, and updated as a historical record to the full life cycle quality file of the material.
[0071] like Figure 8 As shown, in a preferred embodiment of the present invention, the production materials management module 400 includes: The data recording unit 401 is used to store production data, quality judgment records, early warning logs and parameter adjustment records of all processes that the finished product has undergone when the finished product is obtained, and archive them according to the identification code to obtain a full life cycle quality file.
[0072] In this module, when a group of finished products completes all production processes and is ready to be unloaded, the data recording unit 401 uses the identification code of the finished product as the core to collect all production data from the raw material warehousing to coating, baking, slitting, die cutting and other processes, the quality judgment results of each process, all received or triggered early warning logs, and any parameter adjustment records that have been executed, and obtain a full life cycle quality archive.
[0073] The data association unit 402 is used to construct a product traceability chain, record bidirectional data in the product traceability chain, and determine the bidirectional traceability relationship between data.
[0074] The data backtracking unit 403 is used to scan the identification code to retrieve the corresponding full life cycle quality file when performing traceability, and to backtrack the process parameters by querying the full life cycle quality file.
[0075] In this module, a product traceability chain is constructed, which has bidirectional traceability capabilities, including forward and reverse traceability. For example, by entering the identification code of any finished product into the system interface, the buyer of the finished product and the product to which it is applied can be found. In the reverse traceability process, when a battery manufacturer reports a problem with a certain batch of batteries, the batch number of the cover film used can be found by reverse querying the batch number of the battery. Then, by using the identification code of the cover film, the original material batch, production line number, production time, and abnormal events and adjustments during the production process can be traced. When tracing, the entire life cycle quality file can be traced back simply by scanning the code.
[0076] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for coordinated production and quality control of a cover film for new energy substrates, characterized in that, The method includes: The production control parameters are collected in real time by the set data acquisition equipment, and an identification code is assigned to the production materials. The production control parameters are dynamically bound to the identification code. The production control parameters include production equipment parameters, environmental parameters, and material status parameters. The production materials include raw materials, semi-finished rolls, and finished rolls. The production control parameters are compared with the predetermined quality rules to determine the quality status of the output of the process in real time, generate collaborative early warning information, and push the early warning information and the associated identification code to the current process and all downstream processes simultaneously. Based on the category and level of the collaborative early warning information, the pre-stored adaptive adjustment strategy is invoked for the production equipment of the current process and downstream processes to adjust the production parameters of this process; By integrating production process data, a full lifecycle quality archive for the covering film is generated from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back. The production process data includes data bound to the production process, quality judgment results, and warning and adjustment records.
2. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 1, characterized in that, The steps of comparing production control parameters with predetermined quality rules, determining the quality status of the output of the process in real time, generating collaborative early warning information, and synchronously pushing the early warning information and associated identification code to the current process and all downstream processes include: Retrieve production control parameters, retrieve different predetermined quality rules based on different production control parameters, compare the parameters, and extract abnormal parameters that deviate from the normal range; The current warning is divided into different levels based on the value of the abnormal parameters. A structured warning information package is generated based on the warning level, abnormal parameters and corresponding identification code. The warning level is divided into three levels: severe, moderate and mild. The structured early warning information package is pushed to the human-machine interface of the production equipment in the downstream process, and the early warning workstation and identification code are displayed on the corresponding production equipment.
3. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 2, characterized in that, The step of adjusting the production parameters of the current process by invoking a pre-stored adaptive adjustment strategy for the production equipment of the current and downstream processes based on the category and level of the collaborative early warning information specifically includes: Based on the warning level and abnormal parameter type of the collaborative early warning information, the corresponding compensation scheme is matched from the pre-stored adaptive strategy library, and specific equipment control instructions are generated. Based on equipment control commands, control the production equipment of the corresponding process and execute the corresponding adjustment strategies; After the strategy adjustment is implemented, the quality data of the output of this process is monitored in real time, and the adjusted production data is used as effect feedback. The effect feedback is then linked to the identification code of the batch of materials.
4. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 3, characterized in that, Based on the warning level and abnormal parameter type of the collaborative early warning information, the corresponding compensation scheme is matched from the pre-stored adaptive strategy library, and specific equipment control commands are generated. The specific steps are as follows: The abnormal parameter type is obtained from the production control parameters; The warning level is used to perform preliminary screening in a pre-stored adaptive strategy library to determine the scope of preliminary strategy screening. Specifically, the preliminary screening is as follows: severe warning corresponds to the strategy scope of all processes, moderate warning corresponds to the strategy scope of the current and downstream processes, and mild warning corresponds to the strategy scope of the current process, so as to determine the scope of preliminary strategy screening. Within the initial strategy screening range, the abnormal parameter types are matched with historical data in the pre-stored adaptive strategy library. By comparing parameter features, compensation schemes with the same abnormal features are selected, and candidate compensation schemes with matching abnormal features are obtained. Retrieve historical compensation schemes from the pre-stored adaptive strategy library, compare and verify the candidate compensation schemes matching abnormal features with the historical compensation schemes, and select the effective compensation schemes after verification. Using production control parameters, the verified effective compensation scheme is numerically adjusted and adapted to the operating conditions to obtain the adapted compensation scheme. The parameters in the adapted compensation scheme are adjusted to an instruction format that the device can recognize in order to generate specific device control instructions.
5. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 4, characterized in that, The abnormal parameter types are matched with historical data in the pre-stored adaptive strategy library. Compensation schemes with the same abnormal characteristics are selected by comparing parameter features, and candidate compensation schemes with abnormal feature matching are obtained. The specific steps are as follows: Extract the abnormal parameter type identifiers and corresponding warning levels from the production control parameters that deviate from the predetermined quality rules; Using the abnormal parameter type identifiers that deviate from the predetermined quality rules and their corresponding warning levels as query conditions, historical abnormal records are searched in the pre-stored adaptive strategy library to obtain a set of historical abnormal records. Based on the parameter tolerance band set in the predetermined quality rules, the measured values in the abnormal feature set are compared with the parameter values in the historical abnormal record set to obtain a similarity score. Using a preset similarity threshold, historical abnormal records with similarity scores higher than the preset similarity threshold are filtered from the historical abnormal record set to obtain a matching historical record subset; Extract the corresponding device adjustment schemes from the matched historical record subsets to obtain an initial set of candidate compensation schemes; Duplicate adjustment items for the same equipment parameter in the initial candidate compensation scheme set are merged to obtain a deduplicated and optimized candidate compensation scheme set. The set of candidate compensation schemes after deduplication and optimization is used as the matching result of abnormal features to obtain candidate compensation schemes for abnormal feature matching.
6. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 5, characterized in that, The candidate compensation schemes matching the abnormal features are compared and verified with historical compensation schemes to select the effective compensation schemes. The specific steps are as follows: Using the parameter type identifier and warning level of the candidate compensation scheme that matches the abnormal features as query conditions, the system retrieves historical records with the same abnormal features from the pre-stored adaptive strategy library, and obtains the equipment adjustment parameters and corresponding historical production control parameters from the retrieved historical records, so as to obtain the parameter values of the candidate compensation scheme that matches the abnormal features and the parameter values in the historical compensation scheme. The numerical difference between the parameter values of the candidate compensation schemes matching the abnormal features and the parameter values in the historical compensation schemes is calculated to obtain the parameter deviation value. The tolerance zone range is preset by pre-defined quality rules; based on the tolerance zone range, historical compensation schemes whose absolute values of parameter deviations fall within the tolerance zone range are selected to obtain a preliminary subset of matching schemes. Using the identification code corresponding to each historical compensation scheme in the preliminary matching scheme subset, the corresponding quality judgment records and early warning logs are retrieved to obtain effect verification data; Based on the effect verification data, the first indicator is obtained by statistically analyzing whether the production control parameters of the same identification code in subsequent processes return to the predetermined quality rule range after the equipment adjustment parameters in the candidate compensation scheme with anomaly feature matching are applied. Using the effectiveness verification data, we statistically analyze the records of collaborative early warning information associated with identity codes that are terminated in the subsequent push process to obtain the second indicator; by combining the first and second indicators and quantifying them, we obtain the effectiveness score of the solution. Pre-set validity thresholds based on historical production data; Candidate compensation schemes with abnormal feature matching whose scheme effectiveness scores are higher than the effectiveness threshold are selected to obtain a list of effective candidate schemes; each scheme in the list of effective candidate schemes is selected as a valid compensation scheme after verification.
7. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 6, characterized in that, The integrated production process data generates a full lifecycle quality archive for the covering film from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back, including: Upon obtaining the finished product, the production data, quality judgment records, early warning logs, and parameter adjustment records of all processes that the finished product has undergone are stored and archived according to the identification code to obtain a full life cycle quality file; Construct a product traceability chain, record bidirectional data in the product traceability chain, and determine the bidirectional traceability relationship between the data; When tracing the source, the identification code is scanned to retrieve the corresponding full life cycle quality file, and the process parameters are traced back by querying the full life cycle quality file.
8. The method for coordinated production and quality control of the cover film for new energy substrates according to claim 7, characterized in that, Upon obtaining the finished product, all production data, quality judgment records, early warning logs, and parameter adjustment records from all processes the finished product has undergone are stored and archived according to the identification code to obtain a full lifecycle quality file. The specific steps are as follows: When the production process ends, the data acquisition equipment generates a finished product completion signal; based on the finished product completion signal, using the identification code as the retrieval condition, combined with the production control parameters and quality judgment records, all process data corresponding to the target identification code are retrieved to obtain a preliminary data set; Based on the preliminary dataset, the production control parameters and corresponding quality judgment records are sorted according to the actual execution time sequence of each process in order to establish the time relationship between the data and obtain the time series data sequence. Based on time-series data sequences, coating speed, baking temperature, and wet film thickness are extracted from production data, environmental parameters, and material state parameters, respectively. Combining quality judgment results, early warning levels, and equipment control instructions, coating speed, baking temperature, and wet film thickness are classified and organized into six categories: production equipment parameters, environmental parameters and material state parameters, quality judgment results, early warning information, and adjustment records, to obtain a structured parameter dataset. Based on the structured parameter dataset, the categorized parameters are bound to the identification codes to establish a parameter-identification code correspondence and obtain the bound data packet. By using bound data packets, production data, quality judgment records, early warning logs, and parameter adjustment records are stored in the database, and an identification code index is established to obtain archived data; By using archived data, all bound data packets are aggregated to obtain a full lifecycle quality profile.
9. A collaborative production and quality control system for a cover film of a new energy substrate, characterized in that, The system applies the collaborative production and quality control method for cover film of new energy substrate as described in any one of claims 1 to 8, and the system includes: The parameter binding module is used to collect production control parameters in real time through the set data acquisition equipment, assign identification codes to production materials, and dynamically bind production control parameters with identification codes. Production control parameters include production equipment parameters, environmental parameters, and material status parameters. Production materials include raw materials, semi-finished rolls, and finished rolls. The process control module is used to compare production control parameters with predetermined quality rules, determine the quality status of the output of the process in real time, generate collaborative early warning information, and push the early warning information and associated identification code to the current process and all downstream processes simultaneously. The process adjustment module is used to call pre-stored adaptive adjustment strategies for the production equipment of the current process and downstream processes based on the category and level of collaborative early warning information, and adjust the production parameters of the current process. The production materials management module is used to integrate production process data and generate a full life cycle quality file for the covering film from raw materials to finished products. By scanning the identification code on the finished product, the process parameters from raw materials to finished products can be traced back. The production process data includes data bound to the production process, quality judgment results, and warning and adjustment records.
10. The collaborative production and quality control system for the cover film of new energy substrates according to claim 9, characterized in that, The process control module includes: The abnormal parameter identification unit is used to retrieve production control parameters, retrieve different predetermined quality rules according to different production control parameters, compare the parameters, and extract abnormal parameters that deviate from the normal range. The early warning classification unit is used to classify the current early warning into different levels according to the value of the abnormal parameter, and to generate a structured early warning information package based on the early warning level, abnormal parameter and corresponding identification code. The early warning level is divided into three levels: severe, moderate and mild. The early warning information push unit is used to push structured early warning information packages to the human-machine interface of the production equipment in the downstream process, and display the early warning workstation and identification code on the corresponding production equipment.
11. The collaborative production and quality control system for the cover film of new energy substrates according to claim 10, characterized in that, The process adjustment module includes: The control command generation unit is used to match the corresponding compensation scheme from the pre-stored adaptive strategy library according to the warning level and abnormal parameter type of the collaborative early warning information, and generate specific equipment control commands. The strategy adjustment unit is used to control the production equipment of the corresponding process based on the equipment control commands and execute the corresponding adjustment strategies. The adjustment feedback unit is used to monitor the quality data of the output of this process in real time after the adjustment strategy is implemented, and to use the adjusted production data as effect feedback, and to bind the effect feedback with the identification code of the batch of materials.