A risk assessment and management system for battery packaging process optimization

Abstract

This invention relates to the field of battery packaging technology and discloses a risk assessment and management system for battery packaging process optimization. The system includes a historical packaging data acquisition module, a historical data analysis module, a real-time data acquisition module, a risk assessment module, and a real-time management feedback module. It also includes a historical battery packaging fault data acquisition unit and a historical battery packaging fault maintenance data acquisition unit. The system calculates the deviation weight of each parameter based on a historical packaging database and the time and cost required for repair and adjustment of faults that occurred during the battery packaging process. It then combines this with each parameter occurring during the current battery packaging process and calculates the deviation value between each parameter and its corresponding standard range. A comprehensive calculation yields the current risk coefficient. When the current risk coefficient exceeds a risk threshold, a risk warning is issued, and the result is fed back to the staff, enabling accurate identification of risks during the battery packaging optimization process.

Description

Technical Field

[0001] This invention relates to the field of battery packaging technology, specifically to a risk assessment and management system for optimizing battery packaging processes. Background Technology

[0002] Packaging is one of the main processes in the production of soft-pack lithium-ion batteries. Its main functions are: 1) Punching the aluminum-plastic film to create a recess that can accommodate the core; 2) Cutting the aluminum-plastic film into pockets. For thinner cells, a single recess is used, while for thicker cells, double recesses are used. However, double recesses can cause excessive deformation on one side, exceeding the deformation limit of the aluminum-plastic film and leading to breakage. 3) After cutting, the unpunched side of the aluminum-plastic film is folded along the punched side. The core is placed inside the recess, and the folded aluminum-plastic film is then top-sealed and side-sealed to ensure tight adhesion. 4) After top and side sealing, a short-circuit test is performed to check for short circuits within the core and aluminum-plastic film. 5) Marking and scanning are used to label each cell and upload data to the MES system. Because battery packaging involves many production factors, risk assessment for optimizing the battery packaging process is quite challenging. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a risk assessment and management system for battery packaging process optimization, which has advantages such as accurately predicting risks after process optimization and solves the aforementioned technical problems.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a risk assessment and management system for optimizing battery packaging processes, comprising a historical packaging data acquisition module, a historical data analysis module, a real-time data acquisition module, a risk assessment module, and a real-time management feedback module; The historical packaging data acquisition module includes a historical battery packaging fault data acquisition unit and a historical battery packaging fault maintenance data acquisition unit. The historical battery packaging fault data acquisition unit is used to record the specific value of each parameter and the corresponding standard range when a fault occurs during the battery packaging process, so as to establish a historical packaging database. The historical battery packaging fault maintenance data acquisition unit is used to collect the time cost and maintenance cost required for repair and adjustment of faults that occur during the battery packaging process. The historical data analysis module calculates the deviation weight of each parameter based on the historical packaging database and the time and cost required for repair and adjustment of faults that occur during the battery packaging process. The real-time data acquisition module is used to collect every parameter that occurs during the current battery packaging process and calculate the deviation value between each parameter and its corresponding standard range. The risk assessment module calculates the current risk coefficient based on the deviation weight and the corresponding deviation value of each parameter. The real-time management feedback module determines whether management scheduling is required based on the current risk coefficient. If management scheduling is required, it reads the deviation value between each parameter and its corresponding standard interval to determine whether to execute the scheduling instruction.

[0005] As a preferred embodiment of the present invention, the specific expression for the value of each parameter during the historical battery packaging process that the historical battery packaging fault data acquisition unit acquires is as follows: in, Represents the historical parameter dataset, These represent the first stage in the historical production process. The average hot-pressing temperature at which the fault occurred, , No. The average hot-pressing temperature at which the fault occurred, , No. The average hot-pressing temperature at which this fault occurred These represent the first stage in the historical production process. The average heat sealing temperature at which the fault occurred, , No. The average heat sealing temperature at which the fault occurred, , No. The average heat sealing temperature at which this fault occurred. These represent the first stage in the historical production process. Average processing time of each failure , No. Average processing time of each failure , No. The average processing time for each failure These represent the first stage in the historical production process. The average processing pressure at which the fault occurred , No. The average processing pressure at which the fault occurred , No. The average processing pressure at which this fault occurred.

[0006] As a preferred embodiment of the present invention, the historical battery packaging fault maintenance data acquisition unit is used to collect the time cost and maintenance cost required for repair and adjustment of faults occurring during the battery packaging process, as expressed in the following specific expressions: in, This represents a fault repair dataset. These represent the first stage in the historical production process. The time cost of the second failure , No. The time cost of the second failure , No. The time cost of this failure These represent the first stage in the historical production process. Repair costs for this fault , No. Repair costs for this fault , No. The cost of repairing this fault.

[0007] As a preferred technical solution of the present invention, the first The time cost of this failure The specific calculation steps are as follows: Step A1: The timer starts counting from the point when the fault occurred, and at the [number]th [time point]... The timing will stop at the point when the fault repair is completed, and the recorded time will be used as the first... Time loss during the second failure ; Step A2: Obtain the total number of batteries packaged per unit time and the number of employees affected; Step A3: Based on the first step in step A1 Time loss during the second failure The calculation of the total number of batteries packaged per unit time and the number of affected employees in step A2 is as follows: The time cost of this failure The specific expression is as follows: in, Indicates the first The total amount of battery packaged per unit time during this fault. Indicates the first The number of employees affected at the location of the incident. Indicates the first The time loss of the second failure. Indicates the first The time cost of each failure.

[0008] As a preferred technical solution of the present invention, the first Repair costs for this fault The steps to obtain it are as follows: Step B1: Record the first... The cost of all replaced parts during the repair process for this fault ; Step B2: Obtain the total number of maintenance personnel, determine the hourly wage of each maintenance personnel, and sum them to obtain the total wages of the maintenance personnel. The specific expression is as follows: in, Indicates the first The first failure occurred The hourly wage for a maintenance worker Indicates to Sum the hourly wages of the maintenance workers. Indicates the first The time loss of the second failure. Indicates the first Wages of maintenance personnel at the time of the fault; Step B3: Based on steps B1 to B2, obtain the... Repair costs for this fault The specific calculation expression is as follows: in, Indicates the first The wages of the maintenance personnel at the time of the fault. This indicates the cost of all parts replaced during the repair process.

[0009] As a preferred embodiment of the present invention, the specific steps of the historical data analysis module in calculating the deviation weight corresponding to each parameter based on the historical packaging database and the time cost and maintenance cost required for repair and adjustment of faults that occur during the battery packaging process are as follows: Step C1: Based on the historical parameter dataset in the historical encapsulation database Get the If the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure of the fault occur within the corresponding standard range, record it as 0 if they are within the range and 1 if they are not. Store 0 or 1 as the corresponding judgment value and iterate through step C1. Second-rate; Step C2: Calculate the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. The specific expressions are as follows: in, Indicates the first The judgment value of the average hot-pressing temperature during the second failure. Indicates the first The judgment value of the average heat sealing temperature during the second failure. Indicates the first The judgment value of the average processing time of each failure. Indicates the first The judgment value of the average processing pressure during the occurrence of the fault. , , and These represent the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. Indicates support for the common good Sum the values. Indicates the first The time cost of this failure Indicates the first The cost of repairing this fault.

[0010] As a preferred embodiment of the present invention, the specific expression for each parameter that the real-time data acquisition module acquires during the current battery packaging process is as follows: in, , , , These represent the current average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. This represents the current dataset.

[0011] As a preferred embodiment of the present invention, the real-time data acquisition module calculates the deviation value between each parameter and its corresponding standard interval using the following specific expression: in, Indicates parameters The deviation value, Indicates parameters The standard range is obtained through historical encapsulation databases. and Indicates parameters The lower and upper limits of the standard interval, parameters Specifically: , , , .

[0012] As a preferred embodiment of the present invention, the risk assessment module calculates the current risk coefficient based on the deviation weight and the corresponding deviation value of each parameter. The specific expression is as follows: in, , , and These represent the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. , , and Distribution representation , , , The deviation value.

[0013] As a preferred embodiment of the present invention, the scheduling instruction specifically refers to, under the current risk coefficient When the risk threshold is exceeded, a risk warning is issued and the results are reported back to the staff.

[0014] Compared with existing technologies, this invention provides a risk assessment and management system for optimizing battery packaging processes, which has the following beneficial effects: This invention calculates the deviation weight of each parameter based on a historical packaging database and the time and cost of repair and adjustment required for faults that occur during the battery packaging process. It also combines each parameter that occurs during the current battery packaging process and calculates the deviation value between each parameter and its corresponding standard range. The comprehensive calculation yields the current risk coefficient. When the current risk coefficient exceeds the risk threshold, a risk warning is issued and the results are fed back to the staff. This allows for accurate identification and management of risks during the battery packaging optimization process. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1A risk assessment and management system for battery packaging process optimization includes a historical packaging data acquisition module, a historical data analysis module, a real-time data acquisition module, a risk assessment module, and a real-time management feedback module. The historical packaging data acquisition and analysis modules calculate the deviation weight of each parameter based on a historical packaging database and the time and cost of repairs and adjustments required for faults occurring during the battery packaging process. The real-time data acquisition module collects each parameter occurring during the current battery packaging process and calculates the deviation value between each parameter and its corresponding standard range. The risk assessment module comprehensively calculates the current risk coefficient. When the current risk coefficient exceeds a risk threshold, the real-time management feedback module issues a risk warning and provides feedback to staff, thereby accurately identifying and managing risks during the battery packaging optimization process. The historical battery packaging data acquisition module includes a historical battery packaging fault data acquisition unit and a historical battery packaging fault maintenance data acquisition unit. The historical battery packaging fault data acquisition unit records the specific values ​​and corresponding standard ranges of each parameter when a fault occurs during the battery packaging process, in order to establish a historical packaging database. The historical battery packaging fault maintenance data acquisition unit collects the time and cost required for repair and adjustment of faults that occur during the battery packaging process. The specific expressions for the specific values ​​of each parameter collected by the historical battery packaging fault data acquisition unit during the historical battery packaging fault processes are as follows: in, Represents the historical parameter dataset, These represent the first stage in the historical production process. The average hot-pressing temperature at which the fault occurred, , No. The average hot-pressing temperature at which the fault occurred, , No. The average hot-pressing temperature at which this fault occurred These represent the first stage in the historical production process. The average heat sealing temperature at which the fault occurred, , No. The average heat sealing temperature at which the fault occurred, , No. The average heat sealing temperature at which this fault occurred. These represent the first stage in the historical production process. Average processing time of each failure , No. Average processing time of each failure , No. The average processing time for each failure These represent the first stage in the historical production process. The average processing pressure at which the fault occurred , No. The average processing pressure at which the fault occurred , No. The average processing pressure during each fault, and the historical battery packaging fault maintenance data acquisition unit are used to collect the time cost and maintenance cost required for repair and adjustment of faults that occur during the battery packaging process. The specific expressions are as follows:

[0018] in, This represents a fault repair dataset. These represent the first stage in the historical production process. The time cost of the second failure , No. The time cost of the second failure , No. The time cost of the second failure, the first The time cost of this failure The specific calculation steps are as follows: Step A1: The timer starts counting from the point when the fault occurred, and at the [number]th [time point]... The timing will stop at the point when the fault repair is completed, and the recorded time will be used as the first... Time loss during the second failure ; Step A2: Obtain the total number of batteries packaged per unit time and the number of employees affected; Step A3: Based on the first step in step A1 Time loss during the second failure The calculation of the total number of batteries packaged per unit time and the number of affected employees in step A2 is as follows: The time cost of this failure The specific expression is as follows: in, Indicates the first The total amount of battery packaged per unit time during this fault. Indicates the first The number of employees affected at the location of the incident. Indicates the first The time loss of the second failure. Indicates the first The time cost of this failure These represent the first stage in the historical production process. Repair costs for this fault , No. Repair costs for this fault , No. The repair cost of the second failure, Repair costs for this fault The steps to obtain it are as follows: Step B1: Record the first... The cost of all replaced parts during the repair process for this fault ; Step B2: Obtain the total number of maintenance personnel, determine the hourly wage of each maintenance personnel, and sum them to obtain the total wages of the maintenance personnel. The specific expression is as follows: in, Indicates the first The first failure occurred The hourly wage for a maintenance worker Indicates to Sum the hourly wages of the maintenance workers. Indicates the first The time loss of the second failure. Indicates the first Wages of maintenance personnel at the time of the fault; Step B3: Based on steps B1 to B2, obtain the... Repair costs for this fault The specific calculation expression is as follows: in, Indicates the first The wages of the maintenance personnel at the time of the fault. This indicates the cost of all replaced parts during the repair process; The historical data analysis module calculates the deviation weight for each parameter based on the historical packaging database and the time and cost required for repair and adjustment of faults that occurred during the battery packaging process. The specific steps are as follows: Step C1: Based on the historical parameter dataset in the historical encapsulation database Get the If the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure of the fault occur within the corresponding standard range, record it as 0 if they are within the range and 1 if they are not. Store 0 or 1 as the corresponding judgment value and iterate through step C1. Second-rate; Step C2: Calculate the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. The specific expressions are as follows: in, Indicates the first The judgment value of the average hot-pressing temperature during the second failure. Indicates the first The judgment value of the average heat sealing temperature during the second failure. Indicates the first The judgment value of the average processing time of each failure. Indicates the first The judgment value of the average processing pressure during the occurrence of the fault. , , and These represent the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. Indicates support for the common good Sum the values. Indicates the first The time cost of this failure Indicates the first By calculating the repair costs of each failure and assigning a weight to each process parameter (such as hot-pressing temperature, heat-sealing temperature, processing time, and processing pressure), companies can identify which parameters have the greatest impact on product quality. For example, analyzing historical data may reveal that hot-pressing temperature has a greater impact on battery packaging quality, while heat-sealing temperature may contribute more to the sealing effect. Clearly defining these weights allows companies to focus more resources and effort on optimizing the most influential parameters, avoiding resource waste. During production, if certain process parameters have significant weights, precise control of these parameters becomes even more crucial. Weight values ​​calculated from historical data can serve as a basis for adjusting process parameters, helping production personnel pay closer attention to key parameters during operation, enabling precise control, optimizing process flows, and ultimately improving overall product quality. The real-time data acquisition module is used to collect every parameter that occurs during the current battery packaging process and calculate the deviation value between each parameter and its corresponding standard range. The specific expression for each parameter that occurs during the current battery packaging process collected by the real-time data acquisition module is as follows: in, , , , These represent the current average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. Representing the current dataset, the real-time data acquisition module calculates the deviation between each parameter and its corresponding standard interval using the following specific expression:

[0019] in, Indicates parameters The deviation value, Indicates parameters The standard range is obtained through historical encapsulation databases. and Indicates parameters The lower and upper limits of the standard interval, parameters Specifically: , , , The real-time data acquisition module can measure each key process parameter (such as hot-pressing temperature, heat-sealing temperature, processing pressure, and processing time) and calculate its deviation from the standard range, helping operators to immediately understand whether the process parameters exceed the preset normal range. This real-time monitoring can help companies ensure that every parameter in the production process is always within the optimal control range, thereby reducing quality problems caused by parameter fluctuations. The risk assessment module calculates the current risk coefficient by combining the deviation weight and the corresponding deviation value for each parameter. The specific expression is as follows: in, , , and These represent the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. , , and Distribution representation , , , The deviation value; The real-time management feedback module determines whether management scheduling is needed based on the current risk coefficient. If management scheduling is needed, it reads the deviation value between each parameter and its corresponding standard interval to determine whether to execute the scheduling instruction. The scheduling instruction is specifically: based on the current risk coefficient... When the risk threshold is exceeded, a risk warning is issued, and the results are fed back to the staff. For example, when optimizing production parameters, various parameters can be adjusted to meet the current risk coefficient. The calculation outputs the actual risk. In battery packaging technology, when the risk coefficient exceeds a threshold, a rapid and accurate risk warning and feedback mechanism is crucial. Through a multi-step approach involving real-time monitoring, early warning information transmission, staff response, data recording and tracking, result feedback, and closed-loop management, risks in the production process can be effectively reduced, ensuring the quality and safety of battery packaging. Simultaneously, continuous optimization of the early warning system and feedback mechanism can improve production efficiency and avoid potential quality problems and safety hazards. Example

[0020] The specific data recorded in this embodiment is as follows: The time costs for the four failures are as follows: , , , ; The costs of the four repairs were as follows: , , , , The average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure correspond to the following ranges: 130-160, 150-170, 15-30, and 1.7-3.0, respectively. Calculations are performed under these conditions. , , , At this point, the current dataset obtained after the current process adjustment is collected or input. , , , and , When the value is greater than 0.265, a risk warning is issued, and the results are fed back to the staff. This allows for accurate identification and management of the risks during the battery packaging optimization process.

[0021] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A risk assessment and management system for optimizing battery packaging processes, characterized in that: It includes a historical encapsulated data acquisition module, a historical data analysis module, a real-time data acquisition module, a risk assessment module, and a real-time management feedback module; The historical packaging data acquisition module includes a historical battery packaging fault data acquisition unit and a historical battery packaging fault maintenance data acquisition unit. The historical battery packaging fault data acquisition unit is used to record the specific value of each parameter and the corresponding standard range when a fault occurs during the battery packaging process, so as to establish a historical packaging database. The historical battery packaging fault maintenance data acquisition unit is used to collect the time cost and maintenance cost required for repair and adjustment of faults that occur during the battery packaging process. The historical data analysis module calculates the deviation weight of each parameter based on the historical packaging database and the time and cost required for repair and adjustment of faults that occur during the battery packaging process. The real-time data acquisition module is used to collect every parameter that occurs during the current battery packaging process and calculate the deviation value between each parameter and its corresponding standard range. The risk assessment module calculates the current risk coefficient based on the deviation weight and the corresponding deviation value of each parameter. The real-time management feedback module determines whether management scheduling is required based on the current risk coefficient. If management scheduling is required, it reads the deviation value between each parameter and its corresponding standard interval to determine whether to execute the scheduling instruction.

2. The risk assessment and management system for battery packaging process optimization according to claim 1, characterized in that: The specific expression for the value of each parameter during the historical battery packaging fault data acquisition unit is as follows: ， in, Represents the historical parameter dataset, These represent the first stage of the historical production process. The average hot-pressing temperature at which the fault occurred, , No. The average hot-pressing temperature at which the fault occurred, , No. The average hot-pressing temperature at which this fault occurred These represent the first stage of the historical production process. The average heat sealing temperature at which the fault occurred , No. The average heat sealing temperature at which the fault occurred, , No. The average heat sealing temperature at which this fault occurred. These represent the first stage in the historical production process. Average processing time of each failure , No. Average processing time of each failure , No. The average processing time for each failure These represent the first stage in the historical production process. The average processing pressure at which the fault occurred , No. The average processing pressure at which the fault occurred , No. The average processing pressure at which this fault occurred.

3. The risk assessment and management system for battery packaging process optimization according to claim 2, characterized in that: The historical battery packaging fault maintenance data acquisition unit is used to collect the time cost and maintenance cost required for repair and adjustment of faults that occur during the battery packaging process. The specific expressions are as follows: ， in, This represents a fault repair dataset. These represent the first stage in the historical production process. The time cost of the second failure , No. The time cost of the second failure , No. The time cost of this failure These represent the first stage in the historical production process. Repair costs for this fault , No. Repair costs for this fault , No. The cost of repairing this fault.

4. A risk assessment and management system for battery packaging process optimization according to claim 3, characterized in that: The first The time cost of this failure The specific calculation steps are as follows: Step A1: The timer starts counting from the point when the fault occurred, and at the [number]th [time point]... The timing will stop at the point when the fault repair is completed, and the recorded time will be used as the first... Time loss during the second failure ; Step A2: Obtain the total number of batteries packaged per unit time and the number of employees affected; Step A3: Based on the first step in step A1 Time loss during the second failure The calculation of the total number of batteries packaged per unit time and the number of affected employees in step A2 is as follows: The time cost of this failure The specific expression is as follows: ， in, Indicates the first The total amount of battery packaged per unit time during this fault. Indicates the first The number of employees affected at the location of the incident. Indicates the first The time loss of the second failure. Indicates the first The time cost of each failure.

5. A risk assessment and management system for battery packaging process optimization according to claim 4, characterized in that: The first Repair costs for this fault The steps to obtain it are as follows: Step B1: Record the first... The cost of all replaced parts during the repair process for this fault ; Step B2: Obtain the total number of maintenance personnel, determine the hourly wage of each maintenance personnel, and sum them to obtain the total wages of the maintenance personnel. The specific expression is as follows: ， in, Indicates the first The first failure occurred The hourly wage for a maintenance worker Indicates to Sum the hourly wages of the maintenance workers. Indicates the first The time loss of the second failure. Indicates the first Wages of maintenance personnel at the time of the fault; Step B3: Based on steps B1 to B2, obtain the... Repair costs for this fault The specific calculation expression is as follows: ， in, Indicates the first The wages of the maintenance personnel at the time of the fault. This indicates the cost of all parts replaced during the repair process.

6. A risk assessment and management system for battery packaging process optimization according to claim 5, characterized in that: The specific steps for the historical data analysis module to calculate the deviation weight corresponding to each parameter based on the historical packaging database and the time and cost required for repair and adjustment of faults that occurred during the battery packaging process are as follows: Step C1: Based on the historical parameter dataset in the historical encapsulation database Get the If the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure of the fault occur within the corresponding standard range, record it as 0 if they are within the range and 1 if they are not. Store 0 or 1 as the corresponding judgment value and iterate through step C1. Second-rate; Step C2: Calculate the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. The specific expressions are as follows: ， ， ， ， in, Indicates the first The judgment value of the average hot-pressing temperature during the second failure. Indicates the first The judgment value of the average heat sealing temperature during the second failure. Indicates the first The judgment value of the average processing time of each failure. Indicates the first The judgment value of the average processing pressure during the occurrence of the fault. , , and These represent the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. Indicates support for the common good Sum the values. Indicates the first The time cost of this failure Indicates the first The cost of repairing this fault.

7. A risk assessment and management system for battery packaging process optimization according to claim 6, characterized in that: The specific expression for each parameter that appears during the current battery packaging process is as follows: ， in, , , , These represent the current average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. This represents the current dataset.

8. A risk assessment and management system for battery packaging process optimization according to claim 7, characterized in that: The real-time data acquisition module calculates the deviation value between each parameter and its corresponding standard interval using the following specific expression: ， in, Indicates parameters The deviation value, Indicates parameters The standard range is obtained through historical encapsulation databases. and Indicates parameters The lower and upper limits of the standard interval, parameters Specifically: , , , .

9. A risk assessment and management system for battery packaging process optimization according to claim 8, characterized in that: The risk assessment module calculates the current risk coefficient based on the deviation weight and deviation value of each parameter. The specific expression is as follows: ， in, , , and These represent the weights corresponding to the average hot-pressing temperature, average heat-sealing temperature, average processing time, and average processing pressure, respectively. , , and Distribution representation , , , The deviation value.

10. A risk assessment and management system for battery packaging process optimization according to claim 9, characterized in that: The scheduling instruction specifically refers to, at the current risk level When the risk threshold is exceeded, a risk warning is issued and the results are reported back to the staff.

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