MES Optimization Method and System for Lithium Battery Cover Plate Assembly and Welding Line

Abstract

This invention discloses a MES optimization method and system for a lithium battery cover plate assembly and welding line. The method includes: determining process parameters and quality standards and inspection indicators for lithium battery cover plate assembly and welding; constructing a quality assessment model based on the quality standards and inspection indicators; collecting physical state description parameters and finished product images from each production stage of the lithium battery cover plate assembly; determining production state parameters and equipment operating parameters based on the physical state description parameters and finished product images, and performing visual interaction; evaluating the physical state description parameters and finished product images from each stage using the quality assessment model to determine the finished product quality; tracing the source of unqualified finished products based on the finished product quality; and intelligently controlling and monitoring the assembly and welding of qualified finished products. This allows for online quality assessment, ensuring the stability and reliability of the production process and facilitating monitoring and management by operators. It also allows for the traceability of each product, ensuring product traceability and improving quality management levels.

Description

Technical Field

[0001] This invention relates to the field of manufacturing system optimization technology, and in particular to a method and system for optimizing the MES of a lithium battery cover plate assembly and welding line. Background Technology

[0002] Currently, with the rapid development of lithium battery technology, lithium batteries are increasingly widely used in electric vehicles, energy storage devices, and other fields. The assembly and welding of lithium battery cover plates is a crucial step in the production process, directly affecting battery performance and safety. While existing MES systems play an important role in production management, most have failed to optimize for the lithium battery cover plate assembly and welding process, leading to errors and data loss. Furthermore, these systems can only collect data and cannot perform targeted quality assessments and traceability, reducing their practicality and reliability. Summary of the Invention

[0003] To address the aforementioned problems, this invention provides a method and system for optimizing the MES (Manufacturing Execution System) of a lithium battery cover assembly and welding line. This addresses the issues mentioned in the background art, such as the failure to optimize the lithium battery cover assembly and welding process, resulting in errors and loss of process data. Furthermore, the system can only collect data and cannot perform targeted quality assessments and traceability, thus reducing its practicality and reliability.

[0004] A method for optimizing the MES (Manufacturing Execution System) of a lithium battery cover plate assembly and welding line includes the following steps:

[0005] Determine the process parameters for assembling and welding lithium battery cover plates, determine the quality standards and inspection indicators based on the process parameters, and construct a quality assessment model based on the quality standards and inspection indicators;

[0006] Collect physical state description parameters and finished product images of lithium battery cover plates at each production stage, determine production status parameters and equipment operation parameters based on physical state description parameters and finished product images, and perform visual interaction.

[0007] The quality of the finished product is determined by evaluating the physical state description parameters and finished product images at each stage using a quality assessment model.

[0008] Based on the quality of the finished product, trace the source of unqualified finished products, and implement intelligent control and monitoring for the assembly and welding of qualified finished products.

[0009] Preferably, the process parameters for determining the assembly and welding of the lithium battery cover plate, the quality standards and inspection indicators determined based on the process parameters, and the quality assessment model constructed based on the quality standards and inspection indicators include:

[0010] Obtain the process flow description information for the assembly and welding of lithium battery cover plates, and extract the process parameters for the assembly and welding of lithium battery cover plates based on the process flow description information.

[0011] Based on the process parameters, determine multiple work stages, as well as the operation parameters, material parameters, working environment and equipment parameters for each work stage;

[0012] The work standard requirements and working condition requirements for each work stage are determined based on the operating parameters, material parameters, working environment and equipment parameters for each work stage.

[0013] Based on the work standard requirements and working condition requirements, quality standards and inspection indicators are determined, the mapping relationship between quality standards and inspection indicators is established, and a quality assessment model for lithium battery cover plate assembly and welding is constructed based on the mapping relationship.

[0014] Preferably, the step of collecting physical state description parameters and finished product images of each production stage of the lithium battery cover plate, determining production state parameters and equipment operating parameters based on the physical state description parameters and finished product images, and performing visual interaction includes:

[0015] Determine the site environmental parameters for each production stage, determine the data collection method based on the site environmental parameters, and collect the physical state description parameters and finished product images of each production stage of the lithium battery cover through the data collection method;

[0016] The specifications, texture, and shape parameters of the lithium battery cover body are determined based on the actual product status description parameters and finished product images at each production stage.

[0017] The production status parameters are determined based on the specifications, texture parameters, and shape parameters of the lithium battery cover body, while the operating status parameters of each working device are collected.

[0018] Production status parameters and the operating status parameters of each working device are uploaded to the visualization platform for interactive visualization.

[0019] Preferably, the step of evaluating the physical state description parameters and finished product images at each stage using a quality assessment model to determine the quality of the finished product includes:

[0020] Obtain user order requirements, determine the design features of the lithium battery cover based on the order requirements, and input the design features into the quality assessment model to determine the assessment features of superior, good, and defective products.

[0021] The quality assessment model is used to perform feature matching between the physical state description parameters and finished product images at each stage to obtain the matching results.

[0022] The quality characteristics of each lithium battery cover are determined based on the matching results, and the quality attributes of each lithium battery cover are determined based on the quality characteristics.

[0023] The quality of the finished product is determined based on the quality attributes of each lithium battery cover.

[0024] Preferably, the step of tracing unqualified finished products based on finished product quality and intelligently controlling and monitoring the assembly and welding of qualified finished products includes:

[0025] Based on the quality of finished products, unqualified finished products are screened out, and the target work process for unqualified finished products and the record storage data within the target work process are determined.

[0026] Based on the recorded and stored data, the source of unqualified products is traced, the characteristic information of qualified finished products is obtained, and the matching assembly parameters and welding parameters are selected based on the characteristic information;

[0027] The assembly and welding tasks are generated based on the assembly and welding parameters and then written into the intelligent welding robot for intelligent control.

[0028] Identify monitoring risk indicators during the assembly and welding process and monitor and issue early warnings through appropriate means.

[0029] A MES optimization system for a lithium battery cover assembly and welding line, the system comprising:

[0030] The module is used to determine the process parameters for assembling and welding lithium battery cover plates, determine the quality standards and inspection indicators based on the process parameters, and build a quality assessment model based on the quality standards and inspection indicators.

[0031] The determination module is used to collect physical status description parameters and finished product images of lithium battery cover plates at each production stage, and to determine production status parameters and equipment operation parameters based on the physical status description parameters and finished product images, and to perform visual interaction.

[0032] The evaluation module is used to evaluate the physical state description parameters and finished product images at each stage using a quality evaluation model to determine the quality of the finished product.

[0033] The control and monitoring module is used to trace the source of unqualified finished products based on the quality of the finished products, and to intelligently control and monitor the assembly and welding of qualified finished products.

[0034] Preferably, the building module includes:

[0035] The extraction submodule is used to obtain the process flow description information of lithium battery cover plate assembly and welding, and extract the process parameters of lithium battery cover plate assembly and welding based on the process flow description information.

[0036] The first determination submodule is used to determine multiple work stages, as well as the operation parameters, material parameters, working environment and equipment parameters of each work stage, based on process parameters.

[0037] The second determination submodule is used to determine the work standard requirements and work condition requirements for each work stage based on the operation parameters, material parameters, working environment and equipment parameters of each work stage.

[0038] A submodule is constructed to determine quality standards and inspection indicators based on work standard requirements and working condition requirements, to determine the mapping relationship between quality standards and inspection indicators, and to construct a quality assessment model for lithium battery cover plate assembly and welding based on the mapping relationship.

[0039] Preferably, the determining module includes:

[0040] The data acquisition submodule is used to determine the site environment parameters of each production stage, determine the data acquisition method based on the site environment parameters, and collect the physical status description parameters and finished product images of each production stage of the lithium battery cover through the data acquisition method.

[0041] The third determination submodule is used to determine the specifications, texture parameters, and shape parameters of the lithium battery cover body based on the physical state description parameters and finished product images of each production stage.

[0042] The fourth determination submodule is used to determine the production status parameters based on the specifications, texture parameters, and shape parameters of the lithium battery cover body, while also collecting the operating status parameters of each working device.

[0043] The upload submodule is used to upload production status parameters and the operating status parameters of each working device to the visualization platform for visual interaction.

[0044] Preferably, the evaluation module includes:

[0045] The fifth submodule is used to obtain the user's order requirements, determine the design feature information of the lithium battery cover based on the order requirements, and input the design feature information into the quality assessment model to determine the assessment features of superior, good and defective products.

[0046] The matching submodule is used to perform feature matching between the physical status description parameters and finished product images at each stage using the quality assessment model, and obtain the matching results.

[0047] The sixth determination submodule is used to determine the quality characteristics of each lithium battery cover plate based on the matching results, and to determine the quality attributes of each lithium battery cover plate based on the quality characteristics.

[0048] The seventh determination submodule is used to determine the quality of the finished product based on the quality attributes of each lithium battery cover.

[0049] Preferably, the control and monitoring module includes:

[0050] The eighth submodule is used to screen out unqualified finished products based on the quality of finished products, determine the target work process for unqualified finished products, and the record storage data within the target work process;

[0051] The selection submodule is used to trace the source of unqualified products based on the recorded and stored data, obtain the characteristic information of qualified finished products, and select matching assembly parameters and welding parameters based on the characteristic information.

[0052] The control submodule is used to generate assembly and welding tasks based on assembly and welding parameters and write the assembly and welding tasks into the intelligent welding robot for intelligent control.

[0053] The monitoring and early warning submodule is used to identify monitoring risk indicators during the assembly and welding process and to monitor and issue early warnings in appropriate ways.

[0054] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0055] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0056] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0057] Figure 1 A flowchart illustrating the MES optimization method for a lithium battery cover plate assembly and welding line provided by this invention.

[0058] Figure 2 This is another flowchart of the MES optimization method for a lithium battery cover plate assembly and welding line provided by the present invention.

[0059] Figure 3 This is a schematic diagram of the structure of a lithium battery cover plate assembly and welding line MES optimization system provided by the present invention;

[0060] Figure 4 This is a schematic diagram of the structure of a building module in a MES optimization system for a lithium battery cover plate assembly and welding line provided by the present invention. Detailed Implementation

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0062] Currently, with the rapid development of lithium battery technology, lithium batteries are increasingly widely used in electric vehicles, energy storage devices, and other fields. The assembly and welding of lithium battery cover plates is a crucial step in the production process, directly affecting battery performance and safety. While existing MES systems play an important role in production management, most have failed to optimize the lithium battery cover plate assembly and welding process, leading to errors and data loss. Furthermore, they can only collect data and cannot perform targeted quality assessments and traceability, reducing practicality and reliability. To address these issues, this embodiment discloses an MES optimization method for the entire lithium battery cover plate assembly and welding line.

[0063] A method for optimizing the MES of a lithium battery cover plate assembly and welding line, such as Figure 1 As shown, it includes the following steps:

[0064] Step S101: Determine the process parameters for assembling and welding the lithium battery cover plate, determine the quality standards and inspection indicators based on the process parameters, and construct a quality assessment model based on the quality standards and inspection indicators.

[0065] Step S102: Collect the actual product status description parameters and finished product images of each production stage of the lithium battery cover plate, determine the production status parameters and equipment operation parameters based on the actual product status description parameters and finished product images, and perform visual interaction.

[0066] Step S103: Use a quality assessment model to evaluate the physical state description parameters and finished product images at each stage to determine the quality of the finished product;

[0067] Step S104: Trace the source of unqualified finished products based on the quality of the finished products, and implement intelligent control and monitoring for the assembly and welding of qualified finished products.

[0068] In this embodiment, the quality standard is expressed as the evaluation standard for the quality of the lithium battery cover plate;

[0069] In this embodiment, the inspection index refers to the reference index used to evaluate the quality of the lithium battery cover, such as: material, shape, structure, welding area, etc.

[0070] In this embodiment, the quality assessment model is represented as a quality assessment model for all finished products produced during the entire processing of the lithium battery cover plate, including: the cover plate body, the uncolored cover plate, and the assembled and welded cover plate.

[0071] In this embodiment, the physical state description parameters are represented by the structure, shape, hardness, and density of the standard physical products at each production stage.

[0072] The working principle of the above technical solution is as follows: Determine the process parameters for assembling and welding lithium battery cover plates; determine quality standards and inspection indicators based on the process parameters; construct a quality assessment model based on the quality standards and inspection indicators; collect physical state description parameters and finished product images from each production stage of the lithium battery cover plate; determine production state parameters and equipment operating parameters based on the physical state description parameters and finished product images, and perform visual interaction; evaluate the physical state description parameters and finished product images from each stage using the quality assessment model to determine the quality of the finished product; trace the source of unqualified finished products based on the finished product quality; and intelligently control and monitor the assembly and welding of qualified finished products.

[0073] The beneficial effects of the above technical solution are as follows: By constructing a quality assessment model to evaluate the quality of finished products based on finished product images and physical status description parameters at each production stage, online quality assessment can be achieved, ensuring the stability and reliability of the production process. Furthermore, by determining production status parameters and equipment operating parameters based on physical status description parameters and finished product images and providing visual interaction, a user-friendly interface can be provided, displaying production status, equipment operation, and quality data in real time. This facilitates monitoring and management by operators, avoids data errors and loss, and improves stability. Additionally, images of each product that is not yet ready to use can be traced, ensuring product traceability and improving quality management. This solves the problems mentioned in existing technologies, such as the failure to optimize the lithium battery cover assembly and welding process, leading to process data errors and loss, and the inability to perform targeted quality assessment and traceability work, thus reducing practicality and reliability.

[0074] In one embodiment, such as Figure 2 As shown, the process parameters for determining the assembly and welding of the lithium battery cover plate, the quality standards and inspection indicators determined based on the process parameters, and the quality assessment model constructed based on the quality standards and inspection indicators include:

[0075] Step S201: Obtain the process flow description information of lithium battery cover plate assembly and welding, and extract the process parameters of lithium battery cover plate assembly and welding based on the process flow description information.

[0076] Step S202: Determine multiple working stages and the operating parameters, material parameters, working environment and equipment parameters for each working stage based on the process parameters;

[0077] Step S203: Determine the work standard requirements and working condition requirements for each work stage based on the operation parameters, material parameters, working environment and equipment parameters for each work stage;

[0078] Step S204: Determine the quality standards and inspection indicators according to the work standard requirements and work condition requirements, determine the mapping relationship between the quality standards and inspection indicators, and construct a quality assessment model for lithium battery cover plate assembly and welding based on the mapping relationship.

[0079] The beneficial effects of the above technical solution are as follows: by determining the work standard requirements and working condition requirements for each work stage based on the process parameters of lithium battery cover plate assembly and welding, the quality standards and inspection indicators are determined, and a quality assessment model for lithium battery cover plate assembly and welding is constructed. This enables accurate assessment of welding quality, ensures the quality of lithium battery cover plate assembly and welding, and improves assessment efficiency.

[0080] In one embodiment, the step of collecting physical state description parameters and finished product images of each production stage of the lithium battery cover plate, determining production state parameters and equipment operating parameters based on the physical state description parameters and finished product images, and performing visual interaction includes:

[0081] Determine the site environmental parameters for each production stage, determine the data collection method based on the site environmental parameters, and collect the physical state description parameters and finished product images of each production stage of the lithium battery cover through the data collection method;

[0082] The specifications, texture, and shape parameters of the lithium battery cover body are determined based on the actual product status description parameters and finished product images at each production stage.

[0083] The production status parameters are determined based on the specifications, texture parameters, and shape parameters of the lithium battery cover body, while the operating status parameters of each working device are collected.

[0084] Production status parameters and the operating status parameters of each working device are uploaded to the visualization platform for interactive visualization.

[0085] The beneficial effects of the above technical solution are as follows: determining the data acquisition method based on the site environment parameters of each production stage can improve the quality and accuracy of the data and avoid inaccurate parameter acquisition caused by the data acquisition method. At the same time, determining the production status parameters and operating status parameters based on the specifications, texture parameters and shape parameters of the lithium battery cover body can promptly detect potential faults in the production equipment and resolve them, ensuring the normal operation of the working equipment and improving production efficiency.

[0086] In one embodiment, the step of evaluating the physical state description parameters and finished product images at each stage using a quality assessment model to determine the quality of the finished product includes:

[0087] Obtain user order requirements, determine the design features of the lithium battery cover based on the order requirements, and input the design features into the quality assessment model to determine the assessment features of superior, good, and defective products.

[0088] The quality assessment model is used to perform feature matching between the physical state description parameters and finished product images at each stage to obtain the matching results.

[0089] The quality characteristics of each lithium battery cover are determined based on the matching results, and the quality attributes of each lithium battery cover are determined based on the quality characteristics.

[0090] The quality of the finished product is determined based on the quality attributes of each lithium battery cover.

[0091] The beneficial effects of the above technical solution are as follows: by determining the design feature information of the lithium battery cover according to the user's order requirements and performing feature matching, the quality attributes and finished product quality of each lithium battery cover can be determined. By accurately identifying and classifying the quality characteristics of each lithium battery cover, the generation of defective products can be effectively reduced, and the product qualification rate and product quality can be improved.

[0092] In one embodiment, the step of tracing unqualified finished products based on finished product quality and intelligently controlling and monitoring the assembly and welding of qualified finished products includes:

[0093] Based on the quality of finished products, unqualified finished products are screened out, and the target work process for unqualified finished products and the record storage data within the target work process are determined.

[0094] Based on the recorded and stored data, the source of unqualified products is traced, the characteristic information of qualified finished products is obtained, and the matching assembly parameters and welding parameters are selected based on the characteristic information;

[0095] The assembly and welding tasks are generated based on the assembly and welding parameters and then written into the intelligent welding robot for intelligent control.

[0096] Identify monitoring risk indicators during the assembly and welding process and monitor and issue early warnings through appropriate means.

[0097] The beneficial effects of the above technical solution are as follows: by tracing the source of unqualified products based on the target work process and the recorded data stored in the target work process, selecting matching assembly parameters and welding parameters and writing them into the intelligent welding robot for intelligent control, welding quality and welding efficiency can be improved. At the same time, monitoring and early warning of risk indicators in the welding process can improve the safety and reliability of the welding process.

[0098] In this embodiment, the intelligent control process for the intelligent welding robot also includes:

[0099] The welding length and weld position information are determined based on the assembly and welding task, and the first motion trajectory of the intelligent welding robot welding arm is determined based on the welding length and weld position information.

[0100] The second motion trajectory of the welding torch on the intelligent welding robot is determined based on the motion trajectory, and visual data of the horizontal line between the center of gravity of the welding torch and the center of gravity of the welding arm is collected in the four directions of up, down, left and right.

[0101] The positional deviation between the welding torch and the welding arm is determined based on visual data of the same horizontal line. A compensation matrix for the movement of the welding torch with the welding arm is generated based on the positional deviation and the relative motion relationship between the drought and the welding arm.

[0102] The robot arm posture parameters for maintaining the balance point between the welding torch and the welding arm are determined based on the compensation matrix and weld position information.

[0103] Determine the relevant joints for maintaining the robot arm's posture parameters and the rotation adjustment parameters for each joint;

[0104] The collaborative control parameters of the welding arm and welding torch of the intelligent welding robot are determined based on the rotation axis adjustment parameters, and multiple action commands are generated based on the collaborative control parameters.

[0105] Acquire the timing information of each action command, and determine the timing change value of the monitoring base coordinates for the intelligent welding robot to execute each action command based on the timing information;

[0106] The consistency of the welding actions of the intelligent welding robot in the intelligent welding process is evaluated based on the time-series changes of the monitored base coordinates.

[0107] The intelligent welding robot issues a welding offset warning when it responds to a non-matching action.

[0108] The beneficial effects of the above technical solution are as follows: by determining the collaborative control parameters of the welding arm and welding torch of the intelligent welding robot, correction can be made based on the difference in synchronization attributes between the welding arm and welding torch of the intelligent welding robot to ensure the collaborative welding performance of the two, thereby improving welding efficiency and stability. Furthermore, by monitoring the action commands, the accuracy and reliability of the intelligent welding robot's execution can be determined more intuitively and accurately, thereby improving the overall reliability of the welding process control and ensuring product quality.

[0109] In one embodiment, this embodiment also discloses a MES optimization system for a lithium battery cover plate assembly and welding line, such as... Figure 3 As shown, the system includes:

[0110] Module 301 is used to determine the process parameters for assembling and welding lithium battery cover plates, determine the quality standards and inspection indicators based on the process parameters, and build a quality assessment model based on the quality standards and inspection indicators.

[0111] The module 302 is used to collect the actual product status description parameters and finished product images of each production stage of lithium battery cover plates, and to determine the production status parameters and equipment operation parameters based on the actual product status description parameters and finished product images, and to perform visual interaction.

[0112] Evaluation module 303 is used to evaluate the physical state description parameters and finished product images at each stage through a quality evaluation model to determine the quality of the finished product.

[0113] The control and monitoring module 304 is used to trace the source of unqualified finished products based on the quality of finished products, and to intelligently control and monitor the assembly and welding of qualified finished products.

[0114] The working principle and beneficial effects of the above technical solution have been explained in the method embodiments, and will not be repeated here.

[0115] In one embodiment, such as Figure 4 As shown, the construction module 301 includes:

[0116] Extraction submodule 3011 is used to obtain the process flow description information of lithium battery cover plate assembly and welding, and extract the process parameters of lithium battery cover plate assembly and welding based on the process flow description information.

[0117] The first determining submodule 3012 is used to determine multiple working stages and the operating parameters, material parameters, working environment and equipment parameters of each working stage based on process parameters.

[0118] The second determining submodule 3013 is used to determine the working standard requirements and working condition requirements for each working stage based on the operating parameters and material parameters of each working stage, as well as the working environment and equipment parameters.

[0119] Submodule 3014 is constructed to determine quality standards and inspection indicators based on work standard requirements and work condition requirements, determine the mapping relationship between quality standards and inspection indicators, and construct a quality assessment model for lithium battery cover plate assembly and welding based on the mapping relationship.

[0120] In one embodiment, the determining module includes:

[0121] The data acquisition submodule is used to determine the site environment parameters of each production stage, determine the data acquisition method based on the site environment parameters, and collect the physical status description parameters and finished product images of each production stage of the lithium battery cover through the data acquisition method.

[0122] The third determination submodule is used to determine the specifications, texture parameters, and shape parameters of the lithium battery cover body based on the physical state description parameters and finished product images of each production stage.

[0123] The fourth determination submodule is used to determine the production status parameters based on the specifications, texture parameters, and shape parameters of the lithium battery cover body, while also collecting the operating status parameters of each working device.

[0124] The upload submodule is used to upload production status parameters and the operating status parameters of each working device to the visualization platform for visual interaction.

[0125] In one embodiment, the evaluation module includes:

[0126] The fifth submodule is used to obtain the user's order requirements, determine the design feature information of the lithium battery cover based on the order requirements, and input the design feature information into the quality assessment model to determine the assessment features of superior, good and defective products.

[0127] The matching submodule is used to perform feature matching between the physical status description parameters and finished product images at each stage using the quality assessment model, and obtain the matching results.

[0128] The sixth determination submodule is used to determine the quality characteristics of each lithium battery cover plate based on the matching results, and to determine the quality attributes of each lithium battery cover plate based on the quality characteristics.

[0129] The seventh determination submodule is used to determine the quality of the finished product based on the quality attributes of each lithium battery cover.

[0130] In one embodiment, the control and monitoring module includes:

[0131] The eighth submodule is used to screen out unqualified finished products based on the quality of finished products, determine the target work process for unqualified finished products, and the record storage data within the target work process;

[0132] The selection submodule is used to trace the source of unqualified products based on the recorded and stored data, obtain the characteristic information of qualified finished products, and select matching assembly parameters and welding parameters based on the characteristic information.

[0133] The control submodule is used to generate assembly and welding tasks based on assembly and welding parameters and write the assembly and welding tasks into the intelligent welding robot for intelligent control.

[0134] The monitoring and early warning submodule is used to identify monitoring risk indicators during the assembly and welding process and to monitor and issue early warnings in appropriate ways.

[0135] Those skilled in the art should understand that the "first" and "second" in this invention simply refer to different application stages.

[0136] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0137] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for optimizing the MES (Manufacturing Execution System) of a lithium battery cover plate assembly and welding line, characterized in that, Includes the following steps: Determine the process parameters for assembling and welding lithium battery cover plates, determine the quality standards and inspection indicators based on the process parameters, and construct a quality assessment model based on the quality standards and inspection indicators; Collect physical status description parameters and finished product images of lithium battery cover plates at each production stage, determine production status parameters and equipment operation parameters based on physical status description parameters and finished product images, and perform visual interaction. The quality of the finished product is determined by evaluating the physical state description parameters and finished product images at each stage using a quality assessment model. Based on the quality of finished products, trace the source of unqualified finished products, and implement intelligent control and monitoring for the assembly and welding of qualified finished products; The process parameters for assembling and welding the lithium battery cover plate are determined, quality standards and inspection indicators are determined based on the process parameters, and a quality assessment model is constructed based on the quality standards and inspection indicators, including: Obtain the process flow description information for the assembly and welding of lithium battery cover plates, and extract the process parameters for the assembly and welding of lithium battery cover plates based on the process flow description information. Based on the process parameters, determine multiple work stages, as well as the operation parameters, material parameters, working environment, and equipment parameters for each work stage; The work standard requirements and working condition requirements for each work stage are determined based on the operating parameters, material parameters, working environment and equipment parameters for each work stage. Based on the work standard requirements and work condition requirements, quality standards and inspection indicators are determined, the mapping relationship between quality standards and inspection indicators is determined, and a quality assessment model for lithium battery cover plate assembly and welding is constructed based on the mapping relationship. The process of evaluating the physical state description parameters and finished product images at each stage using a quality assessment model to determine the quality of the finished product includes: Obtain user order requirements, determine the design features of the lithium battery cover based on the order requirements, and input the design features into the quality assessment model to determine the assessment features of superior, good, and defective products. The quality assessment model is used to perform feature matching between the physical state description parameters and finished product images at each stage to obtain the matching results. The quality characteristics of each lithium battery cover are determined based on the matching results, and the quality attributes of each lithium battery cover are determined based on the quality characteristics. The quality of the finished product is determined based on the quality attributes of each lithium battery cover.

2. The MES optimization method for the lithium battery cover plate assembly and welding line according to claim 1, characterized in that, The process involves collecting physical state description parameters and finished product images from each stage of the lithium battery cover production process, determining production state parameters and equipment operating parameters based on these parameters, and providing interactive visualization. Determine the site environmental parameters for each production stage, determine the data collection method based on the site environmental parameters, and collect the physical state description parameters and finished product images of each production stage of the lithium battery cover through the data collection method; The specifications, texture, and shape parameters of the lithium battery cover body are determined based on the actual product status description parameters and finished product images at each production stage. The production status parameters are determined based on the specifications, texture parameters, and shape parameters of the lithium battery cover body, while the operating status parameters of each working device are collected. Production status parameters and the operating status parameters of each working device are uploaded to the visualization platform for interactive visualization.

3. The MES optimization method for the lithium battery cover plate assembly and welding line according to claim 1, characterized in that, The process of tracing the source of unqualified finished products based on their quality, and intelligently controlling and monitoring the assembly and welding of qualified finished products, includes: Based on the quality of finished products, unqualified finished products are screened out, and the target work process for unqualified finished products and the record storage data within the target work process are determined. Based on the recorded and stored data, the source of unqualified products is traced, the characteristic information of qualified finished products is obtained, and the matching assembly parameters and welding parameters are selected based on the characteristic information; The assembly and welding tasks are generated based on the assembly and welding parameters and then written into the intelligent welding robot for intelligent control. Identify monitoring risk indicators during the assembly and welding process and monitor and issue early warnings through appropriate means.

4. A MES optimization system for a lithium battery cover plate assembly and welding line, characterized in that, The system includes: The module is used to determine the process parameters for assembling and welding lithium battery cover plates, determine the quality standards and inspection indicators based on the process parameters, and build a quality assessment model based on the quality standards and inspection indicators. The determination module is used to collect physical status description parameters and finished product images of lithium battery cover plates at each production stage, and to determine production status parameters and equipment operation parameters based on the physical status description parameters and finished product images, and to perform visual interaction. The evaluation module is used to evaluate the physical state description parameters and finished product images at each stage using a quality evaluation model to determine the quality of the finished product. The control and monitoring module is used to trace the source of unqualified finished products based on the quality of finished products, and to intelligently control and monitor the assembly and welding of qualified finished products. The building module includes: The extraction submodule is used to obtain the process flow description information of lithium battery cover plate assembly and welding, and extract the process parameters of lithium battery cover plate assembly and welding based on the process flow description information. The first determination submodule is used to determine multiple work stages, as well as the operation parameters, material parameters, working environment and equipment parameters of each work stage, based on process parameters. The second determination submodule is used to determine the work standard requirements and work condition requirements for each work stage based on the operation parameters, material parameters, working environment and equipment parameters of each work stage. A submodule is constructed to determine quality standards and inspection indicators based on work standard requirements and work condition requirements, to determine the mapping relationship between quality standards and inspection indicators, and to construct a quality assessment model for lithium battery cover plate assembly and welding based on the mapping relationship. The evaluation module includes: The fifth submodule is used to obtain the user's order requirements, determine the design feature information of the lithium battery cover based on the order requirements, and input the design feature information into the quality assessment model to determine the assessment features of superior, good and defective products. The matching submodule is used to perform feature matching between the physical status description parameters and finished product images at each stage using the quality assessment model, and obtain the matching results. The sixth determination submodule is used to determine the quality characteristics of each lithium battery cover plate based on the matching results, and to determine the quality attributes of each lithium battery cover plate based on the quality characteristics. The seventh determination submodule is used to determine the quality of the finished product based on the quality attributes of each lithium battery cover.

5. The MES optimization system for the lithium battery cover plate assembly and welding line according to claim 4, characterized in that, The determining module includes: The data acquisition submodule is used to determine the site environment parameters of each production stage, determine the data acquisition method based on the site environment parameters, and collect the physical status description parameters and finished product images of each production stage of the lithium battery cover through the data acquisition method. The third determination submodule is used to determine the specifications, texture parameters, and shape parameters of the lithium battery cover body based on the physical state description parameters and finished product images of each production stage. The fourth determination submodule is used to determine the production status parameters based on the specifications, texture parameters, and shape parameters of the lithium battery cover body, while also collecting the operating status parameters of each working device. The upload submodule is used to upload production status parameters and the operating status parameters of each working device to the visualization platform for visual interaction.

6. The MES optimization system for the lithium battery cover plate assembly and welding line according to claim 4, characterized in that, The control and monitoring module includes: The eighth submodule is used to screen out unqualified finished products based on the quality of finished products, determine the target work process for unqualified finished products, and the record storage data within the target work process; The selection submodule is used to trace the source of unqualified products based on the recorded and stored data, obtain the characteristic information of qualified finished products, and select matching assembly parameters and welding parameters based on the characteristic information. The control submodule is used to generate assembly and welding tasks based on assembly and welding parameters and write the assembly and welding tasks into the intelligent welding robot for intelligent control. The monitoring and early warning submodule is used to identify monitoring risk indicators during the assembly and welding process and to monitor and issue early warnings in appropriate ways.

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