A production intelligent management method for soft-pack batteries

Abstract

The present invention is directed to the technical field of battery production management, and specifically relates to a method for intelligent production management of soft-pack batteries, the method comprising the following steps: setting a raw material data matrix to represent an initial data set of raw materials; monitoring the storage conditions of raw materials based on real-time data, and setting a storage condition matrix to monitor abnormal conditions; the system determines the optimal production plan based on the real-time status of raw materials and production needs; the system controls the equipment to execute the production plan, and monitors the parameters of each link in real time, and automatically adjusts the equipment parameters according to preset process standards; after production is completed, the finished product undergoes quality inspection and is put into storage. The purpose of the present invention is to provide a method for intelligent production management of soft-pack batteries, which can significantly improve production efficiency, reduce production costs, and ensure consistency of product quality in terms of full traceability of raw materials, real-time scheduling, and automated control of the production process.

Description

Technical Field

[0001] The present invention relates to the technical field of soft-pack battery production, and in particular to an intelligent production management method for soft-pack batteries. Background Art

[0002] With the rapid growth of the lithium-ion battery market, especially in electric vehicles and portable electronic devices, demand for high-energy-density batteries continues to increase. Pouch cells, due to their lightweight, flexible design, and high energy density, are becoming the mainstream choice. However, the production process of pouch cells is relatively complex. From raw material procurement and storage to production scheduling and quality control, every step is crucial to the performance and safety of the final product.

[0003] Traditional soft-pack battery production management systems often rely on manual operations and accumulated experience, lacking full automation and intelligent management capabilities. This results in low production efficiency, difficulty ensuring product consistency, and slow response to unexpected issues. Furthermore, the storage and scheduling of raw materials cannot be monitored and optimized in real time, which can easily lead to material waste and bottlenecks in the production process, further affecting production efficiency. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies in the prior art, the purpose of the present invention is to provide an intelligent production management method for soft-pack batteries, which can significantly improve production efficiency, reduce production costs, and ensure consistency in product quality through full traceability of raw materials, real-time scheduling, and automated control of the production process.

[0005] The present invention is achieved through the following technical solutions:

[0006] In a first aspect, the present invention discloses a method for intelligent production management of soft-pack batteries, which comprises the following steps:

[0007] S100 sets a raw material data matrix to represent the initial data set of raw materials;

[0008] S200 monitors the storage conditions of raw materials based on real-time data, setting a storage condition matrix to monitor abnormal conditions;

[0009] S300. The system determines the optimal production plan based on the real-time status of raw materials and production needs;

[0010] S400. The system controls the equipment to execute the production plan and monitors the parameters of each link in real time, automatically adjusting the equipment parameters according to the preset process standards;

[0011] S500. After production is completed, the finished products are quality inspected and put into storage.

[0012] In combination with the first aspect, further, in step S100, the raw material data matrix is set to , and set the acquisition function to represent the initial data set of raw materials. The function of data acquisition is expressed as:

[0013]

[0014] in, Indicates the raw materials at the initial time A data matrix, each element Indicates the The first raw material Item information.

[0015] In combination with the first aspect, further, in step S200, the storage condition matrix is set as:

[0016]

[0017] in, Indicates the The first memory cell Conditions, For the detection function, the initial material data and time as input.

[0018] In combination with the first aspect, further, in step S300, the optimal production plan is determined using a production scheduling function, which is expressed as:

[0019]

[0020] in, is the production revenue function, is the production cost function, is a production variable.

[0021] Combined with the first aspect, further, the calculation formula of the production benefit function is:

[0022]

[0023] in, It is The sales price of the product, It is Products in time production quantity.

[0024] Combined with the first aspect, further, the calculation formula of the production cost function is:

[0025]

[0026] in, It is The unit production cost of a product, It is Products in time production quantity, It is a fixed cost.

[0027] In combination with the first aspect, further, in step S400, the control function of the equipment executing the production plan is:

[0028]

[0029] In combination with the first aspect, further, in step S500, the control function of the equipment executing the production plan is:

[0030]

[0031] In a second aspect, the present invention further discloses a computer device comprising a processor and a storage medium;

[0032] The storage medium is used to store instructions;

[0033] The processor is configured to operate according to the instructions to execute the steps of the method described above.

[0034] Beneficial effects of the present invention:

[0035] The intelligent production management method of soft-pack batteries of the present invention significantly improves production efficiency, reduces production costs, and ensures consistency of product quality through full traceability of raw materials, real-time scheduling, and automated control of the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative effort.

[0037] Figure 1 Flowchart of the management method of the present invention. DETAILED DESCRIPTION

[0038] To make the above-mentioned objects, features, and advantages of the present invention more readily apparent, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following description sets forth numerous specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art may make similar modifications without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0039] With the rapid growth of the lithium-ion battery market, especially in electric vehicles and portable electronic devices, demand for high-energy-density batteries continues to increase. Pouch cells, due to their lightweight, flexible design, and high energy density, are becoming the mainstream choice. However, the production process of pouch cells is relatively complex. From raw material procurement and storage to production scheduling and quality control, every step is crucial to the performance and safety of the final product.

[0040] Traditional soft-pack battery production management systems often rely on manual operations and accumulated experience, lacking full automation and intelligent management capabilities. This results in low production efficiency, difficulty ensuring product consistency, and slow response to unexpected issues. Furthermore, the storage and scheduling of raw materials cannot be monitored and optimized in real time, which can easily lead to material waste and bottlenecks in the production process, further affecting production efficiency.

[0041] Example 1

[0042] In order to solve the above problems, this embodiment discloses a method for intelligent production management of soft-pack batteries, which includes the following steps:

[0043] S100 sets a raw material data matrix to represent the initial data set of raw materials;

[0044] S200 monitors the storage conditions of raw materials based on real-time data, setting a storage condition matrix to monitor abnormal conditions;

[0045] S300. The system determines the optimal production plan based on the real-time status of raw materials and production needs;

[0046] S400. The system controls the equipment to execute the production plan and monitors the parameters of each link in real time, automatically adjusting the equipment parameters according to the preset process standards;

[0047] S500. After production is completed, the finished products are quality inspected and put into storage.

[0048] Furthermore, in step S100, the raw material data matrix is set to , and set the acquisition function to represent the initial data set of raw materials. The function of data acquisition is expressed as:

[0049]

[0050] in, Indicates the raw materials at the initial time A data matrix, each element Indicates the The first raw material Item information.

[0051] Furthermore, in step S200, the storage condition matrix is set as:

[0052]

[0053] in, Indicates the The first memory cell Conditions, For the detection function, the initial material data and time as input.

[0054] Storage Condition Matrix Describes the time The state of each storage unit, such as temperature, humidity, etc. Function To describe how to convert the initial data and time As input, the state of each memory cell is calculated .

[0055] The storage condition matrix calculates the status of each storage unit based on the initial raw material data and time factors, so that the system can track and manage the storage conditions of raw materials in real time. If the storage conditions exceed the preset standard range, the system will issue an alarm or make adjustments.

[0056] Furthermore, in step S300, the optimal production plan is determined using a production scheduling function, which is expressed as:

[0057]

[0058] in, is the production revenue function, is the production cost function, is a production variable.

[0059] Furthermore, the calculation formula of the production benefit function is:

[0060]

[0061] in, It is The sales price of the product, It is Products in time production quantity.

[0062] Production revenue function Describes the time Under the given production variable In the case of production, the benefits brought by the production process are usually related to factors such as production quantity and sales price.

[0063] Furthermore, the calculation formula of the production cost function is:

[0064]

[0065] in, It is The unit production cost of a product, It is Products in time production quantity, It is a fixed cost.

[0066] Production cost function Describes the time Under the given production variable In this case, the costs brought about by the production process usually include the use fees of production equipment, raw material costs, labor costs, etc.

[0067] Furthermore, in step S400, the control function for the equipment to execute the production plan is:

[0068]

[0069] In actual production, this control function can be judged based on multiple parameters at the same time. For example, if the temperature ,pressure and humidity If all are within the standard range, the production process continues; otherwise, the system adjusts the operation of related equipment to bring these parameters back within the standard range or issues an alarm.

[0070] Furthermore, in step S500, the control function for the equipment to execute the production plan is:

[0071]

[0072] If the detection parameters Within the standard range, that is , the product is considered qualified and put into storage; if the test parameters Not within the scope of the standard, i.e. , the product is considered unqualified and needs to be returned or reworked.

[0073] Example 2

[0074] This embodiment provides a computer device, including a processor and a storage medium;

[0075] The storage medium is used to store instructions;

[0076] The processor is configured to operate according to the instructions to execute the steps of any one of the methods described in Example 1.

[0077] Example 3

[0078] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in Example 1 when executed by a processor.

[0079] In summary, the present invention provides an intelligent production management method, electronic device, and storage medium for soft-pack batteries, which significantly improve production efficiency, reduce production costs, and ensure consistency in product quality through full traceability of raw materials, real-time scheduling, and automated control of the production process.

[0080] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present invention.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for intelligent production management of soft-pack batteries, characterized in that: The following steps are involved: S100 sets a raw material data matrix to represent the initial data set of raw materials; S200 monitors the storage conditions of raw materials based on real-time data, setting a storage condition matrix to monitor abnormal conditions; S300. The system determines the optimal production plan based on the real-time status of raw materials and production needs; S400. The system controls the equipment to execute the production plan and monitors the parameters of each link in real time, automatically adjusting the equipment parameters according to the preset process standards; S500. After production is completed, finished products undergo quality inspection and are put into storage; In step S100, the raw material data matrix is set to , and set the acquisition function to represent the initial data set of raw materials. The function of data acquisition is expressed as: in, Indicates the raw materials at the initial time A data matrix, each element Indicates the The first raw material Item information; In step S200, the storage condition matrix is set as: in, Indicates the The first memory cell Conditions, For the detection function, the initial material data and time as input.

2. The intelligent production management method for soft-pack batteries according to claim 1, characterized in that: In step S300, the optimal production plan is determined using a production scheduling function, which is expressed as: in, is the production revenue function, is the production cost function, is a production variable.

3. The intelligent production management method for soft-pack batteries according to claim 2, characterized in that: The calculation formula of the production benefit function is: in, It is The sales price of the product, It is Products in time production quantity.

4. The intelligent production management method for soft-pack batteries according to claim 3, characterized in that: The production cost function is calculated as follows: in, It is The unit production cost of a product, It is Products in time production quantity, It is a fixed cost.

5. The intelligent production management method for soft-pack batteries according to claim 2, characterized in that: In step S400, the control function for the equipment to execute the production plan is: in, For control function Parameters.

6. The intelligent production management method for soft-pack batteries according to claim 5, characterized in that: In step S500, the control function for the equipment to execute the production plan is: in, For control function Parameters.

7. A computer device, characterized in that: including processor and storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 6.

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