Intelligent production management method for soft package battery

Abstract

The invention relates to the technical field of battery production management, in particular to an intelligent production management method for a soft package battery, and the method comprises the following steps: setting a raw material data matrix to represent an initial data set of raw materials; according to storage conditions of real-time data monitoring raw materials, setting a storage condition matrix to monitor abnormal conditions; the system determines an optimal production plan based on the real-time state and the production demand of the raw materials; the system controls the equipment to execute the production plan, monitors parameters of each link in real time, and automatically adjusts the equipment parameters according to a preset process standard; and after production is completed, finished products are subjected to quality inspection and put in storage. According to the intelligent production management method for the soft package battery, in the aspects of whole-course source tracing and real-time scheduling of raw materials, automatic control of the production process and the like, the production efficiency can be remarkably improved, the production cost can be reduced, and the consistency of the product quality can be ensured.

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 the increasing demand for high-energy-density batteries in electric vehicles, portable electronic devices and other fields, soft-pack batteries have gradually become the mainstream choice in the market due to their advantages such as light weight, flexible design and high energy density. However, the production process of soft-pack batteries is relatively complicated. From the procurement and storage of raw materials to production scheduling and quality control, every link is crucial to the performance and safety of the final product.

[0003] Traditional soft-pack battery production management systems often rely on manual operation and experience accumulation, lacking the ability of full automation and intelligent management, which leads to low production efficiency, difficulty in ensuring product consistency, and slow response when faced with unexpected problems. In addition, the storage and scheduling of raw materials cannot be monitored and optimized in real time, which easily leads to waste of raw materials and bottleneck problems 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 of 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: In a first aspect, the present invention discloses a method for intelligent production management of soft-pack batteries, which comprises the following steps: S100. Setting a raw material data matrix to represent an initial data set of raw materials; S200 monitors the storage conditions of raw materials according to real-time data and sets 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, monitors the parameters of each link in real time, and automatically adjusts the equipment parameters according to the preset process standards; S500. After production is completed, the finished products are quality inspected and put into storage.

[0006] 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 the raw materials. The function of data acquisition is expressed as: in, Indicates the raw material at the initial time A data matrix, each element Indicates The raw material Item information.

[0007] In combination with the first aspect, further, in step S200, the storage condition matrix is ​​set as: in, Indicates The first storage unit Conditions, For the detection function, the initial material data and time as input.

[0008] In combination with the first aspect, further, in step S300, the optimal production plan is determined using a production scheduling function, and the production scheduling function is expressed as: in, is the production revenue function, is the production cost function, is a production variable.

[0009] Combined with the first aspect, further, 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.

[0010] Combined with the first aspect, further, the calculation formula of the production cost function is: in, It is The unit production cost of a product, It is Products in time The production quantity, It is a fixed cost.

[0011] In combination with the first aspect, further, in step S400, the control function of the equipment executing the production plan is: In combination with the first aspect, further, in step S500, the control function of the equipment executing the production plan is: In a second aspect, the present invention further discloses a computer device, which includes a processor and a storage medium; The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method described above.

[0012] Beneficial effects of the present invention: The intelligent production management method of a soft-pack battery 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

[0013] The present invention is further described using the accompanying drawings, but 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 work.

[0014] Figure 1 The figure is a flow chart of the management method of the present invention. DETAILED DESCRIPTION

[0015] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0016] With the rapid growth of the lithium-ion battery market, especially the increasing demand for high-energy-density batteries in electric vehicles, portable electronic devices and other fields, soft-pack batteries have gradually become the mainstream choice in the market due to their advantages such as light weight, flexible design and high energy density. However, the production process of soft-pack batteries is relatively complicated. From the procurement and storage of raw materials to production scheduling and quality control, every link is crucial to the performance and safety of the final product.

[0017] Traditional soft-pack battery production management systems often rely on manual operation and experience accumulation, lacking the ability of full automation and intelligent management, which leads to low production efficiency, difficulty in ensuring product consistency, and slow response when faced with unexpected problems. In addition, the storage and scheduling of raw materials cannot be monitored and optimized in real time, which easily leads to waste of raw materials and bottleneck problems in the production process, further affecting production efficiency.

[0018] Example 1 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: S100. Setting a raw material data matrix to represent an initial data set of raw materials; S200 monitors the storage conditions of raw materials according to real-time data and sets 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, monitors the parameters of each link in real time, and automatically adjusts the equipment parameters according to the preset process standards; S500. After production is completed, the finished products are quality inspected and put into storage.

[0019] Furthermore, in step S100, the raw material data matrix is ​​set as , and set the acquisition function to represent the initial data set of the raw materials. The function of data acquisition is expressed as: in, Indicates the raw material at the initial time A data matrix, each element Indicates The raw material Item information.

[0020] Furthermore, in step S200, the storage condition matrix is ​​set as: in, Indicates The first storage unit Conditions, For the detection function, the initial material data and time as input.

[0021] Storage Condition Matrix Describes the time The state of each storage unit, such as temperature, humidity, etc. To describe how to convert the initial data and time As input, the state of each storage unit is calculated .

[0022] 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.

[0023] Furthermore, 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.

[0024] Furthermore, 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.

[0025] Production revenue function Describes the time Given the production variable In the case of production, the profits brought by the production process are usually related to factors such as production quantity and sales price.

[0026] Furthermore, the calculation formula of the production cost function is: in, It is The unit production cost of a product, It is Products in time The production quantity, It is a fixed cost.

[0027] Production cost function Describes the time Given the production variable In this case, the costs brought about by the production process usually include the cost of using production equipment, raw material costs, labor costs, etc.

[0028] Furthermore, in step S400, the control function of the equipment executing the production plan is: 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.

[0029] Furthermore, in step S500, the control function of the equipment executing the production plan is: 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.

[0030] Example 2 This embodiment provides a computer device, including a processor and a storage medium; The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of any method described in Example 1.

[0031] Example 3 An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the method described in Embodiment 1 are implemented.

[0032] 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 of product quality through full traceability of raw materials, real-time scheduling and automated control of the production process.

[0033] 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 adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0034] 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 box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0035] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate 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 A function specified in one or more boxes.

[0036] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the protection scope 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 solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention. Finally, it should be noted that the above embodiments are only used to illustrate the technical solution 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 solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution 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. Setting a raw material data matrix to represent an initial data set of raw materials; S200 monitors the storage conditions of raw materials according to real-time data and sets 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, monitors the parameters of each link in real time, and automatically adjusts the equipment parameters according to the preset process standards; S500. After production is completed, the finished products are quality inspected and put into storage.

2. The method for intelligent production management of soft-pack batteries according to claim 1, characterized in that: In step S100, the raw material data matrix is ​​set as , and set the acquisition function to represent the initial data set of the raw materials. The function of data acquisition is expressed as: in, Indicates the raw material at the initial time A data matrix, each element Indicates The raw material Item information.

3. The method for intelligent production management of soft-pack batteries according to claim 2, characterized in that: In step S200, the storage condition matrix is ​​set as: in, Indicates The first storage unit Conditions, For the detection function, the initial material data and time as input.

4. The method for intelligent production management of 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.

5. The method for intelligent production management of soft-pack batteries according to claim 4, characterized in that: The calculation formula of production benefit function is: in, It is The sales price of the product, It is Products in time production quantity.

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

7. The method for intelligent production management of soft-pack batteries according to claim 4, characterized in that: In step S400, the control function of the equipment executing the production plan is:

8. The method for intelligent production management of soft-pack batteries according to claim 7, characterized in that: In step S500, the control function of the equipment to execute the production plan is:

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

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