Overview Of Lithium Battery Manufacturing
Technology
Development
Overview Of
Lithium Battery Project
Photovoltaic power generation must cooperate with energy
storage. At the same time, the
electric vehicle industry has reduced environmental pollution.
Our team has been deeply involved in this field. The technical
development of our team in the field of lithium battery began
in the Spring Festival of 2012 and has been 10 years now!
During this period, a series of large enterprise projects were
completed, there are more than 100
lithium battery manufacturing related models developed only!
Related items are:
(1)The development of optical film thickness density
consistency optimizes the production process through a large
number of process parameters
(2)The basic model test of lithium battery manufacturing was
personally signed by the founder of a large company; The
project determines the extremely high accuracy of the model:
the contract requires 85% hit rate, and the actual hit rate is
98%
(3)The Level 2 of lithium battery production
optimization, such as the Level 2 of lithium battery
pole slice cutting, has completed a series of software
functions based on the prediction of defect model and the
prediction of knife notch as the main influencing factor; In
order to realize the high accuracy of the model, the model for
predicting this defect and the model for predicting knife
notch are respectively machine learned
(4)The hardware of knife notch measuring device is photo
shooting and processing based on 1000 times microscope, and
the software is the processing logic of knife notch
After the relevant lithium battery project, the company was
accepted as the supplier of the cloud rail project of the same
company (since 2020)
For related lithium
battery project technologies, there are only a dozen ppts
(each can be explained for 2 hours) (more than 100 ppts for
all Smart Manufacturing)
More Than 100 Sets Of Emerging Industry
Models
Emerging Industry Model
In the lithium battery project, more than 100 sets of
prediction models for various defects and display parameters
in each manufacturing section have been developed. See the
related models. In subsequent projects, such as lithium
battery winding, volume division and rolling, a large number
of models have also been developed. The high accuracy of the
model is incredible! See
High precision model prediction.
Field
Problems
After several years of project development of large lithium
battery enterprises, it is obvious that it is difficult to
provide data required for high-quality Smart Manufacturing on site. Enterprises usually have many on-site
problems. For example, the MES system of the enterprise does
not have the key tool data of the project. Therefore, the data
about the knife hole and tool usage can only be found in a
database of the cutting machine, which is often not connected
to the production line. Although every enterprise has a large
amount of data on the table, there are few data that really
meet the needs of high-quality Smart Manufacturing, and
there are often important data omissions. The enterprise has
no clear punishment system for the problem of missing data on
site or deliberately not collecting data.
Development
And
Application Of Defect Early Warning System
The optimization of lithium battery production process mainly
contributes to
the development and application of defect early warning
system; The development and use of defect early warning
system mainly depends on the high accuracy of the model! The
benefits of lithium battery project are summarized as follows:
-
An accurate lithium battery model has been developed to make
accurate defect prediction possible
-
The machine learning of knife gap prediction model and lithium
battery defect model are realized to ensure the high accuracy
of the model
-
The successful development of the software and hardware of the
tool notch measuring device ensures the high-speed automatic
measurement, makes the tool notch machine learning normal, and
also enables the optimal use of the tool on site. (See
the description in the following section)
-
The successful application of soft sensing technology
contributes to high-precision model prediction
-
The successful development and application of defect early
warning system has greatly reduced the defective lithium
battery; Usually, the defective rate of lithium battery is
close to 10% in all factories in China through various
sections of lithium battery manufacturing!
Optimal Use Of Cutting Tools
The loss caused by the time occupied by tool replacement on
site is greater than that caused by tool regrinding.
Therefore, in the use of tools, the tools are grouped
according to the initial tool notch, for example, divided into
five groups. In the installation of tools, all tools are taken
from one group, This can greatly reduce the loss of early
replacement of some tools and simultaneous replacement of
other tools due to tool differences.
The initial tool notch value is automatically measured by a
specially designed and developed tool. For the hardware and
software development of the automatic measuring device, see
the development case of lithium battery defect early warning
system.
Lithium Battery Manufacturing
Optimization Series
Defect Warning System Series
Development case of lithium
battery defect early warning system
Function and application of defect early warning system
products
Customer requirements of defect early warning system
Technical consultation of defect data based on Prediction
Production process optimization based on defect early warning
Introduction to defect early
warning system technology
Project Cases
Summary,
Key Projs,
Model Projs,
Rolling Mills
Model
System,
Intelli Equip.,
New Level 2,
Li-Batt
=========
Contact us: Please scan the figure below to add
Wechat (e.g. myQQfriend); Tel: (+1) 858 6090468 or 13430699003; E-mail
BLi68@QQ.com. See
Profile of the key consultant.
 
|