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Machine Vision helps Smart Manufacturing of Lithium Batteries

Jun 23, 2022
Under the new industrial cycle, the large-scale manufacturing of power batteries has started. Stability and efficiency have become the industry buzzwords. New materials and new processes are emerging and iterations are accelerating, and it has become the industry consensus to conduct production rapidly and with high quality. Extreme smart manufacturing continues to progress, the one-thousandth error inspection rate and the zero miss inspection requirements challenge the manufacturing capacity of the lithium industry ......

3 major difficulties in the lithium vision inspection industry

The new processes and raw materials for lithium-ion batteries are constantly escalating, so the requirements for machine vision inspection are becoming increasingly stringent. How to meet the market expectations with high quality, adapt to new changes in the industry as quickly as possible, and improve product quality, have become the important issues that machine vision inspection companies need to face.
However, there are still three major problems in the field of lithium machine vision inspection, which restrict the rapid release of lithium battery production capacity.

1. Difficult to balance speed and precision

The era of large-scale manufacturing of power batteries has come, and inspection is becoming stricter and more complex. Market requirements are becoming more refined, and it has become a common challenge for the industry to improve production efficiency and reduce product defect rates.

For example, extreme manufacturing requires the power battery defect rate to improve from ppm (parts per million) level to ppb (parts per billion) level and safety performance control from 6 sigmas to 9 sigmas.

2. Slow iteration of machine vision technology

Diversified application scenarios have accelerated the differentiation of power battery demand, the choice of materials and processes varies widely, new materials such as lithium manganese iron phosphate, silicon-based anode, high nickel ternary, etc. have been launched, and the application of new processes such as large cylindrical batteries, CTC and CTB has accelerated.

At the same time, new challenges of machine vision inspection arise. New materials and new processes are bound to bring new defects, machine vision learning ability directly affects the production time. At present, the speed of technology iteration of some machine vision companies is slow, with weak product learning ability, it takes up to a week or two months to achieve stable inspection. This does not meet the expectations of rapid growth in production capacity for new energy companies.

3. Weak data feedbacks

In the lithium machine vision inspection industry, the inspection data has not been better utilized since the beginning. One reason for this is that the industry has not formed a unified defect standard, the same battery factory using multiple machine vision inspection systems, which has a large difference in inspection and inconsistency; Secondly, the data is inadequate to support the use of capacity.

LUSTER's answer to these three difficulties
With more than twenty years of experience and technical strength accumulated in the fields of printing, display, PCB, consumer electronics, etc., LUSTER has deeply analyzed customer needs in the field of lithium machine vision, officially entered this market in 2019, and continues to make efforts. We continue to bring high-quality services to the global new energy customers from three dimensions: technology, production capacity layout and product matrix.

  • Introduced lightweight semantic model and jointly developed G-Box intelligent platform with Nvidia. The platform combines embedded development efficiency, and GPU neural network acceleration features, and can achieve ultra 2GB/s processing bandwidth, which can well satisfy the requirements of battery industry inspection speed and accuracy and match extreme manufacturing.
  • The algorithm is given a large margin so that the machine has a strong response capability when facing new processes; Meanwhile, LUSTER is equipped with industrial data pre-training technology and special structure small sample model technology, so the machine can learn the defects from one sample, which achieves fast process iteration and strong learning ability.
  • The R&D of a quality arbiter for the lithium industry, with a multi-dimensional and multi-angle stable imaging system, combined with the company's intelligent manufacturing deep learning industrial brain platform, can form a stable source of data, laying a good foundation for deep learning applications, enterprise production yield improvement, and subsequent process improvement.

Production capacity layout:
LUSTER intends to invest 1.5 billion yuan for the construction of industrial artificial intelligence Lake Tai industrial base, industrial artificial intelligence algorithm and software platform research and development projects, advanced optics and computational imaging research and development projects, and technology and development reserve funds to expand its own configurable vision systems and intelligent vision equipment business capacity to better match the needs of the company's rapid business growth, including the lithium segment.

Product Matrix:

Currently, LUSTER's machine vision inspection solutions have covered the whole process of lithium battery production, and plan to focus on raw material diaphragm inspection, laser cutting and cutting and stacking integrated inspection of electrode section and welding inspection of post-process section.

Imaging effect of lithium electrode sheet defect inspection

In the future, with a global perspective, LUSTER will optimize the production process, reduce costs and increase efficiency for customers worldwide with high quality, high stability and zero complaint products and services, and work together to help the new energy industry and make unremitting efforts for a greener earth!

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