CATL / Sichuan Plant

As one of 13 production sites belonging to Contemporary Amperex Technology Co., Limited (CATL), the plant in Sichuan (China) is one of the world’s largest manufacturers of lithium-ion batteries.

For several years now, CATL has been facing a significant increase in global demand for its products as well as intensified competition. The battery manufacturer is addressing this by consistently building an end-to-end value chain – customer-, sustainability-oriented, and closely linked to its Industry 4.0 strategy. In this context, the Sichuan plant had to solve production-specific challenges. These included, for example, ensuring process reliability, increasing efficiency in energy and material usage, and further developing logistics processes from manual to automated operations.

These and other market conditions prompted the plant to develop and implement digitalization solutions, partly locally and partly across sites, starting in 2021. From the outset, the development and integration of innovative AI solutions played a central role.

The solution landscape encompasses Industry 4.0 use cases across the entire plant process chain, in which targeted, orchestrated AI technologies have been deployed. This covers several areas and functions, such as energy management systems, closed-loop production process analysis and machine control, predictive maintenance, and logistics.
The solution impressed the INDUSTRIE 4.0 AWARD jury with clear results that AI tools such as deep learning, machine learning, and computer vision are already delivering on-site. In addition, CATL Sichuan is pioneering this solution in developing a standardized technical AI framework that can be scaled to other locations.

Lithium battery production lines require multiple machinery assets to be operated simultaneously (≈ 60% energy share). If these are started in an uncoordinated manner, it leads to high standby rates and considerable waste.

Based on production plans, plant capacity / status, maintenance schedules, and other parameters, an AI solution decides whether to recommend that machine operators shut down individual plants – or whether the AI should switch plants on / off independently. In addition, the digitalization team developed an algorithm for demand detection that generates standardized activation protocols. A PES (Production Energy-saving System) ensures holistic energy management that goes beyond the efficiency control of individual devices.

The uniformity of the coating is a crucial indicator in the manufacture of lithium-ion batteries. Prior to the development of the solution, quality control and data analysis relied primarily on manual experience and fragmented data, making it difficult to identify and analyze errors.

The winner of the INDUSTRIE 4.0 AWARD solved this challenge with a closed-loop system developed in-house that analyzes the causes of coating process errors. An AI application draws conclusions about the effect of machine and process parameters on the quality of the material coating. Additionally, it autonomously adjusts machine parameters at the micrometer- and milligram level. More than 1,000 types of particle and fluid control parameters are considered.

Using an in-house IT platform, the Sichuan plant integrates various computer vision systems. The focus is on hardware and software for AI-supported analysis of image material from manufacturing and maintenance processes.

This enables the award winner to use computer vision systems across manufacturers and to connect them to existing systems such as PLCs, MESs, and standardized software (e.g., AI models) via no-code / low-code applications.