Factors that determine performance of batteries include differences in manufacturing methods and processes, as well as electrode materials. Considering the engineering factors from electrode slurry mixing to coating, the optimal process can be designed to maximize battery performance. In addition, we evaluate electrode manufacturing behavior using various analysis techniques and conduct research to optimize battery production plans through machine learning analysis based on data from battery materials.

With the commercialization of electric vehicles, batteries have become closer to our lives, resulting in safety issues such as fires and explosions. Research is conducted using various data analysis techniques such as statistical analysis, machine learning, deep learning, and artificial intelligence to reduce defects in the manufacturing process. In order to maximize the efficiency of the production system to meet the increasing battery demand, we pursue intelligent automation of the battery production process through smart factory based on digital twin and research to find and improve manufacturing problems through process data analysis.