Industry 4.0 techniques applied to the improvement of the cutting process of Lithium-Ion battery terminals

The transition to Industry 4.0 has brought significant advancements in production, especially in the manufacturing of lithium-ion batteries, through the application of Artificial Intelligence (AI). This study focuses on the development of an intelligent system to improve the cutting of battery terminals, using AI algorithms to optimize precision and reduce defects. The main challenge is the imprecision in the cutting process, which results in a high rate of defective products and increases production costs due to material waste. The application of machine learning and real-time data analysis enabled automatic adjustments in the cutting process, creating a flexible and adaptable manufacturing environment. As a result, there was a significant reduction in the defect rate of the batteries, along with an increase in the quality and uniformity of the terminals. These efficiency gains demonstrate the potential of AI to improve precision and reduce costs while meeting quality requirements. The integration of AI in the cutting process not only improves quality and sustainability but also opens up new possibilities for other applications in Industry 4.0. The study demonstrates that technological innovations in flexible manufacturing processes can generate a significant competitive advantage for the renewable energy and storage sector.