Classification of cell line Halm machine data in solar panel production factories using artificial intelligence models

Abstract

A solar energy module consists of solar cells that convert sunlight into electrical energy. The quality of these cells is the most important determinant of panel performance and lifespan. High-quality cells increase energy efficiency and extend panel life. Solar cells are typically composed of crystalline silicon, thin layers, and organic materials. Each material has its own advantages and disadvantages. However, what all cells have in common is that they produce electrical energy when exposed to solar radiation. Solar cells can be classified and ranked. This classification indicates the efficiency and performance of the cell. Solar energy modules are widely used to meet the energy needs of many homes and businesses. Accurately measuring cell performance can improve the overall efficiency of the panel. Therefore, AI (artificial intelligence) modeling offers many advantages in optimizing cell performance. The study yielded several benefits associated with modeling solar panel cells with artificial intelligence. Some of the benefits derived from this research are: Improved efficiency, Error detection and correction, Reduced maintenance costs, predictability, Increased production. These advantages demonstrate that AI modeling can help optimize solar panel cell performance.