Automation plays a significant role in enhancing the efficiency and accuracy of nanotechnology inspections. Automated systems can handle large volumes of inspections quickly and with high precision. Machine learning algorithms are increasingly being integrated into inspection processes to analyze data and identify defects automatically, reducing human error and improving overall inspection quality.
