Artificial Intelligence-driven Autonomous Robotics for Smart Manufacturing in Industry 4.0

Abstract factories need the robot mechanisms that will provide a high level of accuracy and efficiency in unstable production environments. Traditional industrial robots are useful in repetitive work processes, but they do not respond to adaptive decisions, so the nature of Industry 4.0 assembly operations, where immediate adaptations are necessary, is limited. This study presents an autonomous robotic system based on artificial intelligence that will enhance the precision and reaction time of operations in smart manufacturing factories that require high precision. The approach compares three control strategies, such as conventional robotic control, machine learning-based control, and a lightweight autonomous AI model, which can optimise real-time decisions. The secondary data of industrial performance through manufacturing reports, automation datasets, and simulation-based studies were accessed to ensure that a realistic evaluation is done without a physical experiment. It resulted in the proposed autonomous model having 93.7% operational accuracy, 33% shorter cycle time and 21% less power consumption than when using conventional control systems. These results indicate that optimised AI-controlled robotics can be used to offer scalable, efficient and computationally viable solutions to next-generation smart manufacturing automation.