AI-Driven Vision and Robotics Framework for Intelligent Manufacturing

Abstract

The integration of artificial intelligence (AI) with mechanical systems has become a cornerstone of intelligent manufacturing. As modern industries evolve toward Industry 4.0, the need for adaptive, efficient, and intelligent systems is growing. This paper presents a comprehensive AI-driven framework that integrates computer vision, robotic mechanics, and intelligent planning for automated manufacturing and assembly. The proposed system combines deep learning-based visual recognition with robotic path planning and real-time adaptive control to handle complex industrial tasks. Experimental results in a simulated smart factory environment demonstrate significant improvements in assembly speed (up to 28%), fault tolerance, and recognition accuracy (96.3%) compared to traditional rule-based systems. This work contributes a holistic model to bridge the gap between high-level AI algorithms and low-level mechanical execution.