The Role of Artificial Intelligence in Advanced Manufacturing Control Systems

Abstract

Artificial Intelligence (AI) is reshaping manufacturing control by enabling perception, prediction, and closed-loop optimization at scales and speeds unattainable with conventional control alone. This article surveys key AI paradigms—machine learning, reinforcement learning, and knowledge-based reasoning—and explains how they integrate with hierarchical manufacturing control layers (device, cell, line, and enterprise). We examine applications including model-predictive quality control, predictive maintenance, adaptive scheduling, anomaly detection, and autonomous robotics; discuss architectures that combine edge computing, digital twins, and cloud analytics; and highlight standards and governance for safety, explainability, and cybersecurity. Case-style exemplars illustrate performance gains such as reduced scrap, higher OEE, and lower energy intensity. We conclude with open research challenges in trustworthy RL, data-efficient learning, cross-site generalization, and human-AI collaboration.