AI-Driven Predictive Maintenance for Smart Manufacturing Systems: A Comprehensive Review

Predictive maintenance (PdM) has emerged as a critical application of Artificial Intelligence(AI) in modern manufacturing systems, enabling organizations to anticipate equipment failuresand optimize maintenance schedules. Unlike traditional reactive or preventive maintenancestrategies, AI-based predictive maintenance leverages machine learning, deep learning, and dataanalytics to predict equipment health in real time. This review paper explores the evolution,techniques, applications, benefits, and challenges of AI-based predictive maintenance in manufacturing. It examines key technologies such as Internet of Things (IoT), big data analytics,and digital twins that support predictive maintenance systems. The study highlights that AIdriven PdM significantly reduces downtime, improves operational efficiency, and enhances assetlifespan. However, challenges such as data quality, model interpretability, and implementationcosts remain. The paper concludes with future research directions focusing on explainable AI,edge computing, and scalable industrial solutions.