AI & Machine Learning for Mechanical Systems

Abstract

ABSTRACT Artificial Intelligence (AI) and Machine Learning (ML) have emerged as prominent enablers in modern mechanical systems, enabling enhanced design optimization, fault diagnostics, performance prediction and autonomous control. The confluence of data science with classical mechanics brings substantial opportunities, also with unique challenges like interpretability and real-time implementation. In this review, we provide a detailed examination of contemporary methods and applications of AI & ML in mechanical engineering systems. We explore how AI & ML techniques integrate with traditional mechanical systems design, monitoring and predictive maintenance to improve accuracy, efficiency and robustness. We also discuss limitations, future prospects and practical considerations for industry adoption.

KEYWORDS: Artificial Intelligence, Machine Learning, Mechanical Systems, Predictive Maintenance, Condition Monitoring, System Optimization, Fault Diagnosis