Integration of Artificial Intelligence in Predictive Maintenance for Mechanical Systems

Abstract

The growing complexity of modern mechanical systems demands advanced maintenance strategies that minimize downtime and operational costs. Traditional preventive maintenance is being replaced by predictive maintenance (PdM) driven by Artificial Intelligence (AI). AI algorithms, particularly those involving machine learning (ML) and deep learning (DL), can analyze real-time data from sensors to predict equipment failures before they occur. This paper explores the integration of AI in predictive maintenance for mechanical systems, focusing on key technologies, implementation frameworks, benefits, and challenges. A detailed review of AI-based condition monitoring, feature extraction, and predictive modeling techniques is presented. The study concludes that AI-driven predictive maintenance enhances reliability, optimizes maintenance schedules, and significantly reduces unplanned failures in industrial environments.

Cite as:

Dr. Kondekal Manjunatha. (2025). Integration of Artificial Intelligence in Predictive Maintenance for Mechanical Systems. Recent Trends in Production Engineering, 8(3), 31–34. 

https://doi.org/10.5281/zenodo.17609101