Machine Learning Approaches in Predictive Maintenance for Manufacturing

Abstract

This article examines the role of machine learning in predictive maintenance for manufacturing industries. By leveraging historical data and real-time monitoring, machine learning models can predict equipment failures before they occur, reducing downtime and maintenance costs. The study highlights various machine learning techniques, including supervised and unsupervised learning, and their applications in identifying patterns and anomalies. Comparative analysis with traditional maintenance strategies reveals the advantages in terms of accuracy and efficiency. The results underline the transformative potential of intelligence-driven maintenance solutions in modern manufacturing.

This is a free preview. The complete article is available with a valid subscription.