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     2026:7/1

International Journal of Multidisciplinary Evolutionary Research

ISSN: 3051-3502 (Print) | 3051-3510 (Online) | Impact Factor: 8.40 | Open Access

Machine Learning Applications in Predictive Maintenance for Industry

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Abstract

Predictive maintenance has emerged as a critical strategy for industrial operations, leveraging machine learning (ML) technologies to optimize equipment performance, reduce downtime, and minimize maintenance costs. This article examines the current landscape of ML applications in predictive maintenance, exploring various algorithms, implementation challenges, and future prospects. The integration of artificial intelligence with traditional maintenance practices represents a paradigm shift from reactive to proactive maintenance strategies, offering significant economic and operational benefits across diverse industrial sectors. 

How to Cite This Article

Anna Müller (2023). Machine Learning Applications in Predictive Maintenance for Industry . International Journal of Multidisciplinary Evolutionary Research (IJMER), 4(1), 16-19 .

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