Leveraging AI in the Manufacturing Industry for Predictive Maintenance: A Technical Perspective

This technical article explores the transformative role of artificial intelligence in revolutionizing predictive maintenance practices across the manufacturing industry. By examining the integration of Internet of Things sensor networks with sophisticated machine learning algorithms, the article demonstrates how manufacturers can transition from traditional reactive maintenance approaches to proactive failure prediction systems. The discussion encompasses the technical infrastructure required for implementation, analytical models that drive accurate predictions, integration challenges with existing manufacturing systems, and methods for quantifying return on investment. Through examination of real-world applications and emerging technologies, the article provides a comprehensive framework for understanding how AI-enabled predictive maintenance solutions enhance operational efficiency, extend equipment lifespan, and deliver significant maintenance cost reductions in industrial environments.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-04-08
DOI
https://doi.org/10.32628/cseit25112804
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging AI in the Manufacturing Industry for Predictive Maintenance: A Technical Perspective

Alok Singh
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Industrial Vision Systems and Defect Detection
article

Leveraging AI in the Manufacturing Industry for Predictive Maintenance: A Technical Perspective

Alok Singh
article en

Abstract

This technical article explores the transformative role of artificial intelligence in revolutionizing predictive maintenance practices across the manufacturing industry. By examining the integration of Internet of Things sensor networks with sophisticated machine learning algorithms, the article demonstrates how manufacturers can transition from traditional reactive maintenance approaches to proactive failure prediction systems. The discussion encompasses the technical infrastructure required for implementation, analytical models that drive accurate predictions, integration challenges with existing manufacturing systems, and methods for quantifying return on investment. Through examination of real-world applications and emerging technologies, the article provides a comprehensive framework for understanding how AI-enabled predictive maintenance solutions enhance operational efficiency, extend equipment lifespan, and deliver significant maintenance cost reductions in industrial environments.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Rajiv Gandhi Technical University (IN)
Openalex Percentile: Top 91%
Industrial Vision Systems and Defect Detection
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Leveraging AI in the Manufacturing Industry for Predictive Maintenance: A Technical Perspective — Alok Singh · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS