Artificial Intelligence in Predictive Maintenance of Engineering Systems

Artificial Intelligence (AI) is revolutionizing predictive maintenance by enhancing the reliability and efficiency of engineering systems. This paper examines the integration of AI technologies such as machine learning, deep learning, and natural language processing to predict equipment failures and optimize maintenance schedules. Through advanced data analytics, AI enables real-time monitoring, anomaly detection, and accurate failure prediction, minimizing downtime and operational costs. The study alsoaddresses challenges including data quality, algorithmic complexity, and system integration, and highlights potential advancements in AI-driven predictive maintenance. The findings underscore the transformative role of AI in improving the lifecycle management of engineering systems.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-22
DOI
https://doi.org/10.5281/zenodo.14716128
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in Predictive Maintenance of Engineering Systems

Zenodo (CERN European Organization for Nuclear Research)
Machine Fault Diagnosis Techniques
article

Artificial Intelligence in Predictive Maintenance of Engineering Systems

article en

Abstract

Artificial Intelligence (AI) is revolutionizing predictive maintenance by enhancing the reliability and efficiency of engineering systems. This paper examines the integration of AI technologies such as machine learning, deep learning, and natural language processing to predict equipment failures and optimize maintenance schedules. Through advanced data analytics, AI enables real-time monitoring, anomaly detection, and accurate failure prediction, minimizing downtime and operational costs. The study alsoaddresses challenges including data quality, algorithmic complexity, and system integration, and highlights potential advancements in AI-driven predictive maintenance. The findings underscore the transformative role of AI in improving the lifecycle management of engineering systems.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 48%
Machine Fault Diagnosis Techniques
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