AI-Driven Predictive Maintenance

Ünlü, Ramazan; Söylemez, İsmet

doi:10.1007/978-981-97-5979-8_10

Springer Tracts in Nature-Inspired Computing

2024

DOI: 10.1007/978-981-97-5979-8_10

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AI-Driven Predictive Maintenance

Ramazan Ünlü,

İsmet Söylemez

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Cited by 2 publications

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Enhancing asset management: Integrating digital twins for continuous permitting and compliance - A systematic literature review

Alhadi,

Dr Tom,

Yacine

2025

Journal of Building Engineering

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Enhancing asset management: Integrating digital twins for continuous permitting and compliance - A systematic literature review

Alhadi,

Dr Tom,

Yacine

2025

Journal of Building Engineering

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AI-Driven Predictive Maintenance in Data Infrastructure: A Multi-Modal Framework for Enhanced System Reliability

Madhukar Dharavath

2024

Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol

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This article presents a comprehensive framework for implementing artificial intelligence-driven predictive maintenance in modern data infrastructure environments. While traditional maintenance approaches have relied on reactive or scheduled interventions, the proposed framework leverages multiple AI technologies, including machine learning, natural language processing, and reinforcement learning, to create a proactive maintenance ecosystem. The methodology integrates diverse data streams from infrastructure components, including sensor data, system logs, and historical maintenance records, to predict potential failures and optimize maintenance schedules. The approach combines time series analysis for trend identification, natural language processing for unstructured data analysis, and reinforcement learning for dynamic schedule optimization. Implementation across multiple case studies, including cloud service providers and manufacturing environments, demonstrates significant improvements in system reliability, reduction in unplanned downtime, and optimization of maintenance resource allocation. The results indicate that AI-driven predictive maintenance substantially outperforms traditional approaches in both accuracy and cost-effectiveness. This article contributes to the growing field of intelligent infrastructure management and provides practical guidelines for organizations seeking to enhance their data infrastructure reliability through advanced predictive maintenance strategies.

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AI-Driven Predictive Maintenance

Cited by 2 publications

References 36 publications

Enhancing asset management: Integrating digital twins for continuous permitting and compliance - A systematic literature review

Enhancing asset management: Integrating digital twins for continuous permitting and compliance - A systematic literature review

AI-Driven Predictive Maintenance in Data Infrastructure: A Multi-Modal Framework for Enhanced System Reliability

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