October 1, 2025Open Access

AI-Driven Predictive Maintenance for Industry 4.0: A Systematic Review of Models, Methods, and Challenges

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Systematic review evaluates predictive maintenance methods and challenges in industry 4.0, indicating significant barriers to implementation.

Challenges in predictive maintenance include real-time deployment and model robustness, which hinder effectiveness.
This research presents a taxonomy tracing the evolution of maintenance strategies, from corrective to predictive paradigms.
Machine learning algorithms like deep neural networks and Random Forests are evaluated for their application in predictive maintenance.
Future research avenues include prescriptive maintenance and advancements in explainable artificial intelligence.

Alaoui et al. (2025) studied this question.

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Systematic review evaluates predictive maintenance methods and challenges in industry 4.0, indicating significant barriers to implementation.