This systematic review examines how Multi-Agent Systems can be combined with Digital Twins for predictive maintenance, especially in distributed and resource-constrained industrial environments. Based on a critical analysis of more than 547 papers from venues including IEEE Transactions, Nature, Elsevier, and MDPI, it proposes a taxonomy of hybrid architectures and identifies three open questions: AI deployment on constrained microcontrollers, distributed coordination through lightweight protocols, and hierarchical orchestration of Digital Twins with remaining-useful-life estimation and explainable AI. The authors argue that no current system integrates all three requirements into an embedded, distributed, hierarchical solution for Industry 5.0.
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