LLMs as Cognitive Partners in Shipping 4.0: An Extend AI Approach to Maritime Predictive Maintenance Training

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This paper explores the integration of Generative AI (Gen AI) and Explainable AI (XAI) into Predictive Maintenance (PdM) within the Shipping 4.0 framework for educational use. The authors propose a conceptual framework called IPMDP (Intelligent Predictive Maintenance Decision Process for Education), which involves an architectural approach (System-of-System, SoS) for integrating LLMs (Gen AI approach) into the predictive maintenance of marine engines and systems, in order to support decision-making in the maintenance of systems at sea. The central idea of the conceptual framework lies in the utilization of a decision-making model using Gen AI techniques through the ExtendAI framework, which functions as a “cognitive partner” to a ship’s engine room crew. The ultimate goal is the educational use of such a framework in the training of Merchant Marine engineers and other ship engine room personnel. Essentially, this study is a conceptual framework paper, integrating existing models and literature to propose a novel application domain, rather than presenting original empirical findings.  This cognitive maintenance approach improves operational safety and ensures human-centric, accountable decision-making, which is crucial for regulatory compliance and effective adoption in the maritime industry.