Maritime systems operate in highly dynamic environments where unexpected equipment failures can compromise safety, reliability, and operational efficiency. Recent advances in artificial intelligence (AI), machine learning, digital twins, and predictive maintenance enable proactive failure prediction and prevention. How...
Dionisis Kalogeropoulos, Georgia Sovatzidi, P. Kalozoumis et al.· 0 citations
Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper proposes an explainable decision-making framework that integrates a neuro-fuzzy prediction model with a two-stage explainable component. The first stage of this component p...
Dionisis Kalogeropoulos, Georgia Sovatzidi, D. Iakovidis· 0 citations
The shipping industry has a significant impact on the global economy, emphasizing the need for operational availability and safety through the use of effective maintenance techniques. During the last decades, predictive maintenance (PdM) has emerged as a promising solution compared to the existing conventional maintena...
Dionisis Kalogeropoulos, Georgia Sovatzidi, P. Kalozoumis et al.· 0 citations
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