This paper proposes a novel anomaly detection methodology for industrial systems based on Digital Twin (DT) ecosystems. In addition to DTs, conceived as a digital representation of a physical entity, this paper proposes a ...

This paper proposes a novel anomaly detection methodology for industrial systems based on Digital Twin (DT) ecosystems. In addition to DTs, conceived as a digital representation of a physical entity, this paper proposes a ...

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This paper presents a novel methodology in the field of Prognosis and predictive Maintenance (PdM) of industrial components. It has been designed as an inclusive PdM approach grounded on flexible strategies capable of ...

This paper describes a new methodology that aims to cover a gap detected in the area of detection of anomalies and diagnosis of industrial component behaviors: there is a need of robust procedures compatible with dynamic ...

La Industria 4.0 es ya una realidad. Los sistemas industriales que participan en la cadena de valor son cada vez más complejos e implementar estrategias de diagnóstico y pronóstico basadas en datos puede llegar a convertirse ...

Recommender systems are crucial in optimizing building energy consumption by offering personalized advice based on data analytics and user preferences. However, the need for explainable systems is emphasized to justify ...