Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0 DOI Creative Commons
Emilia Mikołajewska, Dariusz Mikołajewski, Tadeusz Mikołajczyk

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(6), С. 3166 - 3166

Опубликована: Март 14, 2025

Generative AI (GenAI) is revolutionizing digital twins (DTs) for fault diagnosis and predictive maintenance in Industry 4.0 5.0 by enabling real-time simulation, data augmentation, improved anomaly detection. DTs, virtual replicas of physical systems, already use generative models to simulate various failure scenarios rare events, improving system resilience prediction accuracy. They create synthetic datasets that improve training quality while addressing scarcity imbalance. The aim this paper was present the current state art perspectives using AI-based DTs 4.0/5.0. With GenAI, enable proactive minimize downtime, their latest implementations combine multimodal sensor generate more realistic actionable insights into performance. This provides operational profiles, identifying potential traditional methods may miss. New area include incorporation Explainable (XAI) increase transparency decision-making reliability key industries such as manufacturing, energy, healthcare. As emphasizes a human-centric approach, DT can seamlessly integrate with human operators support collaboration decision-making. implementation edge computing increases scalability capabilities smart factories industrial Internet Things (IoT) systems. Future advances federated learning ensure privacy exchange between enterprises diagnostics, evolution GenAI alongside ensuring long-term validity. However, challenges remain managing computational complexity, security, ethical issues during implementation.

Язык: Английский

Generative AI in AI-Based Digital Twins for Fault Diagnosis for Predictive Maintenance in Industry 4.0/5.0 DOI Creative Commons
Emilia Mikołajewska, Dariusz Mikołajewski, Tadeusz Mikołajczyk

и другие.

Applied Sciences, Год журнала: 2025, Номер 15(6), С. 3166 - 3166

Опубликована: Март 14, 2025

Generative AI (GenAI) is revolutionizing digital twins (DTs) for fault diagnosis and predictive maintenance in Industry 4.0 5.0 by enabling real-time simulation, data augmentation, improved anomaly detection. DTs, virtual replicas of physical systems, already use generative models to simulate various failure scenarios rare events, improving system resilience prediction accuracy. They create synthetic datasets that improve training quality while addressing scarcity imbalance. The aim this paper was present the current state art perspectives using AI-based DTs 4.0/5.0. With GenAI, enable proactive minimize downtime, their latest implementations combine multimodal sensor generate more realistic actionable insights into performance. This provides operational profiles, identifying potential traditional methods may miss. New area include incorporation Explainable (XAI) increase transparency decision-making reliability key industries such as manufacturing, energy, healthcare. As emphasizes a human-centric approach, DT can seamlessly integrate with human operators support collaboration decision-making. implementation edge computing increases scalability capabilities smart factories industrial Internet Things (IoT) systems. Future advances federated learning ensure privacy exchange between enterprises diagnostics, evolution GenAI alongside ensuring long-term validity. However, challenges remain managing computational complexity, security, ethical issues during implementation.

Язык: Английский

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