Machine learning models, deep learning architectures, and AI applications across the industrial and engineering domains.
Moving beyond conventional digital twins, this collaboration aims to create comprehensive, physics-based virtual representations of entire industrial environments. The initiative will enable more holistic simulations and AI-driven insights for design, manufacturing, and operations, promising a new level of system-wide optimization.
Engineering.comThe Saipem 12000 is now equipped with an advanced AI-based system to predict equipment failures and optimize maintenance schedules. This marks a significant step in applying predictive analytics to offshore drilling operations, aiming to enhance safety, reduce downtime, and lower operational costs.
SaipemSidharthenee Nayak, Victor Sam Moses Babu, Chandrashekhar Narayan Bhende, Pratyush Chakraborty, Mayukha Pal
Addressing the challenge of fault detection in power systems, this research proposes a deep learning approach using autoencoders. The model achieves high accuracy in identifying faults on both simulated and real-world datasets, offering a promising solution for enhancing grid reliability.
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