Shima Fahima
The presentation illustrates the shift from a reactive and isolated approach in industrial monitoring to a proactive and integrated one.
It presents the layered architecture of the digital twin, which combines real-time data, physical models, and predictive analytics through machine learning.
A case study of a 70MW gas turbine demonstrates significant benefits: improved predictive maintenance accuracy, operational improvements, and substantial cost savings.
Challenges such as integration with legacy systems, cybersecurity, and initial costs are also discussed, offering practical guidelines for implementation.
Technology confirms itself as a strategic competitive advantage for the energy sector.
