Saipem has introduced an artificial intelligence (AI)-based predictive maintenance system onboard its ultra-deepwater drillship Saipem 12000, aiming to improve operational efficiency and offshore safety.
The system uses real-time data and artificial intelligence algorithms to monitor equipment conditions, predict potential failures and schedule interventions before issues occur. By anticipating faults, the approach is designed to reduce downtime and management costs.
The Saipem 12000, described by the company as one of the most advanced drillships in the world, is the first vessel in its drilling fleet to adopt the system.
The solution was developed in collaboration with ADC Energy, a company specializing in rig and vessel assurance. Continuous data analysis enables the timely detection of anomalies and the planning of targeted maintenance, increasing reliability and safety.
Saipem said the pilot project forms part of a broader innovation program aimed at extending artificial intelligence and data analytics across its fleet.
In line with that strategy, a predictive maintenance project is also being implemented on the Saipem 7000, one of the largest semi-submersible crane vessels in the world. The initiative focuses on diesel generators, which are critical for onboard power production.
Using IoT sensors and machine learning models, the system is designed to detect early signs of potential failures, allowing more efficient maintenance planning and supporting operational continuity.
The Saipem 7000 project is being developed in collaboration with BIP, an international consulting firm specializing in technological innovation and data science, and is scheduled to be tested in the coming months.
According to Saipem, the initiatives underscore its focus on integrating artificial intelligence, predictive analytics and advanced digital tools into offshore energy operations to enhance safety, efficiency and sustainability.
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