Saipem has implemented an advanced predictive maintenance system on the Saipem 12000, its ultra-deepwater drillship, aimed at improving operational efficiency and offshore safety.

Predictive maintenance uses real-time data and artificial intelligence algorithms to monitor equipment conditions, predict potential failures, and schedule interventions before problems occur, thereby reducing downtime and management costs.

The Saipem 12000, one of the most advanced drillships in the world, is the first vessel in the company’s drilling fleet to adopt this system, developed in collaboration with ADC Energy, a company specialized in rig and vessel assurance. Continuous data analysis allows for the timely detection of any anomalies and the planning of targeted interventions, increasing reliability and safety.

This pilot project, the result of the integration of Saipem’s technical expertise and ADC’s rig equipment and data science know-how, is part of a broader innovation process that aims to extend the use of artificial intelligence and data analysis to the entire fleet.

Aligned with this approach, a predictive maintenance project is being implemented on the Saipem 7000, one of the largest semi-submersible crane vessels in the world. Focused on the diesel generators, critical components for onboard power production, the project uses IoT sensors and machine learning models to detect early signs of potential failures. This allows maintenance to be planned more efficiently and ensures operational continuity. Developed in collaboration with BIP – an international consulting firm specializing in technological innovation and data science – the system will be tested in the coming months.

Through these projects, Saipem reaffirms its commitment to integrating artificial intelligence, predictive analytics, and advanced digital tools to make its offshore energy operations increasingly safe, efficient, and sustainable.