Saipem introduces AI-based predictive maintenance system aboard Saipem 12000

Saipem implemented a 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 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.

A predictive maintenance project is also being implemented on the Saipem 7000, a large semisubmersible crane vessel. 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.