• The collaboration between the two organisations, which began in 2020, consolidates a strategic commitment to the digitalisation of the wind energy sector.

In the midst of the drive to improve the efficiency and reliability of wind energy, the Gipuzkoa-based company Laulagun Bearings, specialising in the design and manufacture of large bearings, and the technology centre IKERLAN have developed a digital twin that marks a turning point in the management of critical components in the sector.

The solution not only enables the behaviour of bearings under real operating conditions to be predicted, but also allows potential failures to be identified early, their nature to be analysed, and their evolution to be anticipated. This approach facilitates design optimisation and opens up new possibilities for improving operations, maintenance, and associated logistics. In a sector where a failure can translate into millions in costs and long periods of downtime —especially offshore— the ability to anticipate failure becomes a key factor in competitiveness.

The development combines multiscale physical models with real operational data, overcoming the limitations of approaches based solely on data. This cyber-physical integration makes it possible to connect the overall behaviour of the wind turbine with the detail of its components, generating more precise and actionable insights. Validated in test benches under representative conditions, the system not only predicts failures but also learns from real-world operation, closing the loop between field data and engineering.

“The real value lies in the ability to turn data into decisions”, says Mireia Olave, Head of the Mechanical Reliability Team at IKERLAN. 

“Operators can optimise maintenance, adjust operation, and even extend the useful life of assets with greater safety”. The figures reinforce this potential: up to a 20% reduction in unplanned downtime associated with bearings, and a 30% decrease in uncertainty regarding their useful life. In the offshore sector, where each intervention involves complex logistical operations and costs that can reach hundreds of thousands of euros per day, this predictive capability takes on strategic value.

Laulagun Bearings highlights that the impact of the project goes beyond technical product improvement. “The digital twin allows us to understand how our bearings actually behave in operation and to transfer that knowledge both to design and to the services we offer”, says Koldo Ostolaza, Head of R&D at Laulagun Bearings. “It is no longer just about manufacturing a component, but about supporting the operator throughout its entire lifecycle, helping them make better decisions, reduce risks, and maximise operational advantages”.

This approach reflects a shift in positioning: from an industrial supplier to a technology partner. The combination of data, simulation, and field experience makes it possible to deliver direct value in the operation of wind farms, improving availability and contributing to a reduction in total cost of ownership, with an impact on key indicators such as the levelized cost of energy (LCOE).

For IKERLAN, the project consolidates its position in the development of advanced digital solutions applied to mechanical and structural reliability, in a context in which maximising asset lifespan has become a priority for the energy sector. The system is currently in the validation phase in representative environments, with the aim of reaching a high level of technological maturity in the short term that will enable its deployment in operational turbines.

This initiative forms part of a sustained collaboration since 2020, which includes projects such as INNTERESTING, focused on new testing methods; MEEVCE I–II, aimed at extending the service life of components; and ICONIC, currently under development, which addresses the integration of digital twins into the intelligent management of wind farms. A track record that reflects a clear commitment to innovation applied to one of the sector’s major challenges: making wind energy more reliable, efficient, and competitive.

The technology enables real-time prediction of the behaviour of critical components, optimises their design, and improves operation and maintenance, with a particular impact in offshore environments