Tunnel boring machines (TBMs) are critical pieces of equipment in tunnel construction. Their availability and utilisation rate determine the progress of the project. An unexpected failure can halt operations for long periods or reduce excavation performance, significantly affecting project timelines and budgets.

TBMs are highly complex, highly mechanised, and digitised machines — essentially factories that advance as they excavate — making them ideal candidates for the development of predictive maintenance analytics. Moreover, the repetitive nature of TBM work cycles helps in identifying anomalous patterns compared to normal operating conditions.

Currently, preventive maintenance strategies are used to prevent machine failures, in which inspection and maintenance are performed according to a planned schedule. However, there are no technologies that allow these failures to be anticipated ahead of time and enable maintenance work to be adapted to the real needs of the process.

In addition, predictive maintenance enables remote monitoring of the machine’s condition and performance, even during normal operation, allowing operational adjustments that increase performance.

Predictive maintenance allows failures in critical TBM systems to be anticipated through advanced analysis of operational data, reducing unplanned downtime and safety risks. Its application optimises the actual service life of components and improves productivity without compromising equipment reliability.

This evolution opens the door to new value models for ACCIONA, such as predictive maintenance as a service or Machine-as-a-Service schemes, ensuring availability and performance of key assets such as the main bearing, hydraulic systems, electrical systems, and conveyor systems.

ACCIONA is launching this challenge to identify solutions that help define and integrate its own predictive maintenance system for TBMs — including hardware, predictive models, and software.

We seek to identify and prioritise the best predictive techniques and apply them in one of our international projects.

The objectives for this challenge include:

• Increasing operational availability of the TBM

• Improving excavation performance

• Extending the service life of components