Case Study: Metro de Madrid achieves predictive maintenance for tunnels and faster data analysis with MathWorks (MATLAB)

Metro de Madrid Adopts Machine Learning for Predictive Maintenance in Tunnels

Metro de Madrid faced the challenge of analyzing more than 10 GB of new daily data from many different sensors to support predictive maintenance in tunnels. Existing tools only handled single-sensor analysis and lacked domain-specific customization, so Metro de Madrid worked with MathWorks and used MATLAB, MATLAB Compiler, and the Statistics and Machine Learning Toolbox to integrate and customize their signal analysis workflows.

Using MathWorks' MATLAB platform and toolboxes, Metro de Madrid automated data merging, signal analysis, and algorithm sharing with non‑MATLAB users, and developed a catenary degradation model to anticipate and optimize maintenance actions. The MathWorks solution saved time in data validation and analysis, integrated heterogeneous data sources, and enabled widespread use of advanced algorithms, improving the metro’s predictive maintenance capabilities.

Metro de Madrid

Raúl Rico

Metro de Madrid