13 Aug 2024

Spain: Implementing Predictive Maintenance with Advanced Technologies

Case Study 3 minute read

Collaborating on research projects with European and Spanish organisations to integrate advanced technologies into predictive maintenance is a crucial step towards revolutionising railway operations management.

Belén Losada, Research and Development Manager

Challenge

Implement predictive maintenance to optimise infrastructure performance and reduce costs by leveraging advanced technologies. The goal is to intelligently manage field elements using information from the elements themselves, additional sensors, and data analysis tools. This involves managing various railway assets from different manufacturers to maximise performance and capacity while ensuring safety compliance.

Solution

Hitachi Rail, former GTS, has carried out the project "Research and development of a new railway predictive maintenance platform based on advanced technologies: Big Data, AI, IoT and DT", with an execution period from July 2022 to June 2024 in Serrano Galvache, 56 premises, and a budget of 1,215,601.43 euros. It has also been co-financed by CDTI and with funds from the European Regional Development Fund (ERDF).

Design and development of a new platform to aid decision-making related to predictive maintenance. This platform analyses the behaviour of the field elements distributed in the infrastructure by means of advanced technologies (Big Data, Artificial Intelligence, IoT, Digital Twins) allowing an intelligent management of these elements thanks to the information provided by the elements themselves, additional sensors and data analysis tools, for the optimisation of the infrastructure, planning of maintenance activities and, as a consequence, cost savings.

Impact

Hitachi Rail’s services play an essential role in the Spanish rail network, providing support to more than 2,800 km of high-speed lines.

For the implementation of the new platform, the project has been structured into different phases:

Investigation, analysis, and definition of requirements: This phase aims to determine the characteristics of the selected field elements, track circuits, and points with sensors; the procedures for data collection and processing; the monitoring environment; and the digital platform characteristics for decision-making.
Design and development of the digital platform: This phase focuses on obtaining information about the assets for data analysis and monitoring; implementing predictive measures; and applying these in maintenance activities.
Validation and functional tests of the digital platform: This phase ensures the successful implementation through proof of concept.

Cybersecurity standards have been followed in all project activities.