Mantenimiento ferroviario del futuro
Antetítulo de la cabecera
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Approach
Challenge
The future vision of Renfe Manufacturing and Maintenance entails a technological, operational, and cultural transformation that will change the way we currently work, gaining agility and efficiency in processes, extracting greater value from data, and facilitating the operability of interventions.
Adapting different maintenance processes to the paradigm of Industry 4.0 has become one of the main challenges. The digital transformation of maintenance must align versatility, responsiveness, and product quality in an interconnected environment equipped with new intelligent technologies to optimize maintenance management and facilitate decision-making.
We are looking for innovative technological projects in the field of railway manufacturing and maintenance, focused on digitization and the incorporation of new Industry 4.0 technologies (IoT, Big Data, augmented reality, additive manufacturing, computer vision, etc.).
What we're looking for
Challenge
Below are examples of potential solutions for this challenge; however, candidates may propose any solution not included as long as it aligns with the challenge:
- Solutions that facilitate data capture by operators in production processes (maintenance, inspection forms, controls, etc.) through voice recognition technologies, data capture via cognitive automation, robotic process automation, etc.
- Monitoring systems for facilities (maintenance bases) that allow for knowing the status of key elements and acting quickly in case of breakdowns thanks to a self-diagnostic system.
- Digital twin implementation solutions that allow for the optimization of railway maintenance bases.
- Solutions for sensorization and IoT connectivity for the implementation of predictive maintenance for all rolling stock (locomotives, freight wagons, and short, medium, and long-distance trains).
- Augmented reality solutions to support work in workshops.
- Solutions for automating visual inspection of trains in workshops, recording relevant information, and detecting faulty parts.