Construcciones y Auxiliar de Ferrocarriles S.A. (CAF)

CAF is a multinational group with over 100 years of experience in the supply of comprehensive transit solutions. The company is a leader of the railway industry offering one of the most flexible arrays of products in railway related markets, such as rolling stock, components, infrastructure, signalling and services.

CAF has one of the widest ranges of rolling stock in the market. CAF designs, manufactures and maintains all types of vehicles, equipped with the latest technological advances in terms of safety, performance and comfort. The understanding of the needs of each client allows us to offer mobility solution. The CAF Group also incorporates a wide range of conventional and electric buses into its portfolio of mobility solutions. In this way, CAF is able to provide a better response to the needs of its customers in urban transportation, particularly in electric mobility and multimodal door-to-door solutions that are adapted to the particular needs of each transport authority.

CAF I+D, a member of the CAF Group, provides technological excellence to the Group in R&D activities such as structural calculations, railway dynamics, noise & vibration, EMC, fluids, energy, software development, hardware design etc.


Although our vehicles are equipped with service-proven solutions and guarantee optimal reliability throughout their entire life cycle, we are committed to sustained improvement. To improve the reliability of an electronic system, it is essential to have a deep understanding of its behavior in real service, and the best way of getting that knowledge is through real field data.

Taking advantage of CAF´s wide range of rolling stock products distributed worldwide, our role in the project will be to provide field information to analyze the effect of operational conditions to electronic reliability.

Key contribution

CAF’s effort will be mainly focused in guaranteeing that the field data provided for reliability calculations, simulation model fine-tuning, operational conditions’ influence analysis etc. is strictly reliable. A transition between manual data collection and automatic monitoring is foreseen, and mechanisms for both methods need to be defined.

CAF will contribute with:

  • Procedures for data collection and handling
  • Procedure for fault analysis and classification
  • Definition of infrastructures for automatic monitoring and data storage

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