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Implementation proposal of new systems through IoT, to develop the Predictive Maintenance in the High Speed Railways Infrastructures & Systems.


Author/s: Israel Herrero Sánchez

Railway infrastructure and superstructure are a complex system with a long service life. Their performance will depend on the maintenance and renewal decisions that are made during their life cycle. In the current scenario, most maintenance decisions are based on past experience and expert estimates through a combination of preventive and corrective tasks with a low predictive maintenance implementation.

IoT is the fundamental technological component on which the paradigm of Industry 4.0 is based. The inclusion of IoT in preventive maintenance of railway infrastructures and systems will seek to preserve the role of the teams by applying efficient maintenance, inspection and asset control strategies to optimize operational reliability and the availability of railway lines by maximizing in this way the profitability of the operation. For this reason, the application of intelligent technologies (IoT) is proposed through an own maintenance network that allows to optimize the maintenance of the railway infrastructure and superstructure through an adequate management of the operations based on computational intelligence techniques, developing algorithms that allow to define the patterns, calculate the operations of the equipment and learn about the life cycle of the installed components. The article represents and proposes the use of innovative detection technologies as well as their application in many areas for supervision and monitoring of the state of the infrastructure and railway superstructure. It must be taken into account that all the sensorics must comply with minimum quality control for its operation outdoors and the necessary interfaces to adapt it to the new network.

Keywords: Internet of Things (IoT), Railway Infrastructure and Superstructure, Predictive Maintenance, CBM (Condition Based Monitoring/Maintenance), RCM (Reliability Centred Maintenance), Cloud Computing, Big Data, Business Intelligent.

Publication: Vía Libre Railway Research Nª 14 - 2018


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