This paper describes the implementation phase of the Intelligent Asset Management System (IAMS), developed within the Shift2Rail IN2SMART project, under test and validation within its follow-up project, IN2SMART2. The innovative approach to Asset Management is based on techniques and models for data analysis and decision support, able to take into account the knowledge on asset status, the operational constraints of the rail sector and the main target for rail operators. The aim is to move towards an automated decision process and a reduction of human effort in decision-making. The IAMS prototype development and validation is described. In addition, the in-field implementation to the signalling system of an Italian metro line is presented, describing the designed additional functionalities of the system, as well as the considered Key Performance Indicators for its test and the benefits of the approach.

Validation of data analytics and optimization algorithms within an Intelligent Asset Management System for rail signalling [Validazione di algoritmi di analisi dati e di ottimizzazione nell’ambito di un sistema intelligente di Asset Management per il segnalamento ferroviario]

Alice Consilvio;
2020-01-01

Abstract

This paper describes the implementation phase of the Intelligent Asset Management System (IAMS), developed within the Shift2Rail IN2SMART project, under test and validation within its follow-up project, IN2SMART2. The innovative approach to Asset Management is based on techniques and models for data analysis and decision support, able to take into account the knowledge on asset status, the operational constraints of the rail sector and the main target for rail operators. The aim is to move towards an automated decision process and a reduction of human effort in decision-making. The IAMS prototype development and validation is described. In addition, the in-field implementation to the signalling system of an Italian metro line is presented, describing the designed additional functionalities of the system, as well as the considered Key Performance Indicators for its test and the benefits of the approach.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1023395
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