Daydreams: Artificial Intelligence and Blockchain for Railway Maintenance

How to integrate and utilize artificial intelligence to support predictive and prescriptive maintenance of railway infrastructure.

The Daydreams project aims at integrating and using artificial intelligence to support predictive and prescriptive maintenance of railway infrastructure, within the framework of the so-called Intelligent Asset Management Systems (IAMS). In the three-year project, co-financed by the European Commission under the H2020 Shift2Rail program, Cefriel is involved in the development of a solution to support the integration of IAMS components, developed in collaboration with consortium partners.


Client

Companies in the railway infrastructure management sector

Typology
Service
Contact person

Ilaria Baroni

SCENARIO

Need

Shift in maintenance approach from a preventive-predictive to a prescriptive one;

Enhance operators’ decision-making process, considering all possible implications (even conflicting ones);

Strengthen the role of the individual in the maintenance process by designing and developing advanced interfaces to enable information-supported decision-making processes.

Solution

The framework developed by Cefriel enables predictive analysis of failures and optimization of planned maintenance in the railway sector, facilitating the sharing and reuse of data, software, and other digital artefacts, process reproducibility, and the creation of a secure environment, where various stakeholders involved in maintenance can collaborate.

Cefriel developed a catalogue of digital artefacts based on its KCONG asset, with an integrated execution environment and a process traceability solution based on blockchain infrastructure.

RESULTS

Impact

Facilitated creation of maintenance plans


Maintenance of railway assets can not only be predicted but also planned, providing the possibility to easily create and share maintenance plans.

Solution applied to 3 scenarios


Cefriel's solution enabled the integration into 3 realistic use cases, involving Hitachi, RFI, and STIMIO. Stakeholders experimented with it and positively evaluated the proposed solution.

Publication of scientific results


Cefriel published and presented the framework at the 10th Transport Research Arena (TRA) Conference 2024 and at the DaMaLOS Workshop during the Extended Semantic Web Conference (ESWC) 2023.

Sharing of digital artefacts in a catalog


A catalog of digital artefacts was created to enable and test the solution: 18 datasets, 8 software components, and 18 machine learning models.

MEDIA

Project's showcase

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