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Currently available work packages:
The Objective of WP3 is to design the generic architecture and to implement field installations for the setup of an Intelligent Asset Management System (IAMS) paving the way for the development of analytics and the integration with the TMS that WP4 will carry out.
WP4 will focus on the fine-tuning of the data collection processes, on the design refinement, development, and integration of analytics methodologies, and on the integrated demonstration at TRL 6/7 of the Use Cases (UC) defined in WP3 in line with the specific UC requirements and the guidelines of WP2. The objectives are to collect, process and analyse Diagnostic & Operation data coming from different railway systems to provide nowcasting and forecasting capabilities on the status of the monitored assets.
To define predictive and prescriptive functionalities with regards to asset status determination and intelligent maintenance thanks to WP3 data that will be fed to the analytics and to develop a Decision Support System (DSS).
The objective of WP5, addressing Rolling Stock, is to provide and develop technologies for on-board inspection and monitoring of Rolling Stock sub-systems and components, applicable for several line types. Relying on previous European projects such as PIVOT2 (GA ID: 881807) or PINTA2 (GA ID: 826054) where appropriate technologies for some assets like bogie and traction components, esp. for journal bearing and wheel monitoring, have already been successfully developed, WP5 will focus on those technologies that do not yet have reached necessary maturity level and to extend the monitoring range / application of existing technologies to further components by definition of physical parameters for anomaly detection.. Overall WP5 will provide technological foundations to fully leverage the value of data for rolling-stock asset management in WP6.
The objective of WP6, addressing Rolling Stock operating on different types of lines and under different climate conditions, is to design, develop, validate, and deploy at TRL 6/7 CBM (condition-based maintenance) based on ML (machine learning), predictive algorithms and digital process aids capable of supporting the railway maintainers, owners, and operators in the decision-making process. Even though, the focus of this WP will be on passenger trains, there will be a strong link with WP7 which also includes the monitoring of Freight.
This WP7 considers the integration of previous achievements in the railway sector on wayside monitoring, but also the development of new solutions applied for lines with cross-border and mixed traffic to create a more complete European Railway Checkpoint, including the required inputs for their basic specifications. The main objective is to provide and develop technologies for the installation of European Railway Checkpoints being control points in relevant sections of the TEN-T along the railway network with multiple arrays of sensing.
WP9 develops asset management solutions for the track structure, including plain track, switches, and crossings (S&C), catenary, and other elements of the track structure. Particularly, WP9 develops innovative wayside, onboard and crowd-based sensing solutions for the timely extraction of track infrastructure data. The data is converted into information/ knowledge using AI- and physics-based methodologies for anomaly detection and failure prediction. Then, the solutions are embedded into digital tools to support decision-making from existing and improved asset management platforms for track structure to reduce costs and increase safety, while considering constraints given by nowadays requirements on sustainability, resilience, trustworthy digitalization, and ethics.
The objective of this work package is to bring asset management solutions devised in the context of previous EU projects including those in Shift2Rail JU (i.e. IN2SMART and IN2SMART2) not mature enough at the next level of its application, and above all, explore and deploy the innovative solutions for the rail infrastructure subsystem in an operational environment with the focus on “short-term asset management” and off-site work preparation to be integrated as a multi-source/multi-purpose (MSMP) asset management platform. To fulfil this objective the focus is to provide – and apply – traceable diagnostic and prognostic information in a continuous manner based on embedded wayside and onboard sensors to support day-by-day decisions by maintenance experts and asset managers.
The objective of this work package is to conduct the main body of development for work in tasks including the demonstration of the applications conceptualized and started in WP 10 for the multi-source/multi-purpose (MSMP) asset management platform. The scientific development focuses on data analytics to utilize numerous waysides and train borne sensors including new sensor concepts and configurations. The necessary data sets are gathered in operational environment utilizing wayside and train-borne sensor systems in diverse EU member states such as Spain and the Netherlands operational environments and climate types providing the base for a successful cross-border and interoperable demonstration. at The detailed objectives of this work package are aligned with WP10.
Currently available deliverables:
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