Infralert

Publicerad: 21 juni 2016

Due to limited resources and limited land area, the only way to adapt the infrastructure capacity to the expected increased transportation demand is to optimise the performance of the existing infrastructure.

Infralert

Sponsors: EU, H2020
Researchers: Johan Odelius, Adithya Thaduri, Stephen Famurewa, Amir Garmabaki
Duration: 2015-2018
Webpage: http://infralert.eu/

The overall goal of INFRALERT is to improve the operability and functionality of linear asset transport infrastructures based on large-scale automated condition prediction, intervention alert management maintenance, RAMS & LCC analysis and renewal (M&R) planning to support decision making. INFRALERT will develop, deploy and exploit solutions that enhance the land transport network infrastructure performance and adapt its capacity to meet growing needs by:

  1. ensuring the transport infrastructure operability by optimising network functionality under traffic disruptions
  2. keeping and increasing the availability of the existing infrastructure by optimising tactical and operational maintenance interventions and assessing strategic long-term decisions on new construction
  3. ensuring infrastructure service reliability and safety by minimising incidences and failures.

An essential advancement to reach this goal is the development and implementation of expert-based Infrastructure Management System (eIMS) to coordinate and integrate all processes from measurements to decision support for maintenance & renewal. The eIMS will integrate various toolkits that are developed for the following functions: Data Management, Asset Condition, Alert Management, RAMS and LCC, and Decision Support (see Figure 1).  LTU is leading asset condition toolkit that include the methodologies to assess the current condition (nowcasting) and predict the future condition (forecasting). The key issues addressed are dynamic segmentation, condition uncertainty and hybrid modelling for more accurate forecasting.

The performance of the eIMS prototype is demonstrated in two case studies: rail and road use cases. The demonstrator for railway infrastructure in INFRALERT is under the responsibility of LTU with close collaboration with Trafikverket. The track sections to be considered in the demonstrator are the northern and southern loops of the Iron Ore Line in the Trafikverket’s network. For an objective evaluation of eIMS performance, a baseline case is defined covering necessary aspects required to evaluate INFRALERT’s goals. External Key Performance Indicator (KPIs) such as asset utilisation, service quality and financial effectiveness will be used for comparison of the baseline condition and the asset condition. 

Figure 1: INFRALERT eIMS - data to maintenance action coordination
Figure 1: INFRALERT eIMS - data to maintenance action coordination