Zaharah Allah Bukhsh, MSc. - email@example.com
Supervisors: Dr. Irina Stipanovic, Dr.ir. A.G. Dorée
European rail infrastructure managers are managing the ageing rail infrastructure with 95% of the network having built before 1914. EU transport policy imposes the challenges on infrastructure managers to achieve cost-effective transportation operations by increasing the productivity of existing rail networks, prioritizing renewal and optimizing new sections to reduce bottlenecks (European Railway Agency, 2014, European Union, 2012). This needs to be achieved at a time when budgets are restricted whilst dealing with challenges from natural hazards and extreme weather events, which are affecting all of Europe . With the compelling need to prolong the lifetime of the infrastructure, to keep the maintenance cost minimum and to improve the availability of the highly engaged network, taking maintenance decisions have become a very critical task.
This research seeks to facilitate the infrastructure managers in taking maintenance decisions based on explicit data grounds. A maintenance decision require consideration of a number of factors, for instance (a) Effect on network operations, (b) Cost of maintenance and overall life cycle cost, (c) Criticality of an object in network , (d) Risk of failures and many others. A maintenance decision based on the critical evaluation of these factors will improve the network availability as well as result in a cost-effective maintenance activity. Therefore, processing of such maintenance decision questions foster three main requirements (see Jardine et al.(2006):
- Need of data values of various factors, e.g. assets' conditions, available budgets and cost limits, network schedule, etc;
- Need of a decision support model for analysis of data and comparison of various maintenance alternatives;
- Need of computerized decision support tool to minimize the chances of human errors and to improve the visualization.
The aim of this research is to develop a decision support tool based on comprehensive model that provides interactive visualization of various maintenance alternatives and recommend the best maintenance option based on assets' condition, minimal effect on network operations and optimal cost values.
Architecture of Decision support tool