Maintenance analysis and modelling for enhanced railway infrastructure capacity

Projekt:

JVTC

Sammanfattning:
Railway transportation is a sustainable mode of transportation for reasons of safety, cost, carbon emission and energy requirements. It has a notable role in economic expansion in terms of passenger and freight services. In recent years, there has been a continuous demand to increase the competitiveness of railway transport via quantity and quality of service delivered. For instance there is a growing need to shift a substantial volume of freight and passenger traffic to rail. To meet the demand for enhanced railway infrastructure capacity, large modification of the infrastructure, improvement of traffic planning process and improvement of maintenance and renewal process are required. The obvious solution would be capital expansion of infrastructure but this is a long-term cost-intensive approach for improving railway transport performance. This, therefore makes successive improvement of maintenance and renewal (M&R) process an ideal and feasible way of improving availability, capacity and service quality of existing railway infrastructure. This thesis addresses improvements in maintenance to enhance capacity and service quality through systematic maintenance analysis for effective planning and maintenance optimisation for efficient scheduling. This thesis is divided into two parts: the first part deals with maintenance analysis and the second addresses maintenance optimisation. Both parts are aimed at enhancing maintenance effectiveness by improving track possession utilisation and infrastructure integrity. The first part suggests assessment and analysis methods to support continuous improvement of railway infrastructure performance. It entails the use of historical operation and maintenance data to identify, improve and eliminate weak links and bottlenecks. The second part deals with planning and scheduling of maintenance tasks from condition deterioration viewpoint. This part uses infrastructure condition data with model driven approaches to schedule maintenance tasks with the aim of ensuring efficient use of track possession time and maximisation of availability and capacity. First, a fuzzy inference system is developed for computing the integrity index or composite indicator to relate maintenance functions to capacity situation. This is a good measure of the M&R need on a line as imposed by operational profile, capacity consumption and adopted maintenance strategy. It provides additional information that can be used to support high level M&R decisions for enhanced capacity. Second, risk matrix and an adapted criticality analysis method are proposed for identifying weak links and critical assemblies/items that are bottlenecks limiting operational capacity and service

Författare: Stephen Mayowa Famurewa
Utgivare: Luleå tekniska universitet
Utgivningsdatum: 2015-05
Diarienummer: TRV 2011/58769
ISBN: 978-91-7583-320-0
ISSN: 1402-1544
Antal sidor: 82
Språk: Engelska
Kontaktperson: Per Olof Larsson Kråik, UHjbs