Förstasida | Sök | In English

Luleå tekniska universitet

Doctoral thesis / 2008:19

Hämta PDF ( PDF 7257 kb )
TITEL
Maintenance performance indicators (MPIs) for railway infrastructure: identification and analysis for improvement

FöRFATTARE
Åhrén, Thomas

INSTITUTION
Samhällsbyggnad / Drift och underhållsteknik

SAMMANFATTNING
With increasing awareness that maintenance not only ensures safety and track performance, but also creates additional value in the business process; many infrastructure managers and owners are treating maintenance as an integral part of the business process. This is also true for the Banverket (Swedish National Rail Administration). One key issue for Banverket is to verify that the undertaken maintenance activities provides expected results, measured through maintenance performance indicators (MPI) related to technical, economical, and organizational issues. It is also necessary to classify the degree of effect for every single MPI, i.e. to create a logical cause-and-effect structure.

The main purpose of this research work is to identify and study the existing operation and maintenance performance indicators related to railway infrastructure, their application in short term and long-term perspective to analyse their usefulness for operation and maintenance planning of the railway infrastructure. Furthermore, the study is to find a structured, reliable, and cost effective method using maintenance performance indicators (MPI) such as OEE-values to facilitate the operation and maintenance decision making process both in short term and long term perspective for the railway infrastructure management.

A study at Banverket shows that 10 MPIs out of 17 identified ones are in use, where eight of them match the MPIs identified through the documents and two additional ones identified through interviews. Two conducted case studies at Banverket and Jernbaneverket, the Norwegian rail administration, shows that it is possible to quantify and benchmark MPIs between different countries. The comparison from the Iron Ore Line between Kiruna and Narvik indicated more or less the same rail and track related maintenance costs per track kilometre in Norway as in Sweden. The overhead cost per track kilometre results in 12 times higher costs for Jernbaneverket due to different track length in Norway and Sweden, though the number of employees in the infrastructure manager organization work force was the same in both countries.

A case study evaluating technical and financial aspects of grinding campaigns on the track section between Kiruna and Riksgränsen shows that the grinding campaign postpone major rail replacements activities into the future. The yearly cost for grinding and renewal is an example of an aggregated MPI that can be used for future follow-ups and benchmarking. The grinding campaign itself seems not to affect the total system in a negative way.

One important issue for the infrastructure manager is to focus on the overall railway infrastructure effectiveness. A model for calculating the overall railway infrastructure effectiveness (ORIE) is presented in this thesis. Performed case studies on three track sections shows similar ORIE figures that are significantly higher than the industry OEE, which is required for a punctual railway transportation system. The study indicates that ORIE must be calculated on a monthly basis. The findings of the ORIE and calculation are 89.7 - 100% ORIE values. The findings indicate that ORIE can be used as a key performance indicator by the railway infrastructure manager. It is also visualized that ORIE can provide important input and support in decision making for the infrastructure managers.

A railway infrastructure maintenance link and effect model (LinkEM), that supports the overall objectives and focuses on critical strategic areas determined by the nature of the railway industry and public requirements and regulations is suggested.

To conclude, in this research study relevant MPIs for effective management of operation and maintenance of the railway infrastructure are identified and analyzed. Further, models like LinkEM and ORIE are suggested for the railway infrastructure managers to facilitate in the decision-making.

ISSN 1402-1544 / ISRN LTU-DT--08/19--SE / NR 2008:19

Förstasida | Sök | Universitetet | Biblioteket


Till biblioteket
LULEÅ UNIVERSITETSBIBLIOTEK