Latest revision as of 01:10, 2 February 2021

Abstract

Rail infrastructure managers must work with increasing sustainably and efficiency as they are faced with increasing cost pressure. Against this background track engineers face a growing difficulty in legitimizing essential measures owing to strict budget restrictions. This situation requires an objective tool enabling a proper condition monitoring as well as component-specific, preventive maintenance planning.
The present research deals with such an evaluation of railway track condition using innovative track data analyses. Applying functional knowledge - both IT and railway skills – allows for extracting smart data out of big data for railway asset management. Due to a bottom-up approach this methodology enables both the establishing of net-wide maintenance and renewal demands and an in-depth assessment of specific track sections. The planning of specific renewal and maintenance measures for track sections and also strategic asset management will thus both be possible on a net-wide scale.

Original document

The different versions of the original document can be found in:

• https://zenodo.org/record/1445928 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

• https://zenodo.org/record/1445928,

http://dx.doi.org/10.5281/zenodo.1445927 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

• https://zenodo.org/record/1445928,

http://dx.doi.org/10.5281/zenodo.1445928 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

DOIS: 10.5281/zenodo.1445928 10.5281/zenodo.1445927