Railway maintenance especially on infrastructure
produces a vast amount of data. However, having data is not
synonymous with having information; rather, data must be
processed to extract information. In railway maintenance, the
development of KPIs linked to punctuality or capacity can help
plan and schedule maintenance, thus aligning the maintenance
department with corporate objectives.
There is a need for an improved method to analyse railway
data to find the relevant KPIs. The system should support
maintainers, answering such questions as what maintenance
should be done, where and when. The system should equip the
user with the knowledge of the infrastructure's condition and
configuration, and the traffic situation so maintenance resources
can be targeted to only those areas needing work. The amount of
information is vast, so it must be hierarchised and aggregated;
users must filter out the useless indicators. Data are fused by
compiling several individual indicators into a single index; the
resulting composite indicators measure multidimensional
concepts which cannot be captured by a single index.
The paper describes a method of monitoring a complex entity.
In this scenario, a plurality of use indices and weighting values
are used to create a composite and aggregated use index from a
combination of lower level use indices and weighting values. The
resulting composite and aggregated indicators can be a decisionmaking
tool for asset managers at different hierarchical levels.