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Guest article

Determining the economic service life, a function of Life Cycle Management

The railway transport system faces increasing demands. Innovation enables the railway to respond to these demands appropriately. Life Cycle Management at the centre of Asset Management also answers the questions about economic efficiency of innovations.

Guest article
Univ.-Prof. Dipl.-Ing. Dr. techn. PETER VEIT, Chair of the Institute for Railway Engineering & Transport Economy, Graz Technical University

Life cycle management ensures a system-compatible optimised selection and use of assets.

Asset management is to ensure optimum use of existing assets and identify the areas of use of different innovative and existing track components that are dependent on many boundary conditions. In order to enable a comprehensive evaluation, modern asset management has to consider all modes of action of different components, maintenance options and times of re-investment. This can only be done within life cycle assessments.

Learning to understand track behaviour

Designing models for evaluation far exceeds the issues of economic evaluations. The necessity to take into consideration the effect of different options over the whole service life requires behaviour forecasting, i.e. maintenance forecasts. These in turn presuppose an understanding of the track behaviour, be it from specific trend analyses of existing data or – in the case of investment – from overlaying general findings with technically deduced expectations or with initial results from line testing. Furthermore, different track types, maintenance strategies and implementations of work require different possessions. Therefore, the cost of operating complications must also be included in the evaluation.

Determining the economic service life is a continuous task but one which then allows the determination of the optimum time of re-investment in a track section. Therefore, the decision needs to be made whether to continue with maintenance or re-invest.

Maintenance vs. investment

Assets have different service lives, for the issues under consideration here the technical and economic service lives are of relevance. The latter is shorter as the need for maintenance increases considerably towards the end of the technical service life. Extending the service life reduces the annual depreciation; however, this is usually at the cost of an increase in maintenance. Therefore, one has to compare the “depreciation over the service life” with the “maintenance over the service life” to determine the optimum (Figure 1).

An integral view of the track / link between asset management and life cycle management

Asset management and life cycle management are interrelated/interdependent functions. Asset management without any corresponding technical data is without any foundations. Evaluating only current technical data is also unrealistic as the long-term effects and operational consequential costs are not taken into account. Therefore, asset management has to rely on direct access to all technical track data to be able to forecast the track behaviour using analyses and technical understanding. It is also necessary to understand operational principles for the implementation of cost consequences in the economic evaluation methods to be able to obtain comprehensive evaluations that meet the requirements of the railway system.

The future of Life Cycle Management

Currently, life cycle management is extended onto all components of the track system. This is also reflected in research. New methods of analysis for existing data and integration of new data sources with the use of tools such as Big Data or digitalisation are high on the agenda to make new forecasts possible or existing ones more accurate. New tools supply new data but don’t generate knowledge as such. This is and will remain the remit of the processors. Currently, investigations are underway on the significance of Fibre Optic Sensing. The use of power spectral density for specific track components is being analysed, and the use of additional sensors for data capture is investigated. In future, data that is captured during track maintenance work will help to make more accurate forecasts. All this also requires further efforts for the development of adequate evaluation methods to strengthen the future role of life cycle management as an integral component of the railway (infrastructure).