Research Article Transportation Research Record 1–12 Ó National Academy of Sciences: Transportation Research Board 2020 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0361198120946007 journals.sagepub.com/home/trr Measurement Data-Driven Life-Cycle Management of Railway Track Johannes Neuhold 1 , Matthias Landgraf 1 , Stefan Marschnig 1 , and Peter Veit 1 Abstract Track engineers face increasing cost pressure and budget restrictions in their work today. This leads to growing difficulty in legitimizing crucial maintenance and renewal measures. As a result, infrastructure managers must ensure they invest all avail- able financial resources as sustainably and efficiently as possible. These boundary conditions require an objective tool enabling both a component-specific condition evaluation and preventive maintenance with renewal planning. The present research introduces such a tool for railway tracks based on innovative track data analyses. This tool includes time-series analyses for predicting future quality behavior. Consequently, the technical necessity of maintenance actions can be derived for every spe- cific track section. In addition, these technical evaluations are combined with economic and operational considerations to plan reasonable maintenance lengths for different track components in the next few years. In a further step, business evalua- tions by means of annuity monitoring are executed to determine whether ongoing track maintenance or complete track renewal is the most economical solution. This methodology also allows calculating the economic damage caused by neglecting the ideal point in time for reinvestment. On the basis of this economic damage, it is possible to rank projects by priority in the case of insufficient budgets and to ensure that all available resources are invested in the most reasonable manner possible. Furthermore, such analyses clearly show that when a specific degradation level of railway track is reached track renewal is more economic in relation to life-cycle costs than ongoing maintenance. The main tasks of an infrastructure manager are guaran- teeing safe railway operation and a high availability of track simultaneously. This area of responsibility is sum- marized by the term asset management. Asset manage- ment focuses on three main issues (1):  Balancing maintenance, renewal, and enhancement.  Linking infrastructure managers and contracting companies.  Combining the strategy and its implementation based on evidence-based decision making. Managing railway infrastructure and especially rail- way tracks as one of the main cost-drivers is a compre- hensive task. Railway tracks have high initial investment costs and require extensive maintenance to reach their expected service lives. For example, the O ¨ BB Infrastruktur AG’s budget for 2018 equaled 873.1 mil- lion euros for renewal and expansion plus 561.1 million euros for maintenance of the existing Austrian rail net- work (2). For diligent and sustainable handling of these budgets, a proper asset management must consider life- cycle costs (LCCs) instead of only taking short-term investment costs into account. The LCCs of railway tracks are mainly defined by depreciation, maintenance, and costs of operational hindrances (3). As the service life, and therefore the resulting depreciation, is a main factor in the LCC analyses of railway tracks, annuities (4) are used for the economic investigations. This allows for the comparison of different cases with varying life spans. From an economic point of view, depreciation decreases with increasing service life. As long as depreci- ation is the main influencing factor, decrease follows an exponential function as a result of the 1/n-relation. The costs of maintenance and, consequently, the costs of operational hindrances, however, are becoming a grow- ing factor over time. As a result, annuities reach their minimum when the incremental decrease of depreciation is lower than the incremental increase of maintenance 1 Institute of Railway Engineering and Transport Economy, Graz University of Technology, Graz, Austria Corresponding Author: Johannes Neuhold, johannes.neuhold@tugraz.at