## 7 Conclusions  
DB Station&Service AG is the infrastructure operator responsible for station assets in Germany. These infrastructure assets are to be kept in an acceptable and serviceable condition through maintenance and replacement measures. DB Station&Service AG receives funding from the German federal government for replacement measures. In return, the infrastructure must meet an agreed target quality. The quality of the station infrastructure is measured by the BAQ grade. All the assets in DB Station&Service AG's inventory are weighted so that, in the end, a nationwide grade describes the condition of the infrastructure in the nation. However, since there was no known direct relationship between the financial resources used and the quality of the infrastructure assets, a cause-effect relationship was established and modeled for station infrastructure based on the BAQ grade. For this purpose, degradation models for different asset classes of station infrastructure were determined based on available data. Furthermore, the effects of replacement and maintenance measures were determined from the data. In principle, the technical service life of an individual asset class is used to decide the type of measure (replacement or maintenance). Prices for the measures are stored in the model so that a connection between measures and costs can be established. In addition, intervention thresholds must be defined in the model, above which interventions by means of a measure have to be taken. The developed model can be used to predict the quality of infrastructure in the form of the BAQ grade by applying the available budget. The model considers the current quality conditions and characteristics, such as the age of the assets, as well as the budget available for renewal and maintenance in addition to the costs for those measures. Further parameters, such as budget allocation and prioritization strategy, can be selected. The expected quality is output each year. The measures that are implemented in the model depend largely on the budget allocation of the total budget to asset classes and the prioritization strategy used. Various scenarios can be simulated with the model, and the effects on infrastructure quality can be analyzed. The cause-effect relationship for the infrastructure assets of DB Netz AG can also be used to test various scenarios [6; 9]. The validation of the models was based on historical condition data. These were used to reproduce the actual BAQ grades in recent years by means of prediction. The prediction of this historical data provided suitable and plausible results. In this paper, four different scenarios were examined. The prioritization of the measures in particular was shown to have a major influence on the expected quality. Here, the BAQ grade improves in scenarios where the available budget is used for measures that have the greatest impact on the BAQ grade. If measures are selected based on the condition of the assets, the BAQ grade deteriorates compared to the other scenarios. By comparing and analyzing these scenarios, further conclusions can be drawn in addition to expected quality. It can be seen, for example, that the weighting, and thus the methodology used to determine the BAQ grade, create false incentives for management. From a business point of view, it does not necessarily make sense to use the BAQ grade as the sole optimization criterion for the condition of assets. Although relatively good BAQ grades can be achieved in this way, asset classes with a low impact on the BAQ grade are neglected and do not receive any financial resources; therefore, the serviceability of these assets is at risk in the long-term. Hence, by adapting and further developing the BAQ methodology, the avoidance of the formation of disincentives should be ensured. Adjustments to the method include the different weightings of the asset classes on the one hand and the weighting of the stations on the other.