One method to increase the quality of railway traffic flow is to construct a more robust timetable in which trains are able to both recover from delays and the delays are prevented from propagating. Previous research results show that the indicator Robustness in Critical Points (RCP) can be used to increase timetable robustness. In this paper we present the use of a method for RCP optimization, how can be implemented and assessed ex-post via microscopic simulation and subsequently evaluated. From the evaluation we learn more about how increased RCP values influence a timetable’s performance. The aim is to understand more about RCP increase at a localised level within a timetable in terms of effects to the pairs of trains that are part of the indicator. We present a case study where an initial timetable and a timetable with increased RCP values are evaluated. The ex-post evaluation includes the quantification of measures concerning train-borne delay and robustness of traffic flow, as well as measures capturing the subsequent quality of service experienced by passengers to assess the broader effects of improved robustness. The result shows that it is necessary to use several Key Performance Indicators (KPIs) to evaluate the effects of an RCP increase. The robustness will increase at a localised level, but the results also indicate that there is a need to analyse the relationship between ex-post measures and RCP further, to improve the method used to increase RCP and thus its overall effect on timetable robustness.