The electrification of the transport sector is a prerequisite for the achievement of the Paris climatetargets, including freight transport. The planning of the necessary infrastructure for heavy-duty vehicles(HDVs) is subject to several uncertainties. A resilient network of charging stations is a requirement forthe successful electrification of the transport sector. The research objective is to develop a methodologyfor measuring resilience of a charging infrastructure, with the aim of quantifying the effect of removedand relocated stations. The focus is on a case study of synthetic HDV transport routes in Sweden. Theterm of resilience is defined as the network's capacity to maintain electric operations in the absence ofcertain components. This is evaluated using the analysis services of the Gordian SDSS via an API. ThisAPI, which relies on models for a transport electrification scenario, facilitates the evaluation andoptimization of a charging station network. The statistical data obtained from the evaluation is utilisedto calculate a resilience index based on the observed changes in fully electric transport work. The casestudy methodology employs a series of scenarios in which the removal of varying numbers of chargingstations is simulated for different network sizes. The study has revealed that denser networks exhibitedgreater resilience, with northern corridors identified as critical bottlenecks. A moderate negativecorrelation is discovered between the resilience index and eigenvector centrality, providing deeperinsights into network behaviour. Furthermore, the loss of resilience is found to be greater if more stationsare removed. To ascertain the impact of the relocation of stations, a series of distances for repositioningare being examined. It has been demonstrated that the precise location is of particular significance inthe context of thinner charging infrastructure networks, with the potential for greater loss of resiliencethe further the stations are relocated.