Automatic matching algorithms for assessing the similarity between striation marks have been investigated for bullet lands and some tool marks, such as screwdrivers. Here, we are interested in how well automatic algorithms can identify wires that are cut by the same tool in the same location to each other. In a forensic lab, this assessment is of interest to link evidence from multiple crime scenes. Using five previously unused Kaiweets wire cutters (model KWS-105) and aluminum wire (16 Gauge/1.5 mm, anodized), a total of 60 wire cuts was created. The cuts exhibit clear striation marks. From each scan, a representative profile (signature) across the striations was extracted. These signatures provide the basis for evaluating similarities of marks on different wires. The similarity between two signatures was quantified as the maximum of the cross-correlation (CCF). Initial assessment of an algorithmic evaluation of the similarity of wire cuts with functional data analysis shows promising results, with high CCF for cuts of the same source and low CCF for cuts from a different source.