Exploration of striation-based 3D print source evaluation

Over the last decade, international police have witnessed a steady rise in criminal activity related to three-dimensional (3D) printed firearms, documenting seizures of blueprints, components, whole 3D printed firearms as well as 3D printers. Investigators have determined traditional firearm examination techniques are insufficient to facilitate source printer of 3D printed firearms instead requiring foundational research and adapted forensic methodologies that will better suit the novel toolmarks. Therefore, the current study aimed to bridge the gaps in understanding of 3D print to printer relationships. The study conducted a comprehensive examination of 3D printed items manufactured by five UltiMaker S5 3D printers to establish the presence and persistence of nozzle deposited markings; known as drag marks, between 3D prints of the same make and model, as well as assessing their potential for source information. The feature exhibited a strong potential to discriminate to specific UltiMaker S5 printers. To further assess drag marks utility in a forensic scenario, exclusion-based decision trees were developed and applied to a blind study of 3D printed items. Which resulted in successful source determination of 44% of samples, demonstrating the previously unassessed possibility of striations on 3D printed items as class and individual level evaluators. The study suggested suitable implementation into current case work, with the continuance of cataloguing and understanding the presence of toolmarks on seized and laboratory generated 3D printed firearms. Thereby, forensic investigators can begin to disrupt illicit 3D printed firearm manufacturing and distribution. • Exploration of toolmarks on 3D printed items for source differentiation potential • Drag marks generated by 3D printer nozzles showed high incidence and persistence • 16 drag marks identified as having strong discriminatory potential • Data revealed ability to distinguish between five UltiMaker S5 3D printers • Blind testing for 3D printer origin; 44% correct identification of source printer