3D printed object topography analysis and the viability for forensic examination.

Area of Science:

• Forensic Science
• Materials Science
• Computer Science

Background:

• Commercially available 3D printing technology enables the creation of untraceable firearm components.
• A growing need exists for reliable methods to identify the source of 3D printed objects, particularly in forensic contexts.
• Distinct characteristics left by printer nozzles and print beds on 3D printed objects offer potential for source identification.

Purpose of the Study:

• To determine if toolmarks on 3D printed objects are sufficiently distinct and reliable for source identification.
• To evaluate the efficacy of pattern-matching algorithms in analyzing these toolmarks for forensic purposes.

Main Methods:

• 150 3D printed objects were created using 10 different print beds and 10 different nozzles.
• 3D scans of the top and bottom surfaces of each object were acquired using the Cadre Forensics TopMatch-GS system.
• Cadre's pattern-matching algorithms were applied to compare scans, generating similarity scores. Receiver operating characteristic (ROC) curves and area under curve (AUC) scores were used for analysis.

Main Results:

• The pattern-matching algorithm consistently differentiated between same-source and different-source 3D printed objects.
• AUC scores indicated a high degree of reliability in using these toolmarks for source attribution.
• Analysis of 11,175 intercomparisons for both top and bottom surfaces confirmed the algorithm's effectiveness.

Conclusions:

• Toolmarks on 3D printed objects, specifically from printer nozzles and beds, possess distinct characteristics suitable for forensic source identification.
• The utilized algorithmic approach demonstrates the viability of 3D printed object source identification in forensic investigations.
• This research supports the potential for advanced technological solutions in analyzing 3D printed evidence.