Robotic Arm Indenting for Validation, Authentication, and Forensics in Manufacturing
Available for Licensing
US Utility Patent Pending (Not Yet Published)
At A Glance
Researchers at Colorado State University have developed a method to provide a four-fold hybrid validation system for custom manufacturing processes, extending from inspection to authentication and forensic validation – all using the same robotic-arm supported sensor.
Using a nano-indenter method, the system provides a novel means of simultaneously validating a material used in manufacturing; encoding and decoding intentional identifying information at the surface of the material (e.g., the interface between two layers in a joining process during multi-step manufacturing); using the identifying information (e.g., promoting adhesion, binding, or joining during manufacturing); and providing loci for forensic authentication of the specific item.
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Robotic arms are increasingly incorporated into manufacturing. In traditional mass production environments, they are used to provide assistance to human workers and for automation. In the increasingly prevalent custom manufacturing and additive manufacturing arenas, they are used to help perform a multitude of tasks required for assembly and finishing.
Using robotic arms for a wide range of materials and process validation, authentication, and forensic validation tasks is, therefore, a reasonable means of preventing fraud in an increasingly complex and distributed manufacturing environment.
- Four-fold hybrid system to validate the entire custom manufacturing process
- Capable of inspection, authentication, and forensic validation
- All validation methods are supporting using the same robotic-arm supported sensor
- Ensures proper joining of parts
- Use in 3D printing and other manufacture applications
- Custom manufacturing validation
- Manufacturing quality control
Weinmann, K., (2021) “Material validation and part authentication process using hardness indentations with robotic arm implementation”. CSU Dissertation. https://mountainscholar.org/handle/10217/234205