Burr Detection System Features Robotics, Machine Learning

IMTS 2018: All Axis Robotics is featuring an automated burr and Foreign Object Debris (FOD) detection inspection system.


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All Axis Robotics is featuring an automated burr and foreign object debris (FOD) detection inspection system. This turnkey system combines optics, multi-axis and rotational movement and software to automatically identify, detect, locate/map and guide operators to repair or remove burrs or FOD on manufactured workpieces. As delivered, all systems include a six-axis robot with controller systems and basic robotic pedestal. The system works with metals, composite materials and plastics. It also detects abnormalities in the fabrication process, such as tool mis-matches and over-etching, by comparing what is detected to what is expected via system software and 3D CAD models for feature and characteristic identification.

The system software uses machine learning and pattern recognition to identify both regularities and irregularities in data, always comparing to CAD models and operator overrides. The system can be trained to recognize different types of FOD, debris or burrs and this information can be added to the learning database for future recognition and filtering. 

The size of FOD, debris or burr objects can be measured and filtered as a “pass,” “fail,” or
“indeterminate (learn),” depending on the criteria established by the specification.   Indeterminate findings can be submitted for manual intervention to determine future “pass” or “fail” criteria. Once detected, the optics can inspect a feature of interest from a range of Cartesian coordinates.

The system is said to improve the speed of parts inspection by eliminating time-consuming manual inspection. Accuracy is improved through a consistent inspection methodology controlled by software with the ability to consistently inspect difficult-to-view locations. The system improves repair of workpieces by identifying and mapping locations of FOD and burrs for remediation. Identification, classification and tagging of burrs is consistent on every part, the company says.