With Cognex ViDi Suite, the automated aesthetic inspection of complex pad printing is now extremely simple. The software algorithm trains itself on a set of known good samples and creates its reference model.
Once this training phase is completed, the inspection is ready to go. Defective areas of the printing can quickly be identified and reported. ViDi suite does not limit itself to checking ink transfer but complements it with a detailed aesthetic inspection of the substrate. And best of all, there is no need for extensive defects libraries!
CHALLENGES IN PAD PRINTING INSPECTION
- Multi-step tampography can lead to considerable but tolerable relative shifts (registration problem)
- Varying quantities of ink applied results in fonts or lines that are thicker/thinner in appearance
- Random texture of substrate, like brushed or otherwise decorated metal
In-Sight ViDi Read Tool
The In-Sight ViDi Read tool deciphers badly deformed, skewed, and poorly etched codes using optical character recognition (OCR). It works right out of the box, dramatically reducing development time, thanks to the deep learning pretrained font library. Simply define the region of interest and set the character size. In situations where new characters are introduced, without vision expertise, this robust tool can be retrained to read application-specific codes that traditional OCR tools are not able to decode.
In-Sight ViDi Check Tool
The In-Sight ViDi Check tool uses artificial intelligence to reliably detect complex features and objects and verifies parts and kits are assembled correctly based on their location within a pre-defined layout. It can be trained to create an extensive library of components, which can be located in the image even if they appear at different angles or vary in size.
In-Sight ViDi Detect Tool
The In-Sight ViDi Detect tool is ideal for finding anomalies on complex parts and surfaces, even in situations where defects can be unpredictable in their appearance. It learns from images of good parts in order to identify defective parts. This allows the tool to detect a wide range of defects that do not need to be pre-defined at the time of training.
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