Assessing 3D and 2D images for automated optical inspection can be performed by machine vision algorithms. This example from Visteon and the Polytechnic Institute of Setúbal presents an algorithm for assessing 3D solder joint inspection.
One method of ensuring equal assessment of each PCB is the use of specific AOI cameras to reduce the effects of how distance from the lens affects focus. Compared to traditional cameras, AOI cameras can reduce distortion by using a telecentric lens, creating an orthographic projection of a complex 3D structure by « flattening » it to two dimensions. This allows machine vision algorithms to more reliably make accurate measurements of a board.
The auto-alignment feature in the app allows users to more easily match up the reference to the sample, by making the reference sample partially transparent. Prior to officially launching the app, the company said the product went through test use with distributors and end users.
As with any app, one of the qualities Tagarno highlights is the ability to update features and fix bugs remotely. The company issues quarterly updates on the firmware on its applications to make sure any errors or required enhancements are addressed.
What’s your experience with visual inspection of PCBs? Do you have expertise about assessing flattened vs 3D images? Is there an important AOI method or technology missing that you’d like to see covered? Share your thoughts in the comments below..