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Better Vision Through Innovation Blog - John Stamos

John Stamos
I am the Product Marketing Manager for Cognex in the Vision Systems Business unit. I have been at Cognex for over 6 years, having served as sales engineer for all of our factory automation products. In this role, I had the privilege of working on a wide range of applications in a variety of industries, seeing first-hand how our vision technology improves quality and increases productivity. I have a BS in Mechanical Engineering and French from the University of Wisconsin, and an MBA from the University of Chicago. Outside of work I enjoy listening to music, cheering on Wisconsin Badger football on Saturdays and discretely rooting for the Chicago Bears on Sundays from Milwaukee.

Leverage machine vision data for quality control

On Cognex.com, you can read many examples of how machine vision technology has replaced human inspectors on thousands of production lines worldwide. The benefits of a machine vision system are pretty clear—the automated inspection functionality run 24/7, inspect all complex parts at staggering speeds, and allows companies to provide full quality control for every single object, not just spot inspections of small groups of products.

In recent years, machine vision technology experts have the developed more robust defect detection software tools, equipment, and ancillary devices to provide quality control on a truly industrial scale. The data that today’s machine vision tools collect not only improves quality control, but also helps manufacturers make the production process more efficient and streamlined. One quality control strategy that leverages machine vision technology is the automatic calculation of data and its comparison to acceptable levels that you yourself define. If the data falls outside of a predefined acceptable level, you get automatic notification from the machine vision system and can take steps to correct problems in real time.

Make sure the date your machine vision system collects is the highest quality possible – and that it can be shared and analyzed in a simple, straightforward way.

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