Machine Learning is proving to be getting easier to execute on. It might surprise some to learn how much can be done in the area of factory automation using sensors and AI. The following case study does an impressive job explaining exactly what Frito Lay has accomplished in this respect. The article even provides charts on how they are adding more capabilities by automating some of the older pattern-matching software they have in production. In the end, it allowed them to replace a $300,000 potato-weighing machine with a sensor.

Artificial intelligence—and its machine learning applications in particular—have been attracting the attention of industrial companies both large and small. However, if you’ve been following any of the news around machine learning, you’ve likely heard that, as advanced as this technology has become, it’s still quite a ways from being “ready for prime time” in industry. And while this is true, it doesn’t mean the technology is not ready for application in meaningful ways.

Shahmeer Mirza, senior research and development engineer at PepsiCo., is proving that machine learning has plenty of real world usefulness today through his work with the concept at Frito-Lay, a subsidiary of PepsiCo.

Read the full case study on Automation World

You may also like

Leave a comment