Artificial intelligence (AI) has received a lot of attention over recent years. It has also brought awareness to traditional machine vision processes in manufacturing and industrial automation. 

How can manufacturers make the critical transition from data to action? How do they effectively navigate the overabundance of data to pick out what’s meaningful? How do they use these insights to drive overall productivity and efficiency in an automotive context?

The answer to these questions involves deploying a three-tiered IIoT approach that provides automotive OEMs and suppliers with a comprehensive digital roadmap for their operations.

For a product to be assembled successfully, it’s essential to move the right parts, to the right place, in the right orientation, at the right time. Motion control technology makes that happen. Here’s a sampling of the latest technology.

The assembly line in Hall M13 at the ŠKODA plant in Mladá Boleslav is one of the Czech carmaker’s busiest. The best-selling ŠKODA Octavia is assembled here, as is the ŠKODA Enyaq iV electric SUV. Every minute of downtime on this line means losses in the form of unproduced cars.

With more and more customers getting onboard with IIoT applications in their plants, a new era of efficiency is lurking around the corner. 

BMW has been at the forefront of Industry 4.0 for years. For example, the company was an early adopter of additive manufacturing, and today prints hundreds of thousands of production parts annually. 

A recent study by the Packaging Machinery Manufacturers Institute (PMMI) and Interact Analysis takes a close look at packaging industry interest and needs for Condition Monitoring and Predictive Maintenance.

Predicting the future isn’t what it used to be. It’s actually way better, and that’s great news for manufacturers.

ADELPHI, MD — U.S. Army researchers have discovered a way to monitor the performance of 3D printed parts, which tend to have imperfections that affect performance in ways that traditionally machined parts do not.