As plastic pollution continues to mount, with growing risks to ecosystems and wildlife, manufacturers are beginning to make ambitious commitments to keep new plastics out of the environment.

One of the biggest problems when reading about any kind of innovation in the press is the prevalent assumption that everyone understands the topic and how it works.

In a brightly lit subterranean lab at the National Institute of Standards and Technology (NIST) sits a room-sized electromechanical machine called the NIST-4 Kibble balance.

With 2022 firmly in the rearview mirror and the new year now underway, it’s clear many of the opportunities and challenges affecting equipment manufacturers today will remain as relevant as ever in the weeks and months ahead.

Every engineer dreams of having a virtual personal assistant like Jarvis, the disembodied voice that carries out Iron Man’s orders.

A not-so-surprising fact, according to HubSpot: 65 percent of consumers state that the experience they encounter on a website is a “very important” factor in recommending a brand.

When deep-learning models are deployed in the real world—perhaps to detect financial fraud from credit card activity or identify cancer in medical images—they are often able to outperform humans.

Ever since deep learning burst into the mainstream in 2012, the hype around AI research has often outpaced

I’m sure you’ve heard the buzz around the German apprenticeship system—but does it really live up to the hype?

The worldwide pandemic presented unique challenges for every manufacturer in the United States. Hexagon’s Manufacturing Intelligence division was no exception.