The vision system scanned the part and logged a pass. The SPC chart stayed inside its control limits. The line kept moving.

When a CEO tells me they wish their employees were more capable of “self-organizing,” I usually ask what exactly that means.

Enterprise resource planning (ERP) projects are among the most significant technology investments an organization will ever make. They support everything from finance and procurement to inventory management, customer service, and workforce planning.

The premise of AI large language models (LLMs) is that any problem can be solved by vacuuming up as much information as possible, running it through probability models, and performing complex calculations to make predictions and come up with the optimal solution.

Every industry has blind spots. Sometimes the problem is not a lack of expertise, or even information, but of connection.

The deployment of automated software systems called AI agents has recently exploded.

In manufacturing, some of the most important financial gains never appear as an obvious line item.

Whether you’re a researcher stumped by a mystery compound or a manufacturer perplexed by an unknown substance, there’s a major resource you can rely on: a library of chemical fingerprints, known as mass spectra, that the National Institute of Standards and T

Manufacturers are exploring artificial intelligence, but most are still struggling to scale it across operations.

Walk into almost any factory, hospital, office, or warehouse, and you’ll likely encounter tier boards with a familiar set of colors: green, yellow, and red. Green means good. Red means bad. And yellow? Well, it has… some issues.