In industrial manufacturing, quality failures carry consequences far beyond the factory floor. A single defect can trigger warranty claims, production downtime for customers, costly recalls, and long-term damage to brand reputation.

Most manufacturing engineers have experienced some version of the same problem: A production process successfully completes validation. The production part approval process (PPAP) is approved.

Imagine running a race where every second counts and your competition is constantly breathing down your neck. That’s the magic (or madness) of cycle time.

Operations leaders usually have more maintenance data than they can use.

Ask anyone who’s bought a handheld 3D scanner with optical tracking system in the last few years about what sold them, and you’ll hear about speed. More points per second. Larger scanning areas. Faster data capture.

The healthcare technology management (HTM) industry is facing a looming labor shortage and must attract enough skilled professionals to meet future demand.

The complexity of today’s manufacturing operations and ever-evolving digital disruptions, including the biggest of all, artificial intelligence (AI), require standards that set the pace and keep organizations around the world aligned with what quality looks like. 

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

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.