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Why Validated Manufacturing Processes Still Fail

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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.

3 Steps to Reduce Your Manufacturing Cycle Time

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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.

The 5 Maintenance Reports That Operations Leaders Use Most

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

Why Faster Scanners Don’t Always Mean Faster Inspection

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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.

AI’s Role in Strengthening the Future Workforce for Healthcare Technology Management

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

ISO 9001 Sets New Rules of Play for Quality Management

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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. 

Connecting the Dots: Merging Human and AI Potential

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

How Manufacturers Can Move AI From Pilot to Production

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

The Trouble With Yellow

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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.

How Experts Use Decades of Knowledge: Content, Context, Consequence

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Speaking with experts who love their jobs usually makes you aware of two things simultaneously: 1) how much you don’t know, and 2) how much you’d like to know. My conversations with Prashant Darisi and Vick Vaishnavi were no exception.

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