For years, manufacturers have been told the future of Industry 4.0 lives in the cloud. Vendors promised plug-and-play AI that could analyze everything, automate anything, and transform the factory floor overnight.

Performance rarely collapses with fanfare. More often, it flatlines quietly; sales soften, productivity slows, priorities blur, and yet teams run hard without moving the needle.

In manufacturing, failure isn’t an option—it’s a liability. A defective part or a missed delivery triggers a chain reaction that can disrupt schedules, undermine trust, and drain resources.

In 2025, there’s been a marked increase in FDA warning letters. During the second quarter of 2025 alone, the U.S. Food and Drug Administration (FDA) issued 172 warning letters.

Management by objectives isn’t just a way to set direction for an organization. It’s a prerequisite for creating sustainable development and a culture of continuous improvement.

Regular inspection is absolutely vital with industrial transmission systems. Just like the gearbox in an everyday car, components are prone to wear, misalignment, and fatigue—issues that can lead to machinery failure.

I’ve had this conversation countless times—sometimes with a frustrated client, often with a colleague, and occasionally with my own reflection.

What’s truly holding your discrete manufacturing shop back from reaching its full potential? It’s often not the commonly cited culprits like labor shortages, razor-thin margins, or fierce competition. It’s more often paper: the unseen, insidious enemy.

The conversation about generative AI (gen AI) is unavoidable in today’s business land

In this article I’m looking at a question that’s rarely asked in management: What if the most responsible course of action isn’t to maximize benefit, but to minimize harm? In decision theory, this is expressed as the minimax principle.