For a long time, manufacturers could afford to treat growth as a series of separate functions.

With unique device identification (UDI) required under U.S. Food and Drug Administration regulations and the EU Medical Device Regulation, direct part marking has become mandatory for many medical devices, including surgical instruments and implants.

In high-volume manufacturing, inspection often struggles to keep pace with production. That challenge becomes even greater when the material itself is naturally variable and the defects aren’t always easy to define consistently.

When manufacturing leaders discuss operational challenges, “culture” becomes the catch-all explanation: “Our culture doesn’t support discipline like Asian manufacturers,” or, “We need to change the culture around quality,” or, “It’s a cultural resistance to following

When fundamental particles are heavier or lighter than expected, physicists’ understanding of the universe can tip into the unknown.

In a lot of plants, motion-control equipment stays in service far longer than anyone originally expected.

The way we think about our process will shape the way we collect, analyze, and interpret our data when things go wrong. This in turn will shape the actions taken and the results obtained.

There’s no shortage of AI in manufacturing. There is, however, a shortage of AI that works when things get complicated—AI that can move the needle.

At Dozuki, our teams are constantly on the factory floor. We spend hundreds of hours every year walking production lines, sitting in breakrooms with operators, and standing alongside quality managers during high-stakes audits.

Manufacturers can’t control tariffs, supply chain volatility, labor shortages, or geopolitical instability. But they can manage operational efficiency.