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Respondents in a survey said supply chain planning drives better business performance.

New capability adapts process parameters for optimal results independent of operator experience for its LT Fiber EVO and CO2-type LT722D.

In the 1955 short story “Autofac,” Philip K. Dick envisioned a world dominated by self-replicating robots that work incessantly, eventually depleting the planet’s resources.

Using Blockly to make robots easier to install and operate without specialized training.

Modern manufacturing is a data-driven endeavor. The sheer volume of data available to be collected and analyzed is staggering—and something that couldn’t have been envisioned even 20 years ago.

Like most of the digital architecture of manufacturing, computer numerical controllers (CNCs) have advanced rapidly in recent years, producing far more processing speed and implementing advanced algorithms, while at the same time offering simpler, more intuitive user interfaces.

As manufacturing undergoes the revolutionary changes of the Digital Age, the people with the keenest leadership skills have taken up the charge to modernize the industry so that it leverages the cloud and Big Data and is connected and smart.

Robots and job shops have not typically been talked about together. After all, everyone knows that automation is only suitable for high-volume production, and the typical mom-and-pop operation is anything but—its schedule filled with orders for high-mix, low-volume, and often highly complex work.

U.S. manufacturing in general, and small- and medium-sized manufacturers in particular, are in danger of being left behind as Europe and Asia move faster toward Industry 4.0, John Dyck, CEO of the Clean Energy Smart Manufacturing Innovation Institute (CESMII), told congressional staff, federal agency staff in a February briefing.

Edge. Cloud. Digital twin. AI. AR. VR. Cobots. Once they were buzzwords. Now, they are becoming technical realities in mid- to large-scale manufacturing plants in North America.