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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.

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

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.

Manufacturers must avoid costly machine errors that cause catastrophic damage to both machine tools and expensive workpieces. Even a minor error in, say, a titanium aerospace component can be a major expense.

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.

The “Global Robotics Report 2019” found that 79 percent of automation distributors do not believe their customers understand the safety requirements of installing a collaborative robot, or cobot.

Some of the biggest technology trends are in smart manufacturing and Industry 4.0 initiatives.

Around the U.S., the major manufacturing regions are taking stock of the fallout from the pandemic and how they can navigate out of the lockdowns in 2020 to thrive once again.

Why don’t more manufacturers in the United States use smart manufacturing technologies like AI and machine learning to reduce waste, achieve predictive maintenance and enhance their automation systems? Five CESMII roundtable panelists share their insights.

Bosch said it lifted its automation platform to the next level with ctrlX I/O while showing it at the show.