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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.

The rise of cloud-based, Industry 4.0-level computing and networking technology is making multiple documentation and traceability requirements easier to navigate.

A shared testbed for innovation at NIIMBL represents, but doesn’t mimic, what’s happening in an individual firm’s lab.

When Rensselaer Polytechnic Institute needed clear plastic to make face shields for the coronavirus pandemic, conventional suppliers were unable to provide it. “We are now one of the largest purchasers of document covers in the country,” Robert Hull, acting VP for research at Rensselaer, said during a  webinar that SME and CESMII – the Smart Manufacturing Institute hosted last week.

This is the first in a series of articles that will cover the accelerating improvement in manufacturing technology.

AI already helps individual factories improve production, safety, efficiency and other metrics while lowering costs. Marrying AI and cloud technology can supercharge those benefits.

Today, it’s tremendously difficult to get products made. To turn an idea into a tangible object requires a list of difficult-to-obtain resources, including expensive machinery and capital, and a lot of time to program and configure machines.

Building a more sustainable future with additive manufacturing and digitalization.