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Much has been written about potential applications for 5G. But a less well known application exists in the aerospace and defense industry—that pertains to manufacturing processes.

In my capacity as the Chair of the Council of the Manufacturing USA institute directors, I often get asked about trends in U.S. advanced manufacturing.

Manufacturers who have deployed the digital or smart factory have put down their pencils, found new uses for their clipboards and closed their spreadsheet programs in favor of using real-time data gleaned from condition monitoring of their machinery.

Information technology and operations technology are unlikely candidates for a successful marriage. But to ensure that manufacturers thrive in the digital age, OT and IT must find ways to work together—or to at least, as on Tinder, swipe right to indicate interest.

I experienced the end of the Third Industrial Revolution as I began my career in manufacturing. Closed government and private networks gave way to an open network called the Internet.

The institutes that make up Manufacturing USA need to move at the speed of business, considering that the endeavor represents the U.S. government’s biggest investment in the digitization of manufacturing to date.

SHANGHAI—The $150 million “factory of the future” that the Swiss innovator ABB announced nearly a year ago is becoming reality in this enormous city’s Pudong New Area.

Amid predictions of global economic slowdowns and several recent PMI readings indicating manufacturing contraction, it becomes easy to see how slow production performance and data inefficiencies throughout the manufacturing supply chain contribute to economic uncertainty and concerns for future business.

Foundry 45 is helping Delta Air Lines strategize on ways to keep maintenance workers safe in the “ingestion zone”—the dangerous environment underneath the airplane where people and equipment are moving around in close proximity to engines.

Everyone knows that today a ton of data captured on the manufacturing floor goes unused due to the lack of a data scientist on staff or other resources to comb through all the information.