Additive Manufacturing

NOV 2018

ADDITIVE MANUFACTURING is the magazine devoted to industrial applications of 3D printing and digital layering technology. We cover the promise and the challenges of this technology for making functional tooling and end-use production parts.

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Page 19 of 75

NOVEMBER 2018 Additive Manufacturing FEATURE / AM Qualification 18 Development of Additive Processing Technologies (ADAPT) Center was born. "I was scared to death when we won the grant money," Stebner says. "We didn't really have any additive manufacturing faculty at that time, and I was wondering whether everybody I hired would be out of a job in 12 months." But in the three years since the grant award, the opposite has been true. The ADAPT Center has raised more than $20 million in external funding, grown from three member companies to 20, and stood up a full professional degree program and curriculum in advanced man- ufacturing as well as a master's practicum program in additive manufacturing run by several new faculty members. Today, the center's mission still ties back to the core argu- ment Craig Brice put forth while working for NASA: to decode the fundamental physics of energy input, mass flow and time for additive manufacturing processes in a way that allows AM outcomes to drive the qualification programs. And the only way to do that is through the generation of data. Find, Distill, Influence The ADAPT Center is, in essence, a centralized repository of certified, nonproprietary test data. While the center has added a number of additive manufacturing machines (which was not the case as recently as this past February when we wrote about the link between artificial intelligence and AM being studied at the center), the center was fundamentally established to address the data challenges in additive manufacturing. Crucially, that data has to be collected in a manner that encourages would-be compet- itors to feel comfortable that they are not exposing proprietary information or risking their intellectual property (IP). Of course, not all companies define their IP alike. For exam- ple, the additive machine settings utilized by a smaller company or service bureau to create parts is often protected information. Conversely, a large company like Lockheed Martin doesn't oper- ate by running additive machines to create parts, but (typically) purchases parts from smaller companies and service bureaus. So, from a Lockheed perspective, if it can get the smaller company's pre-competitive data—data from examining test samples, for example—out and into a collaborative environment, that data can drive its service bureaus to improve their product. The sheer number of settings in metal additive manufactur- ing machines—the "thousand knobs to turn" conundrum of the A student from the Colorado School of Mines (CSM) works in the ADAPT Center lab. The lab, which serves as a centralized repository of certified, nonproprietary test data, has added a number of additive manufacturing machines in conjunction with advanced manufacturing and AM programs now offered at CSM.

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