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There’s no doubt that additive manufacturing (AM), including emerging 3D printing technologies, is booming. Despite its promise though, AM still has far to go to in understanding the impact of subtle differences in manufacturing methods on the properties and capabilities of resulting materials. Overcoming this shortcoming is necessary to enable reliable mass production of complex components, which must meet demanding specification requirements.

DARPA’s Open Manufacturing program seeks to solve this problem by building and demonstrating rapid qualification technologies that comprehensively capture, analyze, and control variability in the manufacturing process to predict the properties of resulting products.

The challenge with AM parts is that they are typically composed of countless micron-scale weld beads piled on top of each other. Even when well-known and trusted alloys are used, the additive process produces a material with a much different “microstructure,” endowing the manufactured part with different properties and behaviors than would be expected if the same part were made by conventional manufacturing.

Moreover, parts made on different machines may be dissimilar enough from each other that current statistical qualification methods won’t work. Accordingly, each “new” material must be precisely understood—and the new process controlled—to ensure the required degree of confidence in the manufactured product.

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