Additive manufacturing, also known as 3D printing, has the potential to revolutionize how products are made. Using materials that range from ceramics to nylon, 3D printing allows people to create custom parts and products on demand, for use anywhere from space stations to gas stations.
But even though we can now 3D print incredibly complex shapes, predicting how strong or durable a printed part will be is still a major challenge.
Faculty members in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University, are developing new artificial intelligence, or AI, to make the process of 3D printing stainless steel faster and more reliable.
Aviral Shrivastava, a professor of computer science and engineering and Ashif Iquebal, an assistant professor of industrial engineering, have received a grant from the National Science Foundation for the project, “CompAM: Enabling Computational Additive Manufacturing,” to use AI to make metal 3D printing faster and more reliable by predicting how the material will form during the manufacturing process.
In the demonstration phase of the project, the team will 3D print a five-axis, metal naval propeller using 316L stainless steel, a common industrial-grade metal alloy. The goal is to control the printing process so precisely that they can engineer the metal grain size to be less than one micron — about the width of a strand of spider’s silk — which significantly improves the material’s properties.
Why a propeller? Because it’s large, has a tricky geometry and demands precision — exactly the kind of part that pushes current metal additive manufacturing to its limits.
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