Optimizing Metals Additive Manufacturing

Aaron P. Stebner, Rowlinson Associate Professor of Mechanical Engineering and Materials Science, Colorado School of Mines

Abstract

The Alliance for the Development of Additive Processing Technologies (ADAPT) is developing a combined physics – machine learning platform for assessing Process-Structure-Property relationships in metals additive manufacturing. An added benefit of this approach is the inherent statistical core of the models – the AI platform is not only capable of learning the PSP relations of AM, but also providing statistical reports on part quality and variation in a manner conducive to certification. In this presentation, it will be shown how such a framework can be used to optimize parts, processes, and materials for metals additive manufacturing, resulting in reduced times and costs for qualifications. The parts example will cover accelerated qualification of a 17-4 Stainless Steel door hinge for an Army ground vehicle. The materials example will document ways and means to make laser powder bed fusion manufactured Inconel 718 stronger & more ductile than wrought material. The processes example will show how machine learning can be used to determine the parameters for a new printer that has a more powerful laser than previous generations of machines, with verification carried out in printing Ti-64 coupons. These examples will be motivated with a vision for how networks of 3D printers that share a common database can shift paradigms in manufacturing.

Biography

Aaron is the Rowlinson Associate Professor of Mechanical Engineering and Materials Science at the Colorado School of Mines, as well as the Executive Director of the Alliance for the Development of Additive Processing Technologies (ADAPT), a 22-member academic-industry research consortium. He received his B.S. and M.S. from the University of Akron, his Ph.D. from Northwestern University, and he was a Postdoctoral Scholar at the Graduate Aerospace Laboratories of the California Institute of Technology. In between degrees, he worked at the Electric Device Corporation in Canfield, Ohio, developing manufacturing and automation technologies for the circuit breaker industry; NASA Glenn Research Center developing smart materials technologies for morphing aircraft structures; Telezygology, Inc., establishing manufacturing and technologies for shape memory alloy security latching devices; and he consults regularly for shape memory alloy and additive manufacturing industries (medical device, aerospace, consumer products, etc.). He has won numerous awards including an NSF-Career award (2014), the Colorado School of Mines Researcher of the Year Award (2017), and a Visiting Scholar Fellowship from the Japan Society for the Preservation of Science (JSPS, 2019).

Limited seating. Click here to register for the seminar.