The research objective of this award is to develop robust, high-performance control algorithms for Laser Metal Deposition (LMD) processes. LMD is a class of additive manufacturing processes that builds metal parts layer by layer, introducing dynamics that propagate in time and also layer-domains. While conventional control strategies consider only the time-domain dynamics, the layer-domain dynamics introduce significant part defects that affect process reliability and efficiency. Physics-based 2-D (time- and layer-domain) dynamic models of the LMD process will be created and validated on a LMD machine at Missouri S&T and an industrial LMD machine at Optomec, Inc. New Repetitive Process Control (RPC) algorithms will be developed to control the 2-D LMD dynamics addressing issues of robustness and performance. The methodology employed may also be beneficial in other additive and layer-based manufacturing processes.
This project will spur innovation in additive manufacturing by advancing the science, education, and practice of LMD process modeling and control, potentially leading to dramatic improvements in reliability, efficiency, and productivity. Additive manufacturing processes hold tremendous potential to transform the way parts are manufactured, away from multi-step hands-on fabrication, to single-step automation directly from CAD models. The LMD process in particular is a critically important additive manufacturing process because it is able to produce service-ready metal parts with little material waste, repair high-cost parts, and produce functional gradient material metal parts. The PI will develop an online distance course on repetitive process control. The investigators will involve undergraduates directly in the research activities through Missouri S&T undergraduate research programs and their existing REU Site in Additive Manufacturing. With the joint support of OIIS/ISE the PI and graduate students will collaborate with researchers in Poland to leverage expertise and facilities.
