Investigation of Measurements and Standards needs for Metal-based Additive Processes

This project will investigate the fundamental characteristics of the metal-based additive processes, identify critical measurement and standards issues, and develop metrology tools to improve the scientific understanding of these processes. While measurements and standards for metal-based additive manufacturing processes is a new focus area for MEL, we anticipate overlap in manufacturing process measurements and standards issues that make existing MEL skills and expertise relevant and beneficial for topics such as precision motion control, equipment performance assessment and metrics, manufacturing process control and automation,  measurement methods for determining process parameters such as temperatures and forces, and remote sensing and condition monitoring of system performance. As indicated prior, the fundamental metrology and standards developed by this program are intended to be relevant to a wide variety of new and emerging manufacturing processes and equipment.

Additive manufacturing processes such as selective laser sintering (SLS), direct-metal laser sintering (DMLS), and laser engineered net shaping (LENS) hold promise to revolutionize manufacturing by enabling the on-demand manufacture of highly-complex customized products directly from the part description.  These technologies have been in development over the past decade and their capabilities have grown significantly.  However, progress in the development and adoption of these processes has been slower than desired, in particular for processes that address metal parts.  Key challenges include the inability to produce smooth contoured surfaces, limitations in part accuracy, limitations in fabrication speed, and limitations in material density and associated material properties that result from additive fabrication methods. In order to provide a science-based understanding of these processes, this project will develop metrology tools to characterize metal-based additive processes.  Based on such characterization, well defined performance metrics for these processes will be developed.