John R. Middendorf, Research Scientist, Universal Technology Corp
Glen P. Perram PhD, PE, Professor of Physics, Air Force Institute of Technology
This presentation will investigated a number of world-class sensor technologies on the open-source Additive Manufacturing testbed to gauge their competence as in-process monitoring tools for selective laser melting (SLM), including: High-speed thermal imaging, High-speed visible imaging, ultraviolet to near-Infrared spectroscopy, line-laser profilometry, and mid-wave Infrared imaging Fourier transform spectroscopy. All of the sensors used in this investigation are high-end, expensive tools used in niche markets (for example, the imaging Fourier transform spectrometer is >$1.5 million). The goal was to determine what key data features from each of these sensors were most informative of build conditions during the SLM process, then build a low-cost sensor package that tracks only the key data features, and finally use this new low-cost sensor for in-process monitoring, control, and documentation of SLM. Results of the work-to-date analysis are presented including a description of multi-sensor/software package/pricing considerations.