The technology developed under this STTR will enable rapid development and optimization of SLM processes. The experimental process development chamber can be configured to simulate existing commercial SLM machines, and thus process developed with the proposed system can be exported to these machines (which are not themselves well designed for process development). This supports the goals of the SLM laboratory at Marshall Space Flight Center as well as participation of the NASA Space Technology Mission Directorate in the Materials Genome Initiative. Implementation of the fast predictive model technology can improve the processes for SLM manufactured parts. This impacts a number of space platforms and terrestrial applications too long to list. Of particular interest to NASA is the use of in-process monitoring to verify build quality. Because the proposed system has in-process monitoring built into the process development methodology, it has a high likelihood of developing processes of which NASA engineers can be confident and for documentation of process quality can be compiled.
Aerospace commercial applications have high overlap with NASA applications including strong interest in fabrication of rocket engine components and a variety of other light-weighted structures. Apart from a desire for faster SLM process development, the commercial market also has a keen interest in in-process monitoring and closed loop process control. The use of feedback from in-process sensors both to develop the fast predictive model and conduct rapid process development entails concepts and techniques that are closely related to in-process control. (I.e., in-process control is essentially continuous, real-time, in situ process development.) Thus it is likely that fast predictive models, as developed under this project, can be implemented to facilitate or enable closed loop process control. Finally, we note that a key goal of this project is to provide a system that will make SLM process development accessible to a large number of new innovators and industries, allowing them to enter the field and create a wide range of applications that are currently unidentified.